ElShamah - Reason & Science: Defending ID and the Christian Worldview
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ElShamah - Reason & Science: Defending ID and the Christian Worldview

Welcome to my library—a curated collection of research and original arguments exploring why I believe Christianity, creationism, and Intelligent Design offer the most compelling explanations for our origins. Otangelo Grasso


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226Perguntas .... - Page 10 Empty Re: Perguntas .... Mon Aug 07, 2023 2:15 pm

Otangelo


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albeit followed by a swift refutation by Eugene V. Koonin (2007):  The statement that “[e]ukaryote proteins that are rooted in the bacterial or in archaeal clusters are few and far between” is inaccurate. The genomes of both yeast and humans harbor many hundreds of proteins that have readily identifiable homologs among α-proteobacteria but not among archaebacteria, and vice versa. They opine that “t is an attractively simple idea that a primitive eukaryote took up the endosymbiont/mitochondrion by phagocytosis,” yet all testable predictions of that idea have failed. By contrast, examples of prokaryotes that live within other prokaryotes show that prokaryotes can indeed host endosymbionts in the absence of phagocytosis, as predicted by competing alternative theories. They misattribute the notion that a eukaryotic “raptor” phagocytosed the mitochondrion to Stanier and van Niel’s classical paper, which does not mention mitochondrial origin, and to de Duve’s 1982 exposé, which argues for the endosymbiotic origin of microbodies while mentioning “alleged symbiotic adoption” of mitochondria in passing, but without mentioning phagocytosis. Their references and are misattributed as examples of “fusion” hypotheses; indeed, they indiscriminately label views on eukaryote origins that differ from their own as fusion hypotheses.Finally, and most disturbing, if contemporary eukaryotic cells are truly of “irreducible nature,” as Kurland et al.’s title declares, then no stepwise evolutionary process could have possibly brought about their origin, and processes other than evolution must be invoked. Is there a hidden message in their paper? 

which got another response by C. G. KURLAND: OUR VIEW IS THAT CELLULAR AND MOLECULAR biology, especially genomics, reveals signs of an ancient complexity of the eukaryotic cell. This new information was not available to older hypotheses for eukaryote origins; they were answering questions that were incompletely formulated. Our primary conclusions regarding the ancestral complexity of the eukaryote cell microsporidian and the subcellular location of its eukaryote signature proteins (ESPs). Even though Microsporidian genomes are among the most heavily reduced in eukaryotes, they still have many eukaryote signature proteins ESPs. An anaerobic endoparasitic lifestyle (parasites that live in the tissues and organs of their hosts) has reduced their mitochondria to mitosomes and allowed the characteristic proteins of phagocytosis to be lost. Nevertheless, it is striking that characteristic ESPs are found throughout the cell; nothing in this picture suggests they are chimeric descendents of archaeal and bacterial ancestors. 35

1. Kevin Padian: Darwin's enduring legacy 06 February 2008
2. Laurie S. Kaguni: DNA Replication Across Taxa (Volume 39) (The Enzymes, Volume 39) 2016
3. Samta Jain: Biosynthesis of archaeal membrane ether lipids 2014 Nov 26
4. Sultan F Alnomasy: Insights into Glucose Metabolism Inarchaea and Bacteria: Comparison Study of Embden-MeyerhofParnas (EMP) and Entner Doudoroff (ED) Pathways August 2017
5. Wolfgang Nitschke: Beating the acetyl coenzyme A-pathway to the origin of life 2013 Jul 19
6. Eugene V Koonin: The origin and early evolution of eukaryotes in the light of phylogenomics 05 May 2010
7. Eugene V Koonin: Evolution of microbes and viruses: a paradigm shift in evolutionary biology? 2012 Sep 13
8. Brett Deml: Prokaryotic vs. Eukaryotic Trancription 2006
9. Ingo Ebersberger et.al.,:The evolution of the ribosome biogenesis pathway from a yeast perspective 2014 Feb; 4
10. Alan C. Leonard: DNA Replication Origins 2013 Oct; 5
11. Eugene V. Koonin: Global Organization and Proposed Megataxonomy of the Virus World 4 March 2020
12.Viruses and the tree of life:  19 March 2009
13. Eugene V. Koonin: Multiple origins of viral capsid proteins from cellular ancestors March 6, 2017
14. Franklin M. Harold:  In Search of Cell History: The Evolution of Life's Building Blocks  page 96 October 29, 2014
15. Keith A. Webster: Evolution of the coordinate regulation of glycolytic enzyme genes by hypoxia 01 SEPTEMBER 2003
16. Mark A. Ragan: The network of life: genome beginnings and evolution 2009 Aug 12
17. Douglas L. Theobald: A formal test of the theory of universal common ancestry 2010
18. Youtube: Dr. Craig Venter Denies Common Descent in front of Richard Dawkins! 2011 
19. Evolution News: Venter vs. Dawkins on the Tree of Life — and Another Dawkins Whopper March 9, 2011
20. W. Ford Doolittle Pattern pluralism and the Tree of Life hypothesis February 13, 2007
21. D M Raup: Multiple origins of life. May 1, 1983
22. Christopher P. Kempes: The Multiple Paths to Multiple Life 12 July 2021
23. Anja Spang: Evolving Perspective on the Origin and Diversification of Cellular Life and the Virosphere  26 February 2022
24. Eörs Szathmáry: Toward major evolutionary transitions theory 2.0 April 2, 2015
25. Eugene V Koonin: Origin and evolution of eukaryotic apoptosis: the bacterial connection 28 March 2002
26. Josip Skejo: Evidence for a Syncytial Origin of Eukaryotes from Ancestral State Reconstruction July 2021
27. Evelyne Derelle et.al., Genome analysis of the smallest free-living eukaryote Ostreococcus tauri unveils many unique features 2006 Jul 25
28. K. S. KABNICK: Giardia: A Missing Link between Prokaryotes and Eukaryotes  January 1991
29. B.Alberts: Molecular Biology of the Cell, 7th edition 2022
30. Fazale Rana: Why Mitochondria Make My List of Best Biological Designs May 1, 2019
31. Eugene V Koonin: Eukaryogenesis, LECA Mar 14, 2019
32. Thomas Cavalier-Smith: Origin of the cell nucleus, mitosis and sex: roles of intracellular coevolution 2010
33. Eugene V. Koonin: Origin of eukaryotes from within archaea, archaeal eukaryote and bursts of gene gain: eukaryogenesis just made easier?  9 June 2015
34. C. G. Kurland: Genomics and the Irreducible Nature of Eukaryote Cells 19 MAY 2006
35. Eugene V. Koonin: The Evolution of Eukaryotes 27 APRIL 2007
36. Anni Kauko: Eukaryote specific folds: Part of the whole  18 April 2018
37. George E. Mikhailovsky: LUCA to LECA, the Lucacene: A model for the gigayear delay from the first prokaryote to eukaryogenesis  1 April 2021
38. Maureen A. O’Malley: Endosymbiosis and its implications for evolutionary theory April 16, 2015
39. Dr. Daniel Moran, Ph.D.: Molecular Phylogeny Proves Evolution is False. September 9, 2013
40. Arizona State University New research on the emergence of the first complex cells challenges orthodoxy AUGUST 5, 2022
41. O.Zhaxybayeva: Cladogenesis, coalescence and the evolution of the three domains of life 2004 Apr


Koonin continues: Molecular phylogenetics and phylogenomics revealed fundamental aspects of the origin of eukaryotes. The ‘standard model’ of molecular evolution, derived primarily from the classic phylogenetic analysis of 16S RNA by Woese and co-workers and supported by subsequent phylogenetic analyses of universal genes, identifies eukaryotes as the sister group of archaea, to the exclusion of bacteria. Within the eukaryotic part of the tree, early phylogenetic studies have placed into the root position several groups of unicellular organisms, primarily parasites, that unlike the majority of eukaryotes, lack mitochondria. These organisms have been construed as ‘archezoa’, i.e. the primary amitochondrial eukaryotes that were thought to have hosted the proto-mitochondrial endosymbiont. However, advances in comparative genomics jointly with discoveries of cell biology have put the archezoan scenario of eukaryogenesis into serious doubt. First, it has been shown that all the purported archezoa possess organelles, such as hydrogenosomes and mitosomes, that appeared to be derivatives of the mitochondria. These mitochondria-like organelles typically lack genomes but contain proteins encoded by genes of apparent bacterial origin that encode homologous mitochondrial proteins in other eukaryotes. Combined, the structural and phylogenetic observations leave no reasonable doubt that hydrogenosomes and mitosomes indeed evolved from the mitochondria. Accordingly, no primary amitochondrial eukaryotes are currently known, suggesting that the primary a-proteobacterial endosymbiosis antedated the LECA. Compatible with this conclusion, subsequent, refined phylogenetic studies have placed the former ‘archezoa’ within different groups of eukaryotes indicating that their initial position at the root was an artefact caused by their fast evolution, most probably causally linked to the parasitic lifestyle. These parallel developments left the archezoan scenario without concrete support but have not altogether eliminated its attractiveness. An adjustment to the archezoan scenario simply posited that the archezoa was an extinct group that had been driven out of existence by the more efficient mitochondrial eukaryotes. A concept predicated on an extinct group of organisms that is unlikely to have left behind any fossils and is refractory to evolutionary reconstruction due to the presence of mitochondria (or vestiges thereof ) in all eukaryotes is quite difficult to refute but can hardly get much traction without any concrete evidence of the existence of archezoa. The radical alternative to the elusive archezoa is offered by symbiogenetic scenarios of eukaryogenesis according to which archezoa, i.e. primary amitochondrial eukaryotes, have never existed, and the eukaryotic cell is the product of a symbiosis between two prokaryotes. Comparative genomic analysis clearly demonstrates that eukaryotes possess two distinct sets of genes, one of which shows phylogenetic affinity with homologues from archaea, whereas the other one includes genes affiliated with bacterial homologues (apart from these two classes, there are many eukaryotic genes of uncertain provenance). The eukaryotic genes of apparent archaeal descent encode, primarily, proteins involved in information processing (translation, transcription, replication, repair), whereas the genes of inferred bacterial origin encode mostly proteins with ‘operational’ functions such as metabolic enzymes, components of membranes and other cellular structures and others. Notably, altogether, the number of eukaryotic protein-coding genes of bacterial origin exceeds the number of ‘archaeal’ proteins about threefold. Thus, although many highly conserved, universal genes of eukaryotes indeed appear to be of archaeal origin, the archaeo-eukaryotic affinity certainly does not tell the entire story of eukaryogenesis, not even most of that story if judged by the proportions of genes of apparent archaeal and bacterial descent.

Although several symbiogenetic scenarios that differ in terms of the proposed partners and even the number of symbiotic events involved have been proposed, the simplest, parsimonious one that accounts for both the ancestral presence of mitochondria in eukaryotes and the hybrid composition of the eukaryotic gene complement involves engulfment of an α-proteobacterium by an archaeon. Under this scenario, a chain of events has been proposed that leads from the endosymbiosis to the emergence of eukaryotic innovations such as the endomembrane system, including the nucleus and the cytoskeleton. Subsequently, argument has been developed that the energy demand of a eukaryotic cell that is orders of magnitude higher than that of a typical prokaryotic cell cannot be met by means other than utilization of multiple ‘power stations’ such as the mitochondria.

A major problem faced by this scenario (and symbiogenetic scenarios in general) is the mechanistic difficulty of the engulfment of one prokaryotic cell by another. Although bacterial endosymbionts of certain proteobacteria have been described, such a relationship appears to be a rarity. By contrast, in many unicellular eukaryotes, such as amoeba, engulfment of bacterial cells is routine due to the phagotrophic lifestyle of these organisms. The apparent absence of phagocytosis in archaea and bacteria prompted the reasoning that the host of the proto-mitochondrial endosymbiont was a primitive phagotrophic eukaryote, which implies the presence of an advanced endomembrane system and cytoskeleton. Thus, argument from cell biology seemed to justify rescuing the archezoan scenario, the lack of positive evidence notwithstanding.

The diversity of the outcomes of phylogenetic analysis, with the origin of eukaryotes scattered around the archaeal diversity, has led to considerable frustration and suggested that a ‘phylogenomic impasse’ has been reached, owing to the inadequacy of the available phylogenetic methods for disambiguating deep relationships. 33

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227Perguntas .... - Page 10 Empty Re: Perguntas .... Mon Aug 07, 2023 2:15 pm

Otangelo


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M.Syvanen (2012): The flow of genes between different species represents a form of genetic variation. When I first started writing in 1982 about the implications of horizontal gene transfer (HGT) for macroevolutionary trends, the existence of the phenomenon was not yet accepted, given that evidence came only from isolated examples of bacterial plasmid transfer events and a case involving a retrovirus in mammals. There was great explanatory power in a theory that incorporated the notion of horizontally transferred genes as a source of genetic variation upon which natural selection acts. Reports of HGT in nature trickled in, but investigators debated the significance of HGT and the methodology for identifying it. In fact, only in the past 14 years has the number of examples of naturally occurring HGT become too large to ignore. With the recent availability of genome sequence data, the pace of discovery has picked up and interest in the phenomenon has increased. We now know that the ability of genes to function perfectly well across species boundaries has resulted in a significant horizontal flow of genes. Whether the genes are transferred by transposons, viruses, bacteria, or other vectors, or perhaps through direct contact or initial hybridization-like events, the horizontal flow of genes is a part of the story of life. Although the phenomenon of HGT is now widely accepted, current theoretical constructs remain quite resistant to many of its deeper implications. The first area I touch upon concerns the role of phylogenetic trees as a model for biological history. A second and related area concerns the continued speculation about and search for what is called the last universal common ancestor (LUCA) and the evolutionary significance of the biological unities. A third question involves the rethinking of higher taxonomic nomenclature. The chaotic phylogenetic relationships among plants remain unresolved, and a consideration of horizontalgene flow could help solve the puzzle. 24

Shelly Hamilich (2022): Our results suggest that horizontal gene transfer between hosts and their microbiota is a significant and active evolutionary mechanism that contributed new traits to plants and their commensal microbiota. 26

Comment: Rightly, Coppedge points out that: Information shared is not the same as information innovated, nor is borrowing a book as difficult as writing one. 27

Rama P. Bhatia (2022): the fitness effects of horizontally transferred genes are highly dependent on the environment. 28

Comment: The same problem to natural selection applies to HGT: since environmental factors influencing fitness effects would have to be taken into consideration in order to measure/calculate the influence of HGT in fitness, and since that is a variable that is stochastic, and cannot be measured, it becomes de facto impossible to detect up to what degree HGT influences fitness in populations in their natural environment.  

Irreducible complexity 

C.Darwin (1860): “If it could be demonstrated that any complex organ existed, which could not possibly have been formed by numerous, successive, slight modifications, my theory would absolutely break down. But I can find no such case.” 30

Irreducible complexity, a term popularized by Michael Behe in his infamous book Darwin's Black box falsifies the claim that evolution explains the origin of biocomplexity and organismal form. If natural selection makes intelligent design superfluous, is it capable of instantiating proteins, cell types, organs, and organ systems, that have only function in cooperation/joint venture with other functional parts of the organism, or the organism as a whole, by slight, successive modifications over time?  Does it select for structures, functions, traits, or what? 

Behe, Darwin's Black Box (1996), page 39: By irreducibly complex I mean a single system composed of several well-matched, interacting parts that contribute to the basic function, wherein the removal of any one of the parts causes the system to effectively cease functioning. An irreducibly complex system cannot be produced directly (that is, by continuously improving the initial function, which continues to work by the same mechanism) by slight, successive modifications of a precursor system, because any precursor to an irreducibly complex system that is missing a part is by definition nonfunctional. An irreducibly complex biological system, if there is such a thing, would be a powerful challenge to Darwinian evolution.22

An irreducibly complex system is characterized by five points:
1. a single system composed of several well-matched, interacting parts
2. that contribute to the basic function
3. the removal of any one of the parts causes the system to effectively cease functioning
4. An irreducibly complex system cannot be produced directly (that is, by continuously improving the initial function, which continues to work by the same mechanism) by slight, successive modifications of a precursor system
5. any precursor to an irreducibly complex system that is missing a part is by definition nonfunctional.

1. Robert Carter: Genetic entropy and simple organisms 25 October 2012
2. Paul R. Ehrlich Natural Selection 1988
3. Natural History Museum: What is natural selection?
4. David Stack: Charles Darwin: Theory of Natural Selection 01 January 2021
5. Ernst Mayr: WHAT EVOLUTION IS A Conversation With Ernst Mayr [12.31.99]
6. J.Dekker: Natural Selection and its Four Conditions 2007
7. S.El-Showk: Natural selection: On fitness 2012
8. Evolution.Berkley: Evolutionary fitness
9. Adam Eyre-Walker: The distribution of fitness effects of new mutations August 2007
10. R. G. Brajesh: Distribution of fitness effects of mutations obtained from a simple genetic regulatory network model  08 July 2019
11. Thomas Bataillon: Effects of new mutations on fitness: insights from models and data 2014 Jul
18. Christopher J Graves: Variability in fitness effects can preclude selection of the fittest 2019 Sep 30
19. Vita Živa Alif: What is the best fitness measure in wild populations? A case study on the power of short-term fitness proxies to predict reproductive value November 19, 2021.
20. Ivana Cvijović: Fate of a mutation in a fluctuating environment August 24, 2015
21. Xia Hua: Darwinism for the Genomic Age: Connecting Mutation to Diversification  07 February 2017
22. Z Patwa: The fixation probability of beneficial mutations 29 July 2008
23. R. G. Brajesh: Distribution of fitness effects of mutations obtained from a simple genetic regulatory network model 08 July 2019
24. David F. Coppedge Evolutionary Fitness Is Not Measurable November 20, 2021
25. Michael Lynch: The frailty of adaptive hypotheses for the origins of organismal complexity May 15, 2007
26. Molly K Burke et.al.,: Genome-wide analysis of a long-term evolution experiment with Drosophila 2010 Sep 30
27. Ben Bradley: Natural selection according to Darwin: cause or effect? 11 April 2022
28. Adam Levy: How evolution builds genes from scratch 16 October 2019
29. J.Dulle: The (In)adequacy of Darwinian Evolution
30. Matthew Hurles: Gene Duplication: The Genomic Trade in Spare Parts July 13, 2004
31. Alisha K Holloway: Experimental evolution of gene duplicates in a bacterial plasmid model 2007 Feb
32. Joseph Esfandiar: Is gene duplication a viable explanation for the origination of biological information and complexity? 22 December 2010
33. Johan Hallin: Regulation plays a multifaceted role in the retention of gene duplicates November 22, 2019
34. Michael Lynch: The Origins of Genome Architecture 2007
35. Eugene V Koonin: Darwinian evolution in the light of genomics 2009 Mar


12. H. Allen Orr: Testing Natural Selection  2008
13. FRANCISCO J. AYALA: Darwin’s Greatest Discovery: Design Without Designer 2007
14. Paul Gibson : Can Purifying Natural Selection Preserve Biological Information? – May 2013
15. Eugene V. Koonin :Toward a theory of evolution as multilevel learning February 4, 2022
16. Jerry A. Coyne, Why Evolution is True, p. 123. 2009
20. George Ellis: Controversy in Evolutionary Theory: A multilevel view of the issues. 2018
21. Armen Y. Mulkidjanian: Physico-Chemical and Evolutionary Constraints for the Formation and Selection of First Biopolymers: Towards the Consensus Paradigm of the Abiogenic Origin of Life 21 September 2007
22. M.Behe: Darwin's Black Box: The Biochemical Challenge to Evolution 1996
24. Michael Syvanen: Evolutionary Implications of Horizontal Gene Transfer 21 August 2012
25. Libretext: Horizontal Gene Transfer
26. Shelly Hamilich: Widespread horizontal gene transfer between plants and their microbiota August 26, 2022
27. David Coppedge: Gene Sharing Is More Widespread than Thought, with Implications for Darwinism September 20, 2022
28. Rama P. Bhatia: Environment and the Evolutionary Trajectory of Horizontal Gene Transfer April 01, 2022



30. Charles Darwin: Origin of Species: second British edition (1860), page 189
46. Ina Huang: [url=https://scholarblogs.emory.edu/evolutionshorts/2015/12/11/can-we-decide-the-direction-of-evolution/#:~:text=Many%20people%20believe%20that%20natural,random%20mutations%20that%20may%20occur




2

Did life start polyphyletic, diversified, or monophyletic, with a universal common ancestor? 

Most, if not probably all science papers today start with the premise that universal common ancestry, and the tree of life, are true. Rather than questioning Darwin's hypothesis, 160 years old by now, it remains unquestioned. That is the basis upon which all evolutionary investigations today are made. It is accepted dogma and the starting point. The question asked is not: Is the tree of life true, and is universal common ancestry (UCA) true? But: How does the evidence fit into the tree? Even among some creationists, and intelligent design proponents, universal common ancestry is accepted as a plausible and justifiable possibility. But is it so? And what, when the nested hierarchy is not detectable, and evidence is lacking? it is just wiped under the table and ignored. There are many such cases. And scientific researchers find more and more such examples.  

If one looks into the scientific literature, however, nothing is certain. O. Zhaxybayeva (2004): There is disagreement on the location of the root of the tree of life (e.g. different studies place the root: 

1. within the bacterial domain or on the branch that leads to the bacterial domain; 
2. within the eukaryotic domain; 
3. within the archaeal domain; 
4. yield inconclusive results. The timing of the organismal cenancestor is another unresolved question.41

In the meantime, the Genesis account of the special creation of each kind is often discarded from the onset or questioned. Some argue that Genesis does not require to be taken literally, it is perfectly fine to accept that it is an ancient near eastern myth, that uses figurative speech, and allegories that never were intended to be taken literally - so they say. Since Genesis is a several thousand-year-old book, a myth from ancient near eastern tribes, maybe even a copy from even older Mesopotamian texts, from the Babylonians, it by no means deserves to be trusted or taken literally. In special, when talking snakes, and angels with fiery, turning swords are mentioned. The Bible contains the highest information/semantic content in world literature. Genesis 1.1: "In the beginning, God created the heavens and the earth". That informs us in one short sentence about our origins. In information theory, semantics can be defined as the weight of the meanings” per sentence or per paragraph. There are thousands, maybe hundreds of thousands of books about origins, the beginning of the universe, life, and biodiversity, but none provide conclusive answers. All that scientific investigators can say in regard to our origins is: " probably, we suppose, we imagine, we theorize, we hypothesize, most likely, we suggest, it seems, it appears " etc. That extends through ALL evolutionary biology. The Bible, on the other hand, describes the origin of life in definitive terms: According to Genesis in the Bible, God created life during the creation week from the start and diversified it.

Gen. 1.11: Then God said, "Let the land produce vegetation: seed-bearing plants and trees on the land that bear fruit with seed in it, according to their various kinds." And it was so.
Gen. 1.21: So God created the great creatures of the sea and every living and moving thing with which the water teems, according to their kinds, and every winged bird according to its kind. And God saw that it was good.
Gen. 1.24: And God said, "Let the land produce living creatures according to their kinds: livestock, creatures that move along the ground, and wild animals, each according to its kind." And it was so.
Gen. 1.26/27: Then God said, "Let us make man in our image, in our likeness, and let them rule over the fish of the sea and the birds of the air, over the livestock, over all the earth, and over all the creatures that move along the ground." 27 So God created man in his own image, in the image of God he created him; male and female he created them.

It is important to outline: We have in Genesis a complete account of origins. We can take two stances towards the Genesis account: 1. We believe it, or 2. We don't. Darwin contradicts the Genesis account, claiming that a Universal Common Ancestor existed, about 3,5 billion years ago, and gave rise to all biological forms and diversity. Which of the two accounts is most likely true?

Alberts (2022): The living world consists of three major divisions, or domains: eukaryotes, bacteria, and archaea. The great variety of living creatures that we see around us are eukaryotes. The name is from Greek, meaning “truly nucleated”, reflecting the fact that the cells of these organisms have their DNA enclosed in a membrane-bound organelle called the nucleus. Visible by simple light microscopy, this feature was used in the early twentieth century to classify living organisms as either eukaryotes (those with a nucleus) or prokaryotes (those without a nucleus). We now know that prokaryotes comprise two of the three major domains of life, bacteria, and archaea. Eukaryotic cells are typically much larger than those of bacteria and archaea; in addition to a nucleus, they typically contain a variety of membrane-bound organelles that are also lacking in prokaryotes. The genomes of eukaryotes also tend to run much larger—containing more than 20,000 genes for humans and corals, for example, compared with 4000–6000 genes for the typical bacteria or archaea. In addition to plants and animals, the eukaryotes include fungi (such as mushrooms or the yeasts used in beer- and bread-making), as well as an astonishing variety of single-celled, microscopic forms of life. 29

Was there a First and a Last Universal Common Ancestor?

In his book, Darwin suggests that all living organisms are related by ascendency, and therefore they are all derived from ancestral species, which migrate around the world and diversify, generating the amazing biodiversity of organisms (Darwin, 1859).

K. Padian (2008): A sketch Darwin made soon after returning from his voyage on HMS Beagle (1831–36) showed his thinking about the diversification of species from a single stock (see Figure). This branching, extended by the concept of common descent, eventually formed an entire 'tree of life, developed enthusiastically by his German disciple Ernst Haeckel in the decades following the Origin. 1

Perguntas .... - Page 10 41586_2008_Article_BF451632a_Figc_HTML

Charles Darwin's 1837 sketch of the diversification of species from a single stock. Credit: CAMBRIDGE UNIV. LIB./DARWIN-ONLINE.ORG.UK

D.Moran: Though the tree of life idea had been used to visualize taxonomy by Carl Linneaus, it became foundational as a tool for the development of Darwin’s evolutionary hypothesis.  Lines connecting groups of organism branched off to more specific and supposedly related forms.  Darwin saw that the connections made to groups and the position of species within a group were the result of shared similarities through ancestral descent.  His theory was one attempt at explaining how those relationships might have come to exist.  Ancestry was presumed to give rise to multiple lineages that diverged to create new life forms.  Natural selection was the driving force for the divergence of species from a common ancestor.  Natural variation within a type of organism was the generator of novel traits.  Together, variation and selection would prove life evolved to its current time in existence.

M.A. Ragan (2009): The rapid growth of genome-sequence data since the mid-1990s is now providing unprecedented detail on the genetic basis of life, and not surprisingly is catalyzing the most fundamental re-evaluation of origins and evolution since Darwin’s day. Several papers in this theme issue argue that Darwin’s tree of life is now best seen as an approximation—one quite adequate as a description of some parts of the living world (e.g. morphologically complex eukaryotes), but less helpful elsewhere (e.g. viruses and many prokaryotes); indeed, one of our authors goes farther, proclaiming the “demise” of Darwin’s tree as a hypothesis on the diversity and seeming naturalness of hierarchical arrangements of groups of living organisms. 16

10 reasons to refute the claim of  Universal Common Ancestry 

1. The DNA replication machinery is not homologous in the 3 domains of life. 

The bacterial core replisome enzymes do not share a common ancestor with the analogous components in eukaryotes and archaea. L.S. Kaguni (2016): Genome sequencing of cells from the three domains of life, bacteria, archaea, and eukaryotes, reveals that most of the core replisome components evolved twice, independently. Thus, the bacterial core replisome enzymes do not share a common ancestor with the analogous components in eukaryotes and archaea, while the archaea and eukaryotic core replisome machinery share a common ancestor. An exception to this are the clamps and clamp loaders, which are homologous in all three domains of life.2

2. Bacteria and Archaea differ strikingly in the chemistry of their membrane lipids. 

There is no evidence of a common ancestor for any of the four glycolytic kinases or of the seven enzymes that bind nucleotides. S. Jain (2014): The composition of the phospholipid bilayer is distinct in archaea when compared to bacteria and eukarya. In archaea, isoprenoid hydrocarbon side chains are linked via an ether bond to the sn-glycerol-1-phosphate backbone. In bacteria and eukarya on the other hand, fatty acid side chains are linked via an ester bond to the sn-glycerol-3-phosphate backbone. 3 Cell membrane phospholipids are synthesized by different, unrelated enzymes in bacteria and archaea, and yield chemically distinct membranes. Bacteria and archaea have membranes made of water-repellent fatty molecules. Bacterial membranes are made of fatty acids bound to the phosphate group while archaeal membranes are made of isoprenes bonded to phosphate in a different way. This leads to something of a paradox: Since a supposed last universal common ancestor, LUCA already had an impermeable membrane for exploiting proton gradients, why would its descendants have independently evolved two different kinds of impermeable membrane?

Franklin M. Harold (2014): Membranes also pose one of the most stubborn puzzles in all of cell evolution. Shortly after the discovery of the Archaea, it was realized that these organisms differ strikingly from the Bacteria in the chemistry of their membrane lipids. Archaea make their plasma membranes of isoprenoid subunits, linked by ether bonds to glycerol-1-phosphate; by contrast, Bacteria and Eukarya employ fatty acids linked by ester bonds to glycerol-3-phosphate. There are a few partial exceptions to the rule. Archaeal membranes often contain fatty acids, and some deeply branching Bacteria, such as Thermotoga, favor isoprenoid ether lipids (but even they couple the ethers to glycerol-3-phosphate). This pattern of lipid composition, which groups Bacteria and Eukarya together on one side and Archaea on the other, stands in glaring contrast to what would be expected from the universal tree, which puts Eukarya with the Archaea 14

3. Sequences of glycolytic enzymes differ between Archaea and Bacteria/Eukaryotes. 

S. F Alnomasy (2017): Some archaeal enzymes have some similarities with bacteria, but most archaeal enzymes have no similarity with classical glycolytic pathways in Bacteria 4 There is no evidence of a common ancestor for any of the four glycolytic kinases or of the seven enzymes that bind nucleotides.

Keith A. Webster (2003): There is no evidence of a common ancestor for any of the four glycolytic kinases or of the seven enzymes that bind nucleotides. Genetic, protein and DNA analysis, together with major differences in the biochemistry and molecular biology of all three domains – Bacteria, Archaea and Eukaryota – suggest that the three fundamental cell types are distinct and evolved separately (i.e. Bacteria are not actually pro-precursors of the eukaryotes, which have sequence similarities in particular parts of their biochemistry between both Bacteria or Archaea).  Only a relatively small percentage of genes in Archaea have sequence similarity to genes in Bacteria or Eukaryota. Furthermore, most of the cellular events triggered by intracellular Ca2+ in eukaryotes do not occur in either Bacteria or Archaea. 15

4. There are at least six distinct autotrophic carbon fixation pathways.

If common ancestry were true, an ancestral Wood–Ljungdahl pathway should have become life's one and only principle for biomass production. W. Nitschke (2013): At least six distinct autotrophic carbon fixation pathways have been elucidated during the past few decades 5 Since the claim is that this is how life began fixing carbon, and the first carbon fixation pathways were anaerobic, this represents a major puzzle for proponents of common ancestry, and its proponents are led to wonder why an ancestral Wood–Ljungdahl pathway has not become life's one and only principle for biomass production. What is even more puzzling, is the fact that searches of the genomes of acetogenins for enzymes clearly homologous to those of the methanogenic C1-branch came up empty-handed with one notable exception, i.e. the initial step of CO2 reduction which is, in both cases, catalyzed by a molybdo/tungstopterin enzyme from the complex iron-sulfur molybdoenzyme (CISM) superfamily. So, partially, carbon fixation pathways share partially the same enzymes. This points clearly to a common designer choosing different routes for the same reaction but using partially convergent design. Similarities between living organisms could be because they have been designed by the same intelligence, just as we can recognize a Norman Foster building by his characteristic style, or a painting by Van Gogh. We expect to see repeated motifs and re-used techniques in different works by the same artist/designer. 

5. There is a sharp divide in the organizational complexity of the cell between eukaryotes and prokaryotes

E. V. Koonin (2010): There is a sharp divide in the organizational complexity of the cell between eukaryotes, which have complex intracellular compartmentalization, and even the most sophisticated prokaryotes (archaea and bacteria), which do not. The compartmentalization of eukaryotic cells is supported by an elaborate endomembrane system and by the actin-tubulin-based cytoskeleton. There are no direct counterparts of these organelles in archaea or bacteria. The other hallmark of the eukaryotic cell is the presence of mitochondria, which have a central role in energy transformation and perform many additional roles in eukaryotic cells, such as in signaling and cell death. 6

6. A typical eukaryotic cell is about 1,000-fold bigger by volume than a typical bacterium or archaeon

E. V. Koonin (2010): The origin of eukaryotes is a huge enigma and a major challenge for evolutionary biology. There is a sharp divide in the organizational complexity of the cell between eukaryotes, which have complex intracellular compartmentalization, and even the most sophisticated prokaryotes (archaea and bacteria), which do not. A typical eukaryotic cell is about 1,000-fold bigger by volume than a typical bacterium or archaeon, and functions under different physical principles: free diffusion has little role in eukaryotic cells, but is crucial in prokaryotes. The compartmentalization of eukaryotic cells is supported by an elaborate endomembrane system and by the actin-tubulin-based cytoskeleton. There are no direct counterparts of these organelles in archaea or bacteria. The other hallmark of the eukaryotic cell is the presence of mitochondria, which have a central role in energy transformation and perform many additional roles in eukaryotic cells, such as in signaling and cell death. 6

7.  Horizontal gene transfer (HGT)

E. V. Koonin (2012): Subsequent massive sequencing of numerous, complete microbial genomes have revealed novel evolutionary phenomena, the most fundamental of these being: pervasive horizontal gene transfer (HGT), in large part mediated by viruses and plasmids, that shapes the genomes of archaea and bacteria and call for a radical revision (if not abandonment) of the Tree of Life concept 7

8. RNA Polymerase differences

RNA Polymerase differences: Prokaryotes only contain three different promoter elements: -10, -35 promoters, and upstream elements.  Eukaryotes contain many different promoter elements: TATA box, initiator elements, downstream core promoter element, CAAT box, and the GC box to name a few.  Eukaryotes have three types of RNA polymerases, I, II, and III, and prokaryotes only have one type.  Eukaryotes form and initiation complex with the various transcription factors that dissociate after initiation is completed.  There is no such structure seen in prokaryotes.  Another main difference between the two is that transcription and translation occurs simultaneously in prokaryotes and in eukaryotes the RNA is first transcribed in the nucleus and then translated in the cytoplasm.  RNAs from eukaryotes undergo post-transcriptional modifications including: capping, polyadenylation, and splicing.  These events do not occur in prokaryotes.  mRNAs in prokaryotes tend to contain many different genes on a single mRNA meaning they are polycystronic.  Eukaryotes contain mRNAs that are monocystronic.  Termination in prokaryotes is done by either rho-dependent or rho-independent mechanisms.  In eukaryotes transcription is terminated by two elements: a poly(A) signal and a downstream terminator sequence.  8

9. Ribosome and ribosome biogenesis differences

Ribosome and ribosome biogenesis differences: Although we could identify E. coli counterparts with comparable biochemical activity for 12 yeast ribosome biogenesis factors (RBFs), only 2 are known to participate in bacterial ribosome assembly. This indicates that the recruitment of individual proteins to this pathway has been largely independent in the bacterial and eukaryotic lineages. The bacterial version of a universal ribosomal protein tends to be remarkably different from its archaeal equivalent, the same being true, even more dramatically, for the aminoacyl-tRNA synthetases. In both cases, in a sequence alignment, a position constant in composition in the Bacteria tends to be so in its archaeal homolog as well, but the archaeal and bacterial compositions for that position often differ from each other. Moreover, among the aminoacyl-tRNA synthetases, a total lack of homology between large (and characteristic) sections of the bacterial version of a molecule and its archaeal counterpart is common. 9 

10. The replication promoters of bacterial and yeast genes have different structures

A. C. Leonard (2013): Like the origins of DNA replication, the promoters of bacterial and yeast genes have different structures, are recognized by different proteins, and are not exchangeable. The absolute incompatibility between prokaryote (e.g., E. coli) and eukaryote (e.g., yeast) origins of replication and promoters, as well as DNA replication, transcription, and translation machineries, stands as a largely unrecognized challenge to the evolutionary view that the two share a common ancestor. 10

No common ancestor for Viruses

Eugene V. Koonin (2020): In the genetic space of viruses and MGEs, no genes are universal or even conserved in the majority of viruses. Viruses have several distinct points of origin, so there has never been a last common ancestor of all viruses. 11

Viruses and the tree of life (2009): Viruses are polyphyletic: In a phylogenetic tree, the characteristics of members of taxa are inherited from previous ancestors. Viruses cannot be included in the tree of life because they do not share characteristics with cells, and no single gene is shared by all viruses or viral lineages. While cellular life has a single, common origin, viruses are polyphyletic – they have many evolutionary origins. Viruses don’t have a structure derived from a common ancestor.  Cells obtain membranes from other cells during cell division. According to this concept of ‘membrane heredity’, today’s cells have inherited membranes from the first cells.  Viruses have no such inherited structure.  They play an important role by regulating population and biodiversity. 12

Eugene V. Koonin (2017): The entire history of life is the story of virus–host coevolution. Therefore the origins and evolution of viruses are an essential component of this process. A signature feature of the virus state is the capsid, the proteinaceous shell that encases the viral genome. Although homologous capsid proteins are encoded by highly diverse viruses, there are at least 20 unrelated varieties of these proteins. Viruses are the most abundant biological entities on earth and show remarkable diversity of genome sequences, replication and expression strategies, and virion structures. Evolutionary genomics of viruses revealed many unexpected connections but the general scenario(s) for the evolution of the virosphere remains a matter of intense debate among proponents of the cellular regression, escaped genes, and primordial virus world hypotheses. A comprehensive sequence and structure analysis of major virion proteins indicates that they evolved on about 20 independent occasions. Virus genomes typically consist of distinct structural and replication modules that recombine frequently and can have different evolutionary trajectories. The present analysis suggests that, although the replication modules of at least some classes of viruses might descend from primordial selfish genetic elements, bona fide viruses evolved on multiple, independent occasions throughout the course of evolution by the recruitment of diverse host proteins that became major virion components. 13

Comment: The importance of the admission that viruses do not share a common ancestor cannot be outlined enough. Researchers also admit, that under a naturalistic framework, the origin of viruses remains obscure, and has not found an explanation. One reason is that viruses depend on a cell host in order to replicate. Another is, that the virus capsid shells that protect the viral genome are unique, there is no counterpart in life. A science paper that I quote below describes capsids with a "geometrically sophisticated architecture not seen in other biological assemblies". This seems to be interesting evidence of design. The claim that their origin has something to do with evolution is also misleading - evolution plays no role in explaining either the origin of life or the origin of viruses. The fact that "no single gene is shared by all viruses or viral lineages" prohibits drawing a tree of viruses leading to a common ancestor.  

D M Raup (1983):  Life forms are made possible by the remarkable properties of polypeptides. It has been argued that there must be many potential but unrealized polypeptides that could be used in living systems. The number of possible primary polypeptide structures with lengths comparable to those found in living systems is almost infinite. This suggests that the particular subset of polypeptides of which organisms are now composed is only one of a great many that could be associated in viable biochemistries. There is no taxonomic category available to contain all life forms descended from a single event of life origin. Here, we term such a group, earthly or otherwise, a bioclade. If more than one bioclade survives, life is polyphyletic. If only one survives, it is monophyletic. We conclude that multiple origins of life in the early Precambrian is a reasonable possibility.21

W. Ford Doolittle (2007): Darwin claimed that a unique inclusively hierarchical pattern of relationships between all organisms based on their similarities and differences [the Tree of Life (TOL)] was a fact of nature, for which evolution, and in particular a branching process of descent with modification, was the explanation. However, there is no independent evidence that the natural order is an inclusive hierarchy, and incorporation of prokaryotes into the TOL is especially problematic. The only data sets from which we might construct a universal hierarchy including prokaryotes, the sequences of genes, often disagree and can seldom be proven to agree. Hierarchical structure can always be imposed on or extracted from such data sets by algorithms designed to do so, but at its base the universal TOL rests on an unproven assumption about pattern that, given what we know about process, is unlikely to be broadly true. This is not to say that similarities and differences between organisms are not to be accounted for by evolutionary mechanisms, but descent with modification is only one of these mechanisms, and a single tree-like pattern is not the necessary (or expected) result of their collective operation. Pattern pluralism (the recognition that different evolutionary models and representations of relationships will be appropriate, and true, for different taxa or at different scales or fordifferent purposes) is an attractive alternative to the quixotic pursuit of a single true TOL.20

Douglas L. Theobald (2010): In all cases tried, with a wide variety of evolutionary models (from the simplest to the most parameter rich), the multiple-ancestry models for shuffled data sets are preferred by a large margin over common ancestry models (LLR on the order of a thousand), even with the large internal branches. 17

C. P. Kempes (2021): We argue for multiple forms of life realized through multiple different historical pathways. From this perspective, there have been multiple origins of life on Earth—life is not a universal homology. By broadening the class of originations, we significantly expand the data set for searching for life.  We define life as the union of two crucial energetic and informatic processes producing an autonomous system that can metabolically extract and encode information from the environment of adaptive/survival value and propagate it forward through time. We provide a new perspective on the origin of life by arguing that life has emerged many times on Earth and that there are many forms of extant life coexisting on a variety of physical substrates. The ultimate theory of life will certainly have ingredients from abstract theories of engineering, computation, physics, and evolution, but we expect will also require new perspectives and tools, just as theories of computation have.  It should be able to highlight life as the ultimate homoplasy (convergence) rather than homology, where life is discovered repeatedly from many different trajectories.

A science forum was held at Arizona State University in February 2011, where the following dialogue between Dawkins and Venter was reported:

Venter: I'm not so sanguine as some of my colleagues here that there's only one life form on this planet we have a lot of different types of metabolism different organisms I wouldn't call you the same life-form as the one we have that lives in pH12 base that would dissolve your skin if we drop you at it. The same genetic it will have a common anything well you don't have the same genetic code in fact the micoplasmas use a different genetic code and it would not work  in yourself so there are a lot of variations on the unit
Dawkins: But you're not saying it belongs to a different tree of life from me
Venter: I well I think the Tree of Life is an artifact of some early scientific studies that aren't really holding up so the tree you know there may be a bush of life. Bush I don't like that word written but that's only I can see that so there's not a tree of life and in fact from our deep sequencing of organisms in the ocean out of now we have about 60 million different unique gene sets we found 12 that looked like a very very deep branching perhaps fourth domain of life that obviously is extremely rare that it only shows up out of those few sequences but it's still DNA based but you know the diversity we have in the DNA world I'm not so saying what in wedding ready to throw out the DNA world. 18 19

From the Last Universal Common Ancestor, LUCA, to Eukaryotic cells

C. Woese (2002): The evolution of modern cells is arguably the most challenging and important problem the field of Biology has ever faced. 40

G. E. Mikhailovsky (2021): It is puzzling why life on Earth consisted of prokaryotes for up to 2.5 ± 0.5 billion years (Gy) before the appearance of the first eukaryotes. This period, from LUCA (Last Universal Common Ancestor) to LECA (Last Eucaryotic Common Ancestor), we have named the Lucacene, to suggest all prokaryotic descendants of LUCA before the appearance of LECA. The structural diversity of eukaryotic organisms is very large, while the morphological diversity of prokaryotic cells is immeasurably lower.    37

Eukaryotes

As everywhere through evolutionary biology, the claim is that things went from less, to more complex, over long periods of time. 

D. A. Peattie:  The eukaryote has structural features that allow it to communicate better than prokaryotes, features that permit cellular aggregation and multicellular life. In contrast, the more primitive prokaryotes are less well-equipped for intercellular communication and cannot readily organize into multicellular organisms. Not only do eukaryotic cells allow larger and more complex organisms to be made, but they are themselves larger and more complex than prokaryotic cells. Whether eukaryotic cells live singly or as part of a multicellular organism, their activities can be much more complex and diversified than those of their prokaryotic counterparts. In prokaryotes, all internal cellular events take place within a single compartment, the cytoplasm. Eukaryotes contain many subcellular compartments, called organelles. Even single-celled eukaryotes can display remarkable complexity of function; some have features as specialized and diverse as sensory bristles, mouth parts, muscle-like contractile bundles, or stinging darts.

Perguntas .... - Page 10 Eukary11
Structure of a typical animal cell

On a very fundamental level, eukaryotes and prokaryotes are similar. They share many aspects of their basic chemistry, physiology and metabolism. Both cell types are constructed of and use similar kinds of molecules and macromolecules to accomplish their cellular work. In both, for example, membranes are constructed mainly of fatty substances called lipids, and molecules that perform the cell's biological and mechanical work are called proteins.
Eukaryotes and prokaryotes both use the same chemical relay system to make protein. A permanent record of the code for all of the proteins the cell will require is stored in the form of DNA. Because DNA is the master copy of the cell's (or organism's) genetic make-up, the information it contains is absolutely crucial to the maintenance and perpetuation of the cell. As if to safeguard this archive, the cell does not use the DNA directly in protein synthesis but instead copies the information onto a temporary template of RNA, a chemical relative of DNA. Both the DNA and the RNA constitute a "recipe" for the cell's proteins. The recipe specifies the order in which amino acids, the chemical subunits of proteins, should be strung together to make the functional protein. Protein synthesis both in eukaryotes and prokaryotes takes place on structures called ribosomes, which are composed of RNA and protein. This illustrates one way in which prokaryotes and eukaryotes are similar and highlights the idea that differences between these organisms are often architectural. In other words, both cell types use the same bricks and mortar, but the structures they build with these materials vary dramatically.

The prokaryotic cell can be compared to a studio apartment: a one-room living space that has a kitchen area abutting the living room, which converts into a bedroom at night. All necessary items fit into their own locations in one room. There is an everyday; washable rug. Room temperature is comfortable-not too hot, not too cold. Conditions are adequate for everything that must occur in the apartment, but not optimal for any specific activity. In a similar way, all of the prokaryote's functions fit into a single compartment. The DNA is attached to the cell's membrane. Ribosomes float freely in the single compartment. Cellular respiration-the process by which nutrients are metabolized to release energy-is carried out at the cell membrane; there is no dedicated compartment for respiration. A eukaryotic cell can be compared to a mansion, where specific rooms are designed for particular activities. The mansion is more diverse in the activities it supports than the studio apartment. It can accommodate overnight guests comfortably and support social activities for adults in the living room or dining room, for children in the playroom. The baby's room is warm and furnished with bright colors and a soft, thick carpet. The kitchen has a stove, a refrigerator and a tile floor. Items are kept in the room that is most appropriate for them, under conditions ideal for the activities in that specific room. A eukaryotic cell resembles a mansion in that it is subdivided into many compartments. Each compartment is furnished with items and conditions suitable for a specific function, yet the compartments work together to allow the cell to maintain itself, to replicate and to perform more specialized activities.

Taking a closer look, we find three main structural aspects that differentiate prokaryotes from eukaryotes. The definitive difference is the presence of a true (eu) nucleus (karyon) in the eukaryotic cell. The nucleus, a double-membrane casing, sequesters the DNA in its own compartment and keeps it separate from the rest of the cell. In contrast, no such housing is provided for the DNA of a prokaryote. Instead the genetic material is tethered to the cell membrane and is otherwise allowed to float freely in the cell's interior. It is interesting to note that the DNA of eukaryotes is attached to the nuclear membrane, in a manner reminiscent of the attachment of prokaryotic DNA to the cell's outer membrane. 28

The greatest discontinuity in evolution: The gap from prokaryotes to eukaryotes

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Ro Y. STANIER et. al., (1963) “The basic divergence in cellular structure, which separates the bacteria and blue-green algae from all other cellular organisms, represents the greatest single evolutionary discontinuity to be found in the presentday world” 31

E. V. Koonin (2002):The eukaryotic chromatin remodeling machinery, the cell cycle regulation systems, the nuclear envelope, the cytoskeleton, and the programmed cell death (PCD, or apoptosis) apparatus all are such major eukaryotic innovations, which do not appear to have direct prokaryotic predecessors.25

E. Derelle et.al.,(2006): The unicellular green marine alga Ostreococcus tauri is the world's smallest free-living eukaryote known to date, and encodes the fewest number of genes. It has been hypothesized, based on its small cellular and genome sizes, that it may reveal the “bare limits” of life as a free-living photosynthetic eukaryote, presumably having disposed of redundancies and presenting a simple organization and very little noncoding sequence. 27 It has a genome size of 12.560,000 base pairs, 8,166 genes and 7745 proteins. in comparison, the simplest free-living bacteria today is Pelagibacter ubique get by with about 1,300 genes and 1,308,759 base pairs and code for 1,354 proteins.

T. Cavalier-Smith (2010):  This radical transformation of cell structure (eukaryogenesis) is the most complex and extensive case of quantum evolution in the history of life. Beforehand earth was a sexless, purely bacterial and viral world. Afterwards sexy, endoskeletal eukaryotes evolved morphological complexity: diatoms, butterflies, corals, whales, kelps, and trees 32

E. Szathmáry (2015): The divide between prokaryotes and eukaryotes is the biggest known evolutionary discontinuity. There is no space here to enter the whole maze of the recent debate about the origin of the eukaryotic cells; suffice it to say that the picture seems more obscure than 20 y ago. How did eukaryotic life evolve? This is one of the most controversial and puzzling questions in evolutionary history. Life began as single-celled, independent organisms that evolved into cells containing membrane-bound, specialized structures known as organelles. What’s clear is that this new type of cell, the eukaryote, is more complex than its predecessors. What’s unclear is how these changes took place. 24

A.Kauko (2018): The origin of eukaryotes is one of the central transitions in the history of life; without eukaryotes there would be no complex multicellular life.36

F.Rana (2019): The origin of eukaryotes is one of the hardest and most intriguing problems in the study of the evolution of life, and arguably, in the whole of biology. On average, the volume of eukaryotic cells is about 15,000 times larger than that of prokaryotic cells.30

Josip Skejo (2021): Eukaryotic cells are vastly more complex than prokaryotic cells as evident by their endomembrane system 26

A. Spang (2022): Archaea and Bacteria are often referred to as primary domains of life while eukaryotes form a secondary domain of life. The prevalence of horizontal gene transfer (HGT) via both mobile genetic elements (MGEs) and viruses but also directly between distinct organisms has to some extent questioned the concept of a Tree of Life (TOL), which may be more correctly represented as a network including both vertical and horizontal branches.

Arizona State University (2022): The transition from prokaryote to eukaryote has remained a central mystery biologists are still trying to untangle. How this crucial transition came to be remains a central mystery in biology.40

Origin of eukaryotes

M. A. O’Malley (2015):  There are very roughly two main hypotheses for the evolution of eukaryotes: one sees the process as mutation-driven, with lateral acquisitions of genes and organisms also involved but in a causally secondary way; the other sees eukaryogenesis as driven causally by the acquisition of the mitochondrion. The acquisition of the mitochondrion is often portrayed as a one-off event that instigated a rapid transformation with major evolutionary outcomes 38

Eugene V. Koonin (2015): The origin of eukaryotes is one of the hardest and most intriguing problems in the study of the evolution of life, and arguably, in the whole of biology. Compared to archaea and bacteria (collectively, prokaryotes), eukaryotic cells display a qualitatively higher level of complexity of intracellular organization. Unlike the great majority of prokaryotes, eukaryotic cells possess an extended system of intracellular membranes that includes the eponymous eukaryotic organelle, the nucleus, and fully compartmentalizes the intracellular space. In eukaryotic cells, proteins, nucleic acids and small molecules are distributed by specific trafficking mechanisms rather than by free diffusion as is largely the case in bacteria and archaea. Thus, eukaryotic cells function on different physical principles compared to prokaryotic cells, which is directly due to their (comparatively) enormous size. The gulf between the cellular organizations of eukaryotes and prokaryotes is all the more striking because no intermediates have been found. The actin and tubulin cytoskeletons, the nuclear pore, the spliceosome, the proteasome, and the ubiquitin signalling system are only a few of the striking examples of the organizational complexity that seems to be a ‘birthright’ of eukaryotic cells. The formidable problem that these fundamental complex features present to evolutionary biologists makes Darwin’s famous account of the evolution of the eye look like a simple, straightforward case. Indeed, so intimidating is the challenge of eukaryogenesis that the infamous notion of ‘irreducible complexity’ has sneaked into serious scientific debate: 

C. G. Kurland: Genomics and the Irreducible Nature of Eukaryote Cells (2006): Data from many sources give no direct evidence that eukaryotes evolved by genome fusion between archaea and bacteria. Because their cells appear simpler, prokaryotes have traditionally been considered ancestors of eukaryotes. Here, we review recent data from proteomics and genome sequences suggesting that eukaryotes are a unique primordial lineage. Mitochondria, mitosomes, and hydrogenosomes are a related family of organelles that distinguish eukaryotes from all prokaryotes. Recent analyses also suggest that early eukaryotes had many introns, and RNAs and proteins found in modern spliceosomes. Nuclei, nucleoli, Golgi apparatus, centrioles, and endoplasmic reticulum are examples of cellular signature structures (CSSs) that distinguish eukaryote cells from archaea and bacteria. Comparative genomics, aided by proteomics of CSSs such as the mitochondria, nucleoli, and spliceosomes, reveals hundreds of proteins with no orthologs  (Orthologs are genes in different species that evolved from a common ancestral gene by speciation) evident in the genomes of prokaryotes; these are the eukaryotic signature proteins (ESPs). The many ESPs within the subcellular structures of eukaryote cells provide landmarks to track the trajectory of eukaryote genomes from their origins. In contrast, hypotheses that attribute eukaryote origins to genome fusion between archaea and bacteria are surprisingly uninformative about the emergence of the cellular and genomic signatures of eukaryotes (CSSs and ESPs). The failure of genome fusion to directly explain any characteristic feature of the eukaryote cell is a critical starting point for studying eukaryote origins. 34

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TP53: Tumor Suppression and Transcriptional Regulation

Following activation, the TP53 protein functions predominantly as a transcription factor. The TP53 protein forms a homotetramer that binds to specific Tp53 response elements in genomic DNA to direct the transcription of a large number of protein-coding genes. The requirement for TP53 transcriptional activity in tumor suppression has been examined by systematically mutating the transactivation domains of the TP53 protein, rendering it either partially or wholly transcriptionally defective. Importantly, mutations resulting in complete loss of TP53 transcriptional activity ablate its ability to prevent tumor formation, supporting the concept that transcriptional regulation is central to the tumor-suppressor function. TP53-mediated tumor suppression is governed by transcriptional regulation.

TP53-mediated transcriptional regulation varies according to the type of stress stimulus and type of cell, so that appropriate corrective processes can be implemented. For example, minor DNA damage may institute cell-cycle arrest and activate DNA-repair mechanisms, whereas stronger TP53-activating signals induce senescence or apoptosis. Accordingly, the TP53 transcriptional response varies depending on the nature of the activating signal and the type of cell. The number of known or suspected TP53 target genes has increased into the thousands with dramatic differences in transcriptional responses observed among different cell types, different TP53-inducing stress stimuli, and varying time points following TP53 activation. These studies paint an increasingly complex picture of the modes by which TP53 can regulate gene expression. For example, before TP53 activation, a subset of target genes is transcriptionally repressed by the TP53 protein. More recently appreciated functions of the TP53 protein include widespread binding and modulation of enhancer regions throughout the genome and transcriptional activation of noncoding RNAs. Interestingly, the TP53-activated long noncoding RNA, lincRNA-p21, exerts widespread suppression of gene expression. The list of proposed TP53 target genes is vast and they are known to influence diverse cellular processes, including apoptosis, cell-cycle arrest, senescence, DNA-damage repair, metabolism, and global regulation of gene expression, each of which could potentially contribute to its tumor-suppressor function.

The p53 pathway responds to various cellular stress signals (the input) by activating p53 as a transcription factor (increasing its levels and protein modifications) and transcribing a programme of genes (the output) to accomplish a number of functions. Together, these functions prevent errors in the duplication process of a cell that is under stress, and as such the p53 pathway increases the fidelity of cell division and prevents cancers from arising. 63

K. D. Sullivan (2017): The p53 polypeptide contains several functional domains that work coordinately, in a context-dependent fashion, to achieve DNA binding and transactivation. (the increased rate of gene expression) 68

K. Kamagata (2020): Interactions between DNA and DNA-binding proteins play an important role in many essential cellular processes. A key function of the DNA-binding protein p53 is to search for and bind to target sites incorporated in genomic DNA, which triggers transcriptional regulation. How do p53 molecules achieve “rapid” and “accurate” target search in living cells?  The genome encompasses DNA sequences that encode genes, and gene editing is the genetic engineering of a specific DNA sequence, including insertion, deletion, modification, and replacement. The main player in genome editing is a type of protein that can bind to DNA, known as DNA-binding proteins. DNA-binding proteins include enzymes, which can cut DNA or ligate two DNA molecules, and transcription factors, which can activate or deactivate gene expression. These proteins are classified into DNA sequence-specific and nonspecific binders. The transcription factor p53 can induce multiple tumor suppression functions, such as cell cycle arrest, DNA repair, and apoptosis. p53 is presumed to solve the target search problem by utilizing 3D diffusion, 1D diffusion along DNA, and intersegmental transfer between two DNAs in the cell. 67

E. Sentur (2016): Genomic stability is a critical requirement for cell survival and the prevention of tumorigenesis. In order to ensure that mutations that result from DNA damage are not passed on to daughter generations, the cell must pause and repair the damage. The cellular response pathway is a network that involves sensors of damage that ultimately transmit signals to mediator proteins that regulate the transcription of effector proteins that play an important role in arresting the cell cycle. In the cell cycle, transitions (G1/S, intra S, G2/M) that lead from DNA replication to mitosis are monitored for successful completion. In the event of DNA damage, genotoxic stress, or ribonucleotide depletion, cell cycle checkpoints prevent progression to the next phase of the cell cycle until the damage is repaired, the stress is removed, or nutrients are replenished. Other pathways may be activated that result in programmed cell death if the damage is irreparable. When there are defects in the cell cycle checkpoints, gene mutations, chromosome damage, and aneuploidy can result and ultimately, cell transformation can be a consequence of such defects.

p53, a transcription factor and tumor suppressor protein, can regulate the expression of proteins that play critical roles in growth arrest and apoptosis (programmed cell death). p53 plays a critical role both in the G1/S checkpoint, in which cells arrest prior to DNA replication and have a 2N content of DNA, and in the G2/M checkpoint, in which arrest occurs before mitosis and cells have a 4N content of DNA. The activation of p53 following DNA damage results in the expression of many proteins which are important in cell cycle arrest, repair, and apoptosis. Cells in which p53 is deleted or mutated lose the G1 checkpoint and no longer arrest at the G1/S transition. Although they maintain a G2 arrest, this arrest can decay over time thus allowing cells to enter mitosis with unrepaired DNA damage and mutations that increase the risk of progression to malignancy. People in which one allele of the p53 gene is mutated, are susceptible to sarcomas, leukemias, brain and adrenal tumors. In these tumors the remaining allele of p53 is often deleted (loss of heterozygosity) highlighting the importance of the role of p53 in genomic stability. 69

W. Feroz (2020):  “The protein P53 is a transcription factor encoded by the gene TP53 which is the most commonly mutated tumor suppressor gene in human cancers, it performs multiple regulatory functions by receiving information, modulating and relaying the information, carrying out multiple downstream signals such as cellular senescence, cell metabolism, inflammation, autophagy, and other biological processes which control the survival and death of abnormal cells”.  “P53 also plays a crucial role in determining cell’s response to various cellular stress like DNA damage, nutrient deficiency, and hypoxia by inducing gene transcription, which controls the process of cell cycle and programmed cell death (apoptosis)”. Generally, in a cell, P53 is an unstable protein that is present in meagre amounts inside the cell because it is continuously degraded by MDM2 proteins. P53 has a complex array of functions.
P53 plays a central role in DNA damage response and is considered the “Guardian of the Genome”. DNA damage response is dependent on the nature of the stress signal, the cell type, timing, and intensity of the stress signal. “DNA damage promotes Post-translational modifications (PTMs) on P53”, “whereas oncogenic stress activates Alternative reading frame (ARF) tumour suppressor protein to inhibit MDM2”. “In response, P53 can activate cell cycle arrest, repair the damaged DNA, activates specific cell death pathways, and metabolic changes in the cell. “DNA damage causes P53activation which induces an array of genes spanning multiple functions, using various genetic studies the best known P53 targets” are 

1. DNA damage response genes, 
2. “cell cycle arrest genes, 
3. “genes involved in apoptosis, 
4. metabolism, and 
5. “Post-translational regulators of P53 

Expression profiling study identified many target genes of P53 whose number ranged from less than 100 to more than 1500 based on the conditions of P53 activation and approaches used for data processing, “the main drawback was that they could not differentiate among the direct and indirect targets of P53”. 70

Comment: This transcription factor p53 actively searches targets in the genome to be expressed. This is a goal-oriented process implemented to activate processes that avoid the origination of cancer. Various players are required that work as a system. It is a team play.  The p53 transcription factor has to be able to perform “rapid” and “accurate” target search, recognize it, and bind to the DNA sequence so it can be expressed, but most important, before it can act like a switch commanding "on", the gene sequences to be expressed must be there, that is, the actors that are recruited to permit DNA repair, or apoptosis (cell death). It is an all-or-nothing business to convey the function to suppress the development and growth of tumors, and consequently, death. In other words, this is an irreducibly complex system where p53 would be functionless unless the actors to act upon were not there. 

The concepts of machine and factory error monitoring, checking, and repair are all tasks performed with goal-directedness, intent, and purpose
 
1. Repairing things that are broken, malfunctioning, or instantiating complex systems that autonomously prevent things to break are always actions performed by agents with intentions, volition, goal-orientedness, foresight, understanding, and know-how.
2. Man-made machines almost always require direct intelligent intervention by technicians to recognize errors, find which parts of a machine are broken, know how to remove and replace them without breaking surrounding parts of the device, and know how to construct the part that has to be replaced with fidelity, and re-insert and re-connect it where the part was removed. The entire process is complex, demanding know-how, and depends on a high quantity of intelligence in performing all involved actions.
3. Man has not been able to create a fully autonomous, preprogrammed machine or factory, that is able to quality and error monitor all manufacturing processes and the correct performance of all devices involved, and if the products are up to the required quality standard, and, if something drives havoc, repair and re-establish normal function of what was broken or malfunctioning without external intervention.
4. C.H. Loch writes in the science paper: "Organic Production Systems: What the Biological Cell Can Teach Us About Manufacturing" (2004): Biological cells are preprogrammed to use quality-management techniques used in manufacturing today. The cell invests in defect prevention at various stages of its replication process, using 100% inspection processes, quality assurance procedures, and foolproofing techniques. An example of the cell inspecting each and every part of a product is DNA proofreading. As the DNA gets replicated, the enzyme DNA polymerase adds new nucleotides to the growing DNA strand, limiting the number of errors by removing incorrectly incorporated nucleotides with a proofreading function. Following is an impressive example:  Unbroken DNA conducts electricity, while an error blocks the current. Some repair enzymes exploit this. One pair of enzymes lock onto different parts of a DNA strand. One of them sends an electron down the strand. If the DNA is unbroken, the electron reaches the other enzyme and causes it to detach. I.e. this process scans the region of DNA between them, and if it’s clean, there is no need for repairs. But if there is a break, the electron doesn’t reach the second enzyme. This enzyme then moves along the strand until it reaches the error, and fixes it. This mechanism of repair seems to be present in all living things, from bacteria to man. Know-how is needed: 

a. to know that something is broken (DNA damage sensing) 
b. to identify where exactly it is broken 
c. to know when to repair it (e.g. one has to stop/or put on hold some other ongoing processes, in other words, one needs to know lots of other things, one needs to know the whole system, otherwise one creates more damage…) 
d. to know how to repair it (to use the right tools, materials, energy, etc, etc, etc ) 
e. to make sure that the repair was performed correctly. (this can be observed in DNA repair as well)

5. On top of that: Cells do not even wait until a protein machine fails, but replace it long before it has a chance to break down. Furthermore, it completely recycles the machine that is taken out of production. The components derived from this recycling process can be used not only to create other machines of the same type but also to create different machines if that is what is needed in the “plant.” This way of handling its machines has some clear advantages for the cell. New capacity can be installed quickly to meet current demand. At the same time, there are never idle machines around taking up space or hogging important building blocks. Maintenance is a positive “side effect” of the continuous machine renewal process, thereby guaranteeing the quality of output. Finally, the ability to quickly build new production lines from scratch has allowed the cell to take advantage of a big library of contingency plans in its DNA that allow it to quickly react to a wide range of circumstances, as we will describe next.
6. The more sophisticated, advanced, autonomous, complex, and information-driven machines or factories are, the more they carry the hallmark of design. The very concepts of error monitoring, checking, and repair, and replacement in advance to avoid future break-ups are tasks performed with goal-directedness, and purpose. Biological cells are far more advanced than any machine and factory ever devised and invented by man. It is therefore rational and warranted to infer, that biological cells were designed. 

Genetic entropy: Random mutations deteriorate the genome

M.LYNCH (2003): Although uncertainties remain with respect to the form of the mutational-effect distribution, a great deal of evidence from several sources strongly suggests that the overall effects of mutations are to reduce fitness. Indirect evidence comes from asymmetrical responses to artificial selection on life history traits, suggesting that variance for these traits is maintained by downwardly skewed distributions of mutational effects. More direct evidence comes from spontaneous mutation accumulation (MA) experiments in Drosophila, Caenorhabditis elegans, wheat, yeast, Escherichia coli, and different mutation accumulation (MA) experiments in Arabidopsis. All of these experiments detected downward trends in mutation accumulation (MA) line population mean fitness relative to control populations as generations accrued. As far as we know, there is no case of even a single MA line maintained by bottlenecking that showed significantly higher fitness than its contemporary control populations. 48

M.C. Whitlock (2004): The overall effect of mutation on a population is strongly dependent on the population size. A large population has many new mutations in each generation, and therefore the probability is high that it will obtain new favorable mutations. This large population also has effective selection against the bad mutations that occur; deleterious mutations in a large population are kept at a low frequency within a balance between the forces of selection and those of mutation. A population with relatively fewer individuals, however, will have lower fitness on average, not only because fewer beneficial mutations arise, but also because deleterious mutations are more likely to reach high frequencies through random genetic drift. This shift in the balance between fixation of beneficial and deleterious mutations can result in a decline in the fitness of individuals in a small population and, ultimately, may lead to the extinction of that population. As such, a change in population size may determine the ultimate fate of a species affected by anthropogenic change.49

J.C.Sandord (2022): Genetic Entropy is the genetic degeneration of living things.  Genetic entropy is the systematic breakdown of the internal biological information systems that make life alive.  Genetic entropy results from genetic mutations, which are typographical errors in the programming of life (life’s instruction manuals). Mutations systematically erode the information that encodes life’s many essential functions.  Biological information consists of a large set of specifications, and random mutations systematically scramble these specifications – gradually but relentlessly destroying the programming instructions essential to life. Genetic entropy is most easily understood on a personal level. In our bodies there are roughly 3 new mutations (word-processing errors), every cell division. Our cells become more mutant, and more divergent from each other every day. By the time we are old, each of our cells has accumulated tens of thousands of mutations. Mutation accumulation is the primary reason we grow old and die.  This level of genetic entropy is easy to understand. There is another level of genetic entropy that affects us as a population. Because mutations arise in all of our cells, including our reproductive cells, we pass many of our new mutations to our children. So mutations continuously accumulate in the population – with each generation being more mutant than the last. So not only do we undergo genetic degeneration personally, we also are undergoing genetic degeneration as a population. This is essentially evolution going the wrong way. Natural selection can slow down, but cannot stop, genetic entropy on the population level.  Apart from intelligence, information and information systems always degenerate. This is obviously true in the human realm, but is equally true in the biological realm (contrary to what evolutionists claim).  The more technical definition of entropy, as used by engineers and physicists, is simply a measure of disorder. Technically, apart from any external intervention, all functional systems degenerate, consistently moving from order to disorder (because entropy always increases in any closed system). For the biologist it is more useful to employ the more general use of the word entropy, which conveys that since physical entropy is ever-increasing (disorder is always increasing), therefore there is universal tendency for all biological information systems to degenerate over time - apart from intelligent intervention.47


23. James A. Shapiro: Evolution: A View from the 21st Century 2011
40. James Shapiro: Physiology of the read–write genome 9 March 2014
41. Spetner, Lee: The Evolution Revolution: Why Thinking People Are Rethinking the Theory of Evolution 2014
42. James A. Shapiro: How life changes itself: The Read–Write (RW) genome 2013 Sep
43. Science Daily: Study challenges evolutionary theory that DNA mutations are random  January 12, 2022
44. J. Grey Monroe: Mutation bias reflects natural selection in Arabidopsis thaliana 12 January 2022
45. Ryan M. Hull: Environmental change drives accelerated adaptation through stimulated copy number variation June 27, 2017
47. J.C.Sanford: Genetic entropy 2022
48. Michael Lynch: TOWARD A REALISTIC MODEL OF MUTATIONS AFFECTING FITNESS 2003 Mar
49. Michael C. Whitlock: Fixation of New Mutations in Small Populations 2004
50. Uncommon descent: Some Thoughts From A Reader On Behe’s Vindication At Lehigh February 18, 2021
51. Sean W Buskirk: Adaptive evolution of nontransitive fitness in yeast Dec 29, 2020
52. Natural History Museum: What is natural selection?
53. Aditi Gupta: Evolution of Genome Size in Asexual Digital Organisms 16 May 2016
54. D. Joseph: GENETIC DEGENERATION—EVIDENCE FOR INDEPENDENT ORIGINS  August 15, 2021
55. John C. Sanford: Multiple Overlapping Genetic Codes Profoundly Reduce the Probability of Beneficial Mutation 2013
58. John Michael Fischer: Debunking Evolution 2022
59. William DeJong: The Evolutionary Dynamics of Digital and Nucleotide Codes: A Mutation Protection Perspective Feb 13, 2011
60. Niwrad: The Darwinism Contradiction Of Repair Systems  September 15, 2009
61. Marc Tollis: Peto’s Paradox: how has evolution solved the problem of cancer prevention? 13 July 2017
62. J. Scott Turner: The Tinkerer's Accomplice: How Design Emerges from Life Itself 30 september 2010
63. Brandon J. Aubrey: Tumor-Suppressor Functions of the TP53 Pathway 2016
64. A.B. Williams: p53 in the DNA-Damage-Repair Process 2016 May; 6
65. Rodrigo S. Galhardo: Extreme Genome Repair 2012 Apr 4. 
66. T. Devitt: In the lab, scientists coax E. coli to resist radiation damage March 17, 2014
67. Kiyoto Kamagata: How p53 Molecules Solve the Target DNA Search Problem: A Review 2020 Feb; 21
68. Kelly D Sullivan: Mechanisms of transcriptional regulation by p53 2017 Nov 10
69. Emir Senturk: p53 and Cell Cycle Effects After DNA Damage 2016 Jan 14
70. Wasim Feroz: Exploring the multiple roles of guardian of the genome: P53 16 November 2020
71. Rick Durrett: Waiting for Two Mutations: With Applications to Regulatory Sequence Evolution and the Limits of Darwinian Evolution 2008 Nov
72. Michael Behe: The Edge of Evolution: The Search for the Limits of Darwinism 2008
73. Joseph B Fischer: Response to Critics, Part 2: Sean Carroll Jun 27, 2007
74. Michael Behe: The Edge of Evolution: The Search for the Limits of Darwinism 17 junho 2008
75. Gert Korthof: Either Design or Common Descent 22 July 2007
76. Uncommon descent: Fossil Discontinuities: A Refutation Of Darwinism And Confirmation Of Intelligent Design  October 13, 2018
77. John Sanford: The waiting time problem in a model hominin population 17 September 2015
78. Rick Durrett: Waiting for Two Mutations: With Applications to Regulatory Sequence Evolution and the Limits of Darwinian Evolution 2008 Nov  3
79. John Sanford: The Origin of Man and the “Waiting Time” Problem August 10, 2016
80. Gerd B. Muller: The extended evolutionary synthesis: its structure, assumptions and predictions 9 July 2015

J. C. Sanford, Genetic Entropy (2005), p. 47: Natural selection has a fundamental problem. It involves the enormous chasm that exists between genotypic change (a molecular mutation) and phenotypic selection (on the level of the whole organism). There needs to be selection for billions of almost infinitely subtle and complex genetic differences on the molecular level. But this can only be done by controlling reproduction on the level of the whole organism. When Mother Nature selects for or against an individual within a population, she has to accept or reject a complete set of 6 billion nucleotides—all at once! It’s either take the whole book or have nothing of it. In fact, Mother Nature never sees the individual nucleotides. She sees the whole organism. She never has the luxury of seeing, or selecting for, any particular nucleotide. We start to see what a great leap of faith is required to believe that by selecting or rejecting a whole organism, Mother Nature can precisely control the fate of billions of individual misspellings within the assembly manual.

Nearly-neutral mutations have infinitesimally small effects on the genome as a whole. Mutations at all near-neutral nucleotide positions are automatically subject to random drift, meaning they are essentially immune to selection. Their fitness effects are so miniscule that they are masked by even the slightest fluctuations, or noise, in the biological system. —Genetic Entropy, J. C. Sanford,  p. 72

Noise always remains a severe constraint to natural selection. Under artificial conditions, plant and animal breeders have been able to very successfully select for a limited number of traits. They have done this by employing intelligent design to deliberately minimize noise. They have used blocking techniques, replication, statistical analysis, truncation selection, and highly controlled environments. Natural selection does none of this. It is, by definition, a blind and uncontrolled process, subject to unconstrained noise and unlimited random fluctuations. —Genetic Entropy, J. C. Sanford,  p. 97

The problem of near-neutrality is much more severe for beneficial mutations than for deleterious mutations. Essentially every beneficial mutation must fall within Kimura’s “no-selection zone.” All such mutations can never be selected for. —Genetic Entropy, J. C. Sanford,  p. 136

There is only one evolutionary mechanism. That mechanism is mutation/selection (the Primary Axiom). There is no viable alternative mechanism for the spontaneous generation of genomes. It is false to say that mutation selection is only one of various mechanisms of evolution. There are several types of mutations and there are several types of selection but there is still only one basic evolutionary mechanism (mutation/selection) The demise of the Primary Axiom leaves evolutionary theory without any viable mechanism. Without any naturalistic mechanism, evolution is not significantly different from any faith-based religion. —Genetic Entropy, J. C. Sanford,  p. 205 - 206 47

Carter, R. (2012): “When living things reproduce, they make a copy of their DNA and pass this to their progeny. From time to time, mistakes occur, and the next generation does not have a perfect copy of the original DNA. These copying errors are known as mutations. Most people think that ‘natural selection’ can dispose of harmful mutations by eliminating individuals that carry them. But ‘natural selection’ properly defined simply means ‘differential reproduction’, meaning some organisms leave more progeny than others based on the mutations they carry and the environment in which they live. Moreover, reproductive success is only affected by mutations that have a significant effect. Unless mutations cause a noticeable reduction in reproductive rates, the organisms that carry them will be just as successful in leaving offspring as all the others. In other words, if the mutations aren’t ‘bad’ enough, selection can’t ‘see’ them, cannot eliminate them, and the mutations will accumulate. The result is ‘genetic entropy. Each new generation carries all the mutations of previous generations plus their own. Over time, all these very slightly harmful mutations build up to a point that, in combination, they start to have serious effects on reproductive fitness. The downward spiral becomes unstoppable because every member of the population has the same problem: natural selection can’t choose between ‘fit’ and ‘less fit’ individuals if every member of the population is, more or less, equally mutated. The population descends into sickness and finally becomes extinct. There’s simply no way to stop it. 56

In 2021, Rob Stadler wrote at uncommon descent, a website serving the Intelligent Design community: The paper: Adaptive evolution of nontransitive fitness in yeast demonstrates by experimental evolution that evolution actually favors devolution — resulting in a less fit organism. [For me, experimental evolution provides the highest level of confidence among all evidence for evolution, because it is repeatable, is directly observable, and is prospectively designed, therefore making it possible to reduce the influence of bias and assumptions.]

Where did this paper come from? The Department of Biological Sciences at Lehigh University. So, you think, it must have come from our own Mike Behe — that would only make sense. But no, this paper was authored by those who oppose Mike at his own university! Remember, these same authors wrote a scathing review of Darwin Devolves in the journal Evolution. Now, somehow, they must hold their position of opposing Darwin Devolves, while presenting compelling evidence to support Darwin Devolves. Quite a conundrum! 50

In the Discussion, at the end of the paper, the authors confess:
Sean W Buskirk (2020): Our results show that the continuous action of selection can give rise to genotypes that are less fit compared to a distant ancestor. 51

Question: Let's suppose there was a first Last Universal Common Ancestor (LUCA) or a small population of it. How did it overcome deleterious harmful mutations, in order not to go extinct? 

Selection is a result of built-in mechanisms by organisms to adapt to the environment. 

" When we see species variations, it is evidence of superior design, of inbuilt adaptation, not the power of unguided evolution. Adaptation is one thing. Innovation an entirely different one."

Evidence in recent years has demonstrated that mutations can be far from just random but actually orchestrated by cells to adapt to environmental conditions. As such, it is a purposefully designed, pre-programmed process under the cell's control and regulation in order to react to environmental conditions and adapt to them. This goes diametrically against the orthodox evolutionary view that mutations are mere random accidents.

Spetner, Lee (2014): In my book Not By Chance! I introduced a hypothesis suggesting that much of the evolution we actually observe is the result of organisms’ built-in capability to respond adaptively to environmental inputs. I called it the nonrandom evolutionary hypothesis (NREH). This kind of evolution relies on events that are epigenetic in the broad sense. The type of evolution I have suggested is driven by nonrandom epigenetic change triggered by environmental inputs. I have suggested that an environmental change can cause the genome of an individual to be altered to effect an adaptive response to the change, and this altered form of the genome can be inherited. It is generally recognized that environmental inputs can stimulate epigenetic events, but it is not so generally recognized that a significant fraction of these are adaptive to the environment that did the stimulation. Animals and plants have the built-in ability to respond adaptively to environmental stimuli. This capability enables these plants and animals to adapt quickly to a changing environment. The ability to respond requires that an organism be able to perceive a change in the environment and have a mechanism whereby that perception leads to the activation of a latent gene or other genetic resources, which in turn leads to a phenotypic change that will grant the organism an advantage in the new environment. 

In the last several decades there were already some biologists who felt that neo-Darwinian theory could not account for large-scale evolution (Ho and Saunders 1979, Shapiro 1992, 2009, Johnston and Gottlieb 1990). Noble (2013) claims the central assumptions of neo-Darwinism “have been disproved.” I showed (Spetner 1997) that 

(1) speciation by the neo-Darwinian process is so highly improbable that it should be considered impossible, and 
(2) when random mutations were shown to produce some microevolution, they were not the kind of mutations that could lead to Common Descent even if they were to operate over an unlimited span of time. 

Random point mutations, which neo-Darwinian evolution holds are the source of novelty in evolution, have not been shown to add any information to the genome. Usually, they have been seen to have lost information. I have stated (Spetner 1997) that no random point mutation has been observed that adds information to the genome, and the statement still holds. Some biologists are now beginning to realize that the genetic changes required for evolution have to be non-random. Large nonrandom genetic changes are indeed known to occur, and these changes are under cellular control. An environmental change can be a long-term challenge, and the organism can respond through a heritable change that will serve to adapt it and its progeny to the new environment. The organism can do this through an inherent, built-in capability to alter its genome to enable it to respond to the change. The cell may have other tricks it can do as well to accomplish the same purpose. This capability has some similarity to its ability to exercise its short-term control. James Shapiro has suggested that cells have the capability of doing their own genetic engineering. This capability is built into the cell, which enables organisms to alter their genome to adapt to a changing environment. Organisms thus have the capability to adapt quickly to a new environment. The genetic rearrangements that will reveal the adaptive genes are known to be triggered by inputs from the environment.  41

James Shapiro (2011): Stated in terms of an electronic metaphor, the view of traditional genetics and conventional evolutionary theory is that the genome is a read-only memory (ROM) system subject to change by stochastic damage and copying errors. For over six decades, however, an increasingly prevalent alternative view has gained prominence. The alternative view has its basis in cytogenetic and molecular evidence. This distinct perspective treats the genome as a read-write (RW) memory system subject to nonrandom change by dedicated cell functions. The radical difference between the ROM and RW views of genomic information storage is basic to a 21st Century understanding of all aspects of genome action in living cells. 23

We can distinguish at least seven distinct but interrelated genomic functions essential for survival, reproduction, and evolution: 

1. DNA condensation and packaging in chromatin 
2. Correctly positioning DNA-chromatin complexes through the cell cycle 
3. DNA replication once per cell cycle 
4. Proofreading and repair  
5. Ensuring accurate transmission of replicated genomes at cell division 
6. Making stored data accessible to the transcription apparatus at the right time and place 
7. Genome restructuring when appropriate 

In all organisms, functions 1 through 6 are critical for normal reproduction, and quite a few organisms also require function 7 during their normal life cycles. We humans, for instance, could not survive if our lymphocytes (immune system cells) were incapable of restructuring certain regions of their genomes to generate the essential diversity of antibodies needed for adaptive immunity. In addition, function 7 is essential for evolutionary change. 23

On a side note: One of the examples of objects that have the imprint of design is: Creating a specified complex object that performs multiple necessary/essential specific functions simultaneously ( Like a swiss multi-tool army knife) Machines, tools, etc. that perform functions/reactions with multiple possible meaningful, significant outcomes and purposes/ functional products. They can operate forward and reverse, and perform/incorporate interdependent manufacturing processes ( one-pot reactions) to achieve a specific functional outcome. Dna, mentioned above incorporating 7 life-essential functions simultaneously, fits perfectly that description, and is, therefore, one of the many reasons why DNA points to intelligent design.  

James Shapiro (2011): Discoveries in cytogenetics, molecular biology, and genomics have revealed that genome change is an active cell-mediated physiological process. This is distinctly at variance with the pre-DNA assumption that genetic changes arise accidentally and sporadically. The discovery that DNA changes arise as the result of regulated cell biochemistry means that the genome is best modelled as a read–write (RW) data storage system rather than a read-only memory (ROM). Cells have a broad variety of natural genetic engineering (NGE) functions for transporting, diversifying and reorganizing DNA sequences in ways that generate many classes of genomic novelties; natural genetic engineering functions are regulated and subject to activation by a range of challenging life history events; cells can target the action of natural genetic engineering functions to particular genome locations by a range of well-established molecular interactions, including protein binding with regulatory factors and linkage to transcription; and genome changes in cancer can usefully be considered as consequences of the loss of homeostatic control over natural genetic engineering functions.40

James Shapiro (2013): It is essential for scientists to keep in mind the astonishing reliability and complexity of living cells. Even the smallest cells contain millions of different molecules combined into an integrated set of densely packed and continuously changing macromolecular structures. Depending upon the energy source and other circumstances, these indescribably complex entities can reproduce themselves with great reliability at times as short as 10–20 minutes. Each reproductive cell cycle involves literally hundreds of millions of biochemical and biomechanical events. We must recognize that cells possess a cybernetic capacity beyond our ability to imitate. Therefore, it should not surprise us when we discover extremely dense and interconnected control architectures at all levels. Simplifying assumptions about cell informatics can be more misleading than helpful in understanding the basic principles of biological function. Two dangerous oversimplifications have been (i) to consider the genome as a mere physical carrier of hypothetical units called “genes” that determine particular cell or organismal traits, and (ii) to think of the genome as a digitally encoded Read-Only Turing tape that feeds instructions to the rest of the cell about individual characters. As we are learning from the ENCODE project data, the vast majority of genomic DNA, including many so-called “non-coding” (nc) segments, participate in biologically specific molecular interactions. Moreover, the term “gene” is a theoretical construct whose functional properties and physical structure have never been possible to define rigorously. It is telling that genome sequence annotators used to call protein-coding regions (chiefly in prokaryotic DNA) “genes,” but now use the more neutral terms CDS, for “coding sequence.” The Turing tape idea falls short, as we will see, because it does not take into account direct physical participation of the genome in reproductive and regulatory interactions. The concept of a Read-Only Turing genome also fails to recognize the essential Write capability of a universal Turing machine, which fits remarkably well with the ability of cells to make temporary or permanent inscriptions in DNA  42

Gerd B. Muller et.al.,(2015):  Developmental, or phenotypic, plasticity is the capacity of an organism to change its phenotype in response to the environment. Plasticity is ubiquitous across all levels of biological organization. While the evolution of plasticity has been studied for decades, there is renewed interest in plasticity as a cause, and not just a consequence, of phenotypic evolution. For example, plasticity facilitates colonization of novel environments, affects population connectivity and gene flow, contributes to temporal and spatial variation in selection and may increase the chance of adaptive peak shifts, radiations and speciation events. Particularly contentious is the contribution of plasticity to evolution through phenotypic and genetic accommodation. Phenotypic accommodation refers to the mutual and often functional adjustment of parts of an organism during development that typically does not involve genetic mutation. Genetic accommodation may provide a mechanism for rapid adaptation to novel environments.80 

Ryan M. Hull (2017): The assertion that adaptation occurs purely through natural selection of random mutations is deeply embedded in our understanding of evolution. However, we have demonstrated that a controllable mechanism exists in yeast for increasing the mutation rate in response to at least 1 environmental stimulus and that this mechanism shows remarkable allele selectivity. Cells have a remarkable and unexpected ability to alter their own genome in response to the environment.Evidence for adaptation through genome-wide nonrandom mutation is substantial.45

More recent scientific investigations have further bolstered this finding. A more recent scientific news article reported:

Science Daily (2022): Mutations occur when DNA is damaged and left unrepaired, creating a new variation. The scientists wanted to know if mutation was purely random or something deeper. What they found was unexpected. Mutations are very non-random and it's non-random in a way that benefits the plant. It's a totally new way of thinking about mutation. Arabidopsis thaliana, or thale cress, is a small, flowering weed considered the "lab rat among plants" because of its relatively small genome comprising around 120 million base pairs. Humans, by comparison, have roughly 3 billion base pairs. It's a model organism for genetics. Lab-grown plants yield many variations.  Work began at Max Planck Institute where researchers grew specimens in a protected lab environment, which allowed plants with defects that may not have survived in nature be able to survive in a controlled space. Sequencing of those hundreds of Arabidopsis thaliana plants revealed more than 1 million mutations. Within those mutations a nonrandom pattern was revealed, counter to what was expected. At first glance, what we found seemed to contradict established theory that initial mutations are entirely random and that only natural selection determines which mutations are observed in organisms. Instead of randomness they found patches of the genome with low mutation rates. In those patches, they were surprised to discover an over-representation of essential genes, such as those involved in cell growth and gene expression. These are the really important regions of the genome. The areas that are the most biologically important are the ones being protected from mutation. The areas are also sensitive to the harmful effects of new mutations. DNA damage repair seems therefore to be particularly effective in these regions. The way DNA was wrapped around different types of proteins was a good predictor of whether a gene would mutate or not. It means we can predict which genes are more likely to mutate than others and it gives us a good idea of what's going on. The findings add a surprising twist to Charles Darwin's theory of evolution by natural selection because it reveals that the plant has evolved to protect its genes from mutation to ensure survival. The plant has evolved a way to protect its most important places from mutation. 22

J. Grey Monroe (2022): The random occurrence of mutations with respect to their consequences is an axiom upon which much of biology and evolutionary theory rests. This simple proposition has had profound effects on models of evolution developed since the modern synthesis, shaping how biologists have thought about and studied genetic diversity over the past century. From this view, for example, the common observation that genetic variants are found less often in functionally constrained regions of the genome is believed to be due solely to selection after random mutation. Yet, emerging discoveries in genome biology inspire a reconsideration of classical views. It is now known that nucleotide composition, epigenomic features and bias in DNA repair can influence the likelihood that mutations occur at different places across the genome. At the same time, we have learned that specific gene regions and broad classes of genes, including constitutively expressed and essential housekeeping genes, can exist in distinct epigenomic states. This could in turn provide opportunities for adaptive mutation biases to evolve by coupling DNA repair with features enriched in constrained loci. Indeed, evidence that DNA repair is targeted to genic regions and active genes has been found. 

While it will be important to test the degree and extent of mutation bias beyond Arabidopsis, the adaptive mutation bias described here provides an alternative explanation for many previous observations in eukaryotes. Our discovery yields a new account of the forces driving patterns of natural variation, challenging a long-standing paradigm regarding the randomness of mutation.44

Adaptation and is an engineered process, which does not happen by accident. The Cell receives macroscopic signals from the environment and responds by adaptive, nonrandom mutations. The capacity of Mammals and other multicellular organisms to adapt to changing environmental conditions is extraordinary.  In order to effectively produce and secrete mature proteins, cellular mechanisms for monitoring the environment are essential. Exposure of cells to various environmental causes accumulation of unfolded proteins and results in the activation of a well-orchestrated set of pathways during a phenomenon known as the unfolded protein response (UPR). Cells have powerful quality control networks consisting of chaperones and proteases that cooperate to monitor the folding states of proteins and to remove misfolded conformers through either refolding or degradation. Free-living organisms, which are more directly exposed to environmental fluctuations, must often survive even harsher folding stresses. These stresses not only disrupt the folding of newly synthesized proteins but can also cause misfolding of already folded proteins.  In living organisms, robustness is provided by homeostatic mechanismsAt least five epigenetic mechanisms are responsible for these life-essential processes :

- heat shock factors (HSFs)
- The unfolded protein response (UPR)
- nonhomologous end-joining and homologous recombination
- The DNA Damage Response
- The Response to Oxidative Stress

The cell modulates the signalling pathways at transcriptional, post-transcriptional, and post-translational levels. Complex signaling pathways contribute to the maintenance of systemic homeostasis. Homeostasis is the mechanistic fundament of living organisms.

Homeostasis, from the Greek words for "same" and "steady," refers to any process that living things use to actively maintain fairly stable conditions necessary for survival. It is also synonymous with robustness and adaptability.

This essential characteristic of living cells, homeostasis, is the ability to maintain a steady and more-or-less constant chemical balance in a changing environment. Cell survival requires appropriate proportions of molecular oxygen and various antioxidants. Reactive products of oxygen, calles Reactive Oxygen Species ( ROS) are amongst the most potent and omnipresent threats faced by cells. Cells, damaged by ROS, irreversibly infected, functionless and/or potentially oncogenic cells are destined for persistent inactivation or elimination, respectively. If mechanisms that do not trigger controlled and programmed Cell death ( apoptosis) are not present at day 1, the organisms cannot survive and dies. Simply put, the principle is that all of a multicellular organism's cells are prepared to suicide when needed for the benefit of the organism as a whole. They eliminate themselves in a very carefully programmed way so as to minimize damage to the larger organism.  On average, in human adults, it’s about 50-70 BILLION cells that die per day. We shed 30,000 to 50,000 skin cells every minute.

1. The control of metabolism is a fundamental requirement for all life, with perturbations of metabolic homeostasis underpinning numerous disease-associated pathologies.
2. Any incomplete Metabolic network without the control mechanisms in place to get homeostasis would mean disease and cell death.
3. A minimal metabolic network and control mechanisms had to be in place from the beginning, which means, and gradualistic explanation of the origin of biological Cells, and life is unrealistic. 
Life is an all-or-nothing business and points to a creative act of God.


The following molecules must stay in a finely tuned order and balance for life to survive:
Halogens like chlorine, fluoride, iodine, and bromine.  The body needs to maintain a delicate balance between all these elements.
Molybdenum (Mo) and iron (Fe) are essential micronutrients required for crucial enzyme activities and mutually impact their homeostasis, which means, they are interdependent on each other to maintain homeostatic levels. 
Potassium plays a key role in maintaining cell function, and it is important in maintaining fluid and electrolyte balance. Potassium-40 is probably the most dangerous light radioactive isotope, yet the one most essential to life. Its abundance must be balanced on a razor’s edge.
The ability of cells to maintain a large gradient of calcium across their outer membrane is universal. All biological cells have a low cytosolic (liquid found inside Cells ) calcium concentration, can and must keep this even when the free calcium outside is up to 20,000 times higher concentrated! 
- Nutrient uptake and homeostasis must be adjusted to the needs of the organisms according to developmental stages and environmental conditions.
Magnesium is the second most abundant cellular cation after potassium. The concentrations are essential to regulate numerous cellular functions and enzymes
Iron is required for the survival of most organisms, including bacteria, plants, and humans. Its homeostasis in mammals must be fine-tuned to avoid iron deficiency with a reduced oxygen transport 
Phosphate, as a cellular energy currency, essentially drives most biochemical reactions defining living organisms, and thus its homeostasis must be tightly regulated. 
Zinc (Zn) is an essential heavy metal that is incorporated into a number of human Zn metalloproteins. Zn plays important roles in nucleic acid metabolism, cell replication, and tissue repair and growth. Zn contributes to intracellular metal homeostasis. 
Selenium homeostasis and antioxidant selenoproteins in the brain: lack of finetuned balance has implications for disorders in the central nervous system
Copper ion homeostasis is maintained through regulated expression of genes involved in copper ion uptake. 

In the early 1960s, Ernest Nagel and Carl Hempel showed that self-regulated systems are teleological.

In his book: THE TINKERER’S ACCOMPLICE, How Design Emerges from Life Itself  J. S. TURNER, writes on page 12 :
Although I touch upon ID obliquely from time to time, I do so not because I endorse it, but because it is mostly unavoidable. ID theory is essentially warmed-over natural theology, but there is, at its core, a serious point that deserves serious attention. ID theory would like us to believe that some overarching intelligence guides the evolutionary process: to say the least, that is unlikely. Nevertheless, how design arises remains a very real problem in biology.  My thesis is quite simple: organisms are designed not so much because natural selection of particular genes has made them that way, but because agents of homeostasis build them that way. These agents’ modus operandi is to construct environments upon which the precarious and dynamic stability that is homeostasis can be imposed, and design is the result.62

Comment: Turner does not identify these agents, but Wiki describes agents as CONSCIOUS beings, which act with specific goals in mind. In the case of life, this agent made it possible for biological cells to actively maintain fairly stable levels of various metabolites and molecules, necessary for survival. We are once more, upon careful examination of the evidence in nature, justified to infer an intelligent designer as the most case-adequate explanation of the origin of homeostasis and the ability of adaptation, commonly called evolution, of all living organisms.

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Gene duplications

Gene duplication will get you a new allele, but not a novelty - additional new information - which is what evolution needs.

Levy continues: Gene duplication occurs when errors in the DNA-replication process produce multiple instances of a gene. Over generations, the versions accrue mutations and diverge, so that they eventually encode different molecules, each with their own function. Since the 1970s, researchers have found a raft of other examples of how evolution tinkers with genes — existing genes can be broken up or ‘laterally transferred’ between species. All these processes have something in common: their main ingredient is existing code from a well-oiled molecular machine.

Comment: J.Dulle: Duplicating existing information cannot produce new information.  Just as saying, “duplicating a gene does not increase the net information content of the cell” three times does not triple the information content of the sentence, duplicating a gene cannot increase the information content of the cell.  Gene duplication cannot help an organism perform some new function.  Trying to get new biological information/function by duplicating an existing gene is like thinking you can obtain an engine for your car by making a second steering wheel! 29

The following papers challenge the claim that gene duplication events could account for evolutionary novelties:

M. Hurles (2004): A duplicated gene newly arisen in a single genome must overcome substantial hurdles before it can be observed in evolutionary comparisons. First, it must become fixed in the population, and second, it must be preserved over time. Population genetics tells us that for new alleles, fixation is a rare event, even for new mutations that confer an immediate selective advantage. Nevertheless, it has been estimated that one in a hundred genes is duplicated and fixed every million years, although it should be clear from the duplication mechanisms described above that it is highly unlikely that duplication rates are constant over time. However, once fixed, three possible fates are typically envisaged for our gene duplication. Despite the slackened selective constraints, mutations can still destroy the incipient functionality of a duplicated gene: for example, by introducing a premature stop codon or a mutation that destroys the structure of a major protein domain. 30

A. K. Holloway (2007): The fate of gene duplicates subjected to diversifying selection was tested experimentally in a bacterial system. In a striking contradiction to our model, no such conditions were found. The fitness cost of carrying both plasmids increased dramatically as antibiotic levels were raised, and either the wild-type plasmid was lost or the cells did not grow. 31

J. Esfandiar (2010): Although the process of gene duplication and subsequent random mutation has certainly contributed to the size and diversity of the genome, it is alone insufficient in explaining the origination of the highly complex information pertinent to the essential functioning of living organisms. Gene duplication and subsequent evolutionary divergence certainly adds to the size of the genome and in large measure to its diversity and versatility. However, in all of the examples given above, known evolutionary mechanisms were markedly constrained in their ability to innovate and to create any novel information. This natural limit to biological change can be attributed mostly to the power of purifying selection, which, despite being relaxed in duplicates, is nonetheless ever-present.32

Comment: After gene duplication and the arising of a divergent gene, complementary changes involving the regulation of gene expression of that new gene would have to be instantiated in parallel. New gene products require a rewiring of the gene regulatory architecture to function optimally and be integrated into the existing cellular networks. That new information does not have only to be added to the genome, but on top of the gene itself, the gene regulatory program as well has to be reprogrammed with new instructions, on when to express the new gene. Neofunctionalization of the new gene would depend on the right timing of expression. That requires as well the addition of new transcription factor markers, that bind at the right place in the genome. 

This is pointed out in the following quote:

Johan Hallin (2019): One category of molecular changes that appears to play a key role in the evolution of genes that originate from gene duplication (duplicates or paralogs) are regulatory changes, i.e., changes in the gene itself or elsewhere in the genome that determine when, where, and at what level a gene is transcribed and translated. The immediate effect of gene duplication could favor gene retention or loss, or if the expression change is effectively neutral, the duplicate could remain neutral for extended periods of time. 33

Alternative evolutionary forces to natural selection

Michael Lynch (2007): First, evolution is a population-genetic process governed by four fundamental forces. Darwin articulated one of those forces, the process of natural selection. The remaining three evolutionary forces are nonadaptive in the sense that they are not a function of the fitness properties of individuals: mutation is the ultimate source of variation on which natural selection acts, recombination assorts variation within and among chromosomes, and genetic drift ensures that gene frequencies will deviate a bit from generation to generation independent of other forces. Given the century of work devoted to the study of evolution, it is reasonable to conclude that these four broad classes encompass all of the fundamental forces of evolution. 34

Eugene V Koonin (2009):“Evolutionary-genomic studies show that natural selection is only one of the forces that shape genome evolution and is not quantitatively dominant, whereas non-adaptive processes are much more prominent than previously suspected.” There’s quite a lot of this sort of thing around these days, and we confidently predict a lot more in the near future. There is no consistent tendency of evolution towards increased genomic complexity, and when complexity increases, this appears to be a non-adaptive consequence of evolution under weak purifying selection rather than an adaptation. 35

Random genetic drift

H. Allen Orr (2008): Until the 1960s almost all biologists assumed that natural selection drives the evolution of most physical traits in living creatures,  but a group of population geneticists led by Japanese investigator Motoo Kimura sharply challenged that view. Kimura argued that molecular evolution is not usually driven by “positive” natural selection—in which the environment increases the frequency of a beneficial type that is initially rare. Rather, he said, nearly all the genetic mutations that persist or reach high frequencies in populations are selectively neutral—they have no appreciable effect on fitness one way or the other. (Of course, harmful mutations continue to appear at a high rate, but they can never reach high frequencies in a population and thus are evolutionary dead ends.) Since neutral mutations are essentially invisible in the present environment, such changes can slip silently through a population, substantially altering its genetic composition over time. The process is called random genetic drift; it is the heart of the neutral theory of molecular evolution. By the 1980s many evolutionary geneticists had accepted the neutral theory. But the data bearing on it were mostly indirect; more direct, critical tests were lacking. Two developments have helped fix that problem. First, population geneticists have devised simple statistical tests for distinguishing neutral changes in the genome from adaptive ones. Second, new technology has enabled entire genomes from many species to be sequenced, providing voluminous data on which these statistical tests can be applied. The new data suggest that the neutral theory underestimated the importance of natural selection. 8

P. Gibson (2013): In conclusion, numerical simulation shows that realistic levels of biological noise result in a high selection threshold. This results in the ongoing accumulation of low-impact deleterious mutations, with deleterious mutation count per individual increasing linearly over time. Even in very long experiments (more than 100,000 generations), slightly deleterious alleles accumulate steadily, causing eventual extinction. These findings provide independent validation of previous analytical and simulation studies. Previous concerns about the problem of accumulation of nearly neutral mutations are strongly supported by our analysis. Indeed, when numerical simulations incorporate realistic levels of biological noise, our analyses indicate that the problem is much more severe than has been acknowledged, and that the large majority of deleterious mutations become invisible to the selection process. 14

E. V. Koonin (2022): Modern evolutionary theory, steeped in population genetics, gives a detailed and arguably, largely satisfactory account of microevolutionary processes: that is, evolution of allele frequencies in a population of organisms under selection and random genetic drift. However, this theory has little to say about the actual history of life, especially the emergence of new levels of biological complexity, and nothing at all about the origin of life. The preponderance of neutral and slightly deleterious changes provides for evolution by genetic drift whereby a population moves on the same level or even slightly downward on the fitness landscape, potentially reaching another region of the landscape where beneficial mutations are available. 15

Jerry A. Coyne (2009): Both drift and natural selection produce genetic change that we recognize as evolution. But there’s an important difference. Drift is a random process, while selection is the anti-thesis of randomness. … As a purely random process, genetic drift can’t cause the evolution of adaptations. It could never build a wing or an eye. That takes nonrandom natural selection. What drift can do is cause the evolution of features that are neither useful nor harmful to the organism 16

Michael Lynch (2007): Contrary to popular belief, evolution is not driven by natural selection alone. Many aspects of evolutionary change are indeed facilitated by natural selection, but all populations are influenced by non-adaptive forces of mutation, recombination, and random genetic drift. These additional forces are not simple embellishments around a primary axis of selection, but are quite the opposite—they dictate what natural selection can and cannot do … A central point to be explained is that most aspects of evolution at the genome level cannot be fully explained in adaptive terms, and moreover, that many features could not have emerged without a near-complete disengagement of the power of natural selection. This contention is supported by a wide array of comparative data, as well as by well-established principles of population genetics” 19

George Ellis (2018): If most of the variation found in evolutionary lineages is a product of random genetic drift, how does apparent design arise? It surely can’t be an accidental by-product of random events – that was the whole point of Darwin’s momentous discovery (Darwin 1872) of a mechanism to explain apparent design that is so apparent in all of nature. On the face of it, Lynch, Myers, and Moran seem to be saying the ID people are right: evolution cannot dapt life to its environment, because random effects dominate.

Horizontal DNA transfer

Libretext: Horizontal gene transfer (HGT) is the introduction of genetic material from one species to another species by mechanisms other than the vertical transmission from parent(s) to offspring. These transfers allow even distantly-related species (using standard phylogeny) to share genes, influencing their phenotypes. It is thought that HGT is more prevalent in prokaryotes, but that only about 2% of the prokaryotic genome may be transferred by this process. 25


Irreducible complexity falsifies evolution

What function could the heart exercise without blood? or pacemaking cells without there to be determined the rhythm of the heart? Or what good are the subunits of ATP synthase good for without the other subunits that make up the molecular energy turbine? What good is ATP synthase good for without a proton gradient, and the electron transport chain? What good is a nucleobase for without the base? An atom without an electron?  It seems that large structures for specific functions could only exist if all the smaller parts are in place, that are necessary to make up that larger system, and the smaller parts would have no function on their own.

Functional parts are only meaningful within a whole, in other words, it is the whole that gives meaning to its parts.  Natural selection would not select components of a complex system that would be useful only in the completion of that much larger system. It cannot select when the usefulness is only conveyed many steps later. Why would natural selection select an intermediate biosynthesis product, which has by its own no use for the organism, unless that product keeps going through all necessary steps, up to the point to be ready to be assembled in a larger system?  Never do we see blind, unguided processes leading to complex functional systems with integrated parts contributing to the overarching design goal. A minimal amount of instructional complex information is required for a gene to produce useful proteins. A minimal size of a protein is necessary for it to be functional. Thus, before a region of DNA contains the requisite information to make useful proteins, natural selection would not select a positive trait and play no role in guiding its evolution.

The argument of irreducible complexity is obvious and clear. Subparts like a piston in a car engine are only designed, when there is a goal where they will be mounted with specific fitting sizes and correct materials, and have a specific function in the machine as a whole. Individually they have no function. The same is in biological systems, which work as factories ( cells ) or machines ( cells host a big number of the most various molecular machines and equal to factory production lines ) For example, in photosynthesis, there is no function for chlorophyll individually, only when inserted in the light-harvesting complex, to catch photons, and direct their excitation energy by Förster resonance energy transfer to the reaction center in Photosystem one and two. Foreplanning is absolutely essential. This is a  simple fact, which makes the concept of  Irreducible complexity obvious concept. Nonetheless, people argue all the time that it's a debunked argument. Why? That's as if genetic mutations and natural selection had enough probability to generate interdependent individual parts being able to perform new functions while the individual would have no function unless interconnected.

To No.3: A.Y. Mulkidjanian (2007): The principle of evolutionary continuity, succinctly formulated by Albert Lehninger in his Biochemistry textbook. An adaptation that does not increase the fitness is no longer selected for and eventually gets lost in the evolution (in the current view, only those adaptations that effectively decrease the fitness end up getting lost). Hence, any evolutionary scenario has to invoke – at each and every step – only such intermediate states that are functionally useful (or at least not harmful). 21

1. In biology, there are many complex elementary components necessary to build large integrated macromolecular systems like multi-protein complexes (RNA polymerase), 3D printers (the ribosome), organelles (mitochondria), etc., where their making requires complex multistep enzyme-catalyzed biosynthesis pathways. These elementary components are only useful in the completion of that much larger system. Not rarely, these biosynthetic pathways produce intermediate products, that left without further processing, are either a) nonfunctional, or b) harmful and kill the cell (for example, Reactive Oxygen Species (ROS), in the biosynthesis pathway of Chlorophyll b.
2. A minimal amount of prescribed, pre-programmed, instructional complex information stored in genes is required to instruct the making of a) functional elementary components and b) the assembly instructions to integrate them into complex macromolecular systems. Natural selection would not fix an allele variant that would instruct the making of an intermediate, nonfunctional, or harmful elementary component, and play no role in guiding its evolution. Foreknowledge is required to get a complex biological system through implementing a biosemiotic information system (which is irreducibly complex), directing the making of functional elementary components, and assembly into the entire complex integrated system.
3. Therefore, the origin of biological systems based on biosemiotic instructions are best explained by a brilliant, super-powerful mind with foresight and intent, and not undirected evolutionary pressures.

What are the boundaries/limits of beneficial mutations? 

Natural selection does not create or add something. The innovations that permit organisms to evolve have to come from the variations/mutations of pre-existing traits in the genome. It is accidental mutations that would have to convey innovation, that natural selection would select and fix in the genome. There would not only have to be variation but also an increase in genome size. The smallest known free-living bacterium today is called Pelagibacter Ubique. It has a genome of 1,3 million nucleotides. If we suppose that the Last Universal Common Ancestor had the genome size of P.Ubique, it would have to increase to get to 3 billion nucleotides, the size of a human genome 2300 times larger in size.

Behe's second book ( After Darwin's Black Box 1996), The edge of evolution (2008) 72, gave a lot to talk.   

Aditi Gupta (2016): Genome sizes vary widely, from 250 bases in viroids to 670 billion bases in some amoebas. This remarkable variation in genome size is the outcome of complex interactions between various evolutionary factors such as mutation rate and population size. While comparative genomics has uncovered how some of these evolutionary factors influence genome size, we still do not understand what drives genome size evolution. Specifically, it is not clear how the primordial mutational processes of base substitutions, insertions, and deletions influence genome size evolution in asexual organisms. 53

D. Joseph (2021): “Genomes are the genetic specifications that allow life to exist. Specifications are obviously inherently SPECIFIC. This means that random changes in specifications will disrupt information with a very high degree of certainty. This has become especially clear ever since the publication of the ENCODE results, which show that very little of our genome is actually ‘junk DNA’. The ENCODE project also shows that most nucleotides play a role in multiple overlapping codes, making any beneficial mutations which are not deleterious at some level vanishingly rare. In the abstract of the paper titled “Multiple Overlapping Genetic Codes Profoundly Reduce the Probability of Beneficial Mutation”, the authors describe why these overlapping genetic codes present a profoundly serious challenge to evolutionary theory. 54

John C. Sanford (2013): “There is growing evidence that much of the DNA in higher genomes is poly-functional, with the same nucleotide contributing to more than one type of code. Such poly-functional DNA should logically be multiply-constrained in terms of the probability of sequence improvement via random mutation. We describe a model of this relationship, which relates the degree of poly-functionality and the degree of constraint on mutational improvement. We show that: 

a) the probability of beneficial mutation is inversely related to the degree that a sequence is already optimized for a given code; 
b) the probability of beneficial mutation drastically diminishes as the number of overlapping codes increases. 

The growing evidence for a high degree of optimization in biological systems, and the growing evidence for multiple levels of poly-functionality within DNA, both suggest that mutations that are unambiguously beneficial must be especially rare. The theoretical scarcity of beneficial mutations is compounded by the fact that most of the beneficial mutations that do arise should confer extremely small increments of improvement in terms of total biological function. This makes such mutations invisible to natural selection. Beneficial mutations that are below a population's selection threshold are effectively neutral in terms of selection, and so should be entirely unproductive from an evolutionary perspective. We conclude that beneficial mutations that are unambiguous (not deleterious at any level), and useful (subject to natural selection), should be extremely rare.” 55

Gert Korthof (2007): The book "edge of evolution" is principally about the probability of new protein-protein binding sites arising by chance and necessity. Experimental evidence (mostly chloroquine resistance) shows such protein-protein binding sites to be difficult to evolve by chance mechanisms. He says the empirical (extrapolation) of the "edge" of evolution is no more than two coordinated protein-protein binding sites could have evolved in a lineage in all the time available on earth. The flagellum has perhaps dozens of such sites. It is a quantitative argument. 75

M.Behe: Edge of evolution (2008): Recall the example of sickle cell disease. The sickle cell mutation is both a life saver and a life destroyer. It fends off malaria but can lead to sickle cell disease. However, hemoglobin C-Harlem has all the benefits of sickle, but none of its fatal drawbacks. So in western and central Africa, a population of humans that had normal hemoglobin would be worst off, a population that had half normal and half sickle would be better off, and a population that had half normal and half C-Harlem would be best of all. But if that’s the case, why bother with sickle hemoglobin? Why shouldn’t evolution just go from the worst to the best case directly? Why not just produce the C-Harlem mutation straightaway and avoid all the misery of sickle? The problem with going straight from normal hemoglobin to hemoglobin C-Harlem is that, rather than walking smoothly up the stairs, evolution would have to jump a step. C-Harlem differs from normal hemoglobin by two amino acids. In order to go straight from regular hemoglobin to C-Harlem, the right mutations would have to show up simultaneously in positions 6 and 73 of the beta chain of hemoglobin. Why is that so hard? Switching those two amino acids at the same time would be very difficult for the same reason that developing resistance to a cocktail of drugs is difficult for malaria—the odds against getting two needed steps at once are the multiple of the odds for each step happening on its own. What are those odds? Very low. The human genome is composed of over three billion nucleotides. Yet only a hundred million nucleotides seem to be critical, coding for proteins or necessary control features. The mutation rate in humans (and many other species) is around this same number; that is, approximately one in a hundred million nucleotides is changed in a baby compared to its parents (in other words, a total of about thirty changes per generation in the baby’s three-billion-nucleotide genome, one of which might be in coding or control regions).  In order to get the sickle mutation, we can’t change just any nucleotide in human DNA; the change has to occur at exactly the right spot. So the probability that one of those mutations will be in the right place is one out of a hundred million. Put another way, only one out of every hundred million babies is born with a new mutation that gives it sickle hemoglobin. Over a hundred generations in a population of a million people, we would expect the mutation to occur once by chance. That’s within the range of what can be done by mutation/selection. To get hemoglobin C-Harlem, in addition to the sickle mutation we have to get the other mutation in the beta chain, the one at position 73. The odds of getting the second mutation in exactly the right spot are again about one in a hundred million. So the odds of getting both mutations right, to give hemoglobin C-Harlem in one generation in an individual whose parents have normal hemoglobin, are about a hundred million times a hundred million (10^16 ). On average, then, nature needs about that many babies in order to find just one that has the right double mutation. With a generation time of ten years and an average population size of a million people, on average it should take about a hundred billion years for that particular mutation to arise—more than the age of the universe. 

Hemoglobin C-Harlem would be advantageous if it were widespread in Africa, but it isn’t. It was discovered in a single family in the United States, where it doesn’t offer any protection against malaria for the simple reason that malaria has been eradicated in North America. Natural selection, therefore, may not select the mutation, and it may easily disappear by happenstance if the members of the family don’t have children, or if the family’s children don’t inherit a copy of the C-Harlem gene. It’s well known to evolutionary biologists that the majority even of helpful mutations are lost by chance before they get an opportunity to spread in the population. 7 If that happens with C-Harlem, we may have to wait for another hundred million carriers of the sickle gene to be born before another new C-Harlem mutation arises. 74

Of course, providing such a powerful argument demonstrating the edge/limit of evolution, would not keep the opponents silent. Sean Carroll, an evolutionary developmental biologist, wrote a critical response in the magazine Science, named "God as Genetic Engineer", to which Behe responded on his Amazon blog. The link can be accessed in the bibliography of this chapter. 73 

Gunter Bechly (2018):Michael Behe discovered the waiting time problem as a problem for darwinism in his book the age of evolution and he didn't make a mathematical calculation but he looked at the empirical data from malaria drug resistance and what he found is that a lot of the malaria drugs resistance developed very quickly in a few years because only point mutations were necessary but in the case of chloroquine the drug chloroquine it took several decades and the reason was it was discovered later that there you needed a coordinated mutations to mutations neutral for each other had to come together to produce this kind of resistance against chloroquine and then he  simply transpose the data if you look at the vast population size of malaria microbes compared to the population size of vertebrates and their short generation time and you transpose these data he came up to the hypothesis that invertebrates were a single coordinated change he would have to need longer than the existence of the whole universe 10 to the power of 15 years now this is of course would be a problem and for example in human evolution we have all these nice fossils so if the signal coordinated change would take longer than the universe then then it would be game over so of course evolutionary biologists tried to repute me and indeed in 2008 the earth and Schmidt they published a paper in genetics where they said they have refuted his result was completely unrealistic they did they made a mathematical calculation based on the methodological apparatus of population genetics and simulations and they came with a number of 260 million years. Wonderful this is really much shorter than Big E the problem is we have only 6 million years available since the splitting of the human lineage from the chimp lineage so that is what evolutionary biologists say is the time needed for a single coordinated mutation and you have to keep in mind this is a mathematical model which always involves simplifications and simplifications may involve errors so what is more likely that the empirical data from B from a lot of drug resistance are closer to the truth or the mathematical simulation I would suggest that rather this ten to the power of 15 is closer to the the real constraint in nature but anyway we arrive at times that are much too long for for evolution to occur.76

J. B. Fischer: (2007): What about a case where 10 mutations are needed before there is a benefit? If each mutation by itself is neutral, natural selection has nothing to act on. Then the probability of all ten specific mutations ending up in one organism, even if they are acquired sequentially over many generations, is vanishingly small. Once a structure already exists, natural selection can fine-tune it. However, in some cases, natural selection is not sufficient, because multiple mutations are required, which are not beneficial in themselves. They are only beneficial after the basic structure is completed and functioning. Small mutations happen, which cause changes within a species. However,  natural selection cannot have been responsible for the huge differences between the major groups of living things with their vastly different body structures. If evolution is the only cause of the diversity of life, then pathways must exist where multiple mutations are each beneficial in themselves. Until recent advances in DNA research and biochemistry, it has not been possible to propose a detailed, step-by-step, beneficial pathway to a new biological system. 73 

The waiting time problem in a model hominin population

Rick Durrett (2008): We now show that two coordinated changes that turn off one regulatory sequence and turn on another without either mutant becoming fixed are unlikely to occur in the human population. Theorem 1 predicts a mean waiting time of 216 million years. 78

John Sanford (2015): Biologically realistic numerical simulations revealed that a population of this type required inordinately long waiting times to establish even the shortest nucleotide strings. To establish a string of two nucleotides required on average 84 million years. To establish a string of five nucleotides required on average 2 billion years. We found that waiting times were reduced by higher mutation rates, stronger fitness benefits, and larger population sizes. However, even using the most generous feasible parameters settings, the waiting time required to establish any specific nucleotide string within this type of population was consistently prohibitive.77

John Sanford (2016): Our paper shows that the waiting time problem cannot honestly be ignored. Even given best-case scenarios, using parameter settings that are grossly overgenerous (for example, rewarding a given string by increasing total fitness 10 percent), waiting times are consistently prohibitive. This is even for the shortest possible words. Establishment of just a two-letter word (two specific mutations within a hominin population of ten thousand) requires at least 84 million years. A three-letter word requires at least 376 million years. A six-letter word requires over 4 billion years. An eight-letter word requires over 18 billion years (again, see Table 2 in the paper). The waiting time problem is so profound that even given the most generous feasible timeframes, evolution fails. The mutation/selection process completely fails to reproducibly and systematically create meaningful strings of genetic letters in a pre-human population.79

Sophisticated mechanisms prevent cells to accumulate harmful mutations

Imagine changing a blueprint that instructs how to make all the complicated parts of a complex factory, and how they have to be assembled and joined to get the factory's intended end function, inserting different sizes of various sorts, instructing the replacement of one kind of material with another, changing the instructions to assemble the machines in a way that in the end, it cannot convey the intended function. It would result in catastrophic consequences. Sometimes, even switching one tiny thing with another can mean a total inability of a factory to exercise its intended functions. The chance that a random change would instead of driving havoc, improve the functioning of the factory, is negligible.  In the same sense, any random mutation in the genome is likely to result in the synthesis of a protein that does not function properly or not at all. Most mutations are detrimental, causing genetic disorders or even cancer and death.

DNA and RNA error checking and repair: What causal mechanism explains best their origin?

NIWRAD: Molecular biology shows that many complex control-repair mechanisms work inside the cell to recover genetic errors. For example, there are at least three major DNA repair mechanisms. Without such mechanisms, life would be impossible because the internal entropy of the cell would be too high and destructive. Each of them involves the complex and coordinated action of several enzymes/proteins. Random mutations and natural selection are a process that needs errors and at the same time, this process creates mechanisms to eliminate them? The bottom line is that repair mechanisms are incompatible with Darwinism in principle. Since sophisticated repair mechanisms do exist in the cell after all, then the thing to discard in the dilemma to avoid the contradiction necessarily is the Darwinist dogma. 60

J. M. Fischer: Some of the sophisticated and overlapping repair mechanisms found for DNA include:

1. A proofreading system that catches almost all errors
2. A mismatch repair system to back up the proofreading system
3. Photoreactivation (light repair)
4. Removal of methyl or ethyl groups by O6 – methylguanine methyltransferase
5. Base excision repair
6. Nucleotide excision repair
7. Double-strand DNA break repair
8. Recombination repair
9. Error-prone bypass 40

Harmful mutations happen constantly. Without repair mechanisms, life would be very short indeed and might not even get started because mutations often lead to disease, deformity, or death. So even the earliest, “simple” creatures in the evolutionist’s primeval soup or tree of life would have needed a sophisticated repair system. But the (sophisticated repair) mechanisms not only remove harmful mutations from DNA, they would also remove mutations that are believed to build new parts. So there is the problem of the evolution of (sophisticated repair) mechanisms that prevent evolution, all the way back to the very origin of life. 58

A. B. Williams (2016): Cells can revert the large variety of DNA lesions that are induced by endogenous and exogenous genotoxic attacks through a variety of sophisticated DNA-repair machineries,. Nucleotide excision repair (NER) removes a variety of helix-distorting lesions such as typically induced by UV irradiation, whereas base excision repair (BER) targets oxidative base modifications. Mismatch repair (MMR) scans for nucleotides that have been erroneously inserted during replication. DNA DSBs that are typically induced by IR are resolved either by nonhomologous end joining (NHEJ) or by homologous recombination (HR), whereas RECQ helicases assume various roles in genome maintenance during recombination repair and replication.64

Remarkable DNA repair capabilities of Deinococcus radiodurans and E.Coli

Extreme Genome Repair (2009): If its naming had followed, rather than preceded, molecular analyses of its DNA, the extremophile bacterium Deinococcus radiodurans might have been called Lazarus. After shattering of its 3.2 Mb genome into 20–30 kb pieces by desiccation or a high dose of ionizing radiation, D. radiodurans miraculously reassembles its genome such that only 3 hr later fully reconstituted nonrearranged chromosomes are present, and the cells carry on, alive as normal 65

T. Devitt (2014): John R. Battista, a professor of biological sciences at Louisiana State University, showed that E. coli could evolve to resist ionizing radiation by exposing cultures of the bacterium to the highly radioactive isotope cobalt-60. “We blasted the cultures until 99 percent of the bacteria were dead. Then we’d grow up the survivors and blast them again. We did that twenty times,” explains Cox. The result were E. coli capable of enduring as much as four orders of magnitude more ionizing radiation, making them similar to Deinococcus radiodurans, a desert-dwelling bacterium found in the 1950s to be remarkably resistant to radiation. That bacterium is capable of surviving more than one thousand times the radiation dose that would kill a human. 66

1. Organisms are constantly exposed to different environments, and in order to survive, require to be able to adapt to external conditions.
2. Life, in order to perpetuate, has to replicate. That includes DNA, which must be replicated with extreme accuracy. Somehow, the cell knows when DNA is accurately replicated, and when not. There are extremely complex quality control mechanisms in place, which constantly monitor the process. At least 3 error check and repair mechanisms keep error during replication down to 1 error in 10 billion nucleotides replicated.
3. These repair mechanisms, sophisticated proteins, are also encoded in DNA. So proteins are required to error check and repair DNA but accurately replicated DNA is necessary to make the proteins that repair DNA.
4. That is an all-or-nothing business. Therefore, these sophisticated systems had to emerge all at once, and require a designer.  

The existence of multiple layers of repair mechanisms that prevent random mutations from happening to DNA, has been termed the ‘mutation protection paradox’.

W. DeJong (2011): Both digital codes in computers and nucleotide codes in cells are protected against mutations. Mutation protection affects the random change and selection of digital and nucleotide codes. Our mutation protection perspective enhances the understanding of the evolutionary dynamics of digital and nucleotide codes and its limitations, and reveals a paradox between the necessity of dysfunctioning mutation protection for evolution and its disadvantage for survival. Our mutation protection perspective suggests new directions for research into mutational robustness. Unbounded random change of nucleotide codes through the accumulation of irreparable, advantageous, code expanding, inheritable mutations at the level of individual nucleotides, as proposed by evolutionary theory, requires the mutation protection at the level of the individual nucleotides and at the higher levels of the code to be switched off or at least to dysfunction. Dysfunctioning mutation protection, however, is the origin of cancer and hereditary diseases, which reduce the capacity to live and to reproduce. Our mutation protection perspective of the evolutionary dynamics of digital and nucleotide codes thus reveals the presence of a paradox in evolutionary theory between the necessity and the disadvantage of dysfunctioning mutation protection. This mutation protection paradox, which is closely related with the paradox between evolvability and mutational robustness, needs further investigation. 59

Peto's paradox....

Marc Tollis (2017): In a multicellular organism, cells must go through a cell cycle that includes growth and division. Every time a human cell divides, it must copy its six billion base pairs of DNA, and it inevitably makes some mistakes. These mistakes are called somatic mutations (cells in the body other than sperm and egg cells). Some somatic mutations may occur in genetic pathways that control cell proliferation, DNA repair, apoptosis, telomere erosion, and growth of new blood vessels, disrupting the normal checks on carcinogenesis. If every cell division carries a certain chance that a cancer-causing somatic mutation could occur, then the risk of developing cancer should be a function of the number of cell divisions in an organism’s lifetime. Therefore, large-bodied and long-lived organisms should face a higher lifetime risk of cancer simply due to the fact that their bodies contain more cells and will undergo more cell divisions over the course of their lifespan. However, a 2015 study that compared cancer incidence from zoo necropsy data for 36 mammals found that a higher risk of cancer does not correlate with increased body mass or lifespan. In fact, the evidence suggested that larger long-lived mammals actually get less cancer. This has profound implications for our understanding of how the cancer problem is solved.

When individuals in populations are exposed to the selective pressure of cancer risk, the population must evolve cancer suppression as an adaptation or else suffer fitness costs and possibly extinction. Discovering the mechanisms underlying these solutions to Peto’s Paradox requires the tools of numerous subfields of biology including genomics, comparative methods, and experiments with cells. For instance, genomic analyses revealed that the African savannah elephant (Loxodonta africana) genome contains 20 copies, or 40 alleles, of the most famous tumor suppressor gene TP53. The human genome contains only one TP53 copy, and two functional TP53 alleles are required for proper checks on cancer progression. When cells become stressed and incur DNA damage, they can either try to repair the DNA or they can undergo apopotosis, or self-destruction. The protein produced by the TP53 gene is necessary to turn on this apoptotic pathway. Humans with one defective TP53 allele have Li Fraumeni syndrome and a ~90% lifetime risk of many cancers, because they cannot properly shut down cells with DNA damage. Meanwhile, experiments revealed that elephant cells exposed to ionizing radiation behave in a manner consistent with what you would expect with all those TP53 copies—they are much more likely to switch on the apoptotic pathway and therefore destroy cells rather than accumulate carcinogenic mutations. 61

Comment: How does the author explain the origin of these protective mechanisms? He claims: "The solution to Peto’s Paradox is quite simple: evolution". This is an ad-hoc assertion and raises the question: How could complex multicellular organisms have evolved if these cancer protection mechanisms were not implemented before the transition occurred, since, otherwise, these organisms would have gone extinct? But how would cancer protection mechanisms have been selected, if before multicellularity arose, these complex systems would not have conveyed any function? 1. Multicellularity, 2. genome maintenance mechanisms, cell-cycle arrest mechanisms, and apoptosis, and 3. p53 transcription factors would have had to evolve together since they work as a system.   This problem becomes even greater if considering, that animals with large body size supposedly evolved independently many times across the history of life, and, therefore, these mechanisms would have had to be recruited multiple times. The paradox is only solved if we hypothesize that large animals were created independently by God, and right from the beginning equipped with tumor suppressor mechanisms from the get-go.

A. B. Williams (2016): The loss of p53 is a major driver of cancer development mainly because, in the absence of this “guardian of the genome,” cells are no longer adequately protected from mutations and genomic aberrations. Intriguingly, the evolutionary occurrence of p53 homologs appears to be associated with multicellularity. With the advent of metazoans, genome maintenance became a specialized task with distinct requirements in germ cells and somatic tissues. With the central importance of p53 in controlling genome instability–driven cancer development, it might not be surprising that p53 controls DNA-damage checkpoints and impacts the activity of various DNA-repair systems. 64

B. J. Aubrey (2016): The fundamental biological importance of the Tp53 gene family is highlighted by its evolutionary conservation for more than one billion years dating back to the earliest multicellular organisms. The TP53 protein provides essential functions in the cellular response to diverse stresses and safeguards maintenance of genomic integrity, and this is manifest in its critical role in tumor suppression. The importance of Tp53 in tumor prevention is exemplified in human cancer where it is the most frequently detected genetic alteration. This is confirmed in animal models, in which a defective Tp53 gene leads inexorably to cancer development, whereas reinstatement of TP53 function results in regression of established tumors that had been initiated by loss of TP53.

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E.V. Koonin (2007): Major transitions in biological evolution show the same pattern of sudden emergence of diverse forms at a new level of complexity.  The relationships between major groups within an emergent new class of biological entities are hard to decipher and do not seem to fit the tree pattern that, following Darwin's original proposal, remains the dominant description of biological evolution.   The cases in point include the origin of complex RNA molecules and protein folds; major groups of viruses; archaea and bacteria, and the principal lineages within each of these prokaryotic domains; eukaryotic supergroups; and animal phyla. In each of these pivotal nexuses in life's history, the principal "types" seem to appear rapidly and fully equipped with the signature features of the respective new level of biological organization. No intermediate "grades" or intermediate forms between different types are detectable. 21

Stuart Pivar (2010): No coherent causative model of morphogenesis has ever been presented.22 

E. V. Koonin (2010)The summary of the state of affairs on the 150th anniversary of the Origin is somewhat shocking: in the post-genomic era, all major tenets of the Modern Synthesis are, if not outright overturned, replaced by a new and incomparably more complex vision of the key aspects of evolution. So, not to mince words, the Modern Synthesis is gone. The idea of evolution being driven primarily by infinitesimal heritable changes in the Darwinian tradition has become untenable. 23 

J. S. Turner (2010): Although I touch upon ID obliquely from time to time, I do so not because I endorse it, but because it is mostly unavoidable. ID theory is essentially warmed-over natural theology, but there is, at its core, a serious point that deserves serious attention. ID theory would like us to believe that some overarching intelligence guides the evolutionary process: to say the least, that is unlikely. Nevertheless, how design arises remains a very real problem in biology.24 

C. S. Roberts (2012): The three limitations of Darwin's theory concern the origin of DNA, the irreducible complexity of the cell, and the paucity of transitional species. Because of these limitations, the author predicts a paradigm shift away from evolution to an alternative explanation. The intellectual problem is that it remains a suspect theory >150 years after the publication of The Origin of Species (1859). 25

D. E. K. Ferrier (2016): There is uncertainty in our understanding of homeobox gene cluster evolution at present. This relates to our still rudimentary understanding of the dynamics of genome rearrangements and evolution over the evolutionary timescales being considered when we compare lineages from across the animal kingdom.26


1. Richard Dawkins:  IN SHORT: NONFICTION April 9, 1989
2. New trends in evolutionary biology: biological, philosophical and social science perspectives
3. Paul Nelson and David Klinghoffer: Scientists Confirm: Darwinism Is Broken December 13, 2016
4. Libretext: Evidence for Evolution
5. MICHAEL J. BEHE: Experimental Support for the Design Inference DECEMBER 27, 1987
6. Dr. Marc W. Kirschner: The Plausibility of Life: Resolving Darwin's Dilemma 2005
9. Michaela Lewis: Understanding Evolution: Gene Selection
10. David Haig: The strategic gene 30 March 2012
11. Matt Ridley: In retrospect: The Selfish Gene 27 January 2016
12. Paul C. W. Davies: The algorithmic origins of life 2013 Feb 6
13. Kevin Laland: Does evolutionary theory need a rethink? 08 October 2014
14. Gerd B. Müller: Why an extended evolutionary synthesis is necessary 18 August 2017
15. Qiaoying Lu: The Evolutionary Gene and the Extended Evolutionary Synthesis 12 May 2018
16. J.K. Stroble Nagel: Function-Based Biology Inspired Concept Generation  March 1st, 2010
17. Carl Simpson: The Miscellaneous Transitions in Evolution April 2011
18. R. DeSalle: Molecular Systematics and Evolution: Theory and Practice 2002
19. Eugene K Balon: Evolution by epigenesis: farewell to Darwinism, neo- and otherwise 2004 May-Aug
20. Hiroshi Akashi: Molecular Evolution in the Drosophila melanogaster Species Subgroup: Frequent Parameter Fluctuations on the Timescale of Molecular Divergence 2006 Mar
21. Eugene V Koonin: The Biological Big Bang model for the major transitions in evolution 20 August 2007
22. Stuart Pivar: The origin of the vertebrate skeleton  16 August 2010
23. Eugene V. Koonin:  The Origin at 150: is a new evolutionary synthesis in sight? 2010 Nov 1.
24. J. Scott Turner: The Tinkerer's Accomplice: How Design Emerges from Life Itself  30 setember 2010
25. Charles Stewart Roberts: Comments on Darwinism 2012 Jan
26. D. E. K. Ferrier: Evolution of Homeobox Gene Clusters in Animals: The Giga-Cluster and Primary vs. Secondary Clustering 14 April 2016
27. John J. Welch: What’s wrong with evolutionary biology?  20 December 2016
28. Ryohei Seki et.al.,: Functional roles of Aves class-specific cis-regulatory elements on macroevolution of bird-specific features 06 February 2017
29. Phys.Org.: Sweeping gene survey reveals new facets of evolution MAY 28, 2018
30. Sebastian Kittelmann et.al.,: Gene regulatory network architecture in different developmental contexts influences the genetic basis of morphological evolution May 3, 2018
31. M. Linde‑Medina On the problem of biological form 5 May 2020
32. Alison Caldwell, PhD: A simple rule drives the evolution of useless complexity December 9, 2020
33. Gerd B. Müller: Why an extended evolutionary synthesis is necessary 18 August 2017
34. Stephen C. Meyer: The Meanings of Evolution 

22. Abyt Ibraimov: Editorial Open Access Organismal Biology Journal  April 06, 2017
23. John Joe McFadden: Evolution of the best idea that anyone has ever had July 1, 2008


J. J. Welch (2016): There have been periodic claims that evolutionary biology needs urgent reform. Irrespective of the content of the individual critiques, the sheer volume and persistence of the discontent must be telling us something important about evolutionary biology. Broadly speaking, there are two possibilities, both dispiriting. Either (1) the field is seriously deficient, but it shows a peculiar conservatism and failure to embrace ideas that are new, true and very important; or (2) something about evolutionary biology makes it prone to the championing of ideas that are new but false or unimportant, or true and important, but already well studied under a different branding. It has been argued here that the discontent is better understood as stemming from a few inescapable properties of living things, which lead to disappointment with evolutionary biology, and a nagging feeling that reform must be overdue. Evolutionary biology, like history, but unlike other natural sciences, raises issues of purpose and agency, alongside those of complexity and generality.27 

Ryohei Seki et.al., (2017): It has been argued for several decades that the phenotypic variations within and between species can be established by modification of cis-regulatory elements, which can alter the tempo and mode of gene expression. Nevertheless, we still have little knowledge about the genetic basis of macroevolutionary transitions that produced the phenotypic novelties that led to the great leap of evolution and adaptation to new environment. Although numerous efforts have been made to study the evolutionary roles of newly evolved genes in a limited numbers of model species2, little is known about how the genetic changes underlying the major transitions occurred in the deep time, and how they were maintained through long-term macroevolution.28

And Phys.Org (2018): The most extensive genetics study ever completed the Journal of Human Evolution revealed NO genetic evidence for Evolution. The author, an avid proponent of evolution, was reduced to the following conclusions: And yet—another unexpected finding from the study—species have very clear genetic boundaries, and there's nothing much in between. "If individuals are stars, then species are galaxies," said Thaler. "They are compact clusters in the vastness of empty sequence space." The absence of "in-between" species is something that also perplexed Darwin, he said.29 

S. Kittelmann et.al., (2018) A major goal of biology is to identify the genetic causes of organismal diversity. 30
M. Linde‑Medina (2020): At present, the problem of biological form remains unsolved. 31

Joseph Thornton, PhD, professor of human genetics and ecology and evolution (2020): How complexity evolves is one of the great questions of evolutionary biology 32

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I hear often atheists arguing that:" Creationists have no clue how evolution works ". The mechanisms supposedly involved are common knowledge. After quoting the above science papers, one is IMHO warranted to ask: Who has demonstrated that it is indeed unguided evolutionary pressures that explain the origin of millions of different species on earth?

Nonetheless, these facts, many with high confidence continue believing and claiming above a shadow of a doubt that evolution is a settled fact. After all, the professionals in the field say so. But isn't that in reality just the successful result of indoctrination of many generations? Today, more and more biologists are starting to recognize that the construction of phenotypic form & architecture depends on mechanisms that science is far from having fully explored and unraveled. In this book, I will mention and describe almost 50 epigenetic codes and languages, and in most of them, it is a mystery for science where and how the information is stored. Some are recognizing this and trying to incorporate these recently unraveled mechanisms into an expanded evolutionary framework. Like Gerd B. Müller, an Austrian biologist, for example. He writes in the science paper:  Why an extended evolutionary synthesis is necessary? 

These examples of conceptual change in various domains of evolutionary biology represent only a condensed segment of the advances made since the inception of the MS theory some 80 years ago. Relatively minor attention has been paid to the fact that many of these concepts, which are in full use today, sometimes contradict or expand central tenets of the MS theory. Given proper attention, these conceptual expansions force us to consider what they mean for our present understanding of evolution. Obviously, several of the cornerstones of the traditional evolutionary framework need to be revised and new components incorporated into a common theoretical structure. Although today's organismal systems biology is mostly rooted in biophysics and biological function, its endeavors are profoundly integrative, aiming at multiscale and multilevel explanations of organismal properties and their evolution. Instead of chance variation in DNA composition, evolving developmental interactions account for the specificities of phenotypic construction. 33

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One can always bend, stretch, evolve, change the theory of evolution, incorporate new mechanisms, and claim that evolution through unguided genetic and epigenetic changes did it. The challenge is: What is the drawing line of separation, where is it justified to bring intelligence as a required ingredient into the picture to explain these things? I think the two already-known and well-established ID tenets, specified, and irreducible complexity do that just fine and demonstrate why ID is a superior hypothesis. The fact is that the instantiation of information storage systems, languages, codes, information instantiated by using these codes and languages, information transmission systems, encoding, transmitting, decoding, transcribing, translating, transduction, etc. requires a mind, and so does the making of irreducibly complex integrated machines, production lines and factories based on information transmission systems that are the link between the cell's hardware and software, and the cellular machinery that is made, operated and controlled upon it.  The more the number of different software/hardware on genetic and epigenetic levels unraveled, that operates on an intra and extracellular (systems) level, there it is evidence that unguided, non-intelligent natural mechanisms are inadequate, and do not suffice to explain the phenomena in question, and ID becomes a better, more plausible and probable explanation. As this book will show, we are already deep in this territory. 
To get the message out, and have it acknowledged by a wider number of people is the goal of this book.   

Answering Frank Zindler, which I intend to support and substantiate with this book, is: The most devastating thing though that biology has done to naturalism is the failed claim of chemical and biological evolution. Now that we know that Adam and Eve were real people the central creation narrative of Christianity is confirmed. If there was an Adam and Eve there was an original sin. If there was an original sin there is need of salvation. If there is need of salvation there is need of a Savior. And I submit that puts Jesus, historical or otherwise, into the ranks of the necessary. I think that the failure of abiogenesis and evolution is absolutely the death knell of naturalism.

1

What is natural selection? 

Merriam-Webster defines selection as the act or process of selecting: the state of being selected one that is selected: CHOICE. Making choices is always assigned/attributed to intelligent action. Darwin however coined the word "natural selection" to mean something different. Many think that natural selection actively selects favorable traits in a population. But in fact, as EvolutionShorts explains:  It is a passive process that does not involve organisms “trying” to adapt. This concept of the organism becoming more suited to its current environment is roughly the basis of adaptive evolution. This is a fundamental principle for natural selection instead of specific desires of species. 

R.Carter:‘Natural selection’ properly defined simply means ‘differential reproduction’, meaning some organisms leave more progeny than others based on the mutations they carry and the environment in which they live. 1

Paul R. Ehrlich (1988): In modem evolutionary genetics, natural selection is defined as the differential reproduction of genotypes (individuals of some genotypes have more offspring than those of others). Natural selection would be occurring if, in a population of jungle fowl (the wild progenitors of chickens), single-comb genotypes were more reproductively successful than pea-comb genotypes. Note that the emphasis is not on survival  (as it was in Herbert Spencer's famous phrase "survival of the fittest") but on reproduction.2

Natural selection is not an acting force but is passive. It does not invent something new.
E. Osterloff:  Natural selection is a mechanism of evolution. Organisms that are more adapted to their environment are more likely to survive and pass on the genes that aided their success. This process causes species to change and diverge over time. 3

David Stack (2021): Natural selection was the term Darwin used to describe both the mechanism and the effect of the evolutionary process by which favorable or advantageous traits and characteristics are preserved and unfavorable or disadvantageous ones discarded. The “selection” process is “natural” in the sense that it occurs without any conscious intervention (there is no “selector”) in response to an ongoing “struggle for life.” Traits and characteristics favorable to survival in that struggle are preserved and developed. This, for Darwin, is the basis of evolution. Key to the process is inheritance, but, as he was writing without knowledge of modern genetics, Darwin’s presentation of natural selection did not include any detailed understanding of how inheritance worked. 4

FRANCISCO J. AYALA (2007): With Darwin’s discovery of natural selection, the origin and adaptations of organisms were brought into the realm of science. The adaptive features of organisms could now be explained, like the phenomena of the inanimate world, as the result of natural processes, without recourse to an Intelligent Designer.

Variation. Organisms (within populations) exhibit individual variation in appearance and behavior.  These variations may involve body size, hair color, facial markings, voice properties, or number of offspring.  On the other hand, some traits show little to no variation among individuals—for example, number of eyes in vertebrates.
Inheritance.  Some traits are consistently passed on from parent to offspring.  Such traits are heritable, whereas other traits are strongly influenced by environmental conditions and show weak heritability.
High rate of population growth. Most populations have more offspring each year than local resources can support leading to a struggle for resources.  Each generation experiences substantial mortality.
Differential survival and reproduction.  Individuals possessing traits well suited for the struggle for local resources will contribute more offspring to the next generation.

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Is there evidence for natural selection?

According to Darwin's Theory, the main actors that drive evolution, is natural Selection, Genetic Drift, and Gene Flow. Natural selection depends on variation through random mutations. Inheritance,  differential survival, and reproduction ( reproductive success which permits new traits to spread in the population).   The genetic modification is supposed to be due to: Survival of the fittest, in other words, 1.  higher survival rates upon specific gene-induced phenotype adaptations to the environment, and 2. higher reproduction rates upon specific evolutionary genetic modifications. Keep in mind that these are two different, distinct factors. It's a fact that harmful variants, where a mutation influences negatively health, fitness, and reproduction ability of organisms diminish. These are sorted out, or die through disease. In that regard, natural selection is a fact. That says nothing however about an organism gaining more fitness  ( reproductive success )  through the evolution of new advantageous traits.

In an interview in 1999, Mayr stated: “Darwin showed very clearly that you don't need Aristotle's teleology because natural selection applied to bio-populations of unique phenomena can explain all the puzzling phenomena for which previously the mysterious process of teleology had been invoked”. 5

Definitions of fitness:

J. Dekker (2007): 1. The average number of offspring produced by individuals with a certain genotype, relative to the numbers produced by individuals with other genotypes. 2: The relative competitive ability of a given genotype conferred by adaptive morphological, physiological, or behavioral characters, expressed and usually quantified as the average number of surviving progeny of one genotype compared with the average number of surviving progeny of competing genotypes; a measure of the contribution of a given genotype to the subsequent generation relative to that of other genotypes
A condition necessary for evolution to occur is variation in fitness of organisms according to the state they have for a heritable character. Individuals in the population with some characters must be more likely to reproduce, more fit. Organisms in a population vary in reproductive success. We will discuss fitness in Life History when we discuss competition, interference and the effects of neighbor plants.

Three Components of Fitness.  These different components are in conflict with each other, and any estimate of fitness must consider all of them:
1.  Reproduction
2.  Struggle for existence with competitors
3.  Avoidance of predators  6

S.El-Showk (2012): The common usage of the term “fitness” is connected with the idea of being in shape and associated physical attributes like strength, endurance or speed; this is quite different from its use in biology.  To an evolutionary biologist, fitness simply means reproductive success and reflects how well an organism is adapted to its environment.The main point is that fitness is simply a measure of reproductive success and so won’t always depend on traits such as strength and speed; reproductive success can also be achieved by mimicry, colorful displays, sneak fertilization and a host of other strategies that don’t correspond to the common notion of “physical fitness”.

What then are we to make of the phrase “survival of the fittest”? Fitness is just book-keeping; survival and differential reproduction result from natural selection, which actually is a driving mechanism in evolution. Organisms which are better suited to their environment will reproduce more and so increase the proportion of the population with their traits. Fitness is simply a measurement of survival (which is defined as reproductive success); it’s not the mechanism driving survival.  Organisms (or genes or replicators) don’t survive because they are fit; rather, they are considered fit because they survived. 7

The environment is not stable, but changes. Science would need to have the knowledge of what traits of each species are favored in a specific environment. Adaptation rates and mutational diversity and other spatiotemporal parameters, including population density, mutation rate, and the relative expansion speed and spatial dimensions. When the attempt is made to define with more precision what is meant by the degree of adaptation and fitness, we come across very thorny and seemingly intractable problems. 

As Evolution. Berkley explains: Of course, fitness is a relative thing. A genotype's fitness depends on the environment in which the organism lives. The fittest genotype during an ice age, for example, is probably not the fittest genotype once the ice age is over. Fitness is a handy concept because it lumps everything that matters to natural selection (survival, mate-finding, reproduction) into one idea. The fittest individual is not necessarily the strongest, fastest, or biggest. A genotype's fitness includes its ability to survive, find a mate, produce offspring — and ultimately leave its genes in the next generation. 8

Can fitness be measured? 

Claim: Adam Eyre-Walker (2007): All organisms undergo mutation, the effects of which can be broadly divided into three categories. First, there are mutations that are harmful to the fitness of their host; these mutations generally either reduce survival or fertility. Second, there are ‘neutral’ mutations, which have little or no effect on fitness. Finally, there are advantageous mutations, which increase fitness by allowing organisms to adapt to their environment. Although we can divide mutations into these three categories, there is, in reality, a continuum of selective effects, stretching from those that are strongly deleterious, through weakly deleterious mutations, to neutral mutations and then on to mutations that are mildly or highly adaptive. The relative frequencies of these types of mutation are called the distribution of fitness effects (DFE) 9

R. G. Brajesh et.al., (2019): Mutations occur spontaneously during the course of reproduction of an organism. Mutations that impart a beneficial characteristic to the organism are selected and consequently, the frequency of the mutant allele increases in the population. Mutations can be single base changes called point mutations like substitutions, insertions, deletions, as well as gross changes like chromosome recombination, duplication, and translocation 10

Reply:  A theory must be able to make predictions, and it must be testable.  How can it be tested that random mutations give rise to higher fitness and higher reproduction of the individuals with the new allele variation favored by natural selection, and so spread in the population, and how can the results be quantified? This seems in fact to be a core issue that raises questions. The environmental conditions of a population, the weather, food resources, temperatures, etc. are random How do random events, like weather conditions, together with random mutations in the genome, provoke a fitness increase in an organism and a survival advantage over the other individuals without the mutation? 

T.Bataillon (2014): The rates and properties of new mutations affecting fitness have implications for a number of outstanding questions in evolutionary biology. Obtaining estimates of mutation rates and effects has historically been challenging, and little theory has been available for predicting the distribution of fitness effects (DFE); Future work should be aimed at identifying factors driving the observed variation in the distribution of fitness effects. What can we say about the distribution of fitness effects of new mutations? For the distribution of fitness effects DFE of beneficial mutations, experimentally inferred distributions seem to support theory for the most part. Distribution of fitness effects DFE has largely been unexplored and there is a need to extend both theory and experiment in this area. 11

Christopher J Graves (2019): When fitness effects are invariant across a lineage, the long-term fate of an allele can be deduced in a relatively straightforward manner from its recursive effects on survival and reproduction across descendent carriers. In other cases, the evolutionary success of an allele is not an obvious consequence of its effects on individuals. For example, variable environments can cause the same allele to have differing effects on fitness depending on an individuals’ environmental context. 18

V. Ž. Alif et.al., (2021): The concept of fitness is central to evolutionary theory. Natural selection maximizes fitness, which is therefore a driving force of evolution as well as a measure of evolutionary success. One definition  of fitness is how good an individual is at spreading its genes into future generations, relative to all other individuals in the population. A universal definition of fitness in mathematical terms that applies to all population structures and dynamics is however not agreed on. Fitness it is difficult to measure accurately. One way to measure long-term fitness is by calculating the individual’s reproductive value, which represents the expected number of allele copies an individual passes on to distant future generations. However, this metric of fitness is scarcely used because the estimation of individual’s reproductive value requires long-term pedigree data, which is rarely available in wild populations where following individuals from birth to death is often impossible. Wild study systems therefore use short-term fitness metrics as proxies, such as the number of offspring produced. 19

The above confession demonstrates that a key question, namely how mutations in fact affect fitness has not been answered. I go further and say: Darwin's Theory can in reality not be tested, nor quantified. The unknown factors in each case are too many, and the variations in the environment, and population sizes undergo large seasonal fluctuations, providing more opportunities for mutations when the population size is large and a greater probability of fixation of mutation x during the recurring bottlenecks, and population and species behavior vary too. It cannot be defined what influence the given environment exercises in regard to specific animals and traits in that environment, nor how the environmental influence would change the fitness and reproduction success of each distinct animal species. Nor how reproduction success given new traits would change upon environmental changes.  What determines whether a gene variant spreads or not would depend theoretically on an incredibly complex web of factors - the species' ecology, its physical and social environment, altered nutrient conditions,  and sexual behavior. A further factor adding complexity is the fact that high social rank is associated with high levels of both copulatory behavior and the production of offspring which is widespread in the study of animal social behavior. 

As alpha males have on average higher reproductive success than other males, since they outcompete weaker individuals, and get preference to copulate if other (weaker)  males gain beneficial mutations (or the alphas' negative mutations) as the alphas can outperform and win the battle for reproduction,  thus selection has an additional hurdle to overcome and spread the new variant in the population. This does not say anything about the fact that it would have to be determined what gene loci are responsible for sexual selection and behavior, and only mutations that influence sexual behavior would have an influence on fitness and the struggle to contribute more offspring to the next generation.   It is in praxis impossible to isolate these factors and see which is of selective importance,  quantify them, plug them in (usually in this context) to a mixed multivariate computational model, see what's statistically significant, and get meaningful, real-life results. The varying factors are too many and nonpredictive. Darwin's idea, therefore, depends on variable, unquantifiable multitude of factors that cannot be known, and cannot be tested, which turns the theory at best into a non-testable hypothesis, which then remains just that: a hypothesis. Since Darwin's idea cannot be tested, it's by definition, unscientific. 

If fitness is a relative thing, it cannot be detected and proven that natural selection is the mechanism that generates variations that produce more offspring, and therefore the new trait spreads in the population. Therefore, mutations and natural selection cannot be demonstrated to have the claimed effects. What is the relation between mutations in the genome, and the number of offspring? What mutations are responsible for the number of offspring produced? If the theory of evolution is true, there must be a detectable mechanism, that determines or induces, or regulates the number of offspring based due to specific genetic mutations. Only a specific section in the genome is responsible for this regulation.

There are specific regions in the genome responsible for each  mechanism of reproduction, being it sexual, or asexual reproduction, that is:  

1. Regulation and programming of sexual attraction ( hormones, pheromones, instinct, etc.)
2. Frequency of sexual intercourse and reproduction
3. The regulation of the number of offspring produced

What influence do environmental pressures have on these 3 points? What pressures induced organisms to evolve sexual, and asexual reproduction?  Are the tree mechanisms mentioned not amazingly various and differentiated, and each species have individual, species-specific mechanisms? Some have an enormous number of offspring that helps the survival of the species, while others have a very low reproduction rate ( whales  ? ) How could environmental pressures have induced this amazing variation, and why?  That means also on a molecular level, enormous differences from one species to the other exist.  how could accidental mutations have been the basis for all this variation? Would there not have to be SPECIFIC environmental pressures resulting in the selection of  SPECIFIC traits based on mutations of the organism to be selected that provide survival advantage and fitness? ( genome or epigenome, whatever )  AND higher reproduction rates of the organism at the same time?

What is the chance, that random mutations provoke positive phenotypic differences, that help the survival of the individual? What kind of environmental factors influence the survival of a species? What kind of mutations must be selected to guarantee a higher survival rate?

The lack of predictive power of natural selection is due to different environmental conditions that turn it impossible to quantify the effects and measure their outcome.

Ivana Cvijović (2015): Temporal fluctuations in environmental conditions can have dramatic effects on the fate of each new mutation, reducing the efficiency of natural selection and increasing the fixation probability of all mutations, including those that are strongly deleterious on average. This makes it difficult for a population to maintain specialist adaptations, even if their benefits outweigh their costs. Temporally varying selection pressures are neglected throughout much of population genetics, despite the fact that truly constant environments are rare. The fate of each mutation depends critically on its fitness in each environment, the dynamics of environmental changes, and the population size. We still lack both a quantitative and conceptual understanding of more significant fluctuations, where selection in each environment can lead to measurable changes in allele frequency. 20

L.Bromham (2017): The search for simple unifying theories in macroevolution and macroecology seems unlikely to succeed given the vast number of factors that can influence a particular lineage’s evolutionary trajectory, including rare events and the weight of history. Patterns in biodiversity are shaped by a great many factors, both intrinsic and extrinsic to organisms. Both evidence and theory suggests that one such factor is variation in the mutation rate between species. But the explanatory power of the observed relationship between molecular rates and biodiversity is relatively modest, so it does not provide anything like the predictive power that might be hoped for in a unifying theory. However, we feel that the evidence is growing that, in addition to the many and varied influences on the generation of diversity, the differential rate supply of variation through species-specific differences in mutation rate has some role to play in generating different rates of diversification.21

Z. Patwa (2008): To date, the fixation probability of a specific beneficial mutation has never been experimentally measured. 22

More problems: R. G. Brajesh (2019): The genotypic mutational space of an organism is so vast, even for the tiniest of organisms like viruses or even one gene, that it becomes experimentally intractable. Hence, studies have limited to studying only small parts of the genome. For example, experiments have attempted to map the functional effect of mutations at important active site residues in proteins, like Lunzer et al. engineered the IDMH enzyme to use NADP as cofactor instead of NAD, and obtain the fitness landscape in terms of the mutational steps. Other experiments have attempted to ascertain how virulence is affected by mutations at certain important loci in viruses. However, due to the scale of the genotypic mutational space, it has been extremely difficult to experimentally obtain fitness landscapes of larger multicomponent systems, and study the statistical properties of these landscapes like the Distribution of Fitness Effects (DFE). Attempts have also been made to back-calculate the underlying DFE by experimentally observing how frequently new beneficial mutations emerge and of what strength, but the final results were inconclusive. As a result, how the beneficial, neutral, and deleterious mutations and their effects are distributed, when the organism genotype is at different locations on the fitness landscape, has remained largely intractable. 23

And more problems: Adam Eyre-Walker (2007): The distribution of fitness effects DFE of deleterious mutations, in particular the proportion of weakly deleterious mutations, determine a population's expected drift load—the reduction in fitness due to multiple small-effect deleterious mutations that individually are close enough to neutral to occasionally escape selection, but can collectively have important impacts on fitness. The DFE of new mutations influences many evolutionary patterns, such as the expected degree of parallel evolution, the evolutionary potential and capacity of populations to respond to novel environments, the evolutionary advantage of sex, and the maintenance of variation on quantitative traits, to name a few. Thus, an understanding of the DFE of mutations is a pivotal part of our understanding of the process of evolution.  Furthermore, the available data suggest that some aspects of the DFE of advantageous mutations are likely to differ between species9

Conclusion: The positive effects of natural selection on differential reproduction cannot be tested, since too many unknown variables have to be included, and that cannot lead to meaningful, quantifiable results that permit a clear picture. 

D.Coppedge (2021): The central concept of natural selection cannot be measured. This means it has no scientific value. 24

Large-scale evolution by natural selection is a non-testable hypothesis
1. P. R. Ehrlich (1988): In modem evolutionary genetics, natural selection is defined as the differential reproduction of genotypes (individuals of some genotypes have more offspring than those of others) based on the mutations they carry and the environment in which they live. Organisms that are better suited to their environment will reproduce more and so increase the proportion of the population with their traits. ( More reproduction of a genotype = survival of the fittest = measure of  fitness)  
2. T. Bataillon (2014): Obtaining estimates of mutation rates and effects has historically been challengingI. Cvijović (2015): The fate of each mutation depends critically on its fitness in each environment, the dynamics of environmental changes, and the population size. We still lack both a quantitative and conceptual understanding of more significant fluctuations, where selection in each environment can lead to measurable changes in allele frequency.C. J. Graves (2019): Variable environments can cause the same allele to have differing effects on fitness depending on an individual’s environmental context. V. Ž. Alif (2021): Fitness is difficult to measure accurately. The metric of fitness is scarcely used because the estimation of an individual’s reproductive value requires long-term pedigree data, which is rarely available in wild populations where following individuals from birth to death is often impossible. D.Coppedge (2021): The central concept of natural selection cannot be measured. This means it has no scientific value.
3. The key question, namely how mutations in fact affect fitness has not been answered. Darwin's Theory can not be tested, nor quantified. The unknown factors are too many, the variations in the environment, and population and species behavior vary too. It cannot be defined what influence the given environment exercises in regard to specific animals and traits in that environment, nor how the environmental influence would change the fitness and reproduction success of each distinct animal species. Large-scale evolution is at best a non-testable hypothesis, which then remains just that: a hypothesis. Since Darwin's idea cannot be tested, it's by definition, unscientific, and anyone claiming that natural selection explains biodiversity makes that claim based on blind confidence and belief. Not evidence. 


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No evidence of natural selection contributing to the increase in organismal complexity

And if that was not already bad news, it gets worse than that: M.Lynch (2007): Myth: Natural selection promotes the evolution of organismal complexity. Reality: There is no evidence at any level of biological organization that natural selection is a directional force encouraging complexity. What is in question is whether natural selection is a necessary or sufficient force to explain the emergence of the genomic and cellular features central to the building of complex organisms. 25

Molly K Burke et.al. (2010),"Genomic changes caused by epigenetic mechanisms tend to fail to fixate in the population, which reverts back to its initial pattern." That's not all that doesn't fixate. Despite decades of sustained selection in relatively small, sexually reproducing laboratory populations, selection did not lead to the fixation of newly arising unconditionally advantageous alleles. This is notable because in wild populations we expect the strength of natural selection to be less intense and the environment unlikely to remain constant for ~600 generations. Consequently, the probability of fixation in wild populations should be even lower than its likelihood in these experiments.26

Ben Bradley (2022): As soon as contemporary scientists accept that, as per Darwin’s argument in Origin, natural selection does not cause, but results from the ordinary activities of organisms, contemporary evolutionary theorists must address a new foundational challenge: the need to construct a viable, evidence-based picture of the natural world. 27

Comment: In other words, natural selection is not an actor, but a reactor. It is not a protagonist, but passively "selects" or unconsciously, without "intention" gives "preference" to those alleles that are somehow beneficial and therefore are favored to spread into the population and become dominant variants.  It does not "invent" something new. But that is precisely what is required if the tree of life ought to be true. It has to add de novo genes from scratch, with new information, that directs the making of new organismal structures, like limbs, eyes, ears, different cells, organs, and new body plans and forms. 

Adam Levy (2019): The ability of organisms to acquire new genes is testament to evolution’s “plasticity to make something seemingly impossible, possible”, says Yong Zhang, a geneticist at the Chinese Academy of Sciences’ Institute of Zoology in Beijing, who has studied the role of de novo genes in the human brain. But researchers have yet to work out how to definitively identify a gene as being de novo, and questions still remain over exactly how — and how often — they are born.28

Comment:  So Levy confesses, in 2019, there is no answer to this all-relevant question of whether evolution can generate a gene de novo - it has yet to be worked out. Wow...

But then, Levy makes the following claim at the end of the article: Although de novo genes remain enigmatic, their existence makes one thing clear: evolution can readily make something from nothing. “One of the beauties of working with de novo genes,” says Casola, “is that it shows how dynamic genomes are.”

Comment: Remarkable. On the one hand, in the article, Levy admits that researchers do not know (yet) how evolution can generate genes de novo, but in the end, surprise surprise (not): evolution can readily make something from nothing.....  

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2. New trends in evolutionary biology: biological, philosophical and social science perspectives
3. Paul Nelson and David Klinghoffer: Scientists Confirm: Darwinism Is Broken December 13, 2016
4. Libretext: Evidence for Evolution
5. MICHAEL J. BEHE: Experimental Support for the Design Inference DECEMBER 27, 1987
6. Dr. Marc W. Kirschner: The Plausibility of Life: Resolving Darwin's Dilemma 2005
9. Michaela Lewis: Understanding Evolution: Gene Selection
10. David Haig: The strategic gene 30 March 2012
11. Matt Ridley: In retrospect: The Selfish Gene 27 January 2016
12. Paul C. W. Davies: The algorithmic origins of life 2013 Feb 6
13. Kevin Laland: Does evolutionary theory need a rethink? 08 October 2014
14. Gerd B. Müller: Why an extended evolutionary synthesis is necessary 18 August 2017
15. Qiaoying Lu: The Evolutionary Gene and the Extended Evolutionary Synthesis 12 May 2018
16. J.K. Stroble Nagel: Function-Based Biology Inspired Concept Generation  March 1st, 2010
17. Carl Simpson: The Miscellaneous Transitions in Evolution April 2011
18. R. DeSalle: Molecular Systematics and Evolution: Theory and Practice 2002
19. Eugene K Balon: Evolution by epigenesis: farewell to Darwinism, neo- and otherwise 2004 May-Aug
20. Hiroshi Akashi: Molecular Evolution in the Drosophila melanogaster Species Subgroup: Frequent Parameter Fluctuations on the Timescale of Molecular Divergence 2006 Mar
21. Eugene V Koonin: The Biological Big Bang model for the major transitions in evolution 20 August 2007
22. Stuart Pivar: The origin of the vertebrate skeleton  16 August 2010
23. Eugene V. Koonin:  The Origin at 150: is a new evolutionary synthesis in sight? 2010 Nov 1.
24. J. Scott Turner: The Tinkerer's Accomplice: How Design Emerges from Life Itself  30 setember 2010
25. Charles Stewart Roberts: Comments on Darwinism 2012 Jan
26. D. E. K. Ferrier: Evolution of Homeobox Gene Clusters in Animals: The Giga-Cluster and Primary vs. Secondary Clustering 14 April 2016
27. John J. Welch: What’s wrong with evolutionary biology?  20 December 2016
28. Ryohei Seki et.al.,: Functional roles of Aves class-specific cis-regulatory elements on macroevolution of bird-specific features 06 February 2017
29. Phys.Org.: Sweeping gene survey reveals new facets of evolution MAY 28, 2018
30. Sebastian Kittelmann et.al.,: Gene regulatory network architecture in different developmental contexts influences the genetic basis of morphological evolution May 3, 2018
31. M. Linde‑Medina On the problem of biological form 5 May 2020
32. Alison Caldwell, PhD: A simple rule drives the evolution of useless complexity December 9, 2020
33. Gerd B. Müller: Why an extended evolutionary synthesis is necessary 18 August 2017
34. Stephen C. Meyer: The Meanings of Evolution 

22. Abyt Ibraimov: Editorial Open Access Organismal Biology Journal  April 06, 2017
23. John Joe McFadden: Evolution of the best idea that anyone has ever had July 1, 2008

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10. R. G. Brajesh: Distribution of fitness effects of mutations obtained from a simple genetic regulatory network model  08 July 2019

29. J.Dulle: The (In)adequacy of Darwinian Evolution
30. Matthew Hurles: Gene Duplication: The Genomic Trade in Spare Parts July 13, 2004
31. Alisha K Holloway: Experimental evolution of gene duplicates in a bacterial plasmid model 2007 Feb
32. Joseph Esfandiar: Is gene duplication a viable explanation for the origination of biological information and complexity? 22 December 2010
33. Johan Hallin: Regulation plays a multifaceted role in the retention of gene duplicates November 22, 2019
34. Michael Lynch: The Origins of Genome Architecture 2007
35. Eugene V Koonin: Darwinian evolution in the light of genomics 2009 Mar


12. H. Allen Orr: Testing Natural Selection  2008
13. FRANCISCO J. AYALA: Darwin’s Greatest Discovery: Design Without Designer 2007
14. Paul Gibson : Can Purifying Natural Selection Preserve Biological Information? – May 2013
15. Eugene V. Koonin :Toward a theory of evolution as multilevel learning February 4, 2022
16. Jerry A. Coyne, Why Evolution is True, p. 123. 2009
20. George Ellis: Controversy in Evolutionary Theory: A multilevel view of the issues. 2018
21. Armen Y. Mulkidjanian: Physico-Chemical and Evolutionary Constraints for the Formation and Selection of First Biopolymers: Towards the Consensus Paradigm of the Abiogenic Origin of Life 21 September 2007
25. Libretext: Horizontal Gene Transfer

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Irreducible complexity 

C.Darwin (1860): “If it could be demonstrated that any complex organ existed, which could not possibly have been formed by numerous, successive, slight modifications, my theory would absolutely break down. But I can find no such case.” 33

Irreducible complexity, a term popularized by Michael Behe in his infamous book Darwin's Black box falsifies the claim that evolution explains the origin of biocomplexity and organismal form. If natural selection makes intelligent design superfluous, is it capable of instantiating proteins, cell types, organs, and organ systems, that have only function in cooperation/joint venture with other functional parts of the organism, or the organism as a whole, by slight, successive modifications over time?  Does it select for structures, functions, traits, or what? 

Behe, Darwin's Black Box (1996), page 39: By irreducibly complex I mean a single system composed of several well-matched, interacting parts that contribute to the basic function, wherein the removal of any one of the parts causes the system to effectively cease functioning. An irreducibly complex system cannot be produced directly (that is, by continuously improving the initial function, which continues to work by the same mechanism) by slight, successive modifications of a precursor system, because any precursor to an irreducibly complex system that is missing a part is by definition nonfunctional. An irreducibly complex biological system, if there is such a thing, would be a powerful challenge to Darwinian evolution.34

An irreducibly complex system is characterized by five points:
1. a single system composed of several well-matched, interacting parts
2. that contribute to the basic function
3. the removal of any one of the parts causes the system to effectively cease functioning
4. An irreducibly complex system cannot be produced directly (that is, by continuously improving the initial function, which continues to work by the same mechanism) by slight, successive modifications of a precursor system
5. any precursor to an irreducibly complex system that is missing a part is by definition nonfunctional.

Irreducible complexity falsifies evolution

What function could the heart exercise without blood? or pacemaking cells without there to be determined the rhythm of the heart? Or what good are the subunits of ATP synthase good for without the other subunits that make up the molecular energy turbine? What good is ATP synthase good for without a proton gradient, and the electron transport chain? What good is a nucleobase for without the base? An atom without an electron?  It seems that large structures for specific functions could only exist if all the smaller parts are in place, that are necessary to make up that larger system, and the smaller parts would have no function on their own.

Functional parts are only meaningful within a whole, in other words, it is the whole that gives meaning to its parts.  Natural selection would not select components of a complex system that would be useful only in the completion of that much larger system. It cannot select when the usefulness is only conveyed many steps later. Why would natural selection select an intermediate biosynthesis product, which has by its own no use for the organism, unless that product keeps going through all necessary steps, up to the point to be ready to be assembled in a larger system?  Never do we see blind, unguided processes leading to complex functional systems with integrated parts contributing to the overarching design goal. A minimal amount of instructional complex information is required for a gene to produce useful proteins. A minimal size of a protein is necessary for it to be functional. Thus, before a region of DNA contains the requisite information to make useful proteins, natural selection would not select a positive trait and play no role in guiding its evolution.

The argument of irreducible complexity is obvious and clear. Subparts like a piston in a car engine are only designed, when there is a goal where they will be mounted with specific fitting sizes and correct materials, and have a specific function in the machine as a whole. Individually they have no function. The same is in biological systems, which work as factories ( cells ) or machines ( cells host a big number of the most various molecular machines and equal to factory production lines ) For example, in photosynthesis, there is no function for chlorophyll individually, only when inserted in the light-harvesting complex, to catch photons, and direct their excitation energy by Förster resonance energy transfer to the reaction center in Photosystem one and two. Foreplanning is absolutely essential. This is a  simple fact, which makes the concept of  Irreducible complexity obvious concept. Nonetheless, people argue all the time that it's a debunked argument. Why? That's as if genetic mutations and natural selection had enough probability to generate interdependent individual parts being able to perform new functions while the individual would have no function unless interconnected.

To No.3: A.Y. Mulkidjanian (2007): The principle of evolutionary continuity, succinctly formulated by Albert Lehninger in his Biochemistry textbook. An adaptation that does not increase the fitness is no longer selected for and eventually gets lost in the evolution (in the current view, only those adaptations that effectively decrease the fitness end up getting lost). Hence, any evolutionary scenario has to invoke – at each and every step – only such intermediate states that are functionally useful (or at least not harmful). 21

1. In biology, there are many complex elementary components necessary to build large integrated macromolecular systems like multi-protein complexes (RNA polymerase), 3D printers (the ribosome), organelles (mitochondria), etc., where their making requires complex multistep enzyme-catalyzed biosynthesis pathways. These elementary components are only useful in the completion of that much larger system. Not rarely, these biosynthetic pathways produce intermediate products, that left without further processing, are either a) nonfunctional, or b) harmful and kill the cell (for example, Reactive Oxygen Species (ROS), in the biosynthesis pathway of Chlorophyll b.
2. A minimal amount of prescribed, pre-programmed, instructional complex information stored in genes is required to instruct the making of a) functional elementary components and b) the assembly instructions to integrate them into complex macromolecular systems. Natural selection would not fix an allele variant that would instruct the making of an intermediate, nonfunctional, or harmful elementary component, and play no role in guiding its evolution. Foreknowledge is required to get a complex biological system through implementing a biosemiotic information system (which is irreducibly complex), directing the making of functional elementary components, and assembly into the entire complex integrated system.
3. Therefore, the origin of biological systems based on biosemiotic instructions are best explained by a brilliant, super-powerful mind with foresight and intent, and not undirected evolutionary pressures.

33. C.Darwin: Origin of Species: second British edition (1860), page 189 1860 

34. M.Behe: Darwin's Black Box: The Biochemical Challenge to Evolution 1996

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DNA and RNA error checking and repair: What causal mechanism explains best their origin?

NIWRAD: Molecular biology shows that many complex control-repair mechanisms work inside the cell to recover genetic errors. For example, there are at least three major DNA repair mechanisms. Without such mechanisms, life would be impossible because the internal entropy of the cell would be too high and destructive. Each of them involves the complex and coordinated action of several enzymes/proteins. Random mutations and natural selection are a process that needs errors and at the same time, this process creates mechanisms to eliminate them. The bottom line is that repair mechanisms are incompatible with Darwinism in principle. Since sophisticated repair mechanisms do exist in the cell after all, then the thing to discard in the dilemma to avoid the contradiction necessarily is the Darwinist dogma. 60

J. M. Fischer: Some of the sophisticated and overlapping repair mechanisms found for DNA include:

1. A proofreading system that catches almost all errors
2. A mismatch repair system to back up the proofreading system
3. Photoreactivation (light repair)
4. Removal of methyl or ethyl groups by O6 – methylguanine methyltransferase
5. Base excision repair
6. Nucleotide excision repair
7. Double-strand DNA break repair
8. Recombination repair
9. Error-prone bypass 40

Harmful mutations happen constantly. Without repair mechanisms, life would be very short indeed and might not even get started because mutations often lead to disease, deformity, or death. So even the earliest, “simple” creatures in the evolutionist’s primeval soup or tree of life would have needed a sophisticated repair system. But the (sophisticated repair) mechanisms not only remove harmful mutations from DNA, they would also remove mutations that are believed to build new parts. So there is the problem of the evolution of (sophisticated repair) mechanisms that prevent evolution, all the way back to the very origin of life. 58

A. B. Williams (2016): Cells can revert the large variety of DNA lesions that are induced by endogenous and exogenous genotoxic attacks through a variety of sophisticated DNA-repair machineries,. Nucleotide excision repair (NER) removes a variety of helix-distorting lesions such as typically induced by UV irradiation, whereas base excision repair (BER) targets oxidative base modifications. Mismatch repair (MMR) scans for nucleotides that have been erroneously inserted during replication. DNA DSBs that are typically induced by IR are resolved either by nonhomologous end joining (NHEJ) or by homologous recombination (HR), whereas RECQ helicases assume various roles in genome maintenance during recombination repair and replication.64

Nucleotide Counting and Proofreading: Safeguarding DNA Replication Fidelity

One of the mechanisms employed for error-checking and maintaining the accuracy of DNA sequences involves counting nucleotides. This mechanism is particularly relevant during DNA replication and is closely associated with the proofreading activity of DNA polymerases. DNA polymerases are enzymes responsible for synthesizing new DNA strands by adding complementary nucleotides to the growing strand during DNA replication. Many DNA polymerases possess a specialized 3' to 5' exonuclease activity, which allows them to "proofread" the DNA strand as they add nucleotides. During DNA replication, DNA polymerases identify the correct nucleotide to add by ensuring proper base pairing with the template strand. For example, adenine (A) pairs with thymine (T), and cytosine (C) pairs with guanine (G). Checking for Correct Pairing: Before adding a nucleotide, the DNA polymerase briefly pauses to ensure that the incoming nucleotide is correctly base-paired with the template nucleotide. If there's a mismatch, the DNA polymerase can detect it. If a mismatched nucleotide has been added, the DNA polymerase can use its 3' to 5' exonuclease activity to backtrack along the DNA strand. This exonuclease activity allows the polymerase to remove the incorrect nucleotide. Once the incorrect nucleotide is removed, the DNA polymerase resumes its forward movement and adds the correct nucleotide in its place. This proofreading process helps to maintain the accuracy of the DNA sequence. The key here is that the DNA polymerase is effectively "counting" the nucleotides as it moves along the DNA strand. If a mismatched nucleotide is added, the polymerase recognizes the error and takes corrective action by removing the incorrect nucleotide before continuing the replication process. This proofreading mechanism is a crucial part of DNA replication and contributes to the fidelity of the genetic information passed on to daughter cells during cell division. It's worth noting that while this mechanism is effective, it's not infallible, and occasional errors still occur. However, the combination of proofreading, mismatch repair, and other DNA repair mechanisms helps to ensure the integrity of the genetic code.

The intricate process of error checking and repair in DNA replication is a remarkable example of the precision and complexity present in biological systems. The emergence of this process prior to the beginning of life raises important questions about its origin and challenges explanations solely based on unguided, random naturalistic processes. The error-checking and repair mechanisms in DNA replication involve the recognition of correct base pairing, the detection of errors, and the precise removal and replacement of incorrect nucleotides. This process requires information about the correct sequence and the ability to discern errors from the correct information. Information-rich processes, such as error correction, are a hallmark of intelligent design and purposeful engineering. The error-checking and repair machinery in DNA replication is irreducibly complex, meaning that it requires the coordinated function of multiple components to achieve its function. Removing or altering any of these components would disrupt the entire process, rendering it ineffective. Such irreducible complexity presents a challenge for gradual, step-by-step evolution through natural selection, as intermediate stages would not provide a selective advantage until the entire system is in place. From a naturalistic perspective, the emergence of error-checking and repair mechanisms prior to the beginning of life poses several challenges: The error-checking and repair mechanisms involve a variety of proteins with specific functions, as well as sophisticated molecular interactions. Explaining the simultaneous emergence of these components through unguided processes is a significant challenge. Error correction requires knowledge of the correct sequence. Information-rich processes are typically associated with intelligent design. How could this information-rich system arise without a guiding intelligence? The error-checking and repair mechanisms require functional DNA polymerases for their operation. However, functional DNA polymerases themselves require error-checking and repair to ensure accuracy. This creates a chicken-and-egg dilemma in which neither component could have emerged without the other. In the absence of error-checking and repair mechanisms, errors in replication would accumulate rapidly, leading to a loss of genetic information and functional integrity. This raises questions about the selective advantage of gradual, unguided processes in the early stages of life's emergence.

Molecules like DNA do not possess inherent goals, intentions, or purpose. They are subject to the laws of chemistry and physics. The emergence of complex biochemical systems, including error-checking and repair mechanisms, must be explained in terms of the interactions and properties of these molecules within their environment. While molecules themselves lack inherent purpose, the complexity and functionality observed in biological systems raise important questions about their origins. The intricate mechanisms, such as error checking and repair, are critical for the survival and function of living organisms. These mechanisms enable organisms to maintain genetic fidelity, adapt to changing environments, and reproduce successfully. The argument for intelligent design suggests that the presence of purposeful, information-rich systems points toward a designer or creative force. The probability of such complex systems emerging through unguided processes is statistically close to zero.

Remarkable DNA repair capabilities of Deinococcus radiodurans and E.Coli

Extreme Genome Repair (2009): If its naming had followed, rather than preceded, molecular analyses of its DNA, the extremophile bacterium Deinococcus radiodurans might have been called Lazarus. After shattering of its 3.2 Mb genome into 20–30 kb pieces by desiccation or a high dose of ionizing radiation, D. radiodurans miraculously reassembles its genome such that only 3 hr later fully reconstituted nonrearranged chromosomes are present, and the cells carry on, alive as normal 65

T. Devitt (2014): John R. Battista, a professor of biological sciences at Louisiana State University, showed that E. coli could evolve to resist ionizing radiation by exposing cultures of the bacterium to the highly radioactive isotope cobalt-60. “We blasted the cultures until 99 percent of the bacteria were dead. Then we’d grow up the survivors and blast them again. We did that twenty times,” explains Cox. The result were E. coli capable of enduring as much as four orders of magnitude more ionizing radiation, making them similar to Deinococcus radiodurans, a desert-dwelling bacterium found in the 1950s to be remarkably resistant to radiation. That bacterium is capable of surviving more than one thousand times the radiation dose that would kill a human. 66

1. Organisms are constantly exposed to different environments, and in order to survive, require to be able to adapt to external conditions.
2. Life, in order to perpetuate, has to replicate. That includes DNA, which must be replicated with extreme accuracy. Somehow, the cell knows when DNA is accurately replicated, and when not. There are extremely complex quality control mechanisms in place, which constantly monitor the process. At least 3 error check and repair mechanisms keep error during replication down to 1 error in 10 billion nucleotides replicated.
3. These repair mechanisms, sophisticated proteins, are also encoded in DNA. So proteins are required to error check and repair DNA but accurately replicated DNA is necessary to make the proteins that repair DNA.
4. That is an all-or-nothing business. Therefore, these sophisticated systems had to emerge all at once, and require a designer.  

The existence of multiple layers of repair mechanisms that prevent random mutations from happening to DNA, has been termed the ‘mutation protection paradox’.

W. DeJong (2011): Both digital codes in computers and nucleotide codes in cells are protected against mutations. Mutation protection affects the random change and selection of digital and nucleotide codes. Our mutation protection perspective enhances the understanding of the evolutionary dynamics of digital and nucleotide codes and its limitations, and reveals a paradox between the necessity of dysfunctioning mutation protection for evolution and its disadvantage for survival. Our mutation protection perspective suggests new directions for research into mutational robustness. Unbounded random change of nucleotide codes through the accumulation of irreparable, advantageous, code expanding, inheritable mutations at the level of individual nucleotides, as proposed by evolutionary theory, requires the mutation protection at the level of the individual nucleotides and at the higher levels of the code to be switched off or at least to dysfunction. Dysfunctioning mutation protection, however, is the origin of cancer and hereditary diseases, which reduce the capacity to live and to reproduce. Our mutation protection perspective of the evolutionary dynamics of digital and nucleotide codes thus reveals the presence of a paradox in evolutionary theory between the necessity and the disadvantage of dysfunctioning mutation protection. This mutation protection paradox, which is closely related with the paradox between evolvability and mutational robustness, needs further investigation. 59

Peto's paradox....

Marc Tollis (2017): In a multicellular organism, cells must go through a cell cycle that includes growth and division. Every time a human cell divides, it must copy its six billion base pairs of DNA, and it inevitably makes some mistakes. These mistakes are called somatic mutations (cells in the body other than sperm and egg cells). Some somatic mutations may occur in genetic pathways that control cell proliferation, DNA repair, apoptosis, telomere erosion, and growth of new blood vessels, disrupting the normal checks on carcinogenesis. If every cell division carries a certain chance that a cancer-causing somatic mutation could occur, then the risk of developing cancer should be a function of the number of cell divisions in an organism’s lifetime. Therefore, large-bodied and long-lived organisms should face a higher lifetime risk of cancer simply due to the fact that their bodies contain more cells and will undergo more cell divisions over the course of their lifespan. However, a 2015 study that compared cancer incidence from zoo necropsy data for 36 mammals found that a higher risk of cancer does not correlate with increased body mass or lifespan. In fact, the evidence suggested that larger long-lived mammals actually get less cancer. This has profound implications for our understanding of how the cancer problem is solved.

When individuals in populations are exposed to the selective pressure of cancer risk, the population must evolve cancer suppression as an adaptation or else suffer fitness costs and possibly extinction. Discovering the mechanisms underlying these solutions to Peto’s Paradox requires the tools of numerous subfields of biology including genomics, comparative methods, and experiments with cells. For instance, genomic analyses revealed that the African savannah elephant (Loxodonta africana) genome contains 20 copies, or 40 alleles, of the most famous tumor suppressor gene TP53. The human genome contains only one TP53 copy, and two functional TP53 alleles are required for proper checks on cancer progression. When cells become stressed and incur DNA damage, they can either try to repair the DNA or they can undergo apopotosis, or self-destruction. The protein produced by the TP53 gene is necessary to turn on this apoptotic pathway. Humans with one defective TP53 allele have Li Fraumeni syndrome and a ~90% lifetime risk of many cancers, because they cannot properly shut down cells with DNA damage. Meanwhile, experiments revealed that elephant cells exposed to ionizing radiation behave in a manner consistent with what you would expect with all those TP53 copies—they are much more likely to switch on the apoptotic pathway and therefore destroy cells rather than accumulate carcinogenic mutations. 61

Comment: How does the author explain the origin of these protective mechanisms? He claims: "The solution to Peto’s Paradox is quite simple: evolution". This is an ad-hoc assertion and raises the question: How could complex multicellular organisms have evolved if these cancer protection mechanisms were not implemented before the transition occurred, since, otherwise, these organisms would have gone extinct? But how would cancer protection mechanisms have been selected, if before multicellularity arose, these complex systems would not have conveyed any function? 1. Multicellularity, 2. genome maintenance mechanisms, cell-cycle arrest mechanisms, and apoptosis, and 3. p53 transcription factors would have had to evolve together since they work as a system.   This problem becomes even greater if considering, that animals with large body size supposedly evolved independently many times across the history of life, and, therefore, these mechanisms would have had to be recruited multiple times. The paradox is only solved if we hypothesize that large animals were created independently by God, and right from the beginning equipped with tumor suppressor mechanisms from the get-go.

A. B. Williams (2016): The loss of p53 is a major driver of cancer development mainly because, in the absence of this “guardian of the genome,” cells are no longer adequately protected from mutations and genomic aberrations. Intriguingly, the evolutionary occurrence of p53 homologs appears to be associated with multicellularity. With the advent of metazoans, genome maintenance became a specialized task with distinct requirements in germ cells and somatic tissues. With the central importance of p53 in controlling genome instability–driven cancer development, it might not be surprising that p53 controls DNA-damage checkpoints and impacts the activity of various DNA-repair systems. 64

B. J. Aubrey (2016): The fundamental biological importance of the Tp53 gene family is highlighted by its evolutionary conservation for more than one billion years dating back to the earliest multicellular organisms. The TP53 protein provides essential functions in the cellular response to diverse stresses and safeguards maintenance of genomic integrity, and this is manifest in its critical role in tumor suppression. The importance of Tp53 in tumor prevention is exemplified in human cancer where it is the most frequently detected genetic alteration. This is confirmed in animal models, in which a defective Tp53 gene leads inexorably to cancer development, whereas reinstatement of TP53 function results in regression of established tumors that had been initiated by loss of TP53.

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235Perguntas .... - Page 10 Empty Re: Perguntas .... Fri Aug 18, 2023 5:43 am

Otangelo


Admin

"Hi. I am Mary, the mother of Jesus. Servant of the Lord. When I was visited by the Angel Gabriel, he greeted me with these words: Greetings, you who are highly favored! The Lord is with you.

God sent the angel Gabriel to Nazareth, a town in Galilee, where I lived with Joseph, my husband. The angel said to me: 'Greetings, you who are highly favored! The Lord is with you.'

I was greatly troubled at his words and wondered what kind of greeting this might be. But the angel said to me, 'Do not be afraid, Mary; you have found favor with God. You will conceive and give birth to a son, and you are to call him Jesus. He will be great and will be called the Son of the Most High. The Lord God will give him the throne of his father David, and he will reign over Jacob’s descendants forever; his kingdom will never end.'

'How will this be,' I asked the angel, 'since I am a virgin?' The angel answered, 'The Holy Spirit will come on you, and the power of the Most High will overshadow you. So the holy one to be born will be called the Son of God. Even Elizabeth your relative is going to have a child in her old age, and she who was said to be unable to conceive is in her sixth month. For no word from God will ever fail.'

'I am the Lord’s servant,' I answered. 'May your word to me be fulfilled.' Then the angel left me. And I said:

'My soul glorifies the Lord
and my spirit rejoices in God my Savior,
for he has been mindful of the humble state of his servant.
From now on all generations will call me blessed,
for the Mighty One has done great things for me—holy is his name.
His mercy extends to those who fear him,
from generation to generation.
He has performed mighty deeds with his arm;
he has scattered those who are proud in their inmost thoughts.
He has brought down rulers from their thrones
but has lifted up the humble.
He has filled the hungry with good things
but has sent the rich away empty.
He has helped his servant Israel,
remembering to be merciful
to Abraham and his descendants forever,
just as he promised our ancestors.'"

If you are a Catholic, you pray to me through various prayers and devotions. These prayers are intended to seek my intercession and ask for my help, guidance, and protection. Some of the most well-known prayers to me in the Catholic tradition include: Hail Mary (Ave Maria), Hail Holy Queen, (Salve Regina) Memorare, and the Rosary.

Are you devoted to me, and do you believe that I am the "Mediatrix of All Graces" or "Mediatrix between Man and God", that I am an intermediator, between man and God?

Doctrines and practices should be derived exclusively from the Bible.

In 1 Timothy 2:5 it says: "For there is one God and one mediator between God and mankind, the man Christ Jesus."  Jesus is the only mediator between God and humanity.   Devotion to me has no direct biblical basis and is a non-biblical element to your worship and spirituality.

Do you believe that I can intercede with God on your behalf?

Hear what Hebrews 7:25 says: "Therefore he is able to save completely those who come to God through him because he always lives to intercede for them." This verse highlights Jesus' ongoing role as an intercessor, and not me, or other saints.

The Catholic Church might encourage you to approach me as a model of faith, humility, and obedience, and to ask for my prayers. But Jesus teaches us to pray like The Lord's Prayer: In this passage, Jesus teaches his disciples how to pray, emphasizing a direct approach to God. Seek God only in prayers, and a relationship with God, and not me, or the saints.

Do you have statues and images of me in your home ? In Exodus 20:4-5 it says: "You shall not make for yourself an image in the form of anything in heaven above or on the earth beneath or in the waters below. You shall not bow down to them or worship them."

The use of images or statues in veneration of me is idolatry.



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236Perguntas .... - Page 10 Empty Re: Perguntas .... Fri Aug 18, 2023 7:48 am

Otangelo


Admin

Dear Brothers and Sisters in Christ,

In these challenging times of adversity, my heart is united with yours.

I stand with you as you face the trials brought upon the Church by recent events.

The attacks on your places of worship are a painful reminder of the challenges believers may encounter, but remember, you are not alone.

The attacks on our churches are a stark reminder of the world's brokenness, yet they cannot dim the radiant light of your faith.

In the midst of turmoil, cling to the truth that our God is sovereign, and He is in control.

Proverbs 19:21 reminds us, "Many are the plans in a person's heart, but it is the Lord's purpose that prevails."

Despite the chaos around us, His purpose will always stand.

Your strength, resilience, and unwavering trust in God are a powerful testament to your faith.

Let Psalm 46:1-3 resonate deeply within you: "God is our refuge and strength, an ever-present help in trouble.

Therefore, we will not fear. Even in the face of turmoil, God is your refuge and fortress.

I understand the uncertainty you may be feeling, but rest assured that God's presence never wavers.

Deuteronomy 31:6 reassures us, "Be strong and courageous. Do not be afraid or terrified because of them, for the Lord your God goes with you; he will never leave you nor forsake you."

He is with you through every trial, a shield and protector.

The God who parted the Red Sea, who walked with Daniel in the lions' den, who calmed the storm with a single word, is the same God who stands beside you today.

Isaiah 41:10 reminds us, "So do not fear, for I am with you; do not be dismayed, for I am your God.

I will strengthen you and help you; I will uphold you with my righteous right hand."

Even in the face of adversity, remember that your faith community is bound together by an unbreakable bond.

Galatians 6:2 encourages us to "carry each other's burdens, and in this way you will fulfill the law of Christ."

Lean on each other and find strength in your unity.

As you rebuild and heal, remember that Romans 8:28 promises,

"And we know that in all things God works for the good of those who love him, who have been called according to his purpose."

Your faithfulness and perseverance are planting seeds of hope and transformation.

Dear brothers and sisters, in the midst of these trials, stand firm in the assurance that God is in control,

that He is your protector, and that His love for you is unwavering.

May your faith shine even brighter in the face of darkness, and may His peace be your constant guide.

With love and prayers,




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237Perguntas .... - Page 10 Empty Re: Perguntas .... Sat Aug 19, 2023 5:18 am

Otangelo


Admin

Here are some reasons that challenge the likelihood of endosymbiotic events

The process of engulfing an entire bacterial cell and integrating it into a eukaryotic cell would have been an extraordinarily complex and unlikely event to occur spontaneously. The probability of such an event happening in a timely manner is close to zero. The successful fusion of two separate cell membranes poses challenges due to the differences in lipid composition and physical properties of the membranes. The spontaneous fusion of dissimilar membranes is extremely unlikely.  The integration of bacterial DNA into the host cell's genome would have required mechanisms to protect the bacterial DNA from degradation and ensure its stable integration. The complexity of such integration processes raises questions about their plausibility.  Engulfing a foreign bacterium could have triggered a potent immune response in the host cell, leading to the destruction of both the bacterium and the host cell. Overcoming this barrier without causing harm to either party presents a challenge. The absence of intermediate forms or transitional stages indicates that the endosymbiotic events never occurred. The lack of direct evidence showing the gradual transition from free-living bacteria to organelles is a point of contention. The success of endosymbiosis relies on a series of highly specific coincidences, such as the engulfing of a bacterium that possesses the right traits to become an organelle, and the host cell's ability to adapt to this new symbiotic relationship. Such a sequence of events is very improbable. No direct observation of an endosymbiotic event has been made, making it difficult to definitively prove the hypothesis beyond doubt.

Eukaryotic cells possess complex genomes with both nuclear and mitochondrial DNA.  Mitochondria possess a unique genetic code that differs from the universal genetic code found in the nuclear DNA of eukaryotic cells and the DNA of most organisms. The transition from one genetic code to a modified one, especially in the context of endosymbiosis and the evolution of mitochondria,  presents several challenges and potential problems. Mitochondria have their own genetic material and use a slightly different genetic code compared to the nuclear DNA of the host eukaryotic cell. This phenomenon is often referred to as the "genetic code discrepancy."  The transition to a modified genetic code requires changes in the cellular machinery responsible for translating genetic information into proteins. During the integration of a free-living bacterium into a eukaryotic host cell as a mitochondrion, the host cell would need to ensure that its existing translation machinery can still function properly with the new genetic code. Any mismatch between the codes could lead to errors in protein synthesis and potential dysfunction. The host cell would need to develop mechanisms to regulate the expression of both nuclear and mitochondrial genes, which would now use slightly different genetic codes. Coordinating the dual genetic systems of eukaryotic cells—nuclear DNA and mitochondrial DNA—presents significant challenges due to the need to ensure the proper functioning of the cell's overall metabolism. This coordination is essential to prevent conflicts and disruptions that could compromise cellular health. Both nuclear and mitochondrial genomes encode proteins essential for mitochondrial function. Coordinating the expression of genes from two separate genomes requires intricate regulatory mechanisms to ensure that the right proteins are produced at the right levels and times. Mismatches in expression can lead to imbalances and dysfunction. The replication and repair mechanisms of nuclear and mitochondrial DNA are distinct. Coordinating these processes to maintain the integrity of both genomes without causing damage or imbalances requires intricate regulatory mechanisms. Mistakes in replication or repair can lead to mutations, deletions, or other genetic abnormalities. The transcription and translation machineries for nuclear and mitochondrial genes are different due to the evolutionary divergence of these organelles. Ensuring that the right machinery is in the right place and functions harmoniously requires complex coordination to avoid errors in protein synthesis.  Mitochondrial proteins are often encoded in the nuclear genome and then imported into the mitochondria. Coordinating the synthesis, import, and assembly of these proteins to form functional mitochondrial complexes is complex and requires precise timing and targeting signals. Mitochondria are central to energy production through oxidative phosphorylation, involving multiple protein complexes encoded by both nuclear and mitochondrial genes. Coordinating the proper assembly of these complexes and their respective subunits is crucial for efficient energy production. Mitochondria are a major source of reactive oxygen species (ROS), which can be harmful if not controlled. Coordinating the balance between ROS production and antioxidant defenses to maintain cellular homeostasis is essential to prevent oxidative damage.  Over time, the genetic codes, transcription factors, and other molecular components of both genomes would have had to evolve. Coordinating these evolutionary changes while maintaining functional compatibility between the two genomes is a challenging balancing act.  Cellular stress, such as changes in nutrient availability or environmental conditions, would impact both nuclear and mitochondrial functions. Coordinating stress responses and adaptive changes require complex signaling networks to ensure proper cellular responses.  During cell differentiation and development, the energy demands and mitochondrial functions can vary significantly. Coordinating these changes to ensure that mitochondria support the specific needs of different cell types is a complex process.  Coordination breakdowns between nuclear and mitochondrial genomes can lead to genetic disorders and diseases, known as mitochondrial diseases. These conditions can result from mutations in either nuclear or mitochondrial DNA and often involve disrupted coordination between the two genomes. Addressing these challenges requires intricate molecular and cellular mechanisms that would have had to evolve over billions of years. 

The efficient functioning of mitochondria relies on the import of proteins that are encoded by both the nuclear genome and the mitochondrial genome. Importing these proteins into the correct mitochondrial compartments is crucial for maintaining mitochondrial structure, function, and overall cellular health. During the transition from a free-living bacterium to a symbiotic organelle, the host cell would have needed to evolve mechanisms to ensure the recognition, import, and proper targeting of proteins encoded by the modified mitochondrial genetic code. This process involves a combination of complex molecular mechanisms and the coevolution of various components. The evolution of a functional protein import machinery would have been essential for the successful integration of the endosymbiotic bacterium into the host cell. This machinery includes protein complexes located on the mitochondrial outer and inner membranes, which are responsible for recognizing, translocating, and folding imported proteins. Over time, the host cell would have needed to adapt and refine its import machinery to accommodate the changes in protein sequences resulting from the altered mitochondrial genetic code. Proteins destined for specific mitochondrial compartments contain targeting signals that guide them to their proper destinations. These signals can be amino acid sequences or structural motifs that are recognized by the import machinery. As the mitochondrial genetic code evolved, the targeting signals on the proteins encoded by the modified code would need to coevolve to match the changes in the import machinery's recognition sites. The host cell would need to evolve mechanisms that allow the import machinery to distinguish between proteins encoded by the modified mitochondrial genetic code and those encoded by the nuclear genome. This would involve fine-tuning the recognition process to prevent errors in protein import and ensure that only the correct proteins are translocated into the mitochondria. The coevolution of protein import and targeting signals would also require the development of quality control mechanisms. These mechanisms would help identify misfolded or incorrectly targeted proteins and prevent their integration into the mitochondria, which could disrupt mitochondrial function. Imported proteins often need to be properly folded and assembled into functional complexes within the mitochondria. Coordinating the folding processes and interactions among proteins with different origins (nuclear and mitochondrial) would require the evolution of sophisticated chaperones and assembly factors. As the host cell and the newly acquired mitochondria adapted to each other, feedback mechanisms might have developed to ensure the effective functioning of the protein import system. These mechanisms would enable the host cell to adjust the expression and regulation of import components based on the functional needs of the mitochondria.  The coevolution of protein import mechanisms and targeting signals would need to maintain stability over long evolutionary timescales. Ensuring the compatibility of these systems even as both the host cell and the mitochondria underwent further evolutionary changes would be a challenge.

Evolution of tRNA Adaptation: Transfer RNAs (tRNAs) play a key role in translating genetic information into proteins. The tRNAs used in the modified genetic code of mitochondria would need to evolve and adapt to this new code, and this adaptation might not happen smoothly.  The adaptation of the translation machinery to accommodate the modified genetic code of mitochondria involves not only tRNAs but also other key players in the process. This adaptation is a complex and critical aspect of the endosymbiotic transition that would have required significant evolutionary changes. Transfer RNAs (tRNAs) are molecules that bring amino acids to the ribosome during protein synthesis, matching specific codons on the mRNA with the appropriate amino acids. In the context of mitochondria, the tRNAs had to evolve and adapt to recognize the modified codons of the mitochondrial genetic code. This adaptation likely involved changes in tRNA structure and sequence to accommodate the new codon-amino acid assignments.  The anticodon region of tRNAs plays a critical role in base-pairing with the codons on the mRNA. The evolution of the mitochondrial genetic code required tRNAs to have anticodons that specifically recognize the altered codons used in mitochondrial protein-coding genes. This adaptation could involve changes in the anticodon loop and anticodon sequence of mitochondrial tRNAs. Aminoacyl-tRNA synthetases are enzymes responsible for attaching amino acids to their corresponding tRNAs. The evolution of the mitochondrial genetic code would have necessitated changes in these enzymes to ensure accurate charging of tRNAs with the correct amino acids, compatible with the modified genetic code. The ribosome, the molecular machine responsible for protein synthesis, would also need to adapt to accommodate the modified genetic code. This adaptation could involve changes in ribosomal RNA (rRNA) and ribosomal protein components that interact with tRNAs and mRNA during translation. The ribosome and associated translation factors recognize codons on the mRNA to ensure accurate protein synthesis. With the altered genetic code, the codon recognition mechanisms would need to evolve to correctly interpret the new codon-amino acid assignments. The adaptation of tRNAs, aaRS, ribosomes, and other translation factors would likely need to be coordinated to ensure that the entire translation machinery works seamlessly with the modified genetic code. Any discrepancies between these components could lead to errors in translation and protein synthesis. While adapting to the modified genetic code, it's crucial to maintain the functionality of the translation machinery for the universal genetic code in the nucleus. Balancing these two codes and maintaining proper coordination is a complex challenge. Over evolutionary time, the translation machinery's adaptation would need to be stable and consistent to ensure the continued functioning of mitochondria and the overall cellular metabolism. While these challenges might seem daunting, proponents of the endosymbiotic theory argue that natural selection and coevolution over long periods of time could have enabled the gradual adjustment of these systems. The complexity of these processes underscores the remarkable evolutionary journey that eukaryotic cells and their mitochondria would have had to undergo, which stretches plausibility by far.

Cytoskeletal Evolution 

The evolution of the dynamic cytoskeleton in eukaryotic cells, comprised of actin and tubulin filaments, along with associated motor proteins, is a testament to the complexity of cellular organization and function. Developing it would have involved the gradual emergence of the sophisticated molecular machinery that enabled cells to perform essential processes like maintaining shape, facilitating movement, and mediating intracellular transport. The evolution of the cytoskeleton would have had to begin with the emergence of protein components that could form filamentous structures. Actin and tubulin are two primary proteins that form filaments. These proteins have the capacity to self-assemble into filaments, creating a structural framework within the cell. Actin and tubulin filaments are dynamic structures that can polymerize (grow) and depolymerize (shrink) rapidly. This dynamic behavior is crucial for processes like cell division, migration, and intracellular transport. Evolving this dynamic behavior would have required the development of mechanisms that regulate polymerization and depolymerization rates. Motor proteins, such as myosins (associated with actin) and kinesins/dyneins (associated with tubulin) would have had to evolve to interact with cytoskeletal filaments and convert chemical energy into mechanical work. These molecular motors allow cells to move, transport organelles, and perform various other functions by utilizing the energy derived from ATP hydrolysis. Motor proteins have distinct domains responsible for filament binding, ATP binding and hydrolysis, and movement along filaments. Evolving these specialized domains would have required precise coordination to ensure proper function and efficient movement along the cytoskeletal tracks. Motor proteins operate as "molecular cargo carriers" that transport organelles, vesicles, and other cellular components along cytoskeletal filaments. Evolving motor proteins and their interactions with filaments would be required to facilitate the evolution of more complex intracellular transport systems, which are crucial for cell viability and specialization. Actin filaments, along with actin-binding proteins and myosins, are essential for cellular processes like cell crawling, amoeboid movement, and muscle contraction. The evolution of these mechanisms allowed cells to change shape, move, and interact with their environment. Cytoskeletal elements play a critical role in cell division. During cytokinesis, actin and myosin filaments form a contractile ring that pinches the cell into two daughter cells. Evolving these mechanisms would have been necessary to enable eukaryotic cells to divide efficiently. The cytoskeleton is regulated by a complex network of signaling pathways and post-translational modifications. Evolving these regulatory mechanisms would have been necessary to allow cells to respond to internal and external cues, adjusting their cytoskeletal dynamics to changing conditions. Depending on eukaryotic cells evolving and diversifying, the cytoskeleton would have to become more specialized. Different cell types would require the development of unique arrangements of cytoskeletal elements to perform specialized functions, such as the intricate cytoskeletal structures in neurons for rapid and precise signal transmission. The evolution of the cytoskeleton, motor proteins, and associated regulatory mechanisms would have required coordinated changes across multiple components. These changes had to be balanced to ensure that the cytoskeleton could perform its various functions while maintaining overall cellular integrity.

Evolution of intracellular transport mechanisms

The evolution of cellular processes often involves the interdependence of multiple components. For example, in intracellular transport, molecular motors, vesicle sorting signals, and regulatory elements need to coevolve to ensure proper functioning. If one component evolves before the others, it might not provide any selective advantage until the entire system is functional. The gradual evolution of complex systems requires intermediate steps that confer a selective advantage. For processes like intracellular transport and signaling, it would have been difficult to identify functional intermediate stages that would provide a clear advantage without the entire system being in place.  Evolutionary changes often require coordinated mutations in multiple genes or protein domains. The simultaneous occurrence of these mutations in a population is less likely, as the probability of the necessary mutations arising together is lower compared to single mutations. Incomplete or partially functional intermediates might lead to negative selection. If a transitional stage doesn't provide a clear benefit to the cell, it might be selected due to the potential disadvantages it introduces. The step-by-step evolution of complex systems involves maintaining stability and functionality throughout the process. As components evolve and interact, maintaining the overall stability and functionality of the system becomes increasingly challenging. The accumulation of mutations, especially in interconnected systems, can lead to a genetic load where negative effects from mutations outweigh the benefits of adaptive changes. Complex systems often exhibit emergent properties that arise from the interactions of individual components. Predicting these emergent properties during gradual evolution can be difficult, as they might only become apparent when the entire system is functional. Cellular functions, especially complex ones, require precise coordination and organization. Evolutionary changes that disrupt this coordination might lead to dysfunction rather than improvement.

Transport and Communication

The evolution of the complex mechanisms for intracellular transport and organelle communication in eukaryotic cells would have required the emergence and refinement of various players. These players needed to evolve de novo over evolutionary timescales to ensure the proper functioning of the cell. However, achieving such a system through gradual, evolutionary steps would have faced numerous obstacles and difficulties due to the intricacies of the components involved and the challenges posed by step-by-step evolution.  Molecular motors, such as myosins, kinesins, and dyneins, needed to evolve de novo to transport cellular cargo along cytoskeletal filaments. These motors required the development of motor domains for filament binding, ATP hydrolysis, and movement.  Sorting signals would have had to emerge to direct molecules to specific destinations within the cell. These signals, often short amino acid sequences, needed to evolve to ensure precise vesicle targeting. Proteins that mediate interactions between molecular motors and vesicles, such as those with Rab GTPases, were necessary to enable vesicle transport. These adaptors would have required specific binding domains to evolve.  Receptors for signaling pathways needed to evolve to recognize specific ligands and initiate cellular responses. These receptors often have extracellular domains for ligand binding and intracellular domains for downstream signaling.  Signaling pathways required the evolution of intracellular molecules, including kinases, phosphatases, and secondary messengers. These molecules help transmit signals from receptors to effector proteins.  Regulatory elements like transcription factors and post-translational modification enzymes needed to evolve to ensure proper cellular responses to signaling cues. These elements regulate gene expression and protein function.

Obstacles and Difficulties in Achieving the System Gradually

The simultaneous evolution of multiple components, such as molecular motors, vesicle sorting signals, and receptor molecules, would have been required for the entire system to function. Achieving coordinated changes across different genes and protein domains is complex.  Complex systems often require intermediate stages that provide selective advantages. However, identifying functional intermediates for mechanisms like intracellular transport and signaling pathways might be challenging due to the need for multiple components to be in place.  Intermediate stages might not provide clear benefits and could be selected against. Evolution of incomplete systems might lead to negative selection due to decreased fitness. Achieving precise regulation and timing of intracellular transport and communication is crucial. The evolution of regulatory mechanisms would have been necessary to prevent dysregulation and inappropriate signaling.  Newly evolved intracellular transport and communication mechanisms would have needed to integrate seamlessly with existing cellular processes. Achieving this integration without disrupting essential functions poses a challenge.  Many cellular processes depend on intricate protein-protein interactions. Evolving the correct interactions through step-by-step changes is challenging, especially considering the specificity and complexity of these interactions. Achieving the necessary mutations in the right genes and domains, while avoiding negative effects, is a complex interplay of chance and selection. Combining random mutations into functional pathways can be difficult. The correct expression and localization of newly evolved proteins, such as motor proteins and receptor molecules, would have been necessary to ensure proper functionality. 


Genetic and Cellular Complexity: The overall increase in cellular complexity, including the emergence of specialized organelles, regulatory networks, and intricate cellular processes, would have required coordinated changes across multiple levels of organization.

These hurdles collectively imply that the transition from prokaryotic to eukaryotic cellular organization was likely not a simple gradual process but involved intricate and interdependent evolutionary events. While the specifics of how these challenges were overcome remain a topic of ongoing research and debate, the complexities involved underscore the remarkable nature of this transition in the history of life on Earth.

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238Perguntas .... - Page 10 Empty Re: Perguntas .... Wed Aug 23, 2023 8:14 am

Otangelo


Admin

14. Xia Hua: Darwinism for the Genomic Age: Connecting Mutation to Diversification  07 February 2017
15. Z Patwa: The fixation probability of beneficial mutations 29 July 2008
16. 
17. Adam Eyre-Walker: The distribution of fitness effects of new mutations August 2007
18. David F. Coppedge Evolutionary Fitness Is Not Measurable November 20, 2021
19. Michael Lynch: The frailty of adaptive hypotheses for the origins of organismal complexity May 15, 2007
20. Molly K Burke et.al.,: Genome-wide analysis of a long-term evolution experiment with Drosophila 2010 Sep 30
21. Ben Bradley: Natural selection according to Darwin: cause or effect? 11 April 2022
22. Adam Levy: How evolution builds genes from scratch 16 October 2019
23. Michael Syvanen: Evolutionary Implications of Horizontal Gene Transfer 21 August 2012
24. Adam Eyre-Walker: The distribution of fitness effects of new mutations August 2007
25. Michael Lynch: The frailty of adaptive hypotheses for the origins of organismal complexity May 15, 2007
26. Molly K Burke et.al.,: Genome-wide analysis of a long-term evolution experiment with Drosophila 2010 Sep 30
27. Ben Bradley: Natural selection according to Darwin: cause or effect? 11 April 2022
28. Adam Levy: How evolution builds genes from scratch 16 October 2019
29. Michael Syvanen: Evolutionary Implications of Horizontal Gene Transfer 21 August 2012
30. Shelly Hamilich: Widespread horizontal gene transfer between plants and their microbiota August 26, 2022
31. David Coppedge: Gene Sharing Is More Widespread than Thought, with Implications for Darwinism September 20, 2022
32. Rama P. Bhatia: Environment and the Evolutionary Trajectory of Horizontal Gene Transfer April 01, 2022
33. J.Dulle: The (In)adequacy of Darwinian Evolution
34. Matthew Hurles: Gene Duplication: The Genomic Trade in Spare Parts July 13, 2004
35. Alisha K Holloway: Experimental evolution of gene duplicates in a bacterial plasmid model 2007 Feb
36. Joseph Esfandiar: Is gene duplication a viable explanation for the origination of biological information and complexity? 22 December 2010
37. Johan Hallin: Regulation plays a multifaceted role in the retention of gene duplicates November 22, 2019
38. Michael Lynch: The Origins of Genome Architecture 2007
39. Eugene V Koonin: Darwinian evolution in the light of genomics 2009 Mar
40. H. Allen Orr: Testing Natural Selection  2008
41. Paul Gibson : Can Purifying Natural Selection Preserve Biological Information? – May 2013
42. Eugene V. Koonin :Toward a theory of evolution as multilevel learning February 4, 2022
43. Jerry A. Coyne, Why Evolution is True, p. 123. 2009
44. Michael Lynch: The Origins of Genome Architecture 2007
45. Michael Behe: The Edge of Evolution: The Search for the Limits of Darwinism 2008
46. Gert Korthof: Either Design or Common Descent 22 July 2007
47. Michael Behe: The Edge of Evolution: The Search for the Limits of Darwinism 2008
48. Michael Behe: Amazon blog 
49. G.Bechly: Fossil Discontinuities: A Refutation of Darwinism and Confirmation of Intelligent Design 2018
50. Rick Durrett: Waiting for Two Mutations: With Applications to Regulatory Sequence Evolution and the Limits of Darwinian Evolution 2008 Nov  3
51. John Sanford: The waiting time problem in a model hominin population 17 September 2015
52. John Sanford: The Origin of Man and the “Waiting Time” Problem August 10, 2016
53. John C. Sanford: Multiple Overlapping Genetic Codes Profoundly Reduce the Probability of Beneficial Mutation 2013
54. D. Joseph: GENETIC DEGENERATION—EVIDENCE FOR INDEPENDENT ORIGINS  August 15, 2021
55. John C. Sanford: Multiple Overlapping Genetic Codes Profoundly Reduce the Probability of Beneficial Mutation 2013
56. Kathleen Donohue: Multi-tasking as an ancient skill: When one gene does many things well 01 April 2019
57. Yuri Pritykin: Genome-Wide Detection and Analysis of Multifunctional Genes October 5, 2015
58. John Michael Fischer: Debunking Evolution 2022
59. Aditi Gupta: Evolution of Genome Size in Asexual Digital Organisms 16 May 2016
60. David F. Coppedge Evolutionary Fitness Is Not Measurable November 20, 2021

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239Perguntas .... - Page 10 Empty Re: Perguntas .... Wed Aug 23, 2023 8:44 am

Otangelo


Admin

18. David F. Coppedge Evolutionary Fitness Is Not Measurable November 20, 2021
20. Molly K Burke et.al.,: Genome-wide analysis of a long-term evolution experiment with Drosophila 2010 Sep 30
21. Ben Bradley: Natural selection according to Darwin: cause or effect? 11 April 2022
22. Adam Levy: How evolution builds genes from scratch 16 October 2019
23. Michael Syvanen: Evolutionary Implications of Horizontal Gene Transfer 21 August 2012
24. Adam Eyre-Walker: The distribution of fitness effects of new mutations August 2007
25. Michael Lynch: The frailty of adaptive hypotheses for the origins of organismal complexity May 15, 2007
33. J.Dulle: The (In)adequacy of Darwinian Evolution
39. Eugene V Koonin: Darwinian evolution in the light of genomics 2009 Mar
41. Paul Gibson : Can Purifying Natural Selection Preserve Biological Information? – May 2013
42. Eugene V. Koonin :Toward a theory of evolution as multilevel learning February 4, 2022
47. Michael Behe: The Edge of Evolution: The Search for the Limits of Darwinism 2008
55. John C. Sanford: Multiple Overlapping Genetic Codes Profoundly Reduce the Probability of Beneficial Mutation 2013

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240Perguntas .... - Page 10 Empty Re: Perguntas .... Wed Aug 23, 2023 10:29 am

Otangelo


Admin

Diving deeper into each of these major transitions in evolution will provide your readers with a comprehensive understanding of the processes, mechanisms, and significance of these pivotal moments in the history of life on Earth. Here's a suggested approach on how to proceed with exploring each of these transitions:

1. Origin of Life and Viruses:

Provide an overview of the theories and hypotheses about the origin of life on Earth, including the Miller-Urey experiment and other models.
Discuss the key molecular building blocks of life, such as amino acids, nucleotides, and lipids, and their potential roles in the origin of life.
Examine the concept of abiogenesis and the transition from non-life to life.
Explore the nature of viruses, their structure, and their potential relationship to the early stages of life's evolution.

2. Prokaryote to Eukaryote Transition:

Delve into the characteristics that distinguish prokaryotic cells (bacteria and archaea) from eukaryotic cells.
Explore the endosymbiotic theory and the role of symbiosis in the evolution of eukaryotic cells.
Discuss the significance of membrane-bound organelles, such as mitochondria and chloroplasts, in eukaryotic cells.

3. Single-Celled to Multicellular Transition:

Explore the factors that might have led to the transition from single-celled organisms to multicellular organisms.
Discuss the advantages and challenges of multicellularity, including cell differentiation, communication, and division of labor.
Provide examples of the diversity of multicellular life, from simple multicellular organisms to complex multicellular structures in plants and animals.

4. Colonization of Land:

Explain the challenges and adaptations that organisms faced when transitioning from aquatic to terrestrial environments.
Discuss the evolution of features such as lungs, limbs, and water conservation mechanisms in terrestrial organisms.
Explore the significance of the colonization of land in shaping Earth's ecosystems and biodiversity.

5. Origin of Complex Animals:

Dive into the Cambrian explosion and the rapid diversification of complex animal life during this period.
Discuss the emergence of key animal body plans and the development of novel features, such as hard shells and exoskeletons.
Explore the ecological interactions and evolutionary pressures that contributed to the explosion of animal diversity.

6. Vertebrate Terrestrialization:

Trace the evolutionary path of vertebrates from aquatic to terrestrial environments.
Discuss the development of limbs and adaptations for movement on land.
Explore the transition of fish to tetrapods and the emergence of amphibians, reptiles, and eventually mammals.

7. Origin of Flight:

Examine the adaptations and anatomical changes that allowed certain groups of animals to evolve flight.
Discuss the convergent evolution of flight in insects, birds, and bats.
Explore the ecological implications of flight and its role in diversification and species success.

8. Origin of Flowers and Angiosperms:

Detail the characteristics of angiosperms (flowering plants) and their significance in modern ecosystems.
Discuss the co-evolution of plants and pollinators, including insects and animals.
Explore the role of flowers in reproduction, seed dispersal, and the formation of complex ecosystems.

9. Evolution of Social Behavior:

Discuss the emergence of social behaviors in various animal species.
Explore the advantages of social behavior, including cooperation, communication, and division of labor.
Examine examples of social structures in insects, mammals, and birds, and the evolutionary drivers behind them.

10. Cultural Evolution in Humans:

Explore the concept of cultural evolution and its role in shaping human societies.
Discuss the development of language, technology, art, and other cultural traits.
Examine the interplay between biological and cultural evolution in the human species.
For each transition, consider including examples, case studies, and recent research findings to provide a well-rounded and up-to-date perspective. Additionally, integrating diagrams, illustrations, and visual aids can help make complex concepts more accessible to your readers.

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241Perguntas .... - Page 10 Empty Re: Perguntas .... Thu Aug 24, 2023 8:05 am

Otangelo


Admin

give a short overview of                    , describe it, and point out the importance in biological systems


Appearance of                in the evolutionary timeline  



De Novo Genetic Information necessary to instantiate 
Describe the hypothetical process of generating and introducing new genetic information in the correct sequence to the existing genetic material, thereby creating the mechanisms of             during the instantiation of                      , starting from scratch.



Manufacturing codes and languages employed to instantiate 
Explain the manufacturing codes and languages that would have had to be created and instantiated and then involved and employed to go from an organism without                                  to one with a fully developed         .Since genetic information was mentioned and outlined before, do not include genetic  information systems in the response;  genetic information is involved, but since it was described previously, you describe only the manufacturing codes and information besides from genes. 




Epigenetic Regulatory Mechanisms necessary to be instantiated for
Point out the epigenetic regulation that would have had to be created and subsequently employed in order to perform the development of                        , from scratch. List the systems that would have to be employed to instantiate this regulation, and the systems, that operate in a joint venture together, to maintain the systems balance and operation of it.  


Signaling Pathways necessary to create, and maintain 
Point out the Signaling Pathways that would have been created and subsequently involved in the emergence of                      from scratch. Point out how they are interconnected, interdependent, and crosstalk with each other, and eventually with other biological systems. 


Regulatory codes necessary for maintenance and operation
Point out  the regulatory codes and languages that would have had to be instantiated and subsequently involved in the maintenance and operation of

Is there scientific evidence supporting the idea that                         were brought about by the process of evolution?
Point out, why an evolutionary set-up, step by step,of                    is extremely unlikely, faced on the complexity, the requirements to instantiate various codes, languages, signaling, and proteins that had to be operational right from the beginning, and intermediate stages would bear no function, and would not be selected. Explain how this interdependence could and would not have evolved in a stepwise fashion, because one mechanism, language, or code system, without the other, would bear no function, and therefore, they had to be instantiated and created all at once, fully operational, from scratch. write  from the perspective of a proponent of intelligent design. Do not write: " From an intelligent design standpoint ". Just say it.



Irreducibility and Interdependence of the systems to instantiate and operate
explain which of the manufacturing, signaling, and regulatory codes and languages in the process of creating, developing, and operating      are irreducible, and interdependent within each other, and how one would not bear function without the other. Explain which code and languages communicate with each other, crosstalk, and what communication systems are essential to have functional normal cell operation. Explain how this interdependence could and would not have evolved in a stepwise fashion, because one mechanism, language, or code system, without the other, would bear no function, and therefore, they had to be instantiated and created all at once, fully operational, from scratch. write  from the perspective of a proponent of intelligent design. Do not write: " From an intelligent design standpoint ". Just say it.


Once                   is instantiated and operational, what other intra and extracellular systems is it interdependent with?


/// write a syllogism, poiting to a designed set up, since these systems are based on semiotic code, languages, are interdependent, and had to emerge together, interlocked



Last edited by Otangelo on Sat Aug 26, 2023 6:14 am; edited 8 times in total

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242Perguntas .... - Page 10 Empty Re: Perguntas .... Fri Aug 25, 2023 5:59 am

Otangelo


Admin

The deeper I delve into unraveling the mechanisms that underlie our bodies, and the more I learn, the more I disagree with Darwin and his followers, and the more I agree with King David, who wrote:
"I praise you because I am fearfully and wonderfully made; your works are wonderful, I know that full well." Psalm 139:14

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243Perguntas .... - Page 10 Empty Re: Perguntas .... Fri Aug 25, 2023 7:12 pm

Otangelo


Admin

9. Cellular Reprogramming and Pluripotency

Cellular Reprogramming and Pluripotency are remarkable processes that allow cells to be induced into a pluripotent state, where they can potentially differentiate into various cell types. This ability has significant implications for tissue regeneration, disease modeling, and understanding developmental processes. Cellular reprogramming and pluripotency are advanced features that are primarily associated with multicellular eukaryotic organisms, especially mammals. While prokaryotic cells and unicellular eukaryotes exhibit limited forms of differentiation and adaptation, the ability to induce pluripotency represents a more complex and specialized phenomenon that emerged with multicellular organisms.

Information Systems Involved

Genetic Code: The genetic code contains the instructions for building proteins and regulatory factors that play roles in cellular reprogramming. Transcription factors such as Oct4, Sox2, Klf4, and c-Myc are key players in inducing pluripotency.
Epigenetic Regulation: Epigenetic mechanisms are critical for cellular reprogramming. Reprogramming factors work in concert with epigenetic modifiers to reset the epigenetic landscape of the cell, allowing it to regain pluripotency.
Manufacturing: The genetic code directs the synthesis of transcription factors and other molecules involved in cellular reprogramming. These factors can be introduced into cells through various methods to induce pluripotency.
Signaling Pathways: Signaling pathways can influence cellular reprogramming by modulating the activity of key transcription factors or epigenetic modifiers. Understanding these pathways enhances the efficiency of reprogramming techniques.
Regulatory Codes: Transcription factors and regulatory elements are central to the process of inducing pluripotency. The interplay of these factors orchestrates the reprogramming process by activating and silencing specific genes.

Eukaryotes vs. Prokaryotes and Unicellular Organisms

The concept of cellular reprogramming to induce pluripotency is a feature unique to eukaryotic organisms, particularly multicellular ones. Prokaryotic cells, such as bacteria, do not exhibit the same level of cellular differentiation and reprogramming seen in eukaryotic cells. While some unicellular eukaryotes might exhibit adaptation mechanisms, the sophisticated manipulation of cellular states observed in induced pluripotent stem cells (iPSCs) is specific to multicellular eukaryotes. Cellular reprogramming has transformative potential for regenerative medicine, disease modeling, and studying developmental processes. The ability to take specialized cells and return them to a pluripotent state offers new avenues for tissue repair and advancing our understanding of complex biological phenomena.



10. Cellular Senescence

Cellular Senescence refers to the state of irreversible cell cycle arrest that cells enter into as a response to various stresses or as part of normal development and aging. It plays a significant role in tissue repair, regeneration, and shaping during both development and aging. Cellular senescence is a complex phenomenon that has emerged in multicellular eukaryotes. While some aspects of cell cycle arrest and growth inhibition are observed in unicellular organisms, the specific features and regulatory mechanisms associated with cellular senescence are more prevalent and well-developed in multicellular organisms.

Information Systems Involved

Genetic Code: The genetic code contains genes and pathways involved in cellular senescence. Tumor suppressor genes like p53 and p16 are crucial regulators of senescence, as well as genes associated with DNA damage responses and cell cycle control.
Epigenetic Regulation: Epigenetic modifications play a role in determining whether a cell enters a senescent state. These modifications can impact the expression of genes involved in senescence-related pathways.
Signaling Pathways: Various signaling pathways, such as the DNA damage response pathway, contribute to the induction of cellular senescence. These pathways can be triggered by factors like telomere shortening, oxidative stress, and oncogene activation.
Regulatory Codes: Transcription factors and regulatory proteins control the expression of genes associated with cellular senescence. These factors can be influenced by both genetic and environmental cues.

Eukaryotes vs. Prokaryotes and Unicellular Organisms


While prokaryotic cells, such as bacteria, can enter a state of growth arrest in response to various stresses, this is not typically considered cellular senescence in the same sense as observed in eukaryotes. In unicellular eukaryotes, growth arrest can occur as a survival strategy, but the specific features and regulatory networks associated with cellular senescence in multicellular organisms are not commonly observed. Cellular senescence is most relevant in the context of multicellular eukaryotes. In multicellular organisms, senescent cells can contribute to tissue repair, embryonic development, and tissue remodeling. However, the accumulation of senescent cells over time is also implicated in aging and age-related diseases.

11. Centrosomes

Centrosomes are exclusive to eukaryotic cells and are not present in prokaryotic cells. Centrosomes play a central role in cell division, organization, and various cellular processes. They contribute to cell fate determination, tissue morphogenesis, and overall development, especially in multicellular organisms. Centrosomes emerged with the origin of eukaryotic cells. Eukaryotic cells involved the development of membrane-bound organelles and increased cellular complexity. Centrosomes contribute to the enhanced control of microtubule organization and cell division in eukaryotes.

Information Systems Involved

Genetic Code: The genetic code contains the instructions for building the various proteins that constitute centrosomes, such as centrin, pericentrin, and γ-tubulin. These proteins are essential for centrosome structure and function.
Manufacturing: Genetic information is transcribed and translated to produce the proteins that assemble into functional centrosomes. Centrosomes are composed of a pair of centrioles surrounded by pericentriolar material.
Signaling and Regulatory Codes: Signaling pathways and regulatory mechanisms control centrosome duplication, positioning, and function. For instance, the cell cycle machinery regulates centrosome duplication and ensures proper segregation during cell division.

Eukaryotes vs. Prokaryotes and Unicellular Organisms

Centrosomes are unique to eukaryotic cells and are not found in prokaryotic organisms. They are present in both unicellular and multicellular eukaryotes. While the complexity and organization of centrosomes might vary among different organisms, their fundamental role in microtubule organization, cell division, and cellular organization remains consistent. In unicellular eukaryotes, centrosomes aid in processes like cell division and microtubule organization, contributing to cellular functions and behaviors. In multicellular organisms, centrosomes play a central role in cell division and organization, contributing to the development of tissues and overall organismal development.

12. Chromatin Dynamics

Chromatin Dynamics refers to the dynamic and intricate movements of chromatin within the cell nucleus. This movement has a significant impact on gene regulation by influencing the accessibility of DNA for transcription factors, ultimately affecting processes like cellular differentiation, development, and response to external stimuli. Chromatin dynamics are a major contributor to the complexity of cellular organization. Prokaryotic cells lack the compartmentalization and nuclear structures seen in eukaryotes, making the concept of chromatin dynamics unique to eukaryotic organisms.

Information Systems Involved

Genetic Code: The genetic code contains the instructions for building the proteins and enzymes responsible for chromatin remodeling. These proteins can modify the structure of chromatin, making DNA regions more or less accessible for transcription.
Epigenetic Regulation: Epigenetic modifications, such as DNA methylation and histone modifications, play a crucial role in chromatin dynamics. These modifications influence how chromatin is packed and how genes are expressed.
Manufacturing: Genetic information is transcribed and translated to produce the enzymes and proteins involved in chromatin remodeling. These proteins can slide, remove, or modify histones, impacting chromatin structure.
Signaling and Regulatory Codes: Signaling pathways and regulatory mechanisms respond to cellular cues and external stimuli, influencing chromatin dynamics. For instance, growth factors or stress responses can trigger changes in chromatin structure to adapt gene expression.

Eukaryotes vs. Prokaryotes and Unicellular Organisms

Chromatin dynamics are primarily a feature of eukaryotic cells. In prokaryotic cells, such as bacteria, the organization of genetic material is less complex, and the lack of a nucleus and histones results in a different system of gene regulation. While unicellular eukaryotes might exhibit basic forms of chromatin remodeling, the complexity and specialization observed in multicellular organisms are not typically present. In multicellular organisms, chromatin dynamics play a critical role in processes like cell differentiation and development. Different cell types arise from the same genetic material due to variations in gene expression patterns driven by chromatin remodeling.

13. Cytokinesis 

Cytokinesis is the process of dividing the cytoplasm of a cell following nuclear division (mitosis or meiosis). It results in the formation of two daughter cells, each with its own set of organelles and cytoplasmic components. Cytokinesis is essential for proper tissue growth, development, and maintaining the integrity of multicellular organisms. Cytokinesis is a process that started with the emergence of eukaryotic cells. While prokaryotic cells also divide, they lack the complex cytoskeletal and organelle organization present in eukaryotic cells. Therefore, cytokinesis as it occurs in eukaryotes represents a significant advancement in the mechanism of cell division.

Information Systems Involved

Genetic Code: The genetic code contains the instructions for building the proteins and components required for cytokinesis. Proteins involved in the formation of the contractile ring, such as actin and myosin, are encoded in the genetic material.
Manufacturing: Genetic information directs the synthesis of proteins and cytoskeletal components needed for cytokinesis. Contractile ring components are assembled to form the structure responsible for cell division.
Signaling and Regulatory Codes: Signaling pathways and regulatory mechanisms control the timing and coordination of cytokinesis. Protein kinases and other signaling molecules ensure that cytokinesis occurs accurately and efficiently.

Eukaryotes vs. Prokaryotes and Unicellular Organisms

Cytokinesis is specific to eukaryotic cells and is not observed in prokaryotic organisms. In prokaryotes, cell division typically involves binary fission, where the cell simply divides into two daughter cells without complex cytoskeletal mechanisms. In unicellular eukaryotic organisms, cytokinesis is essential for cell division, allowing the formation of new individual cells. In multicellular organisms, cytokinesis takes on additional importance, as proper tissue growth and development rely on accurate cell division to create functional and properly sized tissues.

14. Cytoskeletal Arrays

Cytoskeletal Arrays are complex networks of protein filaments within cells that provide structural support, contribute to cell shape, and enable cell division, migration, and tissue organization. They play a critical role in various cellular processes and are essential for proper development in multicellular organisms. Cytoskeletal arrays are present in eukaryotic cells and are a significant advancement compared to prokaryotic cells. 

Information Systems Involved


Genetic Code: The genetic code contains the instructions for building the proteins that constitute the cytoskeletal filaments. Proteins like actin, microtubules, and intermediate filaments are encoded in the genetic material.
Manufacturing: Genetic information is transcribed and translated to produce the cytoskeletal proteins. These proteins then self-assemble into dynamic networks within the cell.
Signaling and Regulatory Codes: Signaling pathways and regulatory mechanisms control the dynamics of cytoskeletal arrays. Signaling molecules and protein kinases regulate processes like cell division, migration, and shape changes by influencing cytoskeletal organization.

Eukaryotes vs. Prokaryotes and Unicellular Organisms

Cytoskeletal arrays are exclusive to eukaryotic cells and are not present in prokaryotic cells. Cytoskeletal arrays are found in both unicellular and multicellular eukaryotic organisms. In unicellular eukaryotes, they contribute to processes such as cell movement and division. In multicellular organisms, the cytoskeleton is crucial for maintaining tissue structure, coordinating cell movements during development, and facilitating communication between cells.

15. DNA Methylation

DNA Methylation is an epigenetic modification that involves the addition of a methyl group to the cytosine base of DNA molecules. This modification serves as a regulatory marker that can influence gene expression patterns, particularly during development, differentiation, and tissue-specific gene silencing. DNA methylation is observed in a wide range of organisms, including both prokaryotes and eukaryotes. However, the extent, mechanisms, and roles of DNA methylation differ significantly between these two groups.  DNA methylation is complex and likely emerged independently in various lineages.

Information Systems Involved

Genetic Code: The genetic code contains the information necessary for the enzymes known as DNA methyltransferases to recognize specific DNA sequences and add methyl groups. These enzymes modify the DNA molecule by attaching methyl groups to cytosine bases.
Epigenetic Regulation: DNA methylation is an epigenetic modification that alters the accessibility of DNA to transcriptional machinery. Methylated DNA can recruit proteins that repress gene expression, leading to gene silencing.
Manufacturing: Genetic information is used to synthesize DNA methyltransferase enzymes. These enzymes are then involved in adding methyl groups to specific DNA sequences.
Regulatory Codes: DNA methylation is a regulatory code that modulates gene expression. Methylated regions of DNA can serve as binding sites for proteins that either activate or repress gene transcription.

Eukaryotes vs. Prokaryotes and Unicellular Organisms

DNA methylation is present in both prokaryotic and eukaryotic organisms, but its roles and mechanisms can differ significantly. In prokaryotes, DNA methylation is often involved in processes like restriction-modification systems, where it acts as a defense mechanism against foreign DNA. In eukaryotes, DNA methylation is associated with more complex regulatory functions. It plays a crucial role in development, differentiation, X-chromosome inactivation, and tissue-specific gene expression. DNA methylation patterns can be heritable and can change in response to environmental cues, influencing gene expression in multicellular organisms.

16. Egg-Polarity Genes

Egg-Polarity Genes encode macromolecules that play a crucial role in establishing the spatial organization of the embryo by defining its axes. This spatial information is essential for guiding proper tissue and organ formation during development.

Evolution and Major Transitions

Egg-polarity genes are specific to eukaryotic organisms and are not present in prokaryotes. The origin of these genes is associated with multicellular organisms. The emergence of multicellularity required the development of mechanisms to ensure proper tissue and organ formation, and egg-polarity genes are a crucial component of these mechanisms.

Information Systems Involved

Genetic Code: The genetic code contains the instructions for building the macromolecules, such as proteins and regulatory RNAs, encoded by egg-polarity genes. These molecules play a central role in establishing spatial information within the developing embryo.
Epigenetic Regulation: Epigenetic modifications can impact the expression of egg-polarity genes. Epigenetic mechanisms, such as DNA methylation and histone modifications, contribute to the precise regulation of gene expression patterns during development.
Manufacturing: Genetic information is transcribed and translated to synthesize the proteins and regulatory RNAs encoded by egg-polarity genes. These molecules are distributed asymmetrically within the embryo, setting the stage for proper axis formation.
Signaling and Regulatory Codes: Egg-polarity genes often interact with signaling pathways and regulatory networks that provide positional information to cells. These interactions influence the fate and organization of cells within the developing embryo.

Eukaryotes vs. Prokaryotes and Unicellular Organisms

Egg-polarity genes are specific to eukaryotes and are primarily relevant in multicellular organisms. In unicellular eukaryotes, the roles of these genes might be less prominent due to the absence of complex tissue and organ formation. However, they can still contribute to processes related to cellular differentiation and the development of specialized structures. In multicellular organisms, egg-polarity genes are critical for orchestrating the development of tissues and organs. They provide the molecular cues that establish the axes of the embryo, guiding the differentiation and arrangement of cells into functional structures.

17. Epigenetic Codes

The concept of epigenetic codes refers to modifications to DNA and associated proteins that can influence gene expression without altering the underlying DNA sequence. These modifications play a critical role in regulating various cellular processes, including development, differentiation, and responses to environmental cues. They are often described as "multidimensional codes" because they involve a complex interplay of chemical modifications and protein interactions. The emergence of epigenetic mechanisms likely occurred with the origin of life. While the specific mechanisms and complexity of epigenetic regulation may have expanded in eukaryotes, some rudimentary forms of epigenetic regulation are also present in prokaryotes.

Involvement in Major Transitions

Even in the simplest organisms, there is evidence of basic epigenetic-like processes that help regulate gene expression.  The emergence of complex cellular structures and multicellularity depended on epigenetic mechanisms that allowed for the specialization of cell types.  Epigenetic regulation is crucial for the formation and maintenance of different cell types within multicellular organisms. In vertebrates, epigenetic mechanisms play a role in the development of limbs and their specialization.

Information Systems Involved

Genetic Code: Epigenetic modifications influence how the genetic code is read and interpreted, leading to variations in gene expression.
Epigenetic Code: The modifications themselves constitute an epigenetic code that can be inherited across cell divisions and, in some cases, across generations.
Manufacturing Code: Epigenetic modifications influence the production of proteins and other molecules by regulating gene expression.
Signaling Code: Epigenetic regulation can be influenced by cellular signaling pathways, allowing cells to respond to environmental cues and adjust gene expression accordingly.
Regulatory Code: Epigenetic modifications contribute to the establishment of regulatory networks that control gene expression patterns.

Epigenetic mechanisms are not limited to multicellular organisms or eukaryotes: Epigenetic regulation is well-studied in eukaryotes and is particularly complex in multicellular organisms. While the mechanisms might be less elaborate, some prokaryotes also exhibit epigenetic-like processes that involve DNA methylation and other modifications.

18. Gene Regulation Network

The emergence of gene regulation networks was an essential step, especially during the instantiation of multicellular organisms. The setting up of these networks allowed for greater control over gene expression, enabling cells to respond to changing environments and adopt specialized functions within multicellular organisms. Even the simplest prokaryotic organisms have rudimentary gene regulation mechanisms that allow them to respond to environmental cues.  Eukaryotic cells have more complex regulatory systems that enable them to perform more specialized functions. The emergence of multicellular organisms required sophisticated gene regulation networks. These networks facilitated cell differentiation, allowing different cells within a multicellular organism to adopt distinct roles and functions.

Information Systems Involved

Genetic Code: The genetic code is the foundation of gene expression, and gene regulation networks control how the genetic code is read and executed.
Epigenetic Code: Epigenetic modifications are influenced by gene regulation networks, as they can determine which regions of the genome are epigenetically modified and how those modifications are inherited.
Manufacturing Code: Gene regulation networks control the production of proteins and other molecules by activating or repressing the transcription and translation of specific genes.
Signaling Code: Cellular signaling pathways interact with gene regulation networks, allowing cells to respond to external signals and adjust their gene expression accordingly.
Regulatory Code: Gene regulation networks themselves form a regulatory code that determines the precise timing and levels of gene expression in various cell types and conditions.

Occurrence in Organisms

Eukaryotes have more complex gene regulation networks due to the presence of various regulatory elements, transcription factors, and epigenetic modifications. Prokaryotes also have gene regulation networks, although they may be simpler than those in eukaryotes. Bacterial operons and regulatory proteins are examples of prokaryotic gene regulation mechanisms. Even unicellular organisms have gene regulation networks that allow them to respond to environmental changes and optimize their survival and reproduction.

19. Germ Cell Formation and Migration

The formation and migration of germ cells are crucial processes in complex multicellular ones. Germ cells are specialized cells that are involved in sexual reproduction. They are responsible for giving rise to gametes, which are the sex cells necessary for fertilization and the production of offspring in sexually reproducing organisms. Germ cells undergo a unique type of cell division called meiosis, which results in the reduction of their chromosome number by half. This reduction ensures that when two gametes fuse during fertilization, the resulting zygote will have the correct chromosome number for the species. These processes allowed for the development of sexual reproduction, genetic diversity, and the transmission of genetic information across generations. The formation and migration of germ cells played a key role in the emergence of sexual reproduction and multicellular organisms:


Information Systems Involved

Genetic Code: Germ cells carry genetic information from one generation to the next, preserving the genetic code through reproduction.
Epigenetic Code: The emergence of organisms from those without germ cells to those with germ cells would have involved the establishment of various epigenetic mechanisms that facilitated the differentiation and specialization of reproductive cells.  As organisms would have evolved from simple unicellular forms to those with distinct reproductive cells, DNA methylation would have had to emerge as a mechanism for marking genes associated with reproduction and development. The establishment of differential DNA methylation patterns in certain cells would have had to contribute to the specialization of reproductive cells, laying the foundation for the emergence of germ cells. The differentiation of germ cells would have had to be accompanied by the establishment of specific histone modifications that regulated gene expression and cell specialization. Histone modifications would have had to mark genes involved in reproduction and embryonic development. With the emergence of germ cells, the need for precise regulatory networks governing their development and function had to arose. This would have involved the establishment of specific regulatory codes, including transcription factors and non-coding RNAs, that guided the differentiation of germ cells from precursor cells. The development of germ cells requires mechanisms to prevent harmful mutations caused by the activity of transposable elements. Epigenetic modifications, such as DNA methylation and histone modifications, would have had to be employed to silence or regulate the activity of transposons in these specialized cells. The transition to organisms with germ cells would have to lead to the emergence of genomic imprinting, where specific genes are expressed based on their parental origin. This would have had to be facilitated by epigenetic marks, such as DNA methylation, that distinguished the maternal and paternal alleles of certain genes. As germ cells would have developed, the need for epigenetic memory to ensure proper differentiation and function would have become important. Epigenetic marks would have had to be established in precursor cells and preserved in germ cells, enabling them to carry the necessary information for reproduction and embryonic development.

Manufacturing Code: Germ cells carry the machinery necessary for embryonic development and the formation of new individuals.

Signaling Code: Signaling molecules play a role in guiding germ cells to their appropriate locations for fertilization and development.

Regulatory Code: The formation of germ cells is tightly regulated, involving various transcription factors and regulatory elements.

Occurrence in Organisms:
The formation and migration of germ cells occur in sexually reproducing organisms, which include both eukaryotes and some prokaryotes:

Eukaryotes: In eukaryotes, germ cells are specialized cells that give rise to gametes (sperm and egg cells). They undergo meiosis to reduce their chromosome number by half, ensuring genetic diversity during fertilization.

Prokaryotes: While prokaryotes do not have specialized germ cells like eukaryotes, they can exchange genetic material through processes like horizontal gene transfer (e.g., bacterial conjugation). These processes contribute to genetic diversity in prokaryotic populations.

Unicellular Organisms: In unicellular organisms, which reproduce asexually, the concept of germ cells is not applicable as reproduction is typically clonal.


20. Germ Layer Formation


The foundation of all tissue types, influencing the development of organs and systems throughout the organism.

21. Histone PTMs


Post-transcriptional modifications of histones influence gene transcription by altering chromatin structure and accessibility, playing roles in development and adaptation.

24. Homeobox and Hox Genes


Ensure proper regional differentiation within a body plan, guiding the formation of body segments and structures in a coordinated manner.

25. Hormones


Act as chemical messengers to regulate various developmental processes, including growth, differentiation, and metamorphosis.

26. Immune System Development


Involves the differentiation and maturation of immune cells, critical for overall health and response to pathogens.

27. Ion Channels and Electromagnetic Fields


Influence cell behavior and development through electrical signaling, guiding processes like tissue regeneration and embryonic morphogenesis.

28. Membrane Targets


Provide spatial cues that guide cell movement, adhesion, and communication during embryological development and tissue morphogenesis.

29. MicroRNA Regulation


Post-transcriptional regulation by microRNAs impacts gene expression, playing roles in differentiation, development, and cellular responses.

30. Morphogen Gradients


Concentration gradients of signaling molecules guide cell differentiation and tissue patterning.

31. Morphogens and Growth Factors


Secreted molecules that guide cell fate decisions by creating concentration gradients, shaping tissue and organ development.

32. Neural Crest Cells Migration


Migration of these cells contributes to the development of various structures, including the peripheral nervous system and facial features.

33. Neuronal Pruning and Synaptogenesis


Shapes the nervous system by refining connections and ensuring efficient signaling.

34. Neurulation and Neural Tube Formation


Gives rise to the central nervous system, shaping the overall structure and function of the nervous system.

35. Noncoding RNA from Junk DNA


Transcribed noncoding RNAs regulate gene expression by interacting with protein-coding genes, impacting development, differentiation, and cellular function.

36. Oocyte Maturation and Fertilization


Key processes in sexual reproduction that ensure proper development of the embryo.

37. Pattern Formation


Molecular and cellular interactions create intricate patterns in developing tissues and structures.

38. Segmentation and Somitogenesis


Involves the formation of repeated segments during development, seen in structures like the vertebrae and muscles.

39. Signaling Pathways


Generate cell types and patterns by transmitting molecular cues that guide cells in making developmental decisions, such as differentiation, migration, and apoptosis.

40. Stem Cell Regulation and Differentiation


Governs the balance between self-renewal and differentiation, crucial for tissue and organ development and regeneration.

41. Symbiotic Relationships and Microbiota Influence


Influence development, health, and immune responses of the host organism.

42. Transposons and Retrotransposons


Regulate gene expression and genome architecture, potentially influencing adaptation, evolution, and development.

43. Tissue Induction and Organogenesis


Signaling molecules and genetic cues guide the formation of specific tissues and organs during embryonic development.

44. Vascularization and Blood Vessel Formation


Crucial for delivering nutrients and oxygen to tissues during growth and development.

45. Membrane Targets
Provide spatial cues that guide cell movement, adhesion, and communication during embryological development and tissue morphogenesis.

46. Metamorphosis


Involves dramatic changes in body structure and function during development, seen in organisms with complex life cycles.


Following of the processes listed operate based on codes, languages, and signals

Cell-Cell Communication: Relies on molecular signals to coordinate cellular behavior.
Cell Fate Determination and Lineage Specification: Involves genetic and molecular cues that guide cell differentiation.
Cell Migration and Chemotaxis: Cells respond to molecular signals to move in specific directions.
Cellular Reprogramming and Pluripotency: Manipulating cellular behavior by altering genetic and epigenetic programming.
Chromatin Dynamics: Involves changes in chromatin structure based on molecular signals.
DNA Methylation: An epigenetic modification that influences gene expression based on chemical markers.
Epigenetic Codes: Complex regulatory codes that control gene expression without changing DNA sequence.
Gene Regulation Network: Coordinates gene expression through intricate interactions and signals.
Hormones: Act as chemical messengers that regulate various physiological processes.
MicroRNA Regulation: Small RNA molecules that post-transcriptionally regulate gene expression.
Morphogen Gradients: Concentration gradients of signaling molecules that guide cell differentiation.
Morphogens and Growth Factors: Secreted molecules that influence cell fate decisions through signaling.
Neural Crest Cells Migration: Guided migration based on molecular cues during development.
Noncoding RNA from Junk DNA: Transcribed noncoding RNAs that interact with genes, affecting expression.
Signaling Pathways: Transmit molecular signals to guide cell behavior, differentiation, and more.
Stem Cell Regulation and Differentiation: Controlled by various signals and factors to balance renewal and differentiation.
Transposons and Retrotransposons: Can impact gene expression and genome structure through insertion and movement.



Last edited by Otangelo on Sat Aug 26, 2023 8:51 am; edited 1 time in total

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244Perguntas .... - Page 10 Empty Re: Perguntas .... Fri Aug 25, 2023 7:14 pm

Otangelo


Admin

Appearance of   in the evolutionary timeline
De Novo Genetic Information necessary to instantiate
Manufacturing codes and languages that would have to emerge and be employed to instantiate 
Epigenetic Regulatory Mechanisms necessary to be instantiated for
Signaling Pathways necessary to create, and maintain
Regulatory codes necessary for maintenance and operation
Is there scientific evidence supporting the idea that systems were brought about by the process of evolution?
Irreducibility and Interdependence of the systems to instantiate and operate
Once is instantiated and operational, what other intra and extracellular systems is it interdependent with?

give a short overview of     , describe it, and point out the importance in biological systems, and  Developmental Processes Shaping Organismal Form and Function


Appearance of                in the evolutionary timeline  
List the supposed and hypothesized Appearance of                in the evolutionary timeline


De Novo Genetic Information necessary to instantiate 
Describe the hypothetical process of generating and introducing new genetic information in the correct sequence to the existing genetic material, thereby creating the mechanisms of             during the instantiation of                      , starting from scratch. Do not invoke evolution. Just mention what information that would have to originate , de novo, from scratch. Do not put enumeration numbers at the beginning of the sentences. 



Manufacturing codes and languages that would have to emerge and be employed to instantiate 
Explain the manufacturing codes and languages that would have had to be created and instantiated and then involved and employed to go from an organism without                                  to one with a fully developed         .Since genetic information was mentioned and outlined before, do not include genetic  information systems in the response;  genetic information is involved, but since it was described previously, you describe only the manufacturing codes and information besides from genes.Do not put enumeration numbers at the beginning of the sentences.  


Epigenetic Regulatory Mechanisms necessary to be instantiated for
Point out the epigenetic regulation that would have had to be created and subsequently employed in order to perform the development of                        , from scratch. List the systems that would have to be employed to instantiate this regulation, and the systems, that operate in a joint venture and collaborate together, to maintain the systems balance and operation of it.  Do not put enumeration numbers at the beginning of the sentences. 


Signaling Pathways necessary to create, and maintain 
Point out the Signaling Pathways that would have been created and subsequently involved in the emergence of                      from scratch. Point out how they are interconnected, interdependent, and crosstalk with each other, and eventually with other biological systems. Do not put enumeration numbers at the beginning of the sentences. 


Regulatory codes necessary for maintenance and operation
Point out  the regulatory codes and languages that would have had to be instantiated and subsequently involved in the maintenance and operation of     Do not put enumeration numbers at the beginning of the sentences. 





Is there scientific evidence supporting the idea that                       systems were brought about by the process of evolution?
Point out, why an evolutionary set-up, step by step, of                     is extremely unlikely, faced on the complexity, the requirements to instantiate various codes, languages, signaling, and proteins that had to be operational right from the beginning, and intermediate stages would bear no function, and would not be selected. Explain how this interdependence could and would not have evolved in a stepwise fashion, because one mechanism, language, or code system, without the other, would bear no function, and therefore, they had to be instantiated and created all at once, fully operational, from scratch. write  from the perspective of a proponent of intelligent design. Do not write: " From an intelligent design standpoint ". Just say it.Do not put enumeration numbers at the beginning of the sentences. 



Irreducibility and Interdependence of the systems to instantiate and operate
explain which of the manufacturing, signaling, and regulatory codes and languages in the process of creating, developing, and operating      are irreducible, and interdependent within each other, and how one would not bear function without the other. Explain which code and languages communicate with each other, crosstalk, and what communication systems are essential to have functional normal cell operation. Explain how this interdependence could and would not have evolved in a stepwise fashion, because one mechanism, language, or code system, without the other, would bear no function, and therefore, they had to be instantiated and created all at once, fully operational, from scratch. write  from the perspective of a proponent of intelligent design. Do not write: " From an intelligent design standpoint ". Just say it. Do not put enumeration numbers at the beginning of the sentences. 


Once                   is instantiated and operational, what other intra and extracellular systems is it interdependent with?
Do not put enumeration numbers at the beginning of the sentences. 



/// write a syllogism, poiting to a designed set up, since these systems are based on semiotic code, languages, are interdependent, and had to emerge together, interlocked



How do pattern formation processes contribute to the establishment of body plans during embryonic development?
What are the molecular mechanisms that govern the differentiation of stem cells into specific cell lineages?
How do noncoding RNAs play a role in gene regulation and development, and how did they emerge?
What is the role of epigenetic memory in transmitting developmental information across generations?
How did the complex gene regulatory networks that control development evolve?
What are the mechanisms that ensure precise timing and coordination of events during organogenesis?
How do Hox genes contribute to the regionalization of the body along the anterior-posterior axis?
What is the origin of the genetic and molecular machinery responsible for DNA repair and maintenance?
How do environmental factors influence developmental processes and contribute to phenotypic variation?
What are the genetic and molecular factors that regulate the switch from embryonic to adult development?
How did the mechanisms for tissue induction and organogenesis evolve to create functional organs?
What role did gene duplication and divergence play in the evolution of developmental pathways?
How do transposons and retrotransposons contribute to genetic diversity and developmental innovation?
What are the molecular mechanisms underlying the establishment of left-right asymmetry in organisms?
How do symbiotic relationships with microbiota influence developmental processes and immune system function?


29. Neural Crest Cells Migration
30. Neural plate folding and convergence
31. Neuronal Pruning and Synaptogenesis
32. Neurulation and Neural Tube Formation
33. Noncoding RNA from Junk DNA
34. Notch signaling
35. Oogenesis
36. Oocyte Maturation and Fertilization
37. Pattern Formation
38. Photoreceptor development
39. Regional specification
40. Segmentation and Somitogenesis
41. Signaling Pathways
42. Spatiotemporal gene expression
43. Stem Cell Regulation and Differentiation
44. Symbiotic Relationships and Microbiota Influence
45. Syncytium formation
46. Tight junctions, adherens junctions, and desmosomes
47. Transposons and Retrotransposons
48. Tissue Induction and Organogenesis
49. Totipotency and multipotency
50. Vascularization and Blood Vessel Formation


25
How do           contribute to cellular communication, electrical signaling, and development?
What is the role of electromagnetic fields in guiding cellular behaviors and tissue regeneration?
How did the evolution of ion channels and their response to electromagnetic fields shape the development and function of organisms?
Membrane Targets

26
What are the mechanisms by which cellular membranes selectively interact with specific molecules and ligands?
How do membrane targets influence cellular responses, differentiation, and development?
How do membrane targets contribute to the establishment of specialized cellular functions and tissues?


27
How do microRNAs modulate gene expression and post-transcriptional regulation during development?
What are the functions of microRNAs in fine-tuning cellular processes and controlling differentiation?
How did the evolution of microRNA-mediated regulation contribute to the complexity of regulatory networks in organisms?
Morphogen Gradients

28
How do morphogen gradients establish spatial patterns and cell fate determination during embryonic development?
What are the mechanisms that cells use to interpret and respond to morphogen concentration gradients?
How did the evolution of morphogen gradient systems shape the diversity of tissue structures and body plans?
Morphogens and Growth Factors

29
What roles do morphogens and growth factors play in tissue morphogenesis, regeneration, and organ development?
How are morphogens and growth factors produced, secreted, and received by target cells?
How did the evolution of morphogens and growth factor signaling pathways contribute to the development of complex organisms?
Neural Crest Cells Migration

30
How do neural crest cells migrate and differentiate into various cell types, contributing to diverse structures?
What molecular cues guide neural crest cell migration and destination determination?
How did the evolution of neural crest cell migration mechanisms contribute to the diversity of vertebrate structures?
Neuronal Pruning and Synaptogenesis

31
What are the processes of neuronal pruning and synaptogenesis that shape neural circuitry during development?
How do neuronal connections form, strengthen, and eliminate in response to activity and experience?
How did the evolution of neuronal pruning and synaptogenesis mechanisms contribute to the plasticity and adaptability of nervous systems?
Neurulation and Neural Tube Formation

32
How does neurulation lead to the formation of the neural tube, the precursor to the central nervous system?
What are the molecular events that orchestrate neurulation and neural tube closure?
How did the evolution of neurulation mechanisms contribute to the development of complex nervous systems?
Noncoding RNA from Junk DNA

33
What roles do noncoding RNAs, including those derived from "junk DNA," play in gene regulation and development?
How do noncoding RNAs contribute to epigenetic modifications, chromatin organization, and cellular differentiation?
How did the discovery of noncoding RNA functions challenge the notion of "junk DNA" and illuminate the complexity of gene regulation?
Oocyte Maturation and Fertilization

34
How does oocyte maturation prepare the egg for fertilization and embryonic development?
What are the molecular events that occur during fertilization, leading to the formation of a zygote?
How did the evolution of oocyte maturation and fertilization mechanisms contribute to successful reproduction and species propagation?
Pattern Formation

35
How do organisms develop distinct patterns and structures during embryonic development?
What are the molecular signals and interactions that guide the spatial arrangement of cells and tissues?
How did the evolution of pattern formation mechanisms contribute to the diversity of body plans and organ shapes across species?
Segmentation and Somitogenesis

36
What is the role of segmentation and somitogenesis in the formation of repeating body segments and structures?
How are molecular oscillators and signaling pathways involved in the establishment of segmental patterns?
How did the evolution of segmentation mechanisms shape the diversity of body segmentation and locomotion strategies?
Signaling Pathways

37
How do signaling pathways coordinate cellular responses, differentiation, and developmental processes?
What are the key components of signaling cascades, including ligands, receptors, and downstream effectors?
How did the evolution of signaling pathways contribute to the development of complex multicellular organisms?
Stem Cell Regulation and Differentiation

38
What are the mechanisms that regulate stem cell behavior, self-renewal, and differentiation into specialized cell types?
How do stem cells contribute to tissue repair, regeneration, and organ development?
How did the evolution of stem cell regulation mechanisms enable the maintenance and adaptation of organisms in changing environments?

39
Symbiotic Relationships and Microbiota Influence

How do symbiotic relationships between organisms and their microbiota influence development, health, and disease susceptibility?
What are the molecular mechanisms underlying the interactions between host organisms and their resident microbiota?
How did the evolution of symbiotic relationships and microbiota influence the co-evolution of hosts and their associated microbial communities?
Transposons and Retrotransposons

40
What roles do transposons and retrotransposons play in shaping genomes, gene regulation, and evolution?
How do transposons and retrotransposons contribute to genetic diversity and the emergence of new traits?
How did the evolution of transposons and retrotransposons impact genome organization, regulation, and innovation?
Tissue Induction and Organogenesis

41
How do tissues and organs develop through tissue induction, differentiation, and coordinated growth?
What are the signaling molecules and cellular interactions that guide organogenesis and tissue morphogenesis?
How did the evolution of tissue induction and organogenesis mechanisms contribute to the emergence of diverse organ systems and body functions?
Vascularization and Blood Vessel Formation

42
How does vascularization and blood vessel formation contribute to tissue oxygenation, nutrient supply, and waste removal?
What are the molecular cues that guide angiogenesis and vasculogenesis during development and tissue repair?
How did the evolution of vascularization mechanisms enable the growth and complexity of multicellular organisms?
Each of these questions delves into the intricate mechanisms and processes underlying organismal development, highlighting the complexity and interconnectedness of various biological systems. Exploring these questions can provide valuable insights into the origins and evolution of diverse life forms and shed light on the remarkable diversity of life on Earth.



Last edited by Otangelo on Tue Aug 29, 2023 4:38 pm; edited 12 times in total

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245Perguntas .... - Page 10 Empty Re: Perguntas .... Sat Aug 26, 2023 4:52 pm

Otangelo


Admin

11. Centrosomes
12. Chromatin Dynamics
13. Cytokinesis 
14. Cytoskeletal Arrays
15. DNA Methylation
16. Egg-Polarity Genes
17. Epigenetic Codes
18. Gene Regulation Network
19. Germ Cell Formation and Migration
20. Germ Layer Formation
21. Histone PTMs
22. Homeobox and Hox Genes
23. Hormones
24. Immune System Development
25. Ion Channels and Electromagnetic Fields
26. Membrane Targets
27. MicroRNA Regulation
28. Morphogen Gradients
29. Morphogens and Growth Factors
30. Neural Crest Cells Migration
31. Neuronal Pruning and Synaptogenesis
32. Neurulation and Neural Tube Formation
33. Noncoding RNA from Junk DNA
34. Oocyte Maturation and Fertilization
35. Pattern Formation
36. Segmentation and Somitogenesis
40. Signaling Pathways
41. Stem Cell Regulation and Differentiation
42. Symbiotic Relationships and Microbiota Influence
43. Transposons and Retrotransposons
44. Tissue Induction and Organogenesis
45. Vascularization and Blood Vessel Formation
46. Membrane Targets
47. Metamorphosis

Involves dramatic changes in body structure and function during development, as seen in organisms with complex life cycles.

Following of the processes listed operate based on codes, languages, and signals

Cell-Cell Communication: Relies on molecular signals to coordinate cellular behavior.
Cell Fate Determination and Lineage Specification: Involves genetic and molecular cues that guide cell differentiation.
Cell Migration and Chemotaxis: Cells respond to molecular signals to move in specific directions.
Cellular Reprogramming and Pluripotency: Manipulating cellular behavior by altering genetic and epigenetic programming.
Chromatin Dynamics: Involves changes in chromatin structure based on molecular signals.
DNA Methylation: An epigenetic modification that influences gene expression based on chemical markers.
Epigenetic Codes: Complex regulatory codes that control gene expression without changing DNA sequence.
Gene Regulation Network: Coordinates gene expression through intricate interactions and signals.
Hormones: Act as chemical messengers that regulate various physiological processes.
MicroRNA Regulation: Small RNA molecules that post-transcriptionally regulate gene expression.
Morphogen Gradients: Concentration gradients of signaling molecules that guide cell differentiation.
Morphogens and Growth Factors: Secreted molecules that influence cell fate decisions through signaling.
Neural Crest Cells Migration: Guided migration based on molecular cues during development.
Noncoding RNA from Junk DNA: Transcribed noncoding RNAs that interact with genes, affecting expression.
Signaling Pathways: Transmit molecular signals to guide cell behavior, differentiation, and more.
Stem Cell Regulation and Differentiation: Controlled by various signals and factors to balance renewal and differentiation.
Transposons and Retrotransposons: Can impact gene expression and genome structure through insertion and movement.

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246Perguntas .... - Page 10 Empty Re: Perguntas .... Wed Aug 30, 2023 11:54 am

Otangelo


Admin

Interdependence between Intrinsic and  Extrinsic Irreducible Complexity

The concept of irreducible complexity posits that certain systems are so intricate in their interdependent components that removing any one of them would cause the system to cease functioning. This principle can be applied to both intrinsic components (those that are an inherent part of the system) and extrinsic components (external factors or conditions that the system relies upon).  The principle of interdependence is evident in many systems, both artificial and biological. Let me give an example, examining and comparing both hydroelectric turbines and ATP synthase ( molecular turbines, that generate ATP, the energy currency in the cell:

Hydroelectric energy production 

The hydroelectric turbine is intrinsically irreducibly complex

As water flows over the blades of a turbine, it causes the turbine to turn, converting the water's kinetic energy into mechanical energy.  It requires several intrinsic components that make the turbine functional:

Turbine Blades (Runner): These are the components that capture the kinetic energy of water. They are designed in specific shapes and configurations to optimize the conversion of water's kinetic energy into rotational mechanical energy. Without the blades, water would simply flow through without generating rotation.
Shaft: The shaft is connected to the turbine blades and translates the rotational movement of the blades into the generator. Without the shaft, the rotation of the blades couldn't be transferred.
Generator: This is where the mechanical energy (from the rotating shaft) is converted into electrical energy. The generator contains magnets and coils of wire. As the shaft rotates, it induces a flow of electric current in the wires.
Wicket Gates: These are adjustable gates that control the flow of water onto the turbine blades. Without effective wicket gates, the turbine could be overwhelmed by too much water or underutilized with too little.

But the turbine alone will bear no function. It requires a set of extrinsic parts, that together, in a joint venture, will achieve the final goal, which is to generate usable energy. These parts are:

Extrinsic irreducible complexity

Dam: A dam holds back water, creating a reservoir or a lake. This stored water has potential energy due to its height. Without the dam, there's no potential energy from water height.
Water: The moving water's kinetic energy, or the stored potential energy in the dam's reservoir, is what gets converted into mechanical energy by the turbines. Without water, there's no kinetic energy. 
Penstock: This is a conduit that brings water from the reservoir to the turbine. It plays a role in regulating the flow and pressure of the water hitting the turbine blades. Without the penstock, there's no controlled flow of water.
Generator: The turbine is connected to a generator. As the turbine spins, so does the generator, converting mechanical energy into electrical energy. Without the generator, there is electrical energy. 

ATP energy production in the cell

ATP synthase is intrinsically irreducibly complex

ATP synthase is an intricate molecular machine that plays a pivotal role in cellular respiration, generating ATP (adenosine triphosphate) from ADP (adenosine diphosphate) and inorganic phosphate. It harnesses the energy stored in a proton gradient, usually across the inner mitochondrial membrane in eukaryotes, to catalyze this reaction. For this complex enzyme to function, several critical components must be in place.

F1 Subunit (Catalytic Core)
α and β subunits: These subunits form the catalytic core where ATP synthesis or hydrolysis takes place. The β subunit is where ATP is synthesized from ADP and inorganic phosphate.
γ, δ, and ε subunits: These form the central stalk that rotates within the α/β core. The rotation of the γ subunit drives the conformational changes in the β subunit required for ATP synthesis.

Fo Subunit (Proton Channel)
c-Ring (c subunits): This ring is in the membrane and rotates as protons flow through the Fo portion of ATP synthase. The rotation of the c-ring is directly linked to the rotation of the γ subunit in the F1 portion.
a Subunit: This subunit forms a channel allowing protons to flow through the Fo complex. It interacts with the c-ring, enabling the translocation of protons to drive the rotation of the c-ring.
b and δ subunits: These form a peripheral stalk, holding the α/β core stationary while the central stalk and c-ring rotate.

Stator (Peripheral Stalk)
This part of the complex ensures that while the central stalk and c-ring rotate, the catalytic α/β core remains stationary. It is vital for the enzyme's ability to synthesize ATP efficiently.

Proton Channel
The Fo portion, specifically the interaction between the a and c subunits, allows for the passage of protons. This flow of protons is what drives the rotation of the c-ring and, subsequently, the γ subunit inside the F1 portion.

For ATP synthase to function effectively, all of these components must be present and interact in a coordinated manner. The absence or malfunction of any of these parts would disrupt the enzyme's ability to synthesize ATP, making ATP synthase a prime example of a molecular system exhibiting irreducible complexity.

Extrinsic irreducible complexity


ATP Synthase Enzyme: This complex enzyme has a rotating component. As protons flow through the enzyme, they cause this component to rotate.
Proton Gradient: ATP synthase operates in cell membranes, especially the inner mitochondrial membrane. Here, there's a gradient of protons (H+ ions) across the membrane, known as the proton motive force.
Flow of Protons: As protons flow back across the membrane, they pass through ATP synthase.

Just like a dam creates potential energy in water for turbines, the proton gradient sets up potential energy for ATP synthase. The flow of protons through ATP synthase can be likened to the flow of water through turbines. Without the proton gradient, ATP synthase wouldn't function, just as without water, a turbine won't spin. Both systems exemplify how specific conditions and components are crucial for energy conversion processes. The structures, be it a dam or a cellular membrane, and the flow (of water or protons) are not just beneficial but essential for the proper functioning of the respective systems. This interconnectedness underscores the intricacy of both engineered and biological systems and emphasizes the importance of each component in the overall process. While intrinsic irreducible complexity deals with the essentiality of components within a system, extrinsic irreducible complexity pertains to the vital external conditions or components the system relies upon. Both concepts highlight the exquisite level of coordination and specialization present in biological systems, emphasizing their delicate balance and interdependence.

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247Perguntas .... - Page 10 Empty Re: Perguntas .... Wed Aug 30, 2023 8:04 pm

Otangelo


Admin

//// i want the items to appear underlined, since my platform that i am inputting it supports BBCode. like this

1. Formation of Blood Islands: Vasculogenesis begins with the formation of blood islands, which are clusters of angioblasts.
underline, not bolt,  ( in titles use bolt, not underline) which is just an example about how to format:  How do angiogenesis and vasculogenesis contribute to the establishment of blood vessel networks during embryonic development?

Angiogenesis and vasculogenesis are essential processes that contribute to the establishment of blood vessel networks during embryonic development. These processes involve the formation, expansion, and remodeling of blood vessels, which are crucial for supplying nutrients, oxygen, and other essential molecules to developing tissues and organs. Here's how angiogenesis and vasculogenesis work together to create functional vascular systems:

Vasculogenesis

no bolt, but underline
1. Formation of Blood Islands: Vasculogenesis begins with the formation of blood islands, which are clusters of angioblasts
2. Formation of Blood Islands: Vasculogenesis begins with the formation of blood islands,

Vascular Lumen Formation: The endothelial cords undergo lumenization, during which they develop a central channel, or lumen. This lumen becomes the pathway for blood flow.
Hemangioblast Differentiation: Some angioblasts differentiate into hemangioblasts, which give rise to both endothelial cells and blood cells. This connection between blood vessel formation and blood cell production is crucial for the functional development of the circulatory system.

/////// do not use words like likely, could, probably, but use the words:  would, it is hypothesized, would have.  here an example: Neuronal pruning and synaptogenesis are complex processes that are intimately linked to the development and functionality of the nervous system. While the exact point in the evolutionary timeline when these processes first appeared is not definitively known, it's supposed that they emerged gradually as nervous systems became more sophisticated.

The evolution of nervous systems would have been a gradual process that spans millions of years, making it challenging to pinpoint precise stages in which specific mechanisms like neuronal pruning and synaptogenesis emerged.

Early Nervous System Evolution: In the earliest multicellular organisms, nerve cells (neurons) would have started to form basic networks, allowing for simple sensory and motor responses. These early networks would have lacked the complex pruning and refinement mechanisms seen in more advanced nervous systems.
Emergence of Synaptic Connections: As nervous systems would have become more complex, the formation of synaptic connections would have became more important. Synapses, the junctions between neurons, would have allowed for communication and signal transmission between nerve cells. Over time, mechanisms that promoted the strengthening or weakening of synapses would have emerged to enhance the efficiency of signal transmission.
Refinement and Pruning: As nervous systems would have continued to evolve, mechanisms of neuronal pruning probably would have developed as a way to fine-tune neural connections. This would have been driven by the need for more efficient neural circuits, as well as the optimization of limited resources in the developing organisms.
Adaptation and Plasticity: The ability to form new synapses and adapt existing ones, which is a hallmark of synaptogenesis, would have provided significant evolutionary advantages. Organisms with the ability to adjust their neural circuits based on experiences and environmental changes would have been better equipped to survive and thrive in changing conditions.









Point out, why an evolutionary set-up, step by step, is extremely unlikely, faced on the complexity, the requirements to instantiate various codes, languages, signaling, and proteins that had to be operational right from the beginning, and intermediate stages would bear no function, and would not be selected. Explain how this interdependence could and would not have evolved in a stepwise fashion, because one mechanism, language, or code system, without the other, would bear no function, and therefore, they had to be instantiated and created all at once, fully operational, from scratch. write  from the perspective of a proponent of intelligent design. Do not write: " From an intelligent design standpoint ". Just say it.Do not put enumeration numbers at the beginning of the sentences. 


Irreducibility and Interdependence of the systems to instantiate and operate . explain which of the manufacturing, signaling, and regulatory codes and languages in the process of creating, developing, and operating      are irreducible, and interdependent within each other, and how one would not bear function without the other. Explain which code and languages communicate with each other, crosstalk, and what communication systems are essential to have functional normal cell operation. Explain how this interdependence could and would not have evolved in a stepwise fashion, because one mechanism, language, or code system, without the other, would bear no function, and therefore, they had to be instantiated and created all at once, fully operational, from scratch. write  from the perspective of a proponent of intelligent design. Do not write: " From an intelligent design standpoint ". Just say it. Do not put enumeration numbers at the beginning of the sentences. 


Once it is instantiated and operational, what other intra and extracellular systems is it interdependent with?
Do not put enumeration numbers at the beginning of the sentences. 



/// write a syllogism, poiting to a designed set up, since these systems are based on semiotic code, languages, are interdependent, and had to emerge together, interlocked

i want each item plotted out like this in alphabetical order, BBCode:  1. Formation of Blood Islands: Vasculogenesis begins with the formation of blood islands, which are clusters of angioblasts.



Last edited by Otangelo on Thu Aug 31, 2023 4:38 pm; edited 1 time in total

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248Perguntas .... - Page 10 Empty Re: Perguntas .... Thu Aug 31, 2023 3:13 pm

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Admin

31. Neurulation and Neural Tube Formation

How do neurulation and neural tube formation provide the foundation for the development of the central nervous system in vertebrates?

Neurulation and neural tube formation are critical processes in vertebrate embryonic development that lay the foundation for the creation of the central nervous system (CNS). These processes intricately shape and transform the embryonic tissue, setting the stage for the formation of the brain and spinal cord.

Neurulation

Neurulation is the initial step in the formation of the CNS. It begins with the transformation of the neural plate, a flat sheet of ectodermal tissue, into the neural tube. This transformative process involves several key stages:

Elevation of Neural Folds: As the embryo develops, the neural plate undergoes a process of elevation, forming neural folds on both sides. These folds gradually approach each other along the midline.
Fusion of Neural Folds: The neural folds eventually fuse at the midline, creating a neural tube. This tube becomes the precursor to the brain and spinal cord.
Formation of Neural Crest Cells: Alongside the neural tube formation, a population of cells known as neural crest cells emerge at the borders of the neural plate. These cells play a crucial role in forming various structures, including peripheral nerves, ganglia, and some skeletal elements.

Neural Tube Formation

The neural tube, formed through neurulation, is the rudimentary structure that gives rise to the brain and spinal cord. It undergoes further specialization to create distinct regions of the CNS:

Primary Vesicle Formation: The neural tube initially differentiates into three primary vesicles: the prosencephalon (forebrain), mesencephalon (midbrain), and rhombencephalon (hindbrain).
Secondary Vesicle Formation: These primary vesicles subsequently undergo further differentiation into five secondary vesicles: telencephalon and diencephalon from the prosencephalon, mesencephalon remains unchanged, and metencephalon and myelencephalon from the rhombencephalon.
Cavities and Structure Formation: These vesicles expand and develop specific cavities that become the ventricles of the brain and central canal of the spinal cord. The walls of these vesicles differentiate into the various regions of the CNS.

Neurulation and neural tube formation are critical because they set the foundation for the complex structures and functions of the CNS. These processes ensure the proper development of the brain and spinal cord, which are essential for sensory perception, motor control, cognition, and a myriad of other neurological functions.

How does the neural tube differentiate into distinct regions, such as the brain and spinal cord?

The neural tube, formed through the process of neurulation, gives rise to both the brain and the spinal cord in vertebrate embryos. This remarkable differentiation involves complex molecular signaling and patterning mechanisms that lead to the formation of distinct regions with specific functions.

Formation of Primary Vesicles

After the initial fusion of the neural folds, the neural tube differentiates into three primary vesicles along the anterior-posterior axis: the prosencephalon (forebrain), mesencephalon (midbrain), and rhombencephalon (hindbrain). Each primary vesicle serves as the basis for further differentiation.

Secondary Vesicle Formation and Patterning

These primary vesicles then undergo further differentiation into five secondary vesicles through a process called regionalization:

Telencephalon and Diencephalon (Forebrain): The prosencephalon gives rise to the telencephalon (which develops into the cerebral hemispheres) and the diencephalon (which forms structures like the thalamus and hypothalamus).
Mesencephalon (Midbrain): The mesencephalon remains relatively unchanged and develops into the midbrain structures, including the tectum and tegmentum.
Metencephalon and Myelencephalon (Hindbrain): The rhombencephalon differentiates into the metencephalon (developing into the pons and cerebellum) and the myelencephalon (forming the medulla oblongata).

Patterning Signals and Genetic Regulation

The differentiation of the neural tube into these distinct regions is governed by intricate molecular signaling pathways, including the actions of morphogens such as Sonic Hedgehog (Shh), Fibroblast Growth Factors (FGFs), and Bone Morphogenetic Proteins (BMPs). These signaling molecules establish concentration gradients along the neural tube, instructing cells to adopt specific identities based on their location.

Hox Genes

Hox genes, which play a pivotal role in determining regional identities along the anterior-posterior axis of the body, are also crucial for neural tube differentiation. The expression patterns of Hox genes guide the formation of different segments within the neural tube.

Cellular Migration and Differentiation

As cells within the neural tube receive specific signaling cues, they migrate to their designated regions and differentiate into the diverse cell types that make up the brain and spinal cord.

Patterning and Function

This complex differentiation process ultimately gives rise to the various brain structures and spinal cord segments, each with specialized functions that contribute to sensory perception, motor control, cognition, and other essential neurological processes.

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Transverse sections that show the progression of the neural plate to the neural groove from bottom to top 1

At what juncture in the evolutionary timeline are neurulation and neural tube formation postulated to have made their first appearance?

Neurulation and neural tube formation are fundamental embryological processes that lead to the development of the central nervous system (CNS), including the brain and spinal cord. These events are critical for the formation of complex nervous systems and have been conserved across a broad range of vertebrates. Here's a look into their possible evolutionary origins:

Origins of the Nervous System

Simple Nervous Systems: The earliest multicellular organisms would have had rudimentary nervous systems, consisting of simple nerve nets or basic nerve cords. These basic nervous structures wouldn't have required specialized processes like neurulation.
Bilateria and CNS Development: The appearance of bilaterally symmetrical animals, or Bilateria, is a key event in the evolution of the CNS. It is hypothesized that the ancestors of modern bilaterians possessed a centralized nerve cord, which served as a precursor to more advanced nervous systems.
Neurulation and Neural Tube Formation: Neurulation and the formation of a neural tube would have emerged with the need for a more centralized and organized nervous system. This process would have been critical for the development of a dorsal nerve cord in early chordates, which is an ancestral feature of all vertebrates.

Vertebrate Evolution and Neural Tube Specialization

Primitive Chordates: In early chordates like amphioxus, a simple notochord and nerve cord were present. These organisms would have exhibited basic neurulation processes, leading to the formation of a dorsal nerve cord.
Early Vertebrates: With the emergence of early vertebrates, the neural tube would have become more specialized, giving rise to distinct regions such as the forebrain, midbrain, and hindbrain. This differentiation is crucial for the diverse functions and capabilities seen in modern vertebrates.
Neural Crest Cells: Along with the neural tube, the evolution of neural crest cells would have played a pivotal role in vertebrate diversification. These cells originate from the borders of the neural tube and migrate to various parts of the embryo, contributing to structures like cranial bones, peripheral nerves, and more.

The processes of neurulation and neural tube formation are thought to have made their appearance during the evolution of early chordates, setting the stage for the complex nervous systems seen in today's vertebrates. These developmental events would have provided the architectural foundation for advanced neural structures, facilitating sophisticated behaviors and adaptations in vertebrate lineages.

Which de novo genetic information would be requisite to instantiate the processes of neurulation and neural tube formation?

Neurulation and neural tube formation are critical stages in the development of the vertebrate central nervous system. They rely on intricate molecular and cellular processes that are guided by various genes and their corresponding proteins. While numerous genes are involved in this complex developmental process, certain genes are recognized as core players in driving neurulation and establishing the neural tube. Here's an overview of some of these crucial genetic components:

Key Genetic Components

Notochord Induction Genes: The notochord, a midline embryonic structure, secretes signaling molecules that instruct the overlying ectoderm to become neural tissue. Genes like Noggin, Chordin, and Follistatin are crucial for this induction, as they inhibit proteins that would otherwise prevent neural differentiation.
Neural Plate Border Specifiers: Genes such as Pax3, Pax7, Msx1, and Zic1 play roles in specifying cells at the border of the neural plate. These border cells can give rise to both neural crest cells and neural tissue.
Neural Fold Elevation and Convergence: As the neural plate forms, it starts to fold, with its edges (neural folds) elevating and moving towards each other. Genes like Shh (Sonic hedgehog) and BMP4 (Bone Morphogenetic Protein 4) play roles in guiding this morphogenesis.
Neural Tube Closure: The eventual fusion of the neural folds to form a closed neural tube is a critical step. Genes such as Celsr1, Vangl2, and Fzd3 are vital components of the planar cell polarity pathway and are instrumental in coordinating the movements of cells during tube closure.
Neural Differentiation and Patterning: Once the neural tube is formed, it undergoes further differentiation and patterning. Genes like Shh and Wnt are involved in ventral and dorsal patterning of the neural tube, respectively, establishing regions that will later give rise to different structures in the CNS.

The process of neurulation and neural tube formation is orchestrated by a myriad of genes working in concert. These genes provide the de novo genetic information necessary for the successful development of the central nervous system. Any disruptions in the function of these genes can lead to neural tube defects, highlighting their critical importance in embryonic development.

What specific manufacturing codes and languages would have to emerge and be operational for neurulation and the formation of the neural tube?

Neurulation and the formation of the neural tube are intricate processes in embryonic development, driven by a series of tightly regulated molecular and cellular instructions. To understand these "manufacturing codes and languages," one must delve into the complex world of genetic regulation, signaling pathways, and cell-to-cell communications that drive these developmental processes. Here's a glimpse into some of these genetic "codes" and "languages":

Genetic Codes and Regulation

Gene Expression and Transcription Factors: Specific genes are turned on or off during different stages of neurulation. Transcription factors like Sox1, Sox2, and Sox3 are expressed in the early neural plate and are crucial for neural differentiation.
Epigenetic Regulation: Modifications to DNA and its associated proteins can alter gene expression without changing the underlying DNA sequence. Epigenetic changes, such as DNA methylation or histone modifications, are pivotal in determining cell fate during neural tube formation.

Signaling Pathways

Bone Morphogenetic Proteins (BMPs) and Their Antagonists: BMP signaling tends to promote epidermal fates, while its inhibition by molecules like Noggin, Chordin, and Follistatin promotes neural fates.
Sonic Hedgehog (Shh) Signaling: The notochord produces Shh, which plays a crucial role in ventral patterning of the neural tube, determining different neuronal subtypes based on concentration gradients.
Wnt Signaling: Important for dorsal patterning of the neural tube and interacts with other signaling pathways to ensure the right balance of cell types.

Cellular Communication and Interaction

Planar Cell Polarity (PCP) Pathway: This pathway controls the convergent extension movements during neurulation, where cells intercalate and the neural plate narrows and lengthens. Key components include Vangl2, Celsr1, and Fzd3.
Cell Adhesion Molecules: Molecules such as cadherins and integrins play roles in ensuring that cells stick together and move collectively during the bending and folding processes of neurulation.

Neurulation and neural tube formation are orchestrated by a myriad of "manufacturing codes and languages" at the genetic, molecular, and cellular levels. These intricate processes ensure the proper development and functionality of the central nervous system. Any disruptions in these instructions can lead to neural tube defects, emphasizing their vital importance in embryonic development.

Which epigenetic regulatory mechanisms are pivotal in guiding the processes of neurulation and neural tube formation?

Neurulation and neural tube formation are intricate events during embryonic development. These processes are not solely governed by the genomic DNA sequence but also by epigenetic modifications that influence gene expression. Epigenetics, meaning "above genetics," involves chemical modifications to DNA and histones, non-coding RNAs, and chromatin remodeling, which collectively shape the way genes are expressed. Here's a look into some of the epigenetic regulatory mechanisms crucial for neurulation and neural tube formation:

DNA Methylation

DNA Methyltransferases (DNMTs): These enzymes add methyl groups to the cytosine residues in DNA, typically leading to gene silencing. DNMTs play vital roles in neural differentiation and neural tube formation. Anomalous methylation patterns can disrupt the expression of genes essential for these processes.

Histone Modifications

Histone Acetylation and Deacetylation: Acetylation, typically associated with gene activation, is governed by histone acetyltransferases (HATs). In contrast, deacetylation, linked with gene repression, is controlled by histone deacetylases (HDACs). These modifications are crucial in determining the transcriptional activity of genes involved in neurulation.
Histone Methylation: Depending on the specific lysine residue modified and the number of added methyl groups, histone methylation can either activate or repress gene expression. Enzymes like histone methyltransferases and demethylases regulate these modifications, ensuring proper gene expression during neural development.

Chromatin Remodeling

SWI/SNF Complex: This multi-protein complex changes the position of nucleosomes on DNA, allowing or hindering the binding of transcriptional machinery to DNA. This remodeling is essential for the timely activation and repression of genes during neural tube formation.

Non-Coding RNAs

MicroRNAs (miRNAs): These short RNA molecules do not code for proteins but play significant roles in post-transcriptional gene regulation. By targeting specific messenger RNAs (mRNAs), miRNAs can inhibit their translation or lead to their degradation, thus controlling the levels of proteins essential for neurulation.
Long Non-Coding RNAs (lncRNAs): These RNA molecules, longer than miRNAs, can interact with DNA, RNA, or proteins. They play roles in various cellular processes, including the regulation of gene expression at both transcriptional and post-transcriptional levels during neural development.

The orchestration of neurulation and neural tube formation is an intricate ballet of gene expression, with epigenetic regulatory mechanisms serving as the choreographers. Proper epigenetic modifications ensure that the right genes are expressed at the right time, facilitating the harmonious development of the neural tube and, subsequently, the central nervous system.

Are there distinct signaling pathways that are essential for the seamless orchestration of neurulation and neural tube formation?

Neurulation and neural tube formation are complex processes that require precise coordination of cellular behavior. For this to occur, multiple signaling pathways operate in tandem, dictating cell fate, proliferation, migration, and morphogenesis. The following pathways have been recognized as pivotal in guiding the processes of neurulation and neural tube formation:

Sonic Hedgehog (Shh) Signaling

Dorsal-Ventral Patterning: Shh, secreted by the notochord and floor plate, is instrumental in the ventral patterning of the neural tube. It specifies the identity of ventral neural cell types by inducing various transcription factors.

Bone Morphogenetic Protein (BMP) Signaling

Neural Induction: BMPs, members of the TGF-β superfamily, play a critical role in ectodermal patterning. BMP antagonists, secreted by the organizer tissues, such as noggin, chordin, and follistatin, promote neural induction by inhibiting BMP activity.

Wnt Signaling

Neural Plate Border and Neural Crest Specification: Wnt signaling pathways, particularly canonical Wnt/β-catenin signaling, have pivotal roles in specifying the neural plate border and inducing the neural crest, a population of cells that gives rise to a plethora of derivatives, including peripheral neurons and glial cells.

Retinoic Acid (RA) Signaling

Anterior-Posterior Patterning: RA, a derivative of Vitamin A, produced in the posterior neural tissue, helps in establishing anterior-posterior identities within the neural tube. It operates in gradient fashion, with higher concentrations leading to more posterior neural fates.

Fibroblast Growth Factor (FGF) Signaling

Neural Induction and Patterning: FGFs have diverse roles during neurulation, including promoting neural induction and aiding in patterning the neural plate by working alongside other signaling pathways.

Planar Cell Polarity (PCP) Signaling

Convergent Extension Movements: PCP signaling is crucial for the cellular movements that shape the neural plate and tube. Convergent extension movements, driven by this pathway, elongate the neural plate along the anterior-posterior axis and narrow it mediolaterally.

The orchestration of neurulation and neural tube formation hinges on a symphony of signaling pathways that work in harmony. These pathways, sensitive to gradients and timing, collectively guide the cellular behaviors and fate decisions necessary for the construction of a well-formed neural tube, the precursor to the central nervous system.

What are the regulatory codes that underpin and oversee the mechanisms of neurulation and neural tube formation?

Neurulation and the formation of the neural tube are foundational processes during vertebrate embryogenesis that give rise to the central nervous system. These processes are underpinned by a complex interplay of molecular, cellular, and mechanical codes that ensure their proper execution. The following regulatory codes are central to the oversight and execution of these processes:

Gene Regulatory Networks (GRNs)

Master Regulators: Transcription factors such as Sox2, Pax3, and Pax7 are pivotal in initiating and maintaining neural identity during the early stages of neural plate formation. These regulators initiate gene cascades crucial for successive phases of neurulation.
Coordinating Morphogenesis: Certain genes ensure the proper bending, folding, and closure of the neural plate. For instance, genes coding for cell-adhesion molecules like N-cadherin help in maintaining tissue integrity during these morphogenetic movements.

MicroRNAs (miRNAs)

Post-transcriptional Regulation: miRNAs, small non-coding RNAs, modulate gene expression post-transcriptionally. They're involved in fine-tuning the dynamics of protein production necessary for neural tube formation. For example, miR-34 and miR-449 have been implicated in regulating neural crest cell migration and differentiation.

Epigenetic Modifications

Histone Modifications and DNA Methylation: Chemical modifications to DNA and histones, like methylation and acetylation, modulate the accessibility of genes to the transcriptional machinery, thus influencing gene expression patterns during neurulation.

Feedback Loops

Ensuring Robustness: Many of the signaling pathways, such as Shh and BMP, involved in neural tube formation have built-in feedback loops. These loops help ensure that the processes are robust against perturbations and are carried out with fidelity.

Mechanical Forces

Cell Shape and Tissue Morphogenesis: Cellular behaviors, such as apical constriction and cell intercalation, are driven by mechanical forces. These behaviors, in turn, drive the neural plate's bending and folding. Regulatory codes, often in the form of mechanotransduction pathways, ensure that these forces are generated and applied correctly.

The precise orchestration of neurulation and neural tube formation relies on a comprehensive set of regulatory codes, ranging from gene expression and post-transcriptional modifications to mechanical forces. Together, these codes ensure that the embryo develops a well-formed neural tube, setting the stage for the later development of the brain and spinal cord.

Does current scientific literature provide evidence to suggest that neurulation and neural tube formation were evolutionary processes?

Neurulation and neural tube formation are foundational processes during vertebrate embryogenesis that give rise to the central nervous system. These processes involve a myriad of intricate and interdependent molecular, cellular, and mechanical mechanisms, suggesting the complexity of the design and the challenges of evolutionary explanations.

Complexity and Interdependence

Integrated Gene Regulatory Networks (GRNs): Neurulation is driven by a complex set of GRNs that not only need to be present but also intricately tuned to ensure proper timing and patterning of neural development. The coordinated action of master regulators, like Sox2, Pax3, and Pax7, is pivotal. Any disruption or incomplete integration of these GRNs would likely result in non-functional or adverse outcomes.
Signaling Pathways: Key pathways such as Sonic Hedgehog (Shh) and Bone Morphogenic Protein (BMP) have tightly integrated feedback loops ensuring that neural plate cells receive the right signals at the right time. Without the full signaling pathway present and functional, the entire process could be derailed.
Epigenetic Controls: DNA methylation, histone modifications, and other epigenetic controls are necessary for precise temporal and spatial gene expression during neurulation. These controls are not just add-ons but essential layers of regulation.

Challenges for Stepwise Evolution

Coordinated Cellular Behaviors: The physical act of neurulation, where the neural plate bends, folds, and eventually fuses to form the neural tube, requires a multitude of cells to act in concert. These behaviors, driven by mechanical forces and cellular signaling, seem to necessitate a pre-existing set of instructions rather than a gradual, stepwise accumulation.
Symbiotic Protein Interactions: Many proteins involved in neurulation interact in ways that seem symbiotic. For instance, cell adhesion molecules ensure tissue integrity during the folding of the neural plate. The presence of one protein without its partner or counterpart might not only be non-functional but could be detrimental.

The Problem of Intermediates

Functionality of Partial Systems: For evolution to favor a particular trait or mechanism, it generally needs to confer some advantage. However, with neurulation, it's challenging to envision how partial or intermediate stages could offer any functional advantage. Incomplete neural tube formation results in severe abnormalities.
Requirement for Simultaneous Systems: The codes, languages, signaling, and proteins involved in neurulation seem to be so interdependent that they must all be in place for the process to work. The idea of them evolving simultaneously, yet independently, stretches the imagination.

While the scientific community continues to explore the mechanisms and origins of complex processes like neurulation, the sheer intricacy, and interdependence of the involved systems raise profound questions about the feasibility of stepwise evolutionary explanations. The presence of such a well-coordinated and integrated system suggests a design of profound intelligence.

Could the mechanisms and components involved in neurulation and neural tube formation be characterized as irreducibly complex or interdependent?

Neurulation and neural tube formation represent quintessential processes that give rise to the central nervous system in vertebrate embryogenesis. The assembly and function of the structures and pathways within this framework seem to present a deeply interdependent and potentially irreducibly complex system.

Irreducible Complexity and Interdependence

Gene Regulatory Networks (GRNs): Neurulation is underpinned by an intricate set of GRNs, where master regulatory genes like Sox2, Pax3, and Pax7 are pivotal. A failure in one aspect of this network could compromise the entire process. These genes and their networks function collectively, with one component being non-functional in the absence of the others.
Signaling Pathways: Key pathways, including Sonic Hedgehog (Shh) and Bone Morphogenic Protein (BMP), are not just sequences of events, but possess tightly integrated feedback mechanisms. If one part of these pathways was missing or non-functional, it could jeopardize the entire process of neural differentiation.
Cellular Mechanisms and Dynamics: The cellular behaviors during neurulation, from cell migration to changes in cell shape and polarity, hinge on a balance of forces and cellular communications. The mechanisms driving these behaviors seem interdependent, as a malfunction in one would impair the entire physical process of neurulation.
Epigenetic Regulation: DNA methylation, histone modifications, and non-coding RNAs contribute to precise gene expression during neurulation. These components form an interconnected regulatory system, where the absence or malfunction of one aspect could lead to catastrophic developmental errors.

The Cross-Talk and Communication Systems

Intercellular Communication: Cells during neurulation do not operate in isolation. They communicate using signaling molecules, such as growth factors, to ensure synchronized behavior. This communication is vital for the seamless orchestration of cell movements and differentiation.
Intracellular Communication: Within each cell, multiple pathways and molecular processes, from protein synthesis to cellular metabolism, are interconnected. Proteins, metabolites, and ions continually communicate, ensuring the cell's function and survival.

The Evolutionary Implications

Challenge of Stepwise Evolution: Given the myriad of codes, languages, signaling pathways, and proteins involved in neurulation, the evolutionary progression of such an intricate system in a stepwise manner becomes daunting. Intermediate stages might not provide any functional advantage, making natural selection of such stages implausible.
Requirement for Simultaneous Systems: The sheer interdependence means that for one system to function properly, others must already be in place. It challenges the notion of gradual addition, as adding one component without the others could result in a non-functional or even detrimental system.

The profound complexity and interdependence observed in neurulation and neural tube formation are awe-inspiring. Such intricately connected systems, where the absence of one component could lead to the collapse of the entire process, suggest a sophisticated design that goes beyond the capabilities of random, stepwise evolutionary processes.

Once neurulation and neural tube formation are fully operational, what other intra and extracellular systems might they be intricately interconnected with or dependent upon?

Once neurulation and neural tube formation processes are fully realized, they don't act in isolation. The neural tube and its constituent cells become an active hub, intricately connected to various other cellular systems and external influences. These connections and dependencies ensure the proper functioning, differentiation, and survival of the neural tissue.

Intracellular Systems

Cellular Metabolism: Neurons, and the glial cells supporting them, have high metabolic demands. The mitochondria, often referred to as the cellular powerhouses, must supply this demand by producing ATP, and their health and function are vital for neural cell survival.
Protein Synthesis and Degradation: Neural cells constantly produce proteins necessary for synaptic function, neurotransmitter synthesis, and cell maintenance. Ribosomes synthesize these proteins, while proteasomes and lysosomes degrade misfolded or old proteins.
Calcium Signaling: Intracellular calcium levels in neurons are critical for processes like neurotransmitter release, gene expression, and synaptic plasticity. The endoplasmic reticulum, mitochondria, and various ion channels coordinate to manage these levels.

Extracellular Systems and Influences

Neurotrophic Factors: These are molecules that support neuronal survival, differentiation, and growth. Molecules such as nerve growth factor (NGF) or brain-derived neurotrophic factor (BDNF) are essential for the health and function of neurons.
Glial Support: Astrocytes, oligodendrocytes, and microglia provide nutritional, structural, and immune support to neurons. They are not merely passive support cells but play active roles in synaptic function, myelination, and neural defense.
Synaptic Communication: Neurons communicate with each other via synapses, where neurotransmitters like glutamate, GABA, or dopamine are released. This neurotransmitter system is paramount for neural communication and information processing.
Vascular Supply: Blood vessels provide essential nutrients and oxygen to the neural tissue. Moreover, the blood-brain barrier, formed by the interaction of endothelial cells, astrocytes, and pericytes, protects the brain from harmful substances while ensuring the supply of necessary nutrients.
Extracellular Matrix (ECM): The ECM provides structural support and plays a role in guiding cell migration during development. It also influences cell behavior, synaptic stability, and plasticity in the mature nervous system.

The completion of neurulation and neural tube formation is just the beginning of a series of intricate relationships and dependencies that neural cells will establish with both internal cellular systems and external influences. This highly integrated network ensures the optimal functionality and adaptability of the central nervous system throughout an organism's life.

1. If complex systems exhibit properties of interdependence, semiotic coding, and synchronization, implying that their elements had to emerge simultaneously and harmoniously to function properly, then such systems show traits commonly attributed to designed mechanisms.
2. The neurulation and neural tube formation processes, along with their associated intracellular and extracellular systems, exhibit these very properties of interdependence, semiotic coding, and synchronization.
3. Therefore, the neurulation and neural tube formation processes, along with their connected systems, indicate traits commonly attributed to designed mechanisms.

1. Wikipedia: Neurulation

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32. Noncoding RNA from 'Junk' DNA

The term 'junk' DNA was historically used to describe portions of the DNA sequence that do not encode for proteins. However, advancements in genomics have revealed that these 'junk' regions are anything but useless. A significant component of these regions is transcribed into noncoding RNAs (ncRNAs), which, while not translated into proteins, have essential roles in regulating various biological processes.

Description and Biological Significance

Noncoding RNAs are a diverse group of RNA molecules that do not code for proteins. These can range from short molecules like microRNAs (miRNAs) to long noncoding RNAs (lncRNAs). They play crucial roles in gene regulation, impacting when and where genes are turned on or off. This regulation can occur at the transcriptional level, where gene expression is initiated, or post-transcriptionally, after the gene has been transcribed.

Importance in Biological Systems

The functions of ncRNAs are vast and varied:

Gene Expression Regulation: As mentioned, many ncRNAs can bind to DNA, RNA, or proteins, modulating the expression of specific genes.
Chromatin Remodeling: lncRNAs can impact the epigenetic landscape by recruiting enzymes that modify chromatin, influencing gene accessibility.
RNA Processing: snRNAs are part of complexes that modify precursor mRNA molecules into their mature forms.
Protein Synthesis: rRNAs and tRNAs play direct roles in translating mRNA into proteins.

Role in Developmental Processes Shaping Organismal Form and Function

The role of ncRNAs extends to the very blueprint of life. During developmental stages, from the formation of tissues and organs to the maintenance of adult physiology, ncRNAs are fundamental:

Cell Differentiation: ncRNAs can influence the fate of stem cells, determining whether they become skin cells, neurons, or any other cell type.
Organogenesis: ncRNAs play roles in signaling pathways that guide the formation of organs.
Tissue Homeostasis: They help maintain the balance of cell types in various tissues, ensuring proper function.
Response to Environmental Signals: Development is not just about genetics; it's also about responding to external cues. ncRNAs help cells interpret and respond to these signals, ensuring appropriate development.

How do noncoding RNAs, once considered part of 'junk' DNA, influence gene regulation and cellular functions?

Noncoding RNAs (ncRNAs) were once considered non-functional parts of the genome. However, advances in research have revealed that these RNA molecules play critical roles in various cellular processes, including gene regulation. Here's an overview of how noncoding RNAs influence gene regulation and other cellular functions:

Gene Expression Regulation: Some ncRNAs can bind to specific messenger RNAs (mRNAs) and prevent them from being translated into proteins, thus regulating gene expression at the post-transcriptional level.
Chromatin Remodeling: Certain ncRNAs interact with chromatin-modifying complexes, affecting chromatin structure and thereby influencing gene transcription.
Splicing Regulation: Some ncRNAs are involved in alternative splicing, where they play a role in determining which exons are included or excluded from the final mRNA.
Genomic Imprinting: ncRNAs are involved in genomic imprinting, where only one allele of a gene is expressed based on its parent of origin. The non-expressed allele is often silenced by ncRNAs.
Structural Roles: Certain ncRNAs, like ribosomal RNAs (rRNAs) and transfer RNAs (tRNAs), have structural roles in the cell. They are vital components of the ribosome and the protein synthesis machinery.
X-Chromosome Inactivation: Xist, a long noncoding RNA, is critical for the inactivation of one of the two X chromosomes in female mammals, ensuring gene dosage compensation.
Organism Development: Many ncRNAs are involved in developmental processes, guiding the differentiation and growth of specific cell types and tissues.
Response to Stress: Some ncRNAs act as molecular sensors, responding to cellular stress by altering the expression of genes that deal with stressors.
Regulation of Protein Activity: Certain ncRNAs can bind to proteins and influence their activities, either by changing their conformation or by acting as scaffolds that facilitate protein-protein interactions.

Understanding the myriad roles of ncRNAs has shed light on the intricacies of cellular regulation and has highlighted the importance of what was once thought to be 'junk' DNA. They are now considered key players in a multitude of cellular processes, from basic metabolic activities to the complexities of development and disease.

What roles do noncoding RNAs play in the modulation of cellular processes, and how might they interact with protein-coding genes?

Noncoding RNAs (ncRNAs) are versatile molecules that significantly influence a wide array of cellular processes. Their roles extend far beyond simple transcription, and they have profound interactions with protein-coding genes. Here's a deeper look into the roles of ncRNAs and their interactions with protein-coding genes:

Gene Expression Modulation: Many ncRNAs, especially small interfering RNAs (siRNAs) and microRNAs (miRNAs), bind to messenger RNAs (mRNAs) and prevent their translation, thus modulating gene expression at the post-transcriptional level.
Chromatin Structure Alteration: Long noncoding RNAs (lncRNAs) can recruit chromatin-modifying enzymes, leading to changes in chromatin structure, which can activate or repress transcription of nearby genes.
Transcriptional Interference: Some ncRNAs are transcribed from regions that overlap with protein-coding genes. This transcription process can interfere with the transcription of the overlapping gene, thus modulating its expression.
Alternative Splicing Regulation: ncRNAs, particularly some lncRNAs, can interact with the splicing machinery and influence alternative splicing events, which affects the diversity of proteins that can be produced from a single gene.
Genomic Imprinting and X-Chromosome Inactivation: Certain ncRNAs play roles in processes that lead to monoallelic expression of genes, like genomic imprinting. An example is the Xist lncRNA, vital for the inactivation of one X chromosome in female mammals.
Protein Activity Regulation: Some ncRNAs directly bind to proteins and modify their activity. They might change the protein's conformation, stability, or its ability to interact with other molecules.
Enhancer Activity Modulation: Enhancer RNAs (eRNAs) are ncRNAs transcribed from enhancer regions. They play roles in promoting gene expression by facilitating the looping of enhancers to their target gene promoters.
Maintenance of Nuclear and Chromosomal Architecture: Certain lncRNAs maintain the structural integrity of the nucleus and chromosomes, thus playing a role in spatial organization and overall cell health.
Feedback and Regulatory Loops: Some ncRNAs are part of feedback mechanisms, where they are produced in response to the activity of a protein and subsequently regulate the expression or function of that protein.

Noncoding RNAs serve as intricate regulators of cellular processes by interacting with both the DNA and protein components of the cell. Their diverse modes of action and broad spectrum of targets underline their importance in maintaining cellular homeostasis and function. Their interaction with protein-coding genes is multifaceted and ensures the fine-tuning of genetic output in response to various cellular conditions.

When, in the evolutionary timeline, is the emergence of noncoding RNA from 'junk' DNA hypothesized to have occurred?

Understanding the evolution of 'junk' DNA and its transformation into functional noncoding RNA is vital in unraveling the intricate complexities of genomic regulation. While pinpointing an exact time is challenging, several hypotheses attempt to provide insights into this evolutionary journey.

The RNA World Hypothesis: It is hypothesized that prior to the dominance of DNA and proteins, RNA served dual roles as both a genetic storage medium and a catalyst, suggesting that an RNA-centric form of life would have existed around 4 billion years ago. This perspective posits that RNA's multi-functional nature would have been foundational in the early stages of life on Earth.
Accumulation of 'Junk' DNA: Throughout evolution, genomes would have expanded, incorporating sequences not immediately responsible for coding proteins. These sequences would have originated from various sources, including transposable elements and repetitive sequences. Over millennia, vast stretches of eukaryotic genomes did not appear to hold coding value, thus being labeled as 'junk' DNA.
Emergence of Functional Noncoding RNA: By the late 20th century, it became apparent that much of the 'junk' DNA was actively transcribed into RNA, even if it wasn't translated into proteins. Notable RNA molecules such as Xist and various microRNAs, which hold pivotal roles in cellular regulation, began changing the prevailing perceptions of 'junk' DNA.
Insights from the Human Genome Project: Post the completion of the Human Genome Project in the early 21st century, it was revealed that a mere 1-2% of the human genome actually codes for proteins. Subsequent research, including projects like ENCODE, indicated that a significant portion of the noncoding genome would have functional roles, producing diverse ncRNAs that modulate various cellular operations.
Modern Synthesis: Today, it is understood that ncRNAs play indispensable roles in cell function, especially in higher eukaryotes. The emergence of these functional noncoding sequences in the evolutionary timeline would have provided an added layer of regulatory finesse that aided in the development of complex multicellular organisms.

In essence, the transformation of 'junk' DNA into functional noncoding RNA is believed to have played a pivotal role in the evolutionary tapestry, adding complexity and sophistication to the blueprint of life.

Which de novo genetic information is necessary to instantiate the diverse functions of noncoding RNAs derived from 'junk' DNA?

'Junk' DNA, a term once used to describe the noncoding regions of the genome, is now appreciated for its essential role in genomic function and regulation. Over time, segments of these noncoding regions are claimed to have been repurposed or evolved de novo to give rise to various noncoding RNAs (ncRNAs) with diverse functionalities. 

Recognition Sequences: For any ncRNA to function effectively, it must be able to interact with specific molecular partners, such as DNA, RNA, or proteins. Therefore, the ncRNA sequence itself would contain regions that facilitate these interactions. This requires de novo sequences that can form specific secondary and tertiary structures, or motifs, compatible with its molecular targets.
Promoter and Regulatory Elements: For the precise expression of ncRNAs, appropriate promoter and regulatory elements would need to evolve upstream of the ncRNA sequence. These elements ensure that the ncRNA is transcribed in the right cell type, at the right time, and in response to specific cues or conditions.
Secondary and Tertiary Structures: The function of many ncRNAs is heavily dependent on their ability to form specific three-dimensional shapes. These shapes often arise from the formation of stem-loops, bulges, and other secondary structures, which then fold into a functional tertiary structure. De novo sequences that can adopt these specific configurations are essential for the ncRNA's function.
Modification Sites: Some ncRNAs undergo post-transcriptional modifications, like methylation or pseudouridylation, which can influence their stability, interactions, or function. The presence of sequences that signal for these modifications would be essential.
Evolution of Functional Motifs: Just like protein domains, certain motifs in ncRNAs can confer specific functions. The de novo appearance or modification of these motifs can lead to the acquisition of new functionalities or enhance existing ones.
Interaction Domains: For ncRNAs that operate as part of larger complexes (e.g., the ribosome or spliceosome), sequences that facilitate interaction with other RNA or protein components of these complexes are crucial.
Termination Signals: Proper termination of ncRNA transcription ensures that the resultant molecule is of the correct length and has the necessary sequence elements to perform its function. Hence, appropriate termination signals would need to be in place.
Localization Signals: Some ncRNAs function in specific subcellular compartments. Sequences that direct their transport to or retention in these compartments are important for their proper function.

The instantiating functional ncRNAs from 'junk' DNA is not a mere happenstance but a complex process that would involve the establishment of various de novo genetic information and regulatory mechanisms. 

What manufacturing codes and languages would need to be present and operational for the synthesis and function of noncoding RNAs?

To ensure a comprehensive understanding of the process of noncoding RNA synthesis and function, various stages and factors need to be considered. Using the BBCode format, here are the key steps and elements:

Transcription Initiation: For the synthesis of noncoding RNAs, RNA polymerase II (or sometimes III) is required. The initiation of transcription begins with the binding of transcription factors to the promoter regions of the DNA.
RNA Polymerization: RNA polymerase reads the DNA template strand and synthesizes the corresponding RNA strand.
5' Capping: Immediately after the start of transcription, the 5' end of the emerging RNA molecule is modified with the addition of a 7-methylguanosine cap, which plays a role in RNA stability and translation initiation.
Splicing: For some noncoding RNAs, introns are removed, and exons are joined together in a process called splicing. This is mediated by the spliceosome, a large complex of proteins and small nuclear RNAs.
3' Polyadenylation: At the end of the transcription, the 3' end of the RNA is cleaved and a poly(A) tail is added. This tail aids in RNA stability and transport out of the nucleus.
Transport: The synthesized noncoding RNA needs to be transported out of the nucleus to function in the cytoplasm. This is facilitated by nuclear pores and transport proteins.
RNA Stability: The stability and degradation of noncoding RNAs in the cytoplasm is regulated by various RNA-binding proteins and cellular machinery.
Functional Roles: Noncoding RNAs play a plethora of roles in the cell. Some regulate gene expression, some play roles in protein translation, while others are involved in the structural aspects of cellular compartments (e.g., rRNA in ribosomes).
Interactions with Proteins: Many noncoding RNAs function by interacting with specific proteins, modulating their activity or directing them to specific targets.
Degradation: Once their role is fulfilled, noncoding RNAs can be degraded by cellular machinery, including exosomes and endonucleases, ensuring cellular RNA homeostasis.

This is a simplified overview. The synthesis and function of noncoding RNAs is a vast topic, and many details, exceptions, and additional processes exist.

Which epigenetic regulatory mechanisms are involved in the modulation and function of noncoding RNAs from 'junk' DNA?

'Junk' DNA, now more often referred to as noncoding DNA, has been found to have numerous regulatory roles, especially in the context of noncoding RNAs (ncRNAs) and epigenetics. Here are some of the epigenetic regulatory mechanisms that are involved in the modulation and function of noncoding RNAs originating from these regions, presented in the BBCode format:

DNA Methylation: The addition of a methyl group to the cytosine base in DNA can influence the transcription of noncoding RNAs. Hypermethylation typically represses transcription, while hypomethylation can activate it.
Histone Modifications: Histones, around which DNA is wrapped, can undergo post-translational modifications like methylation, acetylation, phosphorylation, and ubiquitination. These modifications can affect the structure of chromatin and, subsequently, the transcription of noncoding RNAs.
Chromatin Remodeling: Chromatin remodeling complexes can change the structure of chromatin, making it either more condensed (heterochromatin) or more relaxed (euchromatin). This, in turn, affects the accessibility of the DNA to the transcriptional machinery and influences ncRNA synthesis.
RNA Editing: After an ncRNA is transcribed, it can undergo editing, where certain bases are changed, added, or removed. This can affect the function and stability of the ncRNA.
ncRNA Interactions: Many noncoding RNAs, such as lncRNAs, can interact with other ncRNAs, DNA, or proteins to form ribonucleoprotein complexes. These complexes can regulate the expression and function of other genes, including other noncoding RNAs.
RNA Methylation: Just as DNA can be methylated, certain bases in RNA (especially adenine to form m6A) can also be modified, affecting the function and fate of the ncRNA.
RNAi Pathway: Some noncoding RNAs, like siRNAs and miRNAs, function through the RNA interference (RNAi) pathway, where they guide the RNA-induced silencing complex (RISC) to target RNAs, leading to their degradation or translational repression.
Nuclear Architecture and Subnuclear Domains: The positioning of genes within the nucleus and their association with specific nuclear domains can influence their transcriptional activity, including that of noncoding RNAs.
Transcriptional Interference: The transcription of one noncoding RNA can interfere with the transcription of another RNA or gene if they are in close proximity or have overlapping regions.
Feedback Mechanisms: Some noncoding RNAs can regulate their own expression or the expression of enzymes and proteins involved in epigenetic modification, creating feedback loops.

The term 'junk' DNA is outdated, as increasing evidence suggests that these regions have essential regulatory roles, many of which are yet to be fully understood.

Are there specific signaling pathways that are influenced or modulated by noncoding RNAs derived from 'junk' DNA?

Yes, noncoding RNAs (ncRNAs) derived from previously termed 'junk' DNA (now more aptly described as noncoding DNA regions) play roles in various signaling pathways. These ncRNAs can either positively or negatively regulate specific pathways, influencing various cellular processes. Here are some of the signaling pathways modulated by noncoding RNAs, presented in the BBCode format:

Wnt/β-Catenin Signaling: Several ncRNAs have been identified that can either activate or inhibit this pathway, which plays a role in cell proliferation, differentiation, and development.
TGF-β Signaling: Noncoding RNAs can modulate this pathway that is involved in cell growth, differentiation, apoptosis, and other cellular functions.
Notch Signaling: Critical in cell-cell communication, development, and stem cell maintenance, the Notch signaling pathway can be modulated by certain ncRNAs.
PI3K/AKT/mTOR Signaling: This pathway, vital for cell survival, growth, and metabolism, can be influenced by noncoding RNAs, especially in the context of cancer.
MAPK/ERK Pathway: ncRNAs can influence this pathway, which plays a role in cell differentiation, proliferation, and survival.
JAK-STAT Signaling: The Janus kinase-signal transducer and activator of transcription pathway, involved in processes like immunity, cell division, cell death, and tumor formation, is another target for regulation by ncRNAs.
Hedgehog Signaling: Noncoding RNAs can modulate this pathway, which is pivotal for embryonic development and is implicated in various cancers when dysregulated.
NF-κB Signaling: This pathway, which plays a central role in inflammatory and immune responses, can be influenced by specific noncoding RNAs.
p53 Signaling: Given its role in cell cycle regulation and apoptosis, the p53 pathway is of significant interest in cancer biology. Some ncRNAs have been found to modulate the activity of this pathway.
Hypoxia-inducible Factor (HIF) Pathway: In response to low oxygen levels, the HIF pathway gets activated, and certain noncoding RNAs have roles in modulating this response, especially in the context of cancer and angiogenesis.

These pathways represent just a subset of cellular signaling cascades that ncRNAs can influence. As research progresses, it's likely that more connections between ncRNAs and signaling pathways will be uncovered. It's also essential to note that many ncRNAs have roles in multiple pathways, reflecting the intricate regulatory network within cells.

What regulatory codes are foundational for the synthesis, processing, and operational mechanisms of noncoding RNAs from 'junk' DNA?

Noncoding RNAs (ncRNAs) derived from regions once termed 'junk' DNA (now more accurately described as noncoding DNA regions) are regulated by a series of codes and mechanisms. These ensure the proper synthesis, processing, and function of these molecules. Here's a breakdown of some foundational regulatory codes, presented in the BBCode format:

Promoter Sequences: Just like protein-coding genes, ncRNA genes have promoter regions upstream of their transcription start sites. These sequences recruit RNA polymerase and associated transcription factors to initiate transcription.
Enhancers and Silencers: These are distal regulatory DNA sequences that can augment (enhancers) or diminish (silencers) the rate of transcription of associated ncRNA genes.
Splicing Codes: While many ncRNAs are unspliced, some undergo splicing. Specific sequences and structures in the pre-RNA help guide the splicing machinery to remove introns and join exons.
Transcription Termination Signals: These sequences signal the end of transcription for RNA polymerase, ensuring that the ncRNA transcript is of the correct length.
RNA Secondary Structures: The ability of RNA to form secondary structures (e.g., hairpin loops) can influence its processing, stability, and function. Some ncRNAs exert their function primarily through their structural configuration.
Polyadenylation Signals: Some ncRNAs, especially long noncoding RNAs (lncRNAs), have sequences that signal for the addition of a poly(A) tail at their 3' end, influencing their stability and transport.
Localization Signals: Specific sequences or structures within ncRNAs can direct them to particular cellular locations, ensuring that they function in the right cellular context.
RNA Modification Codes: Certain bases within ncRNAs can undergo modifications, such as methylation. These modifications can influence the stability, structure, and function of the ncRNA.
Interacting Partner Codes: Specific motifs or structures in ncRNAs can facilitate their interaction with other molecules, such as proteins, DNA, or other RNAs. These interactions are essential for the functional roles of many ncRNAs.
Decay Signals: ncRNAs have specific sequences or motifs that can target them for degradation, ensuring that they don't accumulate unnecessarily within the cell.

These regulatory codes, along with various cellular mechanisms, work in concert to ensure that ncRNAs are synthesized, processed, and function correctly. As research progresses, our understanding of these codes and their nuances continues to deepen.

Is there concrete scientific evidence that supports the idea that noncoding RNAs from 'junk' DNA emerged through evolutionary processes?

The emergence of noncoding RNAs (ncRNAs) from what was once termed 'junk' DNA is an area of ongoing research in evolutionary biology.  

Origins of 'Junk' DNA: It is hypothesized that much of the noncoding DNA, from which ncRNAs are transcribed, originated from ancient repetitive elements, transposable elements, and viral sequences that inserted themselves into the genome. Over time, these sequences would have been repurposed or co-opted for new functions.
Ancient Regulatory Roles: Noncoding DNA regions that give rise to regulatory ncRNAs would have provided an additional layer of gene expression control. Organisms with these regulatory elements would have had an advantage in adapting to various environmental conditions.
Functional Retention: During the course of evolution, sequences that confer a selective advantage tend to be retained. ncRNAs that play vital roles in processes like development, differentiation, or stress response would have been conserved across species.
Duplication and Divergence: Gene duplication is a common evolutionary event. Once a gene is duplicated, one copy can maintain its original function, while the other can accumulate mutations without detrimental effects. Some of these duplicated genes would have evolved into noncoding sequences with novel functions, eventually giving rise to ncRNAs.
Adaptive Roles of ncRNAs: ncRNAs would have provided an avenue for rapid evolutionary adaptation. They can evolve faster than protein-coding genes due to their shorter lengths and fewer functional constraints, enabling organisms to quickly respond to environmental shifts.
Complex Organism Development: As organisms evolved to be more complex, there would have been a need for intricate gene regulation. ncRNAs would have emerged as crucial regulators, guiding processes like embryonic development, tissue differentiation, and cellular response mechanisms.
Evidence from Comparative Genomics: Comparative genomics has shown that certain noncoding DNA regions, and by extension the ncRNAs transcribed from them, are conserved across species. This conservation indicates that these sequences would have essential functions and have been maintained through evolutionary pressures.
Evolving Interactions: As organisms became more sophisticated, ncRNAs would have evolved to interact with a myriad of other cellular components, including proteins, DNA, and other RNAs. These interactions would have been foundational for complex cellular processes and regulatory networks.
Defense Mechanisms: Some ncRNAs would have evolved as part of the cellular defense mechanism against foreign genetic elements, such as viruses. For instance, small interfering RNAs (siRNAs) would have emerged as a way to target and degrade foreign RNA molecules.
Environmental Sensing: The ability to sense and adapt to changing environments would have been crucial for survival. ncRNAs would have evolved as molecular sensors and responders, adjusting gene expression patterns in response to environmental cues.

Are the systems and processes involving noncoding RNAs from 'junk' DNA irreducibly complex or interdependent, indicating that they must function as a complete system to be effective?

Noncoding RNAs, especially those transcribed from what was once termed 'junk' DNA, are part of an intricate network of molecular systems within the cell. These systems often exhibit a level of complexity that suggests a finely tuned coordination between various components. The elaborate coordination between noncoding RNAs and the machinery they interact with often appears to be of a nature where one mechanism, without the other, would bear no function. This interdependence could present challenges to traditional stepwise evolutionary models. For example:

Complexity of RNA Processing: The synthesis and processing of noncoding RNAs involve a range of molecular machines and codes. Splicing, for instance, requires precise sequences and protein assemblies to remove intronic sequences. In the absence of any of these components, splicing could go awry, potentially rendering the RNA nonfunctional.
Interplay of Codes and Machinery: The cell employs a series of codes, from the DNA sequences that signify the start and end of transcription to the motifs that guide RNA modifications. Each code is read and acted upon by specific proteins or protein complexes. A protein that reads a particular motif would have no function if that motif, or the code system it belongs to, didn't exist.
Coordination in RNA-Protein Complexes: Many noncoding RNAs function as part of ribonucleoprotein complexes. These RNAs must be precisely folded and then combined with specific proteins to form a functional unit. An RNA molecule, without its protein partners, or vice versa, would often be nonfunctional.
Feedback and Regulation: Noncoding RNAs play roles in feedback loops, where they help regulate the very processes they are a product of. Such systems exhibit an interdependence where the product of one process influences the initiation or continuation of that process.
Evolutionary Challenges: For these systems to evolve stepwise, each step must confer a selective advantage. However, with such intricate interdependencies, intermediate stages might bear no advantageous function, making them unlikely candidates for positive selection. For instance, a nascent RNA motif, without the machinery to recognize and act upon it, would not provide a benefit to the organism.
Origins of Molecular Machines: Machines like the spliceosome, responsible for RNA splicing, are incredibly complex. Their stepwise assembly seems unlikely, especially if intermediate stages lacked function. A partially formed spliceosome, missing key components, would not splice RNA correctly, if at all.
Symbiotic Relationships: Some noncoding RNAs act in tandem with others, forming symbiotic relationships where one RNA's function is dependent on another's. This relationship raises questions about how both RNAs, and their associated functions, could have simultaneously emerged to work in harmony.

In light of these complexities, the coordinated systems involving noncoding RNAs had to be instantiated and created all at once, fully operational, from scratch. The interwoven nature of codes, languages, signaling, and proteins in these systems presents challenges to gradual, stepwise evolutionary models and instead suggests a design with inherent purpose and function.

Once noncoding RNAs from 'junk' DNA are instantiated and operational, with which other intra- and extracellular systems are they interdependent or intricately connected?

Noncoding RNAs (ncRNAs) derived from regions once termed 'junk' DNA are not isolated entities within the cell. Instead, they integrate into a vast network of intra- and extracellular systems, showcasing a complex web of interdependencies and connections. Delving into these intricate relationships, we find:

Gene Expression Regulation: Many ncRNAs play pivotal roles in controlling gene expression. They can bind to DNA, RNA, or proteins to either upregulate or downregulate the expression of specific genes, ensuring the right genes are active at the appropriate times.
RNA Processing Machinery: The splicing, editing, and modification of RNA transcripts often involve interactions with ncRNAs. Complexes like the spliceosome, which includes small nuclear RNAs (snRNAs), are vital for the correct processing of precursor mRNA into mature mRNA.
Protein Synthesis and Function: Some ncRNAs, such as transfer RNAs (tRNAs) and ribosomal RNAs (rRNAs), are directly involved in protein synthesis. They are essential components of the ribosome, ensuring that amino acids are correctly added to growing polypeptide chains.
Chromatin Remodeling: Long noncoding RNAs (lncRNAs) can recruit chromatin-modifying enzymes to specific genomic loci, influencing the chromatin state and thereby regulating gene expression. This connection underscores the role of ncRNAs in the epigenetic landscape of the cell.
Cellular Stress Responses: In response to various cellular stresses, certain ncRNAs are upregulated to help the cell adapt and survive. They interact with stress granules, protein aggregates, and other cellular machinery to modulate the cell's stress response.
Developmental Pathways: During organismal development, ncRNAs play roles in signaling pathways, helping to guide cell differentiation, organogenesis, and other key processes.
Intercellular Communication: Some ncRNAs are packaged into extracellular vesicles, like exosomes, and are then released into the extracellular space. These ncRNA-loaded vesicles can be taken up by other cells, facilitating cell-to-cell communication and potentially playing roles in processes like immune responses or tissue regeneration.
DNA Damage Repair: ncRNAs are involved in the DNA damage response, helping to recruit repair machinery to damaged sites and playing roles in the repair process itself.
Immune System Modulation: Certain ncRNAs influence the activity of immune cells, modulating responses to pathogens, and shaping overall immune system function.
Cell Cycle Regulation: ncRNAs can regulate the cell cycle, ensuring that cells progress through the stages of growth, DNA replication, and division in a controlled manner.
Signal Transduction Pathways: ncRNAs can be involved in various signaling pathways, modulating the cell's response to internal and external signals.

The interconnectedness of ncRNAs with so many diverse systems within and outside the cell highlights their importance in maintaining cellular and organismal homeostasis. The vast and intricate web of interactions they partake in underscores their pivotal roles in numerous biological processes and their potential implications in health and disease.

Major Premise: Systems that are characterized by semiotic codes, languages, and intricate interdependencies typically arise from intentional, purposeful design rather than from random, unguided processes.
Minor Premise: The network involving noncoding RNAs demonstrates such semiotic codes, languages, and intricate interdependencies, needing a synchronized emergence of multiple components to be functional.
Conclusion: Therefore, the network involving noncoding RNAs is indicative of intentional, purposeful design.

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33. Oogenesis

Oogenesis is the specialized process in females that leads to the formation of ova or eggs. This developmental pathway ensures the continuation of species through sexual reproduction. Delving into its intricacies provides insights into its foundational importance for reproductive biology and the developmental processes shaping organismal form and function.

Overview of Oogenesis

Initiation in the Fetal Ovary: Oogenesis begins during fetal development. Primordial germ cells migrate to the developing ovaries and become oogonia. These oogonia undergo several rounds of mitotic division before they enter meiosis.
Formation of Primary Oocytes: As oogonia enter meiosis, they become primary oocytes. Interestingly, these cells halt in the prophase of meiosis I and remain in this arrested state until puberty.
Development of Follicles: Surrounding the primary oocytes, granulosa cells form, creating primordial follicles. As oocytes grow, the surrounding follicles also mature, transitioning through primary, secondary, and finally to the antral stage.

Maturation and Ovulation

Resumption of Meiosis: Triggered by hormonal cues during the menstrual cycle, primary oocytes resume meiosis. Only one (or occasionally two) is selected each cycle for maturation, while others degenerate.
Formation of Secondary Oocytes: The primary oocyte completes meiosis I, yielding a secondary oocyte and a smaller polar body. The secondary oocyte then begins meiosis II but pauses in metaphase until fertilization.
Ovulation: The mature follicle releases the secondary oocyte from the ovary, an event known as ovulation. If sperm fertilizes this oocyte, it will complete meiosis II, forming an ovum and another polar body.

Importance in Biological Systems and Developmental Processes

Genetic Diversity: Meiosis introduces genetic variation through the process of recombination, ensuring offspring have unique combinations of genes.
Regulation of Female Reproductive Cycle: Oogenesis is intimately connected to the hormonal regulation of the female reproductive cycle, with stages of oocyte maturation, ovulation, and preparation for potential pregnancy being tightly coordinated.
Embryonic Development: Once fertilized, the ovum begins the complex process of embryogenesis. The early stages of embryonic development rely on the cytoplasmic contents of the egg, including RNA, proteins, and other molecules vital for initial cell divisions and differentiation.

In essence, oogenesis is a cornerstone of female reproductive biology. It ensures not only the formation of viable ova for fertilization but also establishes the foundational stages for embryonic development, ultimately shaping the form and function of new organisms.

How does oogenesis facilitate the formation and maturation of female gametes, and what stages does it encompass?

Oogenesis is the biological process responsible for the formation, development, and maturation of ova or eggs in females. This process ensures the continuation of species through sexual reproduction and provides a means for genetic variation. The stages it encompasses are intricate, each playing a pivotal role in the creation of viable female gametes.

Stages of Oogenesis

Initiation in the Fetal Ovary: Oogenesis commences during fetal development. The primordial germ cells migrate to the developing ovaries where they differentiate into oogonia. These oogonia undergo several rounds of mitotic division and then initiate meiosis.
Formation of Primary Oocytes: When oogonia enter the first stage of meiosis, they transition into primary oocytes. These cells are paused in the prophase of meiosis I and remain in this arrested state until the onset of puberty.
Development of Follicles: Granulosa cells surround the primary oocytes, establishing primordial follicles. As the oocyte enlarges, these follicles mature in stages, transitioning from primary to secondary and finally reaching the antral stage.
Maturation and Ovulation: Hormonal signals during the menstrual cycle prompt a primary oocyte to resume meiosis. Typically, only one is selected for maturation each cycle, with the remainder undergoing degeneration.
Formation of Secondary Oocytes: The primary oocyte completes meiosis I, forming a secondary oocyte and a smaller polar body. The secondary oocyte embarks on meiosis II but is halted in metaphase until fertilization occurs.
Ovulation: Ovulation is the event where the mature follicle releases the secondary oocyte from the ovary. If sperm fertilizes the oocyte, meiosis II resumes, resulting in the formation of an ovum and another polar body.
Completion of Meiosis: Post-fertilization, the oocyte completes its second meiotic division, resulting in the formation of the mature ovum and the second polar body.

This multi-stage journey of oogenesis, from the early stages of oogonia development to the formation of a mature ovum, showcases the intricate orchestration of cellular events that underpin female reproduction. The process ensures not only the continuation of life but also offers a window into the cellular and molecular intricacies of developmental biology.

How is oogenesis instrumental in ensuring genetic diversity, and what role does it play in reproductive success and species continuation?

Oogenesis is a cornerstone of female reproductive biology. It not only ensures the formation of mature eggs necessary for fertilization but also serves as a platform for introducing genetic variability, a fundamental asset for the adaptive potential of a species. Delving into the depths of oogenesis, we uncover its paramount significance in genetic diversity, reproductive success, and species continuation.

Ensuring Genetic Diversity

Meiotic Recombination: During prophase I of meiosis in oogenesis, homologous chromosomes exchange genetic material in a process called crossover. This results in the shuffling of alleles, leading to the formation of oocytes with unique combinations of maternal and paternal genes.
Random Assortment of Chromosomes: In metaphase I of meiosis, the way homologous chromosomes line up is random. This random assortment ensures that each oocyte has a different combination of chromosomes, further contributing to genetic variability.

Role in Reproductive Success and Species Continuation

Formation of Healthy Ova: Through oogenesis, healthy and functional ova are produced. These ova are essential for fertilization and subsequently for producing viable offspring.
Maintenance of Chromosome Number: Oogenesis ensures that the ova have a haploid chromosome number, which is essential. When the haploid ovum combines with a haploid sperm during fertilization, the resultant zygote will have the diploid chromosome number, preserving the genetic stability of the species.
Selective Maturation: Not all primary oocytes complete oogenesis. Typically, only the healthiest among them reach ovulation. This selection ensures that the best-quality oocytes, with the highest potential for successful fertilization and embryo development, are released for fertilization.
Storage and Timely Release: Oogenesis, coupled with the female reproductive cycle, ensures that mature oocytes are stored and released in a timely manner, optimizing the chances of encountering sperm and achieving successful fertilization.

Through the intricacies of oogenesis, nature ensures that offspring inherit a mix of genetic material, which is crucial for adaptability and evolution. Moreover, the rigorous processes within oogenesis underscore its vital role in reproductive success, ensuring the continuation and evolutionary success of species.

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Diagram showing the reduction in number of the chromosomes in the process of maturation of the ovum. (In mammals, the first polar body normally disintegrates before dividing, so only two polar bodies are produced. 1

At which point in the evolutionary timeline is the onset of oogenesis speculated to have appeared?

Oogenesis, the process by which female gametes or ova are produced, stands as a pivotal cornerstone in the reproductive biology of multicellular organisms. While the exact point in the evolutionary timeline when oogenesis first appeared is not definitively known, here's a perspective on its emergence based on evolutionary biology.

Early Cellular Reproduction:

Simple Cell Division: In the earliest stages of life on Earth, unicellular organisms would have reproduced primarily through simple cell division methods such as binary fission. This basic form of reproduction would not have necessitated specialized processes like oogenesis.
Emergence of Multicellularity: With the advent of multicellularity, organisms would have begun to develop specialized cell types and tissues. It is hypothesized that as these multicellular organisms evolved, so did the need for specialized reproductive cells to ensure successful reproduction and continuation of the species.

Diversification of Reproductive Mechanisms:

Transition to Sexual Reproduction: As multicellular organisms diversified, sexual reproduction would have emerged as a strategy to increase genetic variation, which in turn enhanced adaptability and survival chances in fluctuating environments. It is against this backdrop that oogenesis would have been introduced, serving the purpose of creating female reproductive cells.
Evolution of Gametogenesis: With sexual reproduction taking center stage, gametogenesis (production of gametes) would have been paramount. Oogenesis, as a form of gametogenesis, would have evolved to ensure the production of ova with the correct haploid number of chromosomes.

Oogenesis and Genetic Diversity:

Meiotic Division: As evolution proceeded, it would have become crucial for gametes to contain half the number of chromosomes of somatic cells. The process of meiosis, a distinct form of cell division giving rise to haploid cells, would have emerged. Within this framework, oogenesis would have evolved to ensure that female gametes underwent meiosis.
Evolutionary Advantages: The ability of oogenesis to introduce genetic variation through processes like meiotic recombination would have conferred significant evolutionary advantages. Genetic diversity is key for adaptability, and organisms harnessing the full potential of oogenesis would have had an edge in terms of survival and reproductive success.

In light of the complexities of oogenesis and its significance in reproduction, it can be posited that this process was a critical evolutionary milestone. It would have facilitated the emergence of advanced forms of life capable of sexual reproduction and capitalizing on the benefits of genetic diversity.

What de novo genetic information would be imperative to instantiate the complex process of oogenesis?

The process of oogenesis, responsible for the formation and maturation of female gametes, hinges on a constellation of genetic information. While it's challenging to encapsulate the entirety of this genetic interplay, certain de novo genetic components would be fundamental to orchestrate this intricate dance of cellular differentiation and development. Here's an exploration of some crucial genetic facets that would be imperative to instantiate oogenesis:

Cellular Differentiation and Development:

Germ Cell Specification: Genes responsible for specifying germ cell lineage would have been essential. These genes direct a subset of embryonic cells to become primordial germ cells, the precursors to ova.
Meiotic Initiation and Progression: The transition from mitosis to meiosis is pivotal in oogenesis. Genes that regulate this shift and ensure the correct progression of meiosis are central to oogenesis.

Regulation of Cellular Growth and Division:

Control of Oocyte Growth: Oogenesis involves significant growth of the oocyte before maturation. Genes that regulate cellular growth, nutrient uptake, and metabolism would have been essential.
Cytoskeletal Dynamics: Proper division during oogenesis, especially the asymmetric divisions that give rise to polar bodies, requires precise cytoskeletal rearrangements. Genes controlling the dynamics of actin, tubulin, and other cytoskeletal proteins play a role here.

Maintenance of Genetic Integrity:

DNA Repair Mechanisms: Given the extended prophase of meiosis I in oogenesis, oocytes are susceptible to DNA damage. Genes involved in DNA repair would have been crucial to ensure the integrity of the genetic material passed to the next generation.
Chromosome Segregation: Proper segregation of chromosomes during meiotic divisions is critical. Genes responsible for spindle assembly, chromosome attachment, and checkpoint mechanisms ensure that oocytes receive the correct genetic complement.

Interplay with Surrounding Environment:

Oocyte-Somatic Cell Communication: Oocytes do not mature in isolation but are supported by surrounding somatic cells. Genes facilitating communication between the oocyte and these somatic cells, like those involved in gap junction formation or signaling pathways, are imperative.
Response to Hormonal Cues: The final stages of oogenesis, especially oocyte maturation, are triggered by hormonal signals. Genes enabling the oocyte to respond to these external cues, including hormone receptors and downstream signaling components, would have been necessary.

The above considerations represent just a snapshot of the vast genetic landscape that governs oogenesis. These de novo genetic components would have been instrumental in driving the evolution and refinement of this process, underscoring its significance in reproductive biology.

What manufacturing codes and languages would be essential for the synthesis, maturation, and successful culmination of oocytes?

Oogenesis, the process of oocyte formation and maturation, is a complex orchestration of molecular and cellular events. If we were to conceptualize these events in terms of "manufacturing codes and languages," the various molecular and genetic mechanisms would serve as the instructions and protocols for ensuring the successful synthesis, maturation, and culmination of oocytes. Here are the pivotal "codes" and "languages" in this intricate process:

Genetic Codes:

DNA Sequence: The primary genetic blueprint encodes every protein and regulatory RNA essential for oocyte development. Without this fundamental code, the entire process wouldn't initiate.
Epigenetic Modifications: Methylation patterns and histone modifications regulate the accessibility of the DNA to transcriptional machinery, ensuring that genes are expressed at the correct time and place.

Regulatory Languages:

Transcriptional Control: Transcription factors, enhancers, and silencers function as regulatory elements, determining which genes are turned on or off during oogenesis.
Post-transcriptional Regulation: Small RNAs, such as miRNAs, and RNA binding proteins modulate mRNA stability and translation, offering an additional layer of gene expression control.

Cellular Signaling Codes:

Hormonal Signals: The maturation of oocytes is finely tuned by hormonal cues, particularly luteinizing hormone (LH) and follicle-stimulating hormone (FSH). These hormones trigger cascades of intracellular events leading to oocyte maturation.
Paracrine Signaling: Surrounding somatic cells (granulosa and theca cells) communicate with the developing oocyte, providing essential factors and signals for its maturation.

Intracellular Communication:

Gap Junctions: These structures allow the exchange of ions and small molecules between the oocyte and adjacent granulosa cells, facilitating mutual communication and support.

Quality Control Mechanisms:

Cell Cycle Checkpoints: Throughout oogenesis, checkpoints ensure the DNA is replicated correctly, and chromosomes are accurately segregated.
Apoptotic Pathways: These pathways serve as a quality control mechanism, ensuring that only the healthiest oocytes complete maturation, while those with anomalies undergo programmed cell death.

Structural and Functional Codes:

Cytoskeletal Arrangements: The cytoskeleton, particularly microtubules and actin filaments, play a critical role in the asymmetric division of oocytes and the expulsion of polar bodies.
Organelle Localization: Proper positioning of organelles, like the mitochondria and endoplasmic reticulum, is essential for oocyte health and function.

In essence, the successful culmination of oogenesis relies on a symphony of molecular "codes" and "languages" that coordinate the formation, maturation, and eventual release of a functional oocyte capable of fertilization and supporting the early stages of embryonic development.

What epigenetic regulatory mechanisms would be critical for guiding the stages of oogenesis, from oogonia to mature oocytes?

Epigenetics plays a pivotal role in the stages of oogenesis, ensuring the proper development, differentiation, and maturation of oocytes. These regulatory mechanisms modulate gene expression without altering the underlying DNA sequence. Here are some key epigenetic regulatory mechanisms that guide the progression of oogenesis, from oogonia to mature oocytes:

DNA Methylation:

Establishment of Imprints: Genomic imprinting ensures that specific genes are expressed in a parent-of-origin-specific manner. During oogenesis, certain genes acquire methylation marks on the maternal allele, ensuring their silence or activation in the resulting embryo.
X-chromosome Inactivation: One of the two X chromosomes in female cells is silenced through a process that heavily involves DNA methylation, ensuring dosage compensation between males and females.

Histone Modifications:

Histone Methylation: Specific histone methylation patterns, such as H3K9me2/3 and H3K27me3, lead to chromatin condensation and transcriptional repression, while others like H3K4me3 are associated with active gene expression.
Histone Acetylation: Histone acetyltransferases (HATs) add acetyl groups to histones, leading to an open chromatin structure and transcriptional activation. Conversely, histone deacetylases (HDACs) remove these groups, causing chromatin condensation and gene repression.

Non-coding RNAs:

Xist RNA: Critical for X-chromosome inactivation, Xist RNA coats the inactive X chromosome, recruiting other factors to aid in its silencing.

MicroRNAs (miRNAs): These small non-coding RNAs target and repress specific mRNAs, modulating the levels of proteins critical for various stages of oocyte development and maturation.

Chromatin Remodeling:

Nucleosome Positioning: Chromatin remodelers reposition nucleosomes, allowing or restricting access to transcriptional machinery, which influences gene expression patterns during oogenesis.
Histone Variants: Replacement of canonical histones with histone variants can influence chromatin structure and function. For example, the incorporation of H3.3, a histone variant, is associated with transcriptionally active regions.

Small RNA-mediated Silencing:

PIWI-interacting RNAs (piRNAs): These small RNAs work with PIWI proteins to suppress the activity of transposable elements in the oocyte, ensuring genome stability.

The intricate dance of epigenetic modifications ensures the proper progression of oogenesis. These mechanisms, from DNA methylation to histone modifications and non-coding RNAs, collaborate to guide the differentiation and maturation of oocytes, preparing them for the next stages of reproductive biology.

Are there signaling pathways that are vital in overseeing the proliferation, differentiation, and maturation events during oogenesis?

Oogenesis is a complex process that requires meticulous coordination of various cellular events, including proliferation, differentiation, and maturation. Several signaling pathways play pivotal roles in these processes, ensuring the successful development and maturation of oocytes. Here are some key signaling pathways involved in oogenesis:

Transforming Growth Factor-β (TGF-β) Superfamily Signaling:

Bone Morphogenetic Protein (BMP) Pathway: BMPs regulate the growth and differentiation of primordial germ cells and influence the transition of primordial follicles to the primary follicular stage.
Activin and Inhibin Pathway: These are crucial for FSH (follicle-stimulating hormone) secretion regulation and play roles in follicle development and oocyte maturation.

Fibroblast Growth Factor (FGF) Signaling:

FGF Receptor Signaling: This pathway is important for primordial follicle activation and the transition to primary follicles. It also plays a role in the proliferation of granulosa cells.

Wnt Signaling Pathway:

Canonical Wnt/β-Catenin Pathway: This pathway is involved in the early stages of oocyte differentiation and folliculogenesis.
Non-Canonical Wnt Signaling: This aids in maintaining oocyte meiotic arrest and regulating the ovarian surface epithelium.

Hippo Signaling Pathway:

Hippo/YAP Pathway: This pathway is important for early oocyte development, controlling organ size, and regulating the proliferation and apoptosis of ovarian cells.

Kit Ligand and c-Kit Signaling:

Kit Ligand/c-Kit Pathway: Essential for primordial germ cell proliferation and survival, this pathway also plays a role in early oocyte growth and follicle development.

Notch Signaling Pathway:

Notch Pathway: This is involved in the communication between oocytes and the surrounding somatic cells. It regulates granulosa cell proliferation and differentiation and plays a role in determining follicle fate.

Phosphatidylinositol 3-kinase (PI3K)/Akt Signaling:

PI3K/Akt/mTOR Pathway: Critical for follicle activation and growth, this pathway plays a role in maintaining the dormancy of primordial follicles and is involved in the transition from primordial to primary follicles.

Oogenesis is a tightly regulated process overseen by various signaling pathways. These pathways ensure that oocytes proliferate, differentiate, and mature appropriately, paving the way for successful fertilization and embryonic development.

What regulatory codes are fundamental for the proper coordination, staging, and hormonal regulation during oogenesis?

Oogenesis is a multifaceted process that is under strict regulatory control to ensure proper coordination, staging, and hormonal response. Here are the fundamental regulatory codes that guide oogenesis:

Genetic Regulation:

Oocyte-Specific Transcription Factors: Proteins such as NOBOX, SOHLH1, SOHLH2, and FIGLA play pivotal roles in initiating and maintaining oogenesis.
Dazl: A critical factor for germ cell development, Dazl aids in the transition from oogonia to primary oocytes.

Hormonal Regulation:

Follicle Stimulating Hormone (FSH): FSH promotes the growth and maturation of immature ovarian follicles.
Luteinizing Hormone (LH): LH triggers ovulation and the formation of the corpus luteum, which produces progesterone.
Estradiol: Produced by the growing follicles, estradiol stimulates the proliferation of granulosa cells and prepares the endometrium for implantation.
Progesterone: Produced by the corpus luteum after ovulation, it aids in preparing the endometrium for a potential implantation.

Regulation by Growth Factors:

Growth Differentiation Factor-9 (GDF9) and Bone Morphogenetic Protein-15 (BMP15): Produced by oocytes, these factors are crucial for follicle growth and maturation.

Regulation by Gap Junctions:

Connexins: These proteins form gap junctions between oocytes and granulosa cells, enabling communication and nutrient supply.

MicroRNA Regulation:

miRNAs: Small non-coding RNAs that regulate gene expression post-transcriptionally, some specific miRNAs have been identified to play crucial roles in oocyte maturation and ovarian follicle development.

Regulation by Epigenetic Modifications:

DNA Methylation and Histone Modifications: These are involved in chromatin remodeling, imprinting, and X-chromosome inactivation in oocytes.
Piwi-interacting RNAs (piRNAs): Essential for transposon silencing during germ cell development.

Oogenesis is a meticulously coordinated process regulated at multiple levels - genetically, hormonally, and epigenetically. Proper synchronization and functioning of these regulatory codes are essential for the successful generation of mature oocytes ready for fertilization.

Is there substantial scientific evidence that supports the evolutionary emergence of oogenesis as a key reproductive mechanism?

Oogenesis, the production of an ovum or egg cell, is a complex reproductive mechanism, encapsulating a myriad of intertwined processes, codes, signaling pathways, and proteins. These intertwined components raise intriguing questions about how such a sophisticated system emerged.

Complexity of Regulatory Codes: For oogenesis to function, a series of regulatory codes govern the progression from oogonia to a mature oocyte. These codes ensure that only one oocyte reaches maturation during each menstrual cycle. Such precision and control indicate a system that, if not in place in its entirety, could lead to reproductive chaos.
Necessity of Signaling Pathways: Oogenesis relies on intricate signaling pathways that oversee proliferation, differentiation, and maturation events. These pathways need to be precisely timed and coordinated. Any misstep in these signals could halt oocyte development, suggesting that a partially formed signaling system might not have been functional or beneficial.
Interdependence of Proteins: Various proteins are essential for the structural and functional aspects of oogenesis. The absence or malfunction of even one of these proteins can disrupt the entire process. Such a delicate balance hints at a system that cannot be broken down into simpler, functional units that could have been favored by natural selection.
Epigenetic Regulations: Oogenesis also involves epigenetic modifications, like DNA methylation and histone modifications, crucial for chromatin remodeling and imprinting. These modifications are not mere add-ons but are essential for the proper progression of oogenesis.
Requirement of Fully-Functional Systems: For oogenesis to be effective, multiple systems like hormonal regulation, genetic control, and cellular signaling need to be in place and fully operational. If one system were present without the others, the entire process could fail, making it hard to envision how these systems could have evolved independently or in a stepwise manner.
Synergy of Codes and Languages: The genetic codes and molecular languages used in oogenesis are not just supplementary. They are vital. One without the other would not result in a viable oocyte. This synergy suggests that these codes and languages had to emerge simultaneously for oogenesis to be functional.

When analyzing the intricate dance of oogenesis, it becomes evident that its many components and processes are so interdependent that the absence or malfunction of just one can throw off the entire system. This raises compelling questions about the stepwise evolutionary emergence of such a complex process, leading some to posit that such a system might not have arisen through incremental changes but rather as a fully formed, operational entity.

Is the oogenesis process, with its intricate staging and regulatory inputs, considered to be irreducibly complex or interdependent in nature?

Oogenesis, the process of female gamete formation, is a highly intricate and coordinated procedure that illustrates the profundity of cellular development and regulation. This procedure is composed of a myriad of manufacturing, signaling, and regulatory codes, each of which appears to be deeply interwoven and interdependent with the others. In the complex dance of oogenesis, the manufacturing codes are responsible for producing the necessary molecules and cellular structures that allow the development and maturation of the oocyte. From the synthesis of specific proteins to the construction of cellular organelles like the mitochondria, these codes ensure that the oocyte is equipped with the essential components for its eventual function. On the other hand, signaling codes play a pivotal role in orchestrating the myriad of events during oogenesis. These include the transitions between different developmental stages, the interactions between the oocyte and surrounding somatic cells, and the eventual release of a mature oocyte during ovulation. Signaling cascades, such as the activation of specific kinases or the release of particular hormones, are paramount in guiding the oocyte through its developmental journey. Regulatory codes ensure that both manufacturing and signaling events occur at the right time and place. They act as safeguards, ensuring that errors in the process are minimal. These codes are especially evident in the checkpoints seen during meiosis, where the oocyte's DNA is meticulously examined for errors, ensuring the genetic integrity of the future offspring. One might observe that these codes and languages seem to operate in tandem. The manufacturing codes, for instance, rely on signaling codes to determine when and what to produce. In turn, signaling codes often depend on the products of the manufacturing codes to function. For example, a signaling pathway might rely on a specific protein to be manufactured before it can be activated. Regulatory codes continuously monitor and adjust both signaling and manufacturing processes. This network of crosstalk between the codes is not just a mere coincidence but an essential requirement for the seamless progression of oogenesis. Arguably, this intricate interdependence seems to challenge the notion of a stepwise evolutionary origin. For if one code or language were to emerge without the simultaneous presence of the others, the entire process might stall or malfunction. An isolated emergence of the manufacturing code, without the corresponding signaling or regulatory processes, would potentially result in chaos — production without purpose or direction. Similarly, signaling without manufacturing would be akin to giving commands to a factory with no machinery. It can be surmised, therefore, that the cohesiveness and interdependence evident in oogenesis speak to a level of coordination and precision that seems to necessitate a simultaneous origin. The co-reliance of these codes and languages on each other seems to imply that they had to be instantiated and created all at once, fully operational, from the outset.

Once oogenesis is active and operational, with which other intra- and extracellular systems does it interact or show interdependencies?

Oogenesis, the process of female gamete or oocyte formation, doesn't operate in isolation. It constantly interacts with, and is regulated by, several other intra- and extracellular systems, highlighting the integrative nature of cellular processes. Here are some of these critical interactions and interdependencies:

Hormonal Regulation: Oogenesis is intricately regulated by hormones, especially those released by the anterior pituitary gland like Follicle Stimulating Hormone (FSH) and Luteinizing Hormone (LH). These hormones control the maturation of the oocytes and the progression of the menstrual cycle.
Follicular Development: Surrounding the oocyte, granulosa cells proliferate and differentiate, forming the follicle. This follicle not only provides a supportive microenvironment for the oocyte but also produces hormones like estrogen, which feedback to regulate the pituitary gland and other aspects of the reproductive system.
Zona Pellucida Formation: As the oocyte matures, it secretes glycoproteins that form the zona pellucida, a protective layer around the oocyte. This layer plays a vital role in sperm binding during fertilization.
Cumulus Oophorus Interaction: Surrounding the oocyte, the cumulus oophorus aids in the oocyte's release during ovulation and provides essential nutrients and signaling molecules.
Gap Junction Communication: Between the oocyte and the surrounding granulosa cells, gap junctions facilitate the exchange of nutrients, ions, and signaling molecules. This communication is essential for the oocyte's growth and maturation.
Oviduct Environment: Once ovulated, the oocyte enters the oviduct, where it might meet sperm and undergo fertilization. The oviduct's environment, including its cilia and secretions, aids in moving the oocyte or embryo towards the uterus and supports early embryonic development.
Metabolic Cooperation: Oocytes rely on surrounding somatic cells for energy supply, especially as the oocyte has limited mitochondrial activity during certain developmental stages. The pyruvate produced by granulosa cells is a crucial energy substrate for the oocyte.
Apoptotic Pathways: Not all oocytes reach maturity. Many undergo apoptosis, a regulated form of cell death. This process ensures that only the best oocytes progress to the next stages, maintaining the quality of the oocyte pool.

Each of these systems and their interactions with oogenesis underline the intricate web of processes required to ensure reproductive success. The harmony between oogenesis and these systems is a testament to the intricacy of cellular and physiological orchestration.

Premise 1: Systems that are founded on semiotic codes, exhibit intricate languages, and demonstrate deep interdependence suggest a coordinated and synchronized origin.
Premise 2: Oogenesis, along with its intra- and extracellular interactions, is founded on semiotic codes, operates with intricate languages, and shows profound interdependence where one system cannot function effectively without the other.
Conclusion: Therefore, oogenesis and its associated systems suggest a coordinated and synchronized origin, pointing towards a designed setup.

1. Wikipedia: Oogenesis

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