Origin and evolution of the genetic code: the universal enigma

Origin and evolution of the genetic code: the universal enigma

http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3293468/

In our opinion, despite extensive and, in many cases, elaborate attempts to model code optimization, ingenious theorizing along the lines of the coevolution theory, and considerable experimentation, very little definitive progress has been made.

Summarizing the state of the art in the study of the code evolution, we cannot escape considerable skepticism. It seems that the two-pronged fundamental question: “why is the genetic code the way it is and how did it come to be?”, that was asked over 50 years ago, at the dawn of molecular biology, might remain pertinent even in another 50 years. Our consolation is that we cannot think of a more fundamental problem in biology.


The specified complexity of amino acid sequencing

http://www.evidenceunseen.com/articles/science-and-scripture/the-origin-of-life/

In order to have a functional protein, we need a specific order  of amino acids—not just any old arrangement. Meyer writes,

In some cases, changing even one amino acid at a given site results in the loss of protein function. Moreover, because there are 20 biologically occurring amino acids, the probability of getting a specific amino acid at a given site is small—1/ 20.[34]

For every combination of amino acids that produces a functional protein there exists a vast number of other possible combinations that do not… Even a relatively short protein of, say, 150 amino acids represents one sequence among an astronomically large number of other possible sequence combinations (approximately 10^195).

On the assumption that each site in a protein chain requires a particular amino acid, the probability of attaining a particular protein 150 amino acids long would be (1/ 20) 150, or roughly 1 chance in 10^195.

If we do not assume that each amino acid needs to be specified (and some variance is allowed), this figure drops. Biochemist Robert Sauer (and is MIT team) determined that even with variance the figures are still astronomical (10^63) for a 100 amino acid string. Other researchers—like Douglas Axe—have determined that 10^77 is a better figure. When all of this is combined, Meyer concludes, “The odds of getting even one functional protein of modest length (150 amino acids) by chance from a prebiotic soup is no better than 1 chance in 10^164.” This is why atheist Francis Crick (discoverer of DNA) writes, “The origin of life appears to be almost a miracle, so many are the conditions which would have had to be satisfied to get it going.”

The Hypothesis that the Genetic Code Originated in Coupled Synthesis of Proteins and the Evolutionary Predecessors of Nucleic Acids in Primitive Cells.

http://www.ncbi.nlm.nih.gov/pubmed/25679748

nucleic acids are highly complicated polymers requiring numerous enzymes for biosynthesis. Secondly, proteins have a simple backbone with a set of 20 different amino acid side chains synthesized by a highly complicated ribosomal process in which mRNA sequences are read in triplets. Apparently, both nucleic acid and protein syntheses have extensive evolutionary histories. Supporting these processes is a complex metabolism and at the hub of metabolism are the carboxylic acid cycles.


Abiotic Synthesis of Organic Molecules

http://users.rcn.com/jkimball.ma.ultranet/BiologyPages/A/AbioticSynthesis.html

As for the first problem, four scenarios have been proposed.

Organic molecules
were synthesized from inorganic compounds in the atmosphere;
rained down on earth from outer space;
were synthesized at hydrothermal vents on the ocean floor;
were synthesized when comets or asteroids struck the early earth.

Assembling Polymers

Another problem is how polymers — the basis of life itself — could be assembled.

In solution, hydrolysis of a growing polymer would soon limit the size it could reach.
Abiotic synthesis produces a mixture of L and D enantiomers. Each inhibits the polymerization of the other. (So, for example, the presence of D amino acids inhibits the polymerization of L amino acids (the ones that make up proteins here on earth).

An RNA Beginning?

All metabolism depends on enzymes and, until recently, every enzyme has turned out to be a protein. But proteins are synthesized from information encoded in DNA and translated into mRNA. So here is a chicken-and-egg dilemma. The synthesis of DNA and RNA requires proteins. So proteins cannot be made without nucleic acids and nucleic acids cannot be made without proteins.

The discovery that certain RNA molecules have enzymatic activity provides a possible solution. These RNA molecules — called ribozymes — incorporate both the features required of life:storage of information
the ability to act as catalysts

http://www.evolutionnews.org/2012/07/with_new_resear061911.html

DNA and information – the Darwinist’s nightmare


DNA and information

Information is neither matter nor energy. It is metaphysical by nature. It is not sugars and enzymes.Information is something other than the matter that contains it. As such, ”Complex Coded Information” (CCI) is something the standard macro-evolutionary theory cannot explain. Where does the information come from?
We call it the genetic code. The very word ”code” implies an symbolic convention created for a specific purpose. The genetic code is such. It has semantics, syntax, pragmatics and is constrained to those rules. It also has exception trapping mechanisms built in.
As a written language is a set of symbols to which meaning has been assigned by some intelligence, and as a spoken language is a set of symbolic sounds to which meaning has been assigned by intelligent originiators, so DNA, as a Complex Coded Information System (CCIS), must necessarily have been originated by some intelligence.
Nature, by default, has no intelligence and so cannot itself be the origin of the genetic code. Therefore, some other intelligence must be responsible for it’s existence. Coded information systems, such as language, do not arise in nature by itself. There is in fact no such thing as a language coming into existence without some intelligent entities ‘inventing’ it.
That it is very brief view of how the Intelligent Design theory looks at the information problem for neo-Darwinian evolutionary theory.
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DNA is a complex coded information system (CCIS)
Dr. Gitt’s laws of information – Gitt, Werner, 1997.
I know that Gitt’s work, while extensive and in fact rather exhaustive, is not yet complete and no doubt contains some errors or unknowns as nearly all scientific theories do. Yet it “holds water”.
Coded information obeys fundamental laws of nature which, in summarized form, can be expressed as follows:

• It is impossible to set up, store, or transmit information without using a code.
  
  
• It is impossible to have a code apart from a free and deliberate convention.
  
  
• It is impossible to have information without a sender.
  
  
• It is impossible that information can exist without having had a mental source.
  
  
• It is impossible for information to exist without having been established voluntarily by a free will.
  
  
• It is impossible for information to exist without all five hierarchical levels: statistics, syntax, semantics, pragmatics, and apobetics [the purpose for which the information is intended, from the Greek apobeinon = result, success, conclusion].
  
  
• It is impossible that information can originate in statistical processes.
  

Careful analysis shows again and again that the process: sender codes a message – receiver decodes and uses the intended information, does not arise without the active involvement of a living intelligence at some point.- Dr. Royal Truman

Yes I know some attempts have been made to refute Truman’s paper on Information as well as Dr. Gitt’s research – talkorigins of course – who else? They basically rant on his differences with Shannon’s information theory and then wander off on poorly reasoned “rebuttals” with very little real content. Gitt’s work is extensive and cannot be shrugged off so easily as that.
From what I’ve read thus far, all opponents of Gitt’s ideas avoid the basic problem. Information does not exist in sugars and enzymes per se. Intelligence always ends up being assumed somewhere in the argument.
Given the above information, it is easy to see why neo-Darwinism fails from the start.
The source of the information contained in DNA, with it’s data transfer protocols, coding protocols and error-control protocols cannot be natural. It requires intelligently designed protocols embedded into the very framework itself.
Communications protocols do not arise from nothing. The very term protocol implies communication conventions between two communicating entities. This intelligence is involved. Amongst humans at this time, TCP/IP (the communications protocol used for Internet and computer comm) is the most widely used, without which no such blogs or web sites would work.
The information travels the physical lines using TCP to insure correct data transfer from source to destination. Checksum algorithms are applied to insure error free messages.
Information in DNA also has transmission and error checking protocols used as well as the translation mechanisms of RNA. These, by default, cannot be acquired in mere matter. They must be designed.Error can never be detected without an obligatorily preceeding knowledge or convention on what is correct.
In computers we use binary coded information to make them work. 0’s and 1’s do a good job for use so far, but they are still limited. DNA does not use binary code. And so in that sense, standard information theory is insufficient for such systems.
DNA uses a 4 letter code ATGC. (A), thymine (T), guanine (G) and cytosine (C). RNA is (A,C,G,Uracil) This code base is far more effecient than binary for the transfer and use of biological information. This code base provides for frame shifts as well, such as the right-left shifts applicable to say, bytes or word sequences, in binary code.
There are three major types of RNA: 1) mRNA, messenger-RNA, which transfer the information about the aminoacid sequence from the DNA to the protein synthesis. 2) rRNA, ribosomal-RNA, which builds up the ribosome together with proteins. 3) tRNA, transfer-RNA, which transfers aminoacids to the ribosome for protein synthesis….
The translation process is the synthesis of proteins directed by a mRNA template. The information contained in the nucleotide sequence of the mRNA is read as three letter words (triplets), calledcodons. Each word stands for one amino acid.
see : http://nobelprize.org/chemistry/educational/dna/index.html
The complexity involed in all of this is mindboggling. Or as one molecular biologist put it, “genius beyond genius”.
Dr. Royal Truman (Ph.D., specializing in organic chemistry), basing some of his analysis on Gitt, adds the following :

1. Information is more than the physical coding used to represent it. The sender and receiver must agree in advance on conventions to represent whatever is to be communicated in the future.
2. Information exchange requires that the frame of reference or context be agreed to in advance.
3. Random processes cannot generate coded information; rather, they only reflect the underlying mechanistic and probabilistic properties of the components which created that physical arrangement.
4. Information efficiency may be denser than implied by Shannon’s log2(n) equation, since a common basis of understanding exists between sender and receiver, often allowing implications with various degrees of certainty to be assumed by both parties, in addition to the raw data of the message.
5. In addition to the data encoded in the physical message the intention of the original sender must be considered. An encoding system can be devised to ensure transmission accuracy or to avoid understanding by an unwanted party.
6. A message allows information to survive over time. Assuming that the physical medium is not destroyed, there is some flexibility as to when the receiver can interpret the information.
7. The underlying meaning of coded information is external to the mere nature and properties of the sender.
8. The physical medium upon which a message is encoded is subject to physical laws such as a natural trend towards increased entropy in the long run (and thereby loss of ncoded information which is dependent on a physical medium).
9. Information content of messages is more easily quantified in a comparative than absolute sense.

One simply cannot avoid the inherent necessity of intelligence in this. An intelligent Designer is absolutely required. It cannot be accomplished by blind, unguided, unpurposing, mindless, speechless nature by mere random mutations + “selection pressures” + millions of years.
Indeed, no one has yet shown anything near like a stepped sequence of mutations that could have built such a CCIS. So what do Darweenies say about this fact? Basically, “It’s ongoing research”. Of course it is. And after 100 years or so, it’s not gotten very far has it. ;-) Indeed, the more we discover, the more complex it gets. And the more complex it gets the less Darwinism suffices.
See : http://trueorigin.org/dawkinfo.asp for a far more complete analysis of the information problem – by Dr. Royal Truman

No accident: genetic codes freeze in error-correcting patterns of the standard genetic code 1

The standard genetic code poses a challenge in understanding the evolution of information processing at a fundamental level of biological organization. Genetic codes are generally coadapted with, or ‘frozen’ by, the protein-coding genes that they translate, and so cannot easily change by natural selection. Yet the standard code has a significantly non-random pattern that corrects common errors in the transmission of information in protein-coding genes. Because of the freezing effect and for other reasons, this pattern has been proposed not to be due to selection but rather to be incidental to other evolutionary forces or even entirely accidental. We present results from a deterministic population genetic model of code-message coevolution. We explicitly represent the freezing effect of genes on genetic codes and the perturbative effect of changes in genetic codes on genes. We incorporate characteristic patterns of mutation and translational error, namely, transition bias and positional asymmetry, respectively. Repeated selection over small successive changes
produces genetic codes that are substantially, but not optimally, error correcting. In particular, our model reproduces the error-correcting patterns of the standard genetic code. Aspects of our model and results may be applicable to the general problem of adaptation to error in other natural information-processing systems.


INFORMATION THEORY AND ERROR-CORRECTING CODES IN GENETICS AND BIOLOGICAL EVOLUTION 2

As semiotics itself, biosemiotics is concerned with semantics. On the other hand, the scientific study of communication engineering led to the development of information theory, which ignores semantics. For this reason, many biologists thought that it would be useless in their disciplines. It turns out however that problems of communication engineering are met in biology and thus can only properly be dealt with using information theory. As an important example, the faithful transmission of genetic information through the ages is a difficult problem which has been overlooked by biologists. Cumulated errors in the DNA molecule due to radiations and even to its own indeterminism as a quantum object actually perturb its communication through time. A simple information-theoretic computation shows that, contrary to the current belief, the genomic memory is ephemeral at the time scale of geology. The conventional template-replication paradigm is thus not tenable. According to a fundamental theorem of information theory, error-correcting codes can perform almost errorless communication provided certain conditions are met. Faithful conservation of genomes can thus be ensured only if they involve error-correcting codes. Then the genomes can be recovered with an arbitrarily small probability of error, provided the interval between successive generations is as short (at the time scale of geology) as to almost always avoid that the number of cumulated errors exceeds the correcting ability of the code

An error-correcting code framework for genetic sequence analysis 3

The conservation of genetic information through the ages can not be explained unless one assumes the existence of genomic error-correcting codes, our main hypothesis. Shielding by phenotypic membranes does not protect the genomes against radiations and their own quantum indeterminism. The cumulated errors then make the genomic memory ephemeral at the time scale of geology. Only means intrinsic to the genome itself, taking the form of error-correcting codes, can ensure the genome permanency. According to information theory, they can achieve reliable communication over unreliable channels, so paradoxical it may look, provided some conditions are met. The experience of communication engineers witnesses their high efficiency. As a subsidiary hypothesis, we assume moreover they take the form of `nested codes', i.e., that several codes are combined into a layered structure which results in an unequal protection: the older and more fundamental parts of the genomic information are better protected than more recent ones. Looking for how nature implements error-correcting codes, we are led to assume that they rely on the many physical, steric, chemical and linguistic constraints to which the DNA molecule and the proteins for which they code are subjected. Taking account of these constraints enables to regenerate the genome provided the number of accumulated errors remains less than the correcting ability of the code, i.e., after a short enough time. 



1) http://www.ncbi.nlm.nih.gov/pmc/articles/PMC1693064/pdf/12495519.pdf
2)http://www.ece.iit.edu/~biitcomm/research/references/Gerard%20Battail/Information%20theory%20and%20error%20correcting%20codes%20in%20genetics%20and%20biological%20evolution.%20Introduction%20to%20Biosemiotics.pdf
3) http://www.ece.iit.edu/~biitcomm/research/references/Elebeoba%20E.%20May/An%20error-correcting%20code%20framework%20for%20genetic%20sequence%20analysis.pdf