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Karl Giberson: Broken Genes Prove Evolution

In yesterday’s CNN blog evolutionist Karl Giberson bemoans the influence of religious thinking in beliefs about origins and then, in evolutionary typical fashion, hypocritically mandates evolution’s own religious beliefs.  Read more

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One Response to Karl Giberson: Broken Genes Prove Evolution

  1. JonathanM has a excellent article up on ENV, commenting on the ‘optimality’ of the 20 amino acid protein set found in life compared to 1 million randomly generated alternatives, and the inadequacy of chance and necessity to explain this ‘optimality’ that we have found for the amino acid set;

    Does Life Use a Non-Random Set of Amino Acids? – Jonathan M. – April 2011
    Excerpt: The authors compared the coverage of the standard alphabet of 20 amino acids for size, charge, and hydrophobicity with equivalent values calculated for a sample of 1 million alternative sets (each also comprising 20 members) drawn randomly from the pool of 50 plausible prebiotic candidates.

    The results?

    The authors noted that:

    …the standard alphabet exhibits better coverage (i.e., greater breadth and greater evenness) than any random set for each of size, charge, and hydrophobicity, and for all combinations thereof.


    Shannon Information – Channel Capacity – Perry Marshall – video

    “Because of Shannon channel capacity that previous (first) codon alphabet had to be at least as complex as the current codon alphabet (DNA code), otherwise transferring the information from the simpler alphabet into the current alphabet would have been mathematically impossible”
    Donald E. Johnson – Bioinformatics: The Information in Life

    Venter vs. Dawkins on the Tree of Life – and Another Dawkins Whopper – March 2011
    Excerpt:,,, But first, let’s look at the reason Dawkins gives for why the code must be universal:
    “The reason is interesting. Any mutation in the genetic code itself (as opposed to mutations in the genes that it encodes) would have an instantly catastrophic effect, not just in one place but throughout the whole organism. If any word in the 64-word dictionary changed its meaning, so that it came to specify a different amino acid, just about every protein in the body would instantaneously change, probably in many places along its length. Unlike an ordinary mutation…this would spell disaster.” (2009, p. 409-10)
    OK. Keep Dawkins’ claim of universality in mind, along with his argument for why the code must be universal, and then go here (linked site listing 23 variants of the genetic code).
    Simple counting question: does “one or two” equal 23? That’s the number of known variant genetic codes compiled by the National Center for Biotechnology Information. By any measure, Dawkins is off by an order of magnitude, times a factor of two.

    Deciphering Design in the Genetic Code
    Excerpt: When researchers calculated the error-minimization capacity of one million randomly generated genetic codes, they discovered that the error-minimization values formed a distribution where the naturally occurring genetic code’s capacity occurred outside the distribution. Researchers estimate the existence of 10 possible genetic codes possessing the same type and degree of redundancy as the universal genetic code. All of these codes fall within the error-minimization distribution. This finding means that of the 10 possible genetic codes, few, if any, have an error-minimization capacity that approaches the code found universally in nature.

    DNA – The Genetic Code – Optimal Error Minimization & Parallel Codes – Dr. Fazale Rana – video

    Nick Lane Takes on the Origin of Life and DNA – Jonathan McLatchie – July 2010
    Excerpt: It appears then, that the genetic code has been put together in view of minimizing not just the occurrence of amino acid substitution mutations, but also the detrimental effects that would result when amino acid substitution mutations do occur.

    Though the DNA code is found to be optimal from a error minimization standpoint, it is also now found that the fidelity of the genetic code, of how a specific amino acid is spelled, is far greater than had at first been thought:

    Synonymous Codons: Another Gene Expression Regulation Mechanism – September 2010
    Excerpt: There are 64 possible triplet codons in the DNA code, but only 20 amino acids they produce. As one can see, some amino acids can be coded by up to six “synonyms” of triplet codons: e.g., the codes AGA, AGG, CGA, CGC, CGG, and CGU will all yield arginine when translated by the ribosome. If the same amino acid results, what difference could the synonymous codons make? The researchers found that alternate spellings might affect the timing of translation in the ribosome tunnel, and slight delays could influence how the polypeptide begins its folding. This, in turn, might affect what chemical tags get put onto the polypeptide in the post-translational process. In the case of actin, the protein that forms transport highways for muscle and other things, the researchers found that synonymous codons produced very different functional roles for the “isoform” proteins that resulted in non-muscle cells,,, In their conclusion, they repeated, “Whatever the exact mechanism, the discovery of Zhang et al. that synonymous codon changes can so profoundly change the role of a protein adds a new level of complexity to how we interpret the genetic code.”,,,

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