The Genetic Code Is One in a Million

  title={The Genetic Code Is One in a Million},
  author={Stephen J. Freeland and Laurence D. Hurst},
  journal={Journal of Molecular Evolution},
Abstract. [] Key Result We find that if the bias affects all codon positions equally, as might be expected were the code adapted to a mutational environment with transition/transversion bias, then any reasonable transition/transversion bias increases the relative efficiency of the second base by an order of magnitude. In addition, if we employ weightings to allow for biases in translation, then only 1 in every million random alternative codes generated is more efficient than the natural code. We thus…

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The model establishes a weighting scheme for mistranslation biases of the three different codon positions, transition/transversion biases, and codon usage that shows that the natural genetic code is not fully optimized for error minimization.

Optimality of the genetic code with respect to protein stability and amino-acid frequencies

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Early fixation of an optimal genetic code.

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Load minimization of the genetic code: history does not explain the pattern

  • S. FreelandL. Hurst
  • Biology
    Proceedings of the Royal Society of London. Series B: Biological Sciences
  • 1998
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Optimization of the standard genetic code according to three codon positions using an evolutionary algorithm

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An Alternative Look at Code Evolution: Using Non-canonical Codes to Evaluate Adaptive and Historic Models for the Origin of the Genetic Code

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Al Amino acids whose codons differed by a single base in the first and third codon positions were very similar with respect to polar requirement and hydropathy, which is most easily explained by selection to minimize deleterious effects of translation errors during the early evolution of the code.

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Wong's theory that the genetic code arose by coevolution with the biosynthetic pathways of amino acids, based on codon correlations between biosynthetically related amino acid, is statistical in nature.

The genetic code and error transmission.

  • C. Alff-Steinberger
  • Biology
    Proceedings of the National Academy of Sciences of the United States of America
  • 1969
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Rates of transition and transversion in coding sequences since the human-rodent divergence.

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    Progress in biophysics and molecular biology
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