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PMID: 9732450 Published · ppublish English Journal Article

The genetic code is one in a million.

Journal of molecular evolution ·Vol. 47 ·No. 3 ·1998-09-00 ·Pages 238-48

Freeland SJ, Hurst LD

Abstract

Statistical and biochemical studies of the genetic code have found evidence of nonrandom patterns in the distribution of codon assignments. It has, for example, been shown that the code minimizes the effects of point mutation or mistranslation: erroneous codons are either synonymous or code for an amino acid with chemical properties very similar to those of the one that would have been present had the error not occurred. This work has suggested that the second base of codons is less efficient in this respect, by about three orders of magnitude, than the first and third bases. These results are based on the assumption that all forms of error at all bases are equally likely. We extend this work to investigate (1) the effect of weighting transition errors differently from transversion errors and (2) the effect of weighting each base differently, depending on reported mistranslation biases. 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 conclude not only that the natural genetic code is extremely efficient at minimizing the effects of errors, but also that its structure reflects biases in these errors, as might be expected were the code the product of selection.

MeSH Terms
Amino Acids Base Composition Codon Evolution, Molecular Genetic Code Models, Genetic Protein Biosynthesis Selection, Genetic
Chemicals
Amino Acids Codon
Authors & Affiliations
2 authors, click to expand affiliations / ORCID
Freeland S J
Department of Genetics, Downing Street, Cambridge CB2 3EH, UK. freeland@gen.cam.ac.uk
Hurst L D
Article Info
Journal
Journal of molecular evolution
Abbr.
J Mol Evol
ISSN
0022-2844
Published
1998-09-00
Pages
238-48
Language
English
Region
Germany
NLM ID
0360051
Subset
IM
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