title: The genetic code is one in a million.
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.
authors.affiliation: Department of Genetics, Downing Street, Cambridge CB2 3EH, UK. freeland@gen.cam.ac.uk
authors.forename: S J
authors.initials: SJ
authors.lastname: Freeland
authors.forename: L D
authors.initials: LD
authors.lastname: Hurst
mesh_terms: D000596:Amino Acids; D001482:Base Composition; D003062:Codon; D019143:Evolution, Molecular; D005815:Genetic Code; D008957:Models, Genetic; D014176:Protein Biosynthesis; D012641:Selection, Genetic
chemical_list: D000596:Amino Acids; D003062:Codon