Early fixation of an optimal genetic code

The evolutionary forces that produced the canonical genetic code before the last universal ancestor remain obscure. One hypothesis is that the arrange ment of amino acid/codon assignments results from selection to minimize the effects of errors (e.g., mistranslation and mutation) on resulting protein s. If amino acid similarity is measured as polarity, the canonical code doe s indeed outperform most theoretical alternatives. However, this finding do es not hold for other amino acid properties, ignores plausible restrictions on possible code structure, and does not address the naturally occurring n onstandard genetic codes. Finally, other analyses have shown that significa ntly better code structures are possible. Here, we show that if theoretical ly possible code structures are limited to reflect plausible biological con straints, and amino acid similarity is quantified using empirical data of s ubstitution frequencies, the canonical code is at or very close to a global optimum for error minimization across plausible parameter space. This resu lt is robust to variation in the methods and assumptions of the analysis. A lthough significantly better codes do exist under some assumptions, they ar e extremely rare and thus consistent with reports of an adaptive code: prev ious analyses which suggest otherwise derive from a misleading metric. Howe ver, all extant, naturally occurring, secondarily derived, nonstandard gene tic codes do appear less adaptive. The arrangement of amino acid assignment s to the codons of the standard genetic code appears to be a direct product of natural selection for a system that minimizes the phenotypic impact of genetic error. Potential criticisms of previous analyses appear to be witho ut substance. That known variants of the standard genetic code appear less adaptive suggests that different evolutionary factors predominated before a nd after fixation of the canonical code. While the evidence for an adaptive code is clear, the process by which the code achieved this optimization re quires further attention.