BACKGROUND:

Natural selection has traditionally been understood as a force responsible for pushing genes to states of higher translational efficiency, whereas lower translational efficiency has been explained by neutral mutation and genetic drift. We looked for evidence of directional selection resulting in increased unpreferred codon usage (and presumably reduced translational efficiency) in three divergent clusters of eukaryotic genomes using a simple optimal-codon-based metric (Kp/Ku).

RESULTS:

Here we show that for some genes natural selection is indeed responsible for causing accelerated unpreferred codon substitution, and document the scope of this selection. In Cryptococcus and to a lesser extent Drosophila, we find many genes showing a statistically significant signal of selection for unpreferred codon usage in one or more lineages. We did not find evidence for this type of selection in Saccharomyces. The signal of positive selection observed from unpreferred synonymous codon substitutions is coincident in Cryptococcus and Drosophila with the distribution of upstream open reading frames (uORFs), another genic feature known to reduce translational efficiency. Functional enrichment analysis of genes exhibiting low Kp/Ku ratios reveals that genes in regulatory roles are particularly subject to this type of selection.

CONCLUSION:

Through genome-wide scans, we find recent selection for unpreferred codon usage at approximately 1% of genetic loci in a Cryptococcus and several genes in Drosophila. Unpreferred codons can impede translation efficiency, and we find that genes with translation-impeding uORFs are enriched for this selection signal. We find that regulatory genes are particularly likely to be subject to selection for unpreferred codon usage. Given that expression noise can propagate through regulatory cascades, and that low translational efficiency can reduce expression noise, this finding supports the hypothesis that translational efficiency may be suppressed in some cases to reduce stochastic noise in gene expression.