Coupling Between Protein Level Selection and Codon Usage Optimization in the Evolution of Bacteria and Archaea
David M. Kristensen,
Eugene V. Koonin
National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, Maryland, USA.
The relationship between the selection affecting codon usage and selection on protein sequences of orthologous genes in diverse groups of bacteria and archaea was examined by using the Alignable Tight Genome Clusters database of prokaryote genomes. The codon usage bias is generally low, with 57.5% of the gene-specific optimal codon frequencies (Fopt) being below 0.55. This apparent weak selection on codon usage contrasts with the strong purifying selection on amino acid sequences, with 65.8% of the gene-specific dN/dS ratios being below 0.1. For most of the genomes compared, a limited but statistically significant negative correlation between Fopt and dN/dS was observed, which is indicative of a link between selection on protein sequence and selection on codon usage. The strength of the coupling between the protein level selection and codon usage bias showed a strong positive correlation with the genomic GC content. Combined with previous observations on the selection for GC-rich codons in bacteria and archaea with GC-rich genomes, these findings suggest that selection for translational fine-tuning could be an important factor in microbial evolution that drives the evolution of genome GC content away from mutational equilibrium. This type of selection is particularly pronounced in slowly evolving, “high-status” genes. A significantly stronger link between the two aspects of selection is observed in free-living bacteria than in parasitic bacteria and in genes encoding metabolic enzymes and transporters than in informational genes. These differences might reflect the special importance of translational fine-tuning for the adaptability of gene expression to environmental changes. The results of this work establish the coupling between protein level selection and selection for translational optimization as a distinct and potentially important factor in microbial evolution.