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. 2004 Nov;14(11):2279-86.
doi: 10.1101/gr.2896904. Epub 2004 Oct 12.

Codon usage bias from tRNA's point of view: redundancy, specialization, and efficient decoding for translation optimization

Eduardo P C Rocha  1
Affiliations

Codon usage bias from tRNA's point of view: redundancy, specialization, and efficient decoding for translation optimization

Eduardo P C Rocha. Genome Res. 2004 Nov.

Erratum in

  • Genome Res. 2004 Dec;14(12):2510

Abstract

The selection-mutation-drift theory of codon usage plays a major role in the theory of molecular evolution by explaining the co-evolution of codon usage bias and tRNA content in the framework of translation optimization. Because most studies have focused only on codon usage, we analyzed the tRNA gene pool of 102 bacterial species. We show that as minimal generation times get shorter, the genomes contain more tRNA genes, but fewer anticodon species. Surprisingly, despite the wide G+C variation of bacterial genomes these anticodons are the same in most genomes. This suggests an optimization of the translation machinery to use a small subset of optimal codons and anticodons in fast-growing bacteria and in highly expressed genes. As a result, the overrepresented codons in highly expressed genes tend to be the same in very different genomes to match the same most-frequent anticodons. This is particularly important in fast-growing bacteria, which have higher codon usage bias in these genes. Three models were tested to understand the choice of codons recognized by the same anticodons, all providing significant fit, but under different classes of genes and genomes. Thus, co-evolution of tRNA gene composition and codon usage bias in genomes seen from tRNA's point of view agrees with the selection-mutation-drift theory. However, it suggests a much more universal trend in the evolution of anticodon and codon choice than previously thought. It also provides new evidence that a selective force for the optimization of the translation machinery is the maximization of growth.

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Figures

Figure 1.
Figure 1.
(A) Number of tRNA genes per genome as a function of the bacterial optimal generation time. (B) Number of tRNA genes per genome as a function of codon usage bias given as the difference in ENC′ between the set of genes coding for ribosomal proteins (ENC′RP) and the whole genome (ENC′All). (C) Enrichment in G and T in the last codon position of twofold-degenerated amino acids in ribosomal proteins compared to the average genome (ΔGT) as a function of codon usage bias. ○, fast growers; •, slow growers (generation time >2.5 h).
Figure 2.
Figure 2.
Observed versus expected G+C composition of tRNA anticodons. Expected was computed using an update of the Muto and Osawa (1987) equations and is indicated by the black dashed main diagonal. The horizontal dashed line indicates the expected value if there was no change in G+C anticodon composition with genome G+C content. The linear regression of the observed data is shown as a solid black line (it has an R2 of 0.50 and a slope of 0.26, significantly different from 1 and 0, P < 0.001).
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