Abstract
Codons that code for the same amino acid are often used with unequal frequencies. This phenomenon is termed codon bias. Here, we report a computational analysis of codon bias in yeast using experimental and theoretical genome-wide data. We show that the most used codons in highly expressed genes can be predicted by mRNA structural data and that the codon choice at each synonymous site within an mRNA is not random with respect to the local secondary structure. Because we also found that the folding stability of intron sequences is strongly correlated with codon bias and mRNA level, our results suggest that codon bias is linked to mRNA folding structure through a mechanism that, at least partially, operates before pre-mRNA splicing. Consistent with this, we report evidence supporting the adaptation of the tRNA pool to the codon profile of the most expressed genes rather than vice versa. We show that the correlation of codon usage with the gene expression level also includes the stop codons that are normally not decoded by aminoacyl-tRNAs. The results reported here are consistent with a role for transcriptional forces in driving codon usage bias via a mechanism that improves gene expression by optimizing mRNA folding structures.
Highlights
The DNA genomic regions that code for proteins are sequences of codons
Did evolution seize the opportunity to use different DNA sequences for coding a protein? Is it possible that under selective pressure, a finer genetic code, shaping the efficiency or accuracy of gene expression, evolved? This appears to be the case because codons that code for the same amino acid, called synonymous codons, are not used randomly and, for a wide variety of organisms, the shift from their equal use is correlated with the level of gene expression [1,2,3,4]
A comparative analysis of the correlation of codon usage with gene expression levels and GC-content should help to distinguish the relative contributions of selection and mutation in shaping codon bias
Summary
The DNA genomic regions that code for proteins are sequences of codons. Each codon is formed by three nucleotides and codes for one amino acid. The exact mechanisms that generate codon bias are poorly understood, a general theory of its causes, known as the mutation-selection-drift balance model, has been commonly acknowledged [5,6,7] This theory assumes that the high frequency of optimal synonymous codons is maintained by selection, whereas neutral mutational pressure and genetic drift allow the minor codons to maintain their low frequency. The coevolution of the tRNA pool and the codon usage of highly expressed genes is a major argument invoked to explain the translational selection hypothesis [4,14,15]. We propose a model in which, at least partially, codon bias of highly transcribed genes is the result of transcriptional and translational forces that act to improve gene expression by optimizing mRNA folding structures. The transcriptional and translational explanations of codon bias are not mutually exclusive, but the two processes can cooperate, consistent with the findings that both processes are modulated by mRNA secondary structures [16,17,18]
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