Stop codons in bacteria are not selectively equivalent

Author:

Povolotskaya Inna S,Kondrashov Fyodor A,Ledda Alice,Vlasov Peter K

Abstract

Abstract Background The evolution and genomic stop codon frequencies have not been rigorously studied with the exception of coding of non-canonical amino acids. Here we study the rate of evolution and frequency distribution of stop codons in bacterial genomes. Results We show that in bacteria stop codons evolve slower than synonymous sites, suggesting the action of weak negative selection. However, the frequency of stop codons relative to genomic nucleotide content indicated that this selection regime is not straightforward. The frequency of TAA and TGA stop codons is GC-content dependent, with TAA decreasing and TGA increasing with GC-content, while TAG frequency is independent of GC-content. Applying a formal, analytical model to these data we found that the relationship between stop codon frequencies and nucleotide content cannot be explained by mutational biases or selection on nucleotide content. However, with weak nucleotide content-dependent selection on TAG, -0.5 < Nes < 1.5, the model fits all of the data and recapitulates the relationship between TAG and nucleotide content. For biologically plausible rates of mutations we show that, in bacteria, TAG stop codon is universally associated with lower fitness, with TAA being the optimal for G-content < 16% while for G-content > 16% TGA has a higher fitness than TAG. Conclusions Our data indicate that TAG codon is universally suboptimal in the bacterial lineage, such that TAA is likely to be the preferred stop codon for low GC content while the TGA is the preferred stop codon for high GC content. The optimization of stop codon usage may therefore be useful in genome engineering or gene expression optimization applications. Reviewers This article was reviewed by Michail Gelfand, Arcady Mushegian and Shamil Sunyaev. For the full reviews, please go to the Reviewers’ Comments section.

Publisher

Springer Science and Business Media LLC

Subject

Applied Mathematics,General Agricultural and Biological Sciences,General Biochemistry, Genetics and Molecular Biology,Modeling and Simulation,Ecology, Evolution, Behavior and Systematics,Immunology

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