4.5 Article

Selection-driven cost-efficiency optimization of transcripts modulates gene evolutionary rate in bacteria

期刊

GENOME BIOLOGY
卷 19, 期 -, 页码 -

出版社

BMC
DOI: 10.1186/s13059-018-1480-7

关键词

Gene evolution; Synonymous codon use; Codon bias; Translational efficiency; Bacteria; Natural selection; Transcript optimization; Molecular evolution

资金

  1. Biotechnology and Biological Sciences Research Council (BBSRC) [BB/J014427/1]
  2. European Union's Horizon 2020 research and innovation programme [637765]
  3. European Research Council (ERC) [637765] Funding Source: European Research Council (ERC)

向作者/读者索取更多资源

Background: Most amino acids are encoded by multiple synonymous codons. However, synonymous codons are not used equally, and this biased codon use varies between different organisms. It has previously been shown that both selection acting to increase codon translational efficiency and selection acting to decrease codon biosynthetic cost contribute to differences in codon bias. However, it is unknown how these two factors interact or how they affect molecular sequence evolution. Results: Through analysis of 1320 bacterial genomes, we show that bacterial genes are subject to multi-objective selection-driven optimization of codon use. Here, selection acts to simultaneously decrease transcript biosynthetic cost and increase transcript translational efficiency, with highly expressed genes under the greatest selection. This optimization is not simply a consequence of the more translationally efficient codons being less expensive to synthesize. Instead, we show that transfer RNA gene copy number alters the cost-efficiency trade-off of synonymous codons such that, for many species, selection acting on transcript biosynthetic cost and translational efficiency act in opposition. Finally, we show that genes highly optimized to reduce cost and increase efficiency show reduced rates of synonymous and non-synonymous mutation. Conclusions: This analysis provides a simple mechanistic explanation for variation in evolutionary rate between genes that depends on selection-driven cost-efficiency optimization of the transcript. These findings reveal how optimization of resource allocation to messenger RNA synthesis is a critical factor that determines both the evolution and composition of genes.

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