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Amino acid compositions contribute to the proteins' evolution under the influence of their abundances and genomic GC content.


ABSTRACT: Inconsistent results on the association between evolutionary rates and amino acid composition of proteins have been reported in eukaryotes. However, there are few studies of how amino acid composition can influence evolutionary rates in bacteria. Thus, we constructed linear regression models between composition frequencies of amino acids and evolutionary rates for bacteria. Compositions of all amino acids can on average explain 21.5% of the variation in evolutionary rates among 273 investigated bacterial organisms. In five model organisms, amino acid composition contributes more to variation in evolutionary rates than protein abundance, and frequency of optimal codons. The contribution of individual amino acid composition to evolutionary rate varies among organisms. The closer the GC-content of genome to its maximum or minimum, the better the correlation between the amino acid content and the evolutionary rate of proteins would appear in that genome. The types of amino acids that significantly contribute to evolutionary rates can be grouped into GC-rich and AT-rich amino acids. Besides, the amino acid with high composition also contributes more to evolutionary rates than amino acid with low composition in proteome. In summary, amino acid composition significantly contributes to the rate of evolution in bacterial organisms and this in turn is impacted by GC-content.

SUBMITTER: Du MZ 

PROVIDER: S-EPMC5943316 | biostudies-literature | 2018 May

REPOSITORIES: biostudies-literature

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Amino acid compositions contribute to the proteins' evolution under the influence of their abundances and genomic GC content.

Du Meng-Ze MZ   Liu Shuo S   Zeng Zhi Z   Alemayehu Labena Abraham LA   Wei Wen W   Guo Feng-Biao FB  

Scientific reports 20180509 1


Inconsistent results on the association between evolutionary rates and amino acid composition of proteins have been reported in eukaryotes. However, there are few studies of how amino acid composition can influence evolutionary rates in bacteria. Thus, we constructed linear regression models between composition frequencies of amino acids and evolutionary rates for bacteria. Compositions of all amino acids can on average explain 21.5% of the variation in evolutionary rates among 273 investigated  ...[more]

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