Elucidation of Codon Usage Signatures across the Domains of Life.

Abstract:

:Because of the degeneracy of the genetic code, multiple codons are translated into the same amino acid. Despite being "synonymous," these codons are not equally used. Selective pressures are thought to drive the choice among synonymous codons within a genome, while GC content, which is typically attributed to mutational drift, is the major determinant of variation across species. Here, we find that in addition to GC content, interspecies codon usage signatures can also be detected. More specifically, we show that a single amino acid, arginine, is the major contributor to codon usage bias differences across domains of life. We then exploit this finding and show that domain-specific codon bias signatures can be used to classify a given sequence into its corresponding domain of life with high accuracy. We then wondered whether the inclusion of codon usage codon autocorrelation patterns, which reflects the nonrandom distribution of codon occurrences throughout a transcript, might improve the classification performance of our algorithm. However, we find that autocorrelation patterns are not domain-specific, and surprisingly, are unrelated to tRNA reusage, in contrast to previous reports. Instead, our results suggest that codon autocorrelation patterns are a by-product of codon optimality throughout a sequence, where highly expressed genes display autocorrelated "optimal" codons, whereas lowly expressed genes display autocorrelated "nonoptimal" codons.

journal_name

Mol Biol Evol

authors

Novoa EM,Jungreis I,Jaillon O,Kellis M

doi

10.1093/molbev/msz124

subject

Has Abstract

pub_date

2019-10-01 00:00:00

pages

2328-2339

issue

10

eissn

0737-4038

issn

1537-1719

pii

5492082

journal_volume

36

pub_type

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