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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.

Type Journal
ISBN 1537-1719 (Electronic) 0737-4038 (Linking)
Authors Novoa, E. M.; Jungreis, I.; Jaillon, O.; Kellis, M.
Responsible Garvan Author Dr Eva Maria Novoa Pardo
Publisher Name MOLECULAR BIOLOGY AND EVOLUTION
Published Date 2019-05-20
Published Volume 36
Published Issue 10
Published Pages 2328-2339
Status Published in-print
DOI 10.1093/molbev/msz124
URL link to publisher's version https://www.ncbi.nlm.nih.gov/pubmed/31220870