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dc.contributor.authorNovoa Pardo, Eva Maria
dc.contributor.authorJungreis, Irwin
dc.contributor.authorJaillon, Olivier
dc.contributor.authorKellis, Manolis
dc.date.accessioned2021-01-27T21:40:31Z
dc.date.available2021-01-27T21:40:31Z
dc.date.issued2019-05
dc.identifier.issn0737-4038
dc.identifier.issn1537-1719
dc.identifier.urihttps://hdl.handle.net/1721.1/129590
dc.description.abstractPress on behalf of the Society for Molecular Biology and Evolution. 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.en_US
dc.description.sponsorshipHuman Frontier Science Program (Award LT000307/2013- L)en_US
dc.description.sponsorshipAustralian Research Council (Award DE170100506)en_US
dc.description.sponsorshipNIH (Grant R01 HG004037)en_US
dc.description.sponsorshipWellcome Trust (Grant U41 HG007234)en_US
dc.language.isoen
dc.publisherOxford University Press (OUP)en_US
dc.relation.isversionofhttp://dx.doi.org/10.1093/molbev/msz124en_US
dc.rightsCreative Commons Attribution 4.0 International licenseen_US
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/en_US
dc.sourceOxford University Pressen_US
dc.titleElucidation of Codon Usage Signatures across the Domains of Lifeen_US
dc.typeArticleen_US
dc.identifier.citationNovoa, Eva Maria et al. "Elucidation of Codon Usage Signatures across the Domains of Life." Molecular Biology and Evolution 36, 10 (May 2019): 2328–2339 © 2019 The Author(s)en_US
dc.contributor.departmentMassachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratoryen_US
dc.relation.journalMolecular Biology and Evolutionen_US
dc.eprint.versionFinal published versionen_US
dc.type.urihttp://purl.org/eprint/type/JournalArticleen_US
eprint.statushttp://purl.org/eprint/status/PeerRevieweden_US
dc.date.updated2021-01-05T18:16:42Z
dspace.orderedauthorsNovoa, EM; Jungreis, I; Jaillon, O; Kellis, Men_US
dspace.date.submission2021-01-05T18:16:47Z
mit.journal.volume36en_US
mit.journal.issue10en_US
mit.licensePUBLISHER_CC
mit.metadata.statusComplete


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