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dc.contributor.authorGarcia, Victor-
dc.contributor.authorZoller, Stefan-
dc.contributor.authorAnisimova, Maria-
dc.date.accessioned2019-01-10T13:40:32Z-
dc.date.available2019-01-10T13:40:32Z-
dc.date.issued2018-
dc.identifier.urihttps://digitalcollection.zhaw.ch/handle/11475/14285-
dc.description.abstractExperimental evidence shows that synonymous mutations can have important consequences on genetic fitness. Many organisms display codon usage bias (CUB), where synonymous codons that are translated into the same amino acid appear with distinct frequency. Within genomes, CUB is thought to arise from selection for translational efficiency and accuracy, termed the translational efficiency hypothesis (TEH). Indeed, CUB indices correlate with protein expression levels, which is widely interpreted as evidence for translational selection. However, these tests neglect -1 programmed ribosomal frameshifting (-1 PRF), an important translational disruption effect found across all organisms of the tree of life. Genes that contain -1 PRF signals should cost more to express than genes without. Thus, CUB indices that do not consider -1 PRF may overestimate genes’ true adaptation to translational efficiency and accuracy constraints. Here, we first investigate whether -1 PRF signals do indeed carry such translational cost. We then propose two corrections for CUB indices for genes containing -1 PRF signals. We retest the TEH in Saccharomyces cerevisiae under these corrections. We find that the correlation between corrected CUB index and protein expression remains intact for most levels of uniform -1 PRF efficiencies, and tends to increase when these efficiencies decline with protein expression. We conclude that the TEH is strengthened and that -1 PRF events constitute a promising and useful tool to examine the relationships between CUB and selection for translation efficiency and accuracy.de_CH
dc.language.isoende_CH
dc.rightsLicence according to publishing contractde_CH
dc.subjectCodon Usage Biasde_CH
dc.subjectProgrammed ribosomal frameshiftingde_CH
dc.subjectGeneticsde_CH
dc.subjectProtein expressionde_CH
dc.subject.ddc572: Biochemiede_CH
dc.titleAccounting for programmed ribosomal frameshifting in the computation of codon usage bias indicesde_CH
dc.typeKonferenz: Posterde_CH
dcterms.typeTextde_CH
zhaw.departementLife Sciences und Facility Managementde_CH
zhaw.organisationalunitInstitut für Computational Life Sciences (ICLS)de_CH
zhaw.conference.detailsSymposium on Quantitative Network Biology, Kandersteg, 19-20 November 2018de_CH
zhaw.funding.euNode_CH
zhaw.originated.zhawYesde_CH
zhaw.publication.statusupdatedVersionde_CH
zhaw.publication.reviewKeine Begutachtungde_CH
zhaw.webfeedComputational Genomicsde_CH
zhaw.webfeedApplied Mathematical Biologyde_CH
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Garcia, V., Zoller, S., & Anisimova, M. (2018). Accounting for programmed ribosomal frameshifting in the computation of codon usage bias indices. Symposium on Quantitative Network Biology, Kandersteg, 19-20 November 2018.
Garcia, V., Zoller, S. and Anisimova, M. (2018) ‘Accounting for programmed ribosomal frameshifting in the computation of codon usage bias indices’, in Symposium on Quantitative Network Biology, Kandersteg, 19-20 November 2018.
V. Garcia, S. Zoller, and M. Anisimova, “Accounting for programmed ribosomal frameshifting in the computation of codon usage bias indices,” in Symposium on Quantitative Network Biology, Kandersteg, 19-20 November 2018, 2018.
GARCIA, Victor, Stefan ZOLLER und Maria ANISIMOVA, 2018. Accounting for programmed ribosomal frameshifting in the computation of codon usage bias indices. In: Symposium on Quantitative Network Biology, Kandersteg, 19-20 November 2018. Conference poster. 2018
Garcia, Victor, Stefan Zoller, and Maria Anisimova. 2018. “Accounting for Programmed Ribosomal Frameshifting in the Computation of Codon Usage Bias Indices.” Conference poster. In Symposium on Quantitative Network Biology, Kandersteg, 19-20 November 2018.
Garcia, Victor, et al. “Accounting for Programmed Ribosomal Frameshifting in the Computation of Codon Usage Bias Indices.” Symposium on Quantitative Network Biology, Kandersteg, 19-20 November 2018, 2018.


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