Please use this identifier to cite or link to this item: https://doi.org/10.21256/zhaw-4732
Publication type: Article in scientific journal
Type of review: Peer review (publication)
Title: Accounting for programmed ribosomal frameshifting in the computation of codon usage bias indices
Authors: Garcia, Victor
Zoller, Stefan
Anisimova, Maria
DOI: 10.21256/zhaw-4732
10.1534/g3.118.200185
Published in: G3 - Genes, Genomes, Genetics
Volume(Issue): 8
Issue: 10
Page(s): 3173
Pages to: 3183
Issue Date: Oct-2018
Publisher / Ed. Institution: Genetics Society of America
ISSN: 2160-1836
Language: English
Subjects: Codon usage bias; Genetics; Molecular biology; Programmed ribosomal frameshifting; Translation efficiency hypothesis
Subject (DDC): 572: Biochemistry
Abstract: Experimental 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.
URI: https://digitalcollection.zhaw.ch/handle/11475/11537
Fulltext version: Published version
License (according to publishing contract): CC BY 4.0: Attribution 4.0 International
Departement: Life Sciences and Facility Management
Organisational Unit: Institute of Computational Life Sciences (ICLS)
Appears in collections:Publikationen Life Sciences und Facility Management

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Garcia, V., Zoller, S., & Anisimova, M. (2018). Accounting for programmed ribosomal frameshifting in the computation of codon usage bias indices. G3 - Genes, Genomes, Genetics, 8(10), 3173–3183. https://doi.org/10.21256/zhaw-4732
Garcia, V., Zoller, S. and Anisimova, M. (2018) ‘Accounting for programmed ribosomal frameshifting in the computation of codon usage bias indices’, G3 - Genes, Genomes, Genetics, 8(10), pp. 3173–3183. Available at: https://doi.org/10.21256/zhaw-4732.
V. Garcia, S. Zoller, and M. Anisimova, “Accounting for programmed ribosomal frameshifting in the computation of codon usage bias indices,” G3 - Genes, Genomes, Genetics, vol. 8, no. 10, pp. 3173–3183, Oct. 2018, doi: 10.21256/zhaw-4732.
GARCIA, Victor, Stefan ZOLLER und Maria ANISIMOVA, 2018. Accounting for programmed ribosomal frameshifting in the computation of codon usage bias indices. G3 - Genes, Genomes, Genetics. Oktober 2018. Bd. 8, Nr. 10, S. 3173–3183. DOI 10.21256/zhaw-4732
Garcia, Victor, Stefan Zoller, and Maria Anisimova. 2018. “Accounting for Programmed Ribosomal Frameshifting in the Computation of Codon Usage Bias Indices.” G3 - Genes, Genomes, Genetics 8 (10): 3173–83. https://doi.org/10.21256/zhaw-4732.
Garcia, Victor, et al. “Accounting for Programmed Ribosomal Frameshifting in the Computation of Codon Usage Bias Indices.” G3 - Genes, Genomes, Genetics, vol. 8, no. 10, Oct. 2018, pp. 3173–83, https://doi.org/10.21256/zhaw-4732.


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