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Modeling coding-sequence evolution within the context of residue solvent accessibility

BACKGROUND: Protein structure mediates site-specific patterns of sequence divergence. In particular, residues in the core of a protein (solvent-inaccessible residues) tend to be more evolutionarily conserved than residues on the surface (solvent-accessible residues). RESULTS: Here, we present a mode...

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Detalles Bibliográficos
Autores principales: Scherrer, Michael P, Meyer, Austin G, Wilke, Claus O
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2012
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3527230/
https://www.ncbi.nlm.nih.gov/pubmed/22967129
http://dx.doi.org/10.1186/1471-2148-12-179
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author Scherrer, Michael P
Meyer, Austin G
Wilke, Claus O
author_facet Scherrer, Michael P
Meyer, Austin G
Wilke, Claus O
author_sort Scherrer, Michael P
collection PubMed
description BACKGROUND: Protein structure mediates site-specific patterns of sequence divergence. In particular, residues in the core of a protein (solvent-inaccessible residues) tend to be more evolutionarily conserved than residues on the surface (solvent-accessible residues). RESULTS: Here, we present a model of sequence evolution that explicitly accounts for the relative solvent accessibility of each residue in a protein. Our model is a variant of the Goldman-Yang 1994 (GY94) model in which all model parameters can be functions of the relative solvent accessibility (RSA) of a residue. We apply this model to a data set comprised of nearly 600 yeast genes, and find that an evolutionary-rate ratio ω that varies linearly with RSA provides a better model fit than an RSA-independent ω or an ω that is estimated separately in individual RSA bins. We further show that the branch length t and the transition-transverion ratio κ also vary with RSA. The RSA-dependent GY94 model performs better than an RSA-dependent Muse-Gaut 1994 (MG94) model in which the synonymous and non-synonymous rates individually are linear functions of RSA. Finally, protein core size affects the slope of the linear relationship between ω and RSA, and gene expression level affects both the intercept and the slope. CONCLUSIONS: Structure-aware models of sequence evolution provide a significantly better fit than traditional models that neglect structure. The linear relationship between ω and RSA implies that genes are better characterized by their ω slope and intercept than by just their mean ω.
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spelling pubmed-35272302013-01-03 Modeling coding-sequence evolution within the context of residue solvent accessibility Scherrer, Michael P Meyer, Austin G Wilke, Claus O BMC Evol Biol Research Article BACKGROUND: Protein structure mediates site-specific patterns of sequence divergence. In particular, residues in the core of a protein (solvent-inaccessible residues) tend to be more evolutionarily conserved than residues on the surface (solvent-accessible residues). RESULTS: Here, we present a model of sequence evolution that explicitly accounts for the relative solvent accessibility of each residue in a protein. Our model is a variant of the Goldman-Yang 1994 (GY94) model in which all model parameters can be functions of the relative solvent accessibility (RSA) of a residue. We apply this model to a data set comprised of nearly 600 yeast genes, and find that an evolutionary-rate ratio ω that varies linearly with RSA provides a better model fit than an RSA-independent ω or an ω that is estimated separately in individual RSA bins. We further show that the branch length t and the transition-transverion ratio κ also vary with RSA. The RSA-dependent GY94 model performs better than an RSA-dependent Muse-Gaut 1994 (MG94) model in which the synonymous and non-synonymous rates individually are linear functions of RSA. Finally, protein core size affects the slope of the linear relationship between ω and RSA, and gene expression level affects both the intercept and the slope. CONCLUSIONS: Structure-aware models of sequence evolution provide a significantly better fit than traditional models that neglect structure. The linear relationship between ω and RSA implies that genes are better characterized by their ω slope and intercept than by just their mean ω. BioMed Central 2012-09-12 /pmc/articles/PMC3527230/ /pubmed/22967129 http://dx.doi.org/10.1186/1471-2148-12-179 Text en Copyright ©2012 Scherrer et al.; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Scherrer, Michael P
Meyer, Austin G
Wilke, Claus O
Modeling coding-sequence evolution within the context of residue solvent accessibility
title Modeling coding-sequence evolution within the context of residue solvent accessibility
title_full Modeling coding-sequence evolution within the context of residue solvent accessibility
title_fullStr Modeling coding-sequence evolution within the context of residue solvent accessibility
title_full_unstemmed Modeling coding-sequence evolution within the context of residue solvent accessibility
title_short Modeling coding-sequence evolution within the context of residue solvent accessibility
title_sort modeling coding-sequence evolution within the context of residue solvent accessibility
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3527230/
https://www.ncbi.nlm.nih.gov/pubmed/22967129
http://dx.doi.org/10.1186/1471-2148-12-179
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