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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...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2012
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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. |
format | Online Article Text |
id | pubmed-3527230 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2012 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
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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