Correlated mutations: a hallmark of phenotypic amino acid substitutions.

Point mutations resulting in the substitution of a single amino acid can cause severe functional consequences, but can also be completely harmless. Understanding what determines the phenotypical impact is important both for planning targeted mutation experiments in the laboratory and for analyzing n...

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Main Authors: Andreas Kowarsch, Angelika Fuchs, Dmitrij Frishman, Philipp Pagel
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2010-01-01
Series:PLoS Computational Biology
Online Access:http://europepmc.org/articles/PMC2940720?pdf=render
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spelling doaj-3b0c056dee614f6291a7df936982faa32020-11-25T01:45:19ZengPublic Library of Science (PLoS)PLoS Computational Biology1553-734X1553-73582010-01-01693307331410.1371/journal.pcbi.1000923Correlated mutations: a hallmark of phenotypic amino acid substitutions.Andreas KowarschAngelika FuchsDmitrij FrishmanPhilipp PagelPoint mutations resulting in the substitution of a single amino acid can cause severe functional consequences, but can also be completely harmless. Understanding what determines the phenotypical impact is important both for planning targeted mutation experiments in the laboratory and for analyzing naturally occurring mutations found in patients. Common wisdom suggests using the extent of evolutionary conservation of a residue or a sequence motif as an indicator of its functional importance and thus vulnerability in case of mutation. In this work, we put forward the hypothesis that in addition to conservation, co-evolution of residues in a protein influences the likelihood of a residue to be functionally important and thus associated with disease. While the basic idea of a relation between co-evolution and functional sites has been explored before, we have conducted the first systematic and comprehensive analysis of point mutations causing disease in humans with respect to correlated mutations. We included 14,211 distinct positions with known disease-causing point mutations in 1,153 human proteins in our analysis. Our data show that (1) correlated positions are significantly more likely to be disease-associated than expected by chance, and that (2) this signal cannot be explained by conservation patterns of individual sequence positions. Although correlated residues have primarily been used to predict contact sites, our data are in agreement with previous observations that (3) many such correlations do not relate to physical contacts between amino acid residues. Access to our analysis results are provided at http://webclu.bio.wzw.tum.de/~pagel/supplements/correlated-positions/.http://europepmc.org/articles/PMC2940720?pdf=render
collection DOAJ
language English
format Article
sources DOAJ
author Andreas Kowarsch
Angelika Fuchs
Dmitrij Frishman
Philipp Pagel
spellingShingle Andreas Kowarsch
Angelika Fuchs
Dmitrij Frishman
Philipp Pagel
Correlated mutations: a hallmark of phenotypic amino acid substitutions.
PLoS Computational Biology
author_facet Andreas Kowarsch
Angelika Fuchs
Dmitrij Frishman
Philipp Pagel
author_sort Andreas Kowarsch
title Correlated mutations: a hallmark of phenotypic amino acid substitutions.
title_short Correlated mutations: a hallmark of phenotypic amino acid substitutions.
title_full Correlated mutations: a hallmark of phenotypic amino acid substitutions.
title_fullStr Correlated mutations: a hallmark of phenotypic amino acid substitutions.
title_full_unstemmed Correlated mutations: a hallmark of phenotypic amino acid substitutions.
title_sort correlated mutations: a hallmark of phenotypic amino acid substitutions.
publisher Public Library of Science (PLoS)
series PLoS Computational Biology
issn 1553-734X
1553-7358
publishDate 2010-01-01
description Point mutations resulting in the substitution of a single amino acid can cause severe functional consequences, but can also be completely harmless. Understanding what determines the phenotypical impact is important both for planning targeted mutation experiments in the laboratory and for analyzing naturally occurring mutations found in patients. Common wisdom suggests using the extent of evolutionary conservation of a residue or a sequence motif as an indicator of its functional importance and thus vulnerability in case of mutation. In this work, we put forward the hypothesis that in addition to conservation, co-evolution of residues in a protein influences the likelihood of a residue to be functionally important and thus associated with disease. While the basic idea of a relation between co-evolution and functional sites has been explored before, we have conducted the first systematic and comprehensive analysis of point mutations causing disease in humans with respect to correlated mutations. We included 14,211 distinct positions with known disease-causing point mutations in 1,153 human proteins in our analysis. Our data show that (1) correlated positions are significantly more likely to be disease-associated than expected by chance, and that (2) this signal cannot be explained by conservation patterns of individual sequence positions. Although correlated residues have primarily been used to predict contact sites, our data are in agreement with previous observations that (3) many such correlations do not relate to physical contacts between amino acid residues. Access to our analysis results are provided at http://webclu.bio.wzw.tum.de/~pagel/supplements/correlated-positions/.
url http://europepmc.org/articles/PMC2940720?pdf=render
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