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The effects of linkage on comparative estimators of selection

BACKGROUND: A major goal of molecular evolution is to determine how natural selection has shaped the evolution of a gene. One approach taken by methods such as K( A )/K( S ) and the McDonald-Kreitman (MK) test is to compare the frequency of non-synonymous and synonymous changes. These methods, howev...

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Autores principales: Chan, Carmen HS, Hamblin, Steven, Tanaka, Mark M
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2013
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3828407/
https://www.ncbi.nlm.nih.gov/pubmed/24199711
http://dx.doi.org/10.1186/1471-2148-13-244
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author Chan, Carmen HS
Hamblin, Steven
Tanaka, Mark M
author_facet Chan, Carmen HS
Hamblin, Steven
Tanaka, Mark M
author_sort Chan, Carmen HS
collection PubMed
description BACKGROUND: A major goal of molecular evolution is to determine how natural selection has shaped the evolution of a gene. One approach taken by methods such as K( A )/K( S ) and the McDonald-Kreitman (MK) test is to compare the frequency of non-synonymous and synonymous changes. These methods, however, rely on the assumption that a change in frequency of one mutation will not affect changes in frequency of other mutations. RESULTS: We demonstrate that linkage between sites can bias measures of selection based on synonymous and non-synonymous changes. Using forward simulation of a Wright-Fisher process, we show that hitch-hiking of deleterious mutations with advantageous mutations can lead to overestimation of the number of adaptive substitutions, while background selection and clonal interference can distort the site frequency spectrum to obscure the signal for positive selection. We present three diagnostics for detecting these effects of linked selection and apply them to the human influenza (H3N2) hemagglutinin gene. CONCLUSION: Various forms of linked selection have characteristic effects on MK-type statistics. The extent of background selection, hitch-hiking and clonal interference can be evaluated using the diagnostic statistics presented here. The diagnostics can also be used to determine how well we expect the MK statistics to perform and whether one form of the statistic may be preferable to another.
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spelling pubmed-38284072013-11-20 The effects of linkage on comparative estimators of selection Chan, Carmen HS Hamblin, Steven Tanaka, Mark M BMC Evol Biol Research Article BACKGROUND: A major goal of molecular evolution is to determine how natural selection has shaped the evolution of a gene. One approach taken by methods such as K( A )/K( S ) and the McDonald-Kreitman (MK) test is to compare the frequency of non-synonymous and synonymous changes. These methods, however, rely on the assumption that a change in frequency of one mutation will not affect changes in frequency of other mutations. RESULTS: We demonstrate that linkage between sites can bias measures of selection based on synonymous and non-synonymous changes. Using forward simulation of a Wright-Fisher process, we show that hitch-hiking of deleterious mutations with advantageous mutations can lead to overestimation of the number of adaptive substitutions, while background selection and clonal interference can distort the site frequency spectrum to obscure the signal for positive selection. We present three diagnostics for detecting these effects of linked selection and apply them to the human influenza (H3N2) hemagglutinin gene. CONCLUSION: Various forms of linked selection have characteristic effects on MK-type statistics. The extent of background selection, hitch-hiking and clonal interference can be evaluated using the diagnostic statistics presented here. The diagnostics can also be used to determine how well we expect the MK statistics to perform and whether one form of the statistic may be preferable to another. BioMed Central 2013-11-07 /pmc/articles/PMC3828407/ /pubmed/24199711 http://dx.doi.org/10.1186/1471-2148-13-244 Text en Copyright © 2013 Chan 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
Chan, Carmen HS
Hamblin, Steven
Tanaka, Mark M
The effects of linkage on comparative estimators of selection
title The effects of linkage on comparative estimators of selection
title_full The effects of linkage on comparative estimators of selection
title_fullStr The effects of linkage on comparative estimators of selection
title_full_unstemmed The effects of linkage on comparative estimators of selection
title_short The effects of linkage on comparative estimators of selection
title_sort effects of linkage on comparative estimators of selection
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3828407/
https://www.ncbi.nlm.nih.gov/pubmed/24199711
http://dx.doi.org/10.1186/1471-2148-13-244
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