Document Detail


Multivariate QST-FST comparisons: a neutrality test for the evolution of the g matrix in structured populations.
MedLine Citation:
PMID:  18245845     Owner:  NLM     Status:  MEDLINE    
Abstract/OtherAbstract:
Neutrality tests in quantitative genetics provide a statistical framework for the detection of selection on polygenic traits in wild populations. However, the existing method based on comparisons of divergence at neutral markers and quantitative traits (Q(st)-F(st)) suffers from several limitations that hinder a clear interpretation of the results with typical empirical designs. In this article, we propose a multivariate extension of this neutrality test based on empirical estimates of the among-populations (D) and within-populations (G) covariance matrices by MANOVA. A simple pattern is expected under neutrality: D = 2F(st)/(1 - F(st))G, so that neutrality implies both proportionality of the two matrices and a specific value of the proportionality coefficient. This pattern is tested using Flury's framework for matrix comparison [common principal-component (CPC) analysis], a well-known tool in G matrix evolution studies. We show the importance of using a Bartlett adjustment of the test for the small sample sizes typically found in empirical studies. We propose a dual test: (i) that the proportionality coefficient is not different from its neutral expectation [2F(st)/(1 - F(st))] and (ii) that the MANOVA estimates of mean square matrices between and among populations are proportional. These two tests combined provide a more stringent test for neutrality than the classic Q(st)-F(st) comparison and avoid several statistical problems. Extensive simulations of realistic empirical designs suggest that these tests correctly detect the expected pattern under neutrality and have enough power to efficiently detect mild to strong selection (homogeneous, heterogeneous, or mixed) when it is occurring on a set of traits. This method also provides a rigorous and quantitative framework for disentangling the effects of different selection regimes and of drift on the evolution of the G matrix. We discuss practical requirements for the proper application of our test in empirical studies and potential extensions.
Authors:
Guillaume Martin; Elodie Chapuis; Jérôme Goudet
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Publication Detail:
Type:  Journal Article; Research Support, Non-U.S. Gov't     Date:  2008-02-03
Journal Detail:
Title:  Genetics     Volume:  180     ISSN:  0016-6731     ISO Abbreviation:  Genetics     Publication Date:  2008 Dec 
Date Detail:
Created Date:  2008-12-17     Completed Date:  2009-03-27     Revised Date:  2013-06-06    
Medline Journal Info:
Nlm Unique ID:  0374636     Medline TA:  Genetics     Country:  United States    
Other Details:
Languages:  eng     Pagination:  2135-49     Citation Subset:  IM    
Affiliation:
Département d'Ecologie et Evolution, Université de Lausanne, CH 1015 Lausanne, Switzerland. guillaume.martin@univ-montp2.fr
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MeSH Terms
Descriptor/Qualifier:
Computer Simulation
Evolution, Molecular*
Genetics, Population / methods*
Multivariate Analysis
Quantitative Trait, Heritable*
Selection, Genetic
Comments/Corrections

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