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How much can the orientation of G's eigenvectors tell us about genetic constraints?

A key goal in evolutionary quantitative genetics is to understand how evolutionary trajectories are constrained by pleiotropic coupling among multiple traits. Because studying pleiotropic constraints directly at the molecular genetic level remains very difficult, several analytical approaches attemp...

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Detalles Bibliográficos
Autor principal: Berner, Daniel
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Blackwell Publishing Ltd 2012
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3433988/
https://www.ncbi.nlm.nih.gov/pubmed/22957186
http://dx.doi.org/10.1002/ece3.306
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author Berner, Daniel
author_facet Berner, Daniel
author_sort Berner, Daniel
collection PubMed
description A key goal in evolutionary quantitative genetics is to understand how evolutionary trajectories are constrained by pleiotropic coupling among multiple traits. Because studying pleiotropic constraints directly at the molecular genetic level remains very difficult, several analytical approaches attempt to draw conclusions about constraints by relating the orientation of the eigenvectors of the traits' (co)variance matrix to vectors of multivariate selection. On the basis of explicit models of genetic architecture, I here argue that the value of such approaches is greatly overestimated. The reason is that eigenvector orientation can be highly unstable and lack a biologically meaningful relationship with the underlying traits' genetic architecture. Genetic constraints are more profitably explored through experimental approaches avoiding the mathematical abstraction inherent in eigenanalysis.
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spelling pubmed-34339882012-09-06 How much can the orientation of G's eigenvectors tell us about genetic constraints? Berner, Daniel Ecol Evol Original Research A key goal in evolutionary quantitative genetics is to understand how evolutionary trajectories are constrained by pleiotropic coupling among multiple traits. Because studying pleiotropic constraints directly at the molecular genetic level remains very difficult, several analytical approaches attempt to draw conclusions about constraints by relating the orientation of the eigenvectors of the traits' (co)variance matrix to vectors of multivariate selection. On the basis of explicit models of genetic architecture, I here argue that the value of such approaches is greatly overestimated. The reason is that eigenvector orientation can be highly unstable and lack a biologically meaningful relationship with the underlying traits' genetic architecture. Genetic constraints are more profitably explored through experimental approaches avoiding the mathematical abstraction inherent in eigenanalysis. Blackwell Publishing Ltd 2012-08 2012-07-04 /pmc/articles/PMC3433988/ /pubmed/22957186 http://dx.doi.org/10.1002/ece3.306 Text en © 2012 Published by Blackwell Publishing Ltd. http://creativecommons.org/licenses/by/2.5/ Re-use of this article is permitted in accordance with the Creative Commons Deed, Attribution 2.5, which does not permit commercial exploitation.
spellingShingle Original Research
Berner, Daniel
How much can the orientation of G's eigenvectors tell us about genetic constraints?
title How much can the orientation of G's eigenvectors tell us about genetic constraints?
title_full How much can the orientation of G's eigenvectors tell us about genetic constraints?
title_fullStr How much can the orientation of G's eigenvectors tell us about genetic constraints?
title_full_unstemmed How much can the orientation of G's eigenvectors tell us about genetic constraints?
title_short How much can the orientation of G's eigenvectors tell us about genetic constraints?
title_sort how much can the orientation of g's eigenvectors tell us about genetic constraints?
topic Original Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3433988/
https://www.ncbi.nlm.nih.gov/pubmed/22957186
http://dx.doi.org/10.1002/ece3.306
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