Literature DB >> 20059364

The contribution of selection and genetic constraints to phenotypic divergence.

Stephen F Chenoweth1, Howard D Rundle, Mark W Blows.   

Abstract

Although divergent natural selection is common in nature, the extent to which genetic constraints bias evolutionary trajectories in its presence remains largely unknown. Here we develop a general framework to integrate estimates of divergent selection and genetic constraints to estimate their contributions to phenotypic divergence among natural populations. We apply these methods to estimates of phenotypic selection and genetic covariance from sexually selected traits that have undergone adaptive divergence among nine natural populations of the fly Drosophila serrata. Despite ongoing sexual selection within populations, differences in its direction among them, and genetic variance for all traits in all populations, divergent sexual selection only weakly resembled the observed pattern of divergence. Accounting for the influence of genetic covariance among the traits significantly improved the alignment between observed and predicted divergence. Our results suggest that the direction in which sexual selection generates divergence may depend on the pattern of genetic constraint in individual populations, ultimately restricting how sexually selected traits may diversify. More generally, we show how evolution is likely to proceed in the direction of major axes of genetic variance, rather than the direction of selection itself, when genetic variance-covariance matrices are ill conditioned and genetic variance is low in the direction of selection.

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Year:  2010        PMID: 20059364     DOI: 10.1086/649594

Source DB:  PubMed          Journal:  Am Nat        ISSN: 0003-0147            Impact factor:   3.926


  32 in total

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Authors:  Roi Holzman; David C Collar; Samantha A Price; C Darrin Hulsey; Robert C Thomson; Peter C Wainwright
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2.  Simultaneous Estimation of Additive and Mutational Genetic Variance in an Outbred Population of Drosophila serrata.

Authors:  Katrina McGuigan; J David Aguirre; Mark W Blows
Journal:  Genetics       Date:  2015-09-16       Impact factor: 4.562

3.  Characterizing the evolution of genetic variance using genetic covariance tensors.

Authors:  Emma Hine; Stephen F Chenoweth; Howard D Rundle; Mark W Blows
Journal:  Philos Trans R Soc Lond B Biol Sci       Date:  2009-06-12       Impact factor: 6.237

4.  Multivariate sexual selection in a rapidly evolving speciation phenotype.

Authors:  Kevin P Oh; Kerry L Shaw
Journal:  Proc Biol Sci       Date:  2013-05-01       Impact factor: 5.349

5.  Why does allometry evolve so slowly?

Authors:  David Houle; Luke T Jones; Ryan Fortune; Jacqueline L Sztepanacz
Journal:  Integr Comp Biol       Date:  2019-11-01       Impact factor: 3.326

6.  High evolutionary constraints limited adaptive responses to past climate changes in toad skulls.

Authors:  Monique Nouailhetas Simon; Fabio Andrade Machado; Gabriel Marroig
Journal:  Proc Biol Sci       Date:  2016-10-26       Impact factor: 5.349

7.  Accounting for Sampling Error in Genetic Eigenvalues Using Random Matrix Theory.

Authors:  Jacqueline L Sztepanacz; Mark W Blows
Journal:  Genetics       Date:  2017-05-05       Impact factor: 4.562

8.  Evidence that divergent selection shapes a developmental cline in a forest tree species complex.

Authors:  João Costa E Silva; Peter A Harrison; Robert Wiltshire; Brad M Potts
Journal:  Ann Bot       Date:  2018-06-28       Impact factor: 4.357

9.  Comparing G: multivariate analysis of genetic variation in multiple populations.

Authors:  J D Aguirre; E Hine; K McGuigan; M W Blows
Journal:  Heredity (Edinb)       Date:  2013-03-13       Impact factor: 3.821

10.  Physical and Linkage Maps for Drosophila serrata, a Model Species for Studies of Clinal Adaptation and Sexual Selection.

Authors:  Ann J Stocker; Bosco B Rusuwa; Mark J Blacket; Francesca D Frentiu; Mitchell Sullivan; Bradley R Foley; Scott Beatson; Ary A Hoffmann; Stephen F Chenoweth
Journal:  G3 (Bethesda)       Date:  2012-02-01       Impact factor: 3.154

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