scholarly journals Orientation of the Genetic Variance‐Covariance Matrix and the Fitness Surface for Multiple Male Sexually Selected Traits

2004 ◽  
Vol 163 (3) ◽  
pp. 329-340 ◽  
Author(s):  
Mark W. Blows ◽  
Stephen F. Chenoweth ◽  
Emma Hine
Keyword(s):  
Covariance Matrix ◽  
Genetic Variance ◽  
Sexually Selected Traits ◽  
Fitness Surface ◽  
Selected Traits ◽  
Multiple Male ◽  
Variance Covariance Matrix

scholarly journals Evolution of the additive genetic variance–covariance matrix under continuous directional selection on a complex behavioural phenotype

2015 ◽  
Vol 282 (1819) ◽  
pp. 20151119 ◽  
Author(s):  
Vincent Careau ◽  
Matthew E. Wolak ◽  
Patrick A. Carter ◽  
Theodore Garland
Keyword(s):  
Covariance Matrix ◽  
Adaptive Response ◽  
Genetic Variance ◽  
Environmental Changes ◽  
Wheel Running ◽  
Additive Genetic Variance ◽  
Phenotypic Selection ◽  
Directional Selection ◽  
Genetic Covariance ◽  
Variance Covariance Matrix

Given the pace at which human-induced environmental changes occur, a pressing challenge is to determine the speed with which selection can drive evolutionary change. A key determinant of adaptive response to multivariate phenotypic selection is the additive genetic variance–covariance matrix ( G ). Yet knowledge of G in a population experiencing new or altered selection is not sufficient to predict selection response because G itself evolves in ways that are poorly understood. We experimentally evaluated changes in G when closely related behavioural traits experience continuous directional selection. We applied the genetic covariance tensor approach to a large dataset ( n = 17 328 individuals) from a replicated, 31-generation artificial selection experiment that bred mice for voluntary wheel running on days 5 and 6 of a 6-day test. Selection on this subset of G induced proportional changes across the matrix for all 6 days of running behaviour within the first four generations. The changes in G induced by selection resulted in a fourfold slower-than-predicted rate of response to selection. Thus, selection exacerbated constraints within G and limited future adaptive response, a phenomenon that could have profound consequences for populations facing rapid environmental change.

scholarly journals Evolutionary rates for multivariate traits: the role of selection and genetic variation

2014 ◽  
Vol 369 (1649) ◽  
pp. 20130252 ◽  
Author(s):  
William Pitchers ◽  
Jason B. Wolf ◽  
Tom Tregenza ◽  
John Hunt ◽  
Ian Dworkin
Keyword(s):  
Evolutionary Biology ◽  
Genetic Architecture ◽  
Genetic Variance ◽  
Evolutionary Rates ◽  
Phenotypic Traits ◽  
Sexually Selected Traits ◽  
Rates Of Evolution ◽  
Selected Traits ◽  
Multivariate Traits

A fundamental question in evolutionary biology is the relative importance of selection and genetic architecture in determining evolutionary rates. Adaptive evolution can be described by the multivariate breeders' equation ( ), which predicts evolutionary change for a suite of phenotypic traits ( ) as a product of directional selection acting on them ( β ) and the genetic variance–covariance matrix for those traits ( G ). Despite being empirically challenging to estimate, there are enough published estimates of G and β to allow for synthesis of general patterns across species. We use published estimates to test the hypotheses that there are systematic differences in the rate of evolution among trait types, and that these differences are, in part, due to genetic architecture. We find some evidence that sexually selected traits exhibit faster rates of evolution compared with life-history or morphological traits. This difference does not appear to be related to stronger selection on sexually selected traits. Using numerous proposed approaches to quantifying the shape, size and structure of G , we examine how these parameters relate to one another, and how they vary among taxonomic and trait groupings. Despite considerable variation, they do not explain the observed differences in evolutionary rates.

scholarly journals Characterizing the evolution of genetic variance using genetic covariance tensors

2009 ◽  
Vol 364 (1523) ◽  
pp. 1567-1578 ◽  
Author(s):  
Emma Hine ◽  
Stephen F. Chenoweth ◽  
Howard D. Rundle ◽  
Mark W. Blows
Keyword(s):  
Genetic Variance ◽  
Natural Populations ◽  
Covariance Structure ◽  
Evolutionary Genetics ◽  
Geometric Framework ◽  
Genetic Covariance ◽  
Sexually Selected Traits ◽  
Selected Traits ◽  
Higher Order Tensors ◽  
The Individual

Determining how genetic variance changes under selection in natural populations has proved to be a very resilient problem in evolutionary genetics. In the same way that understanding the availability of genetic variance within populations requires the simultaneous consideration of genetic variance in sets of functionally related traits, determining how genetic variance changes under selection in natural populations will require ascertaining how genetic variance–covariance ( G ) matrices evolve. Here, we develop a geometric framework using higher-order tensors, which enables the empirical characterization of how G matrices have diverged among populations. We then show how divergence among populations in genetic covariance structure can then be associated with divergence in selection acting on those traits using key equations from evolutionary theory. Using estimates of G matrices of eight male sexually selected traits from nine geographical populations of Drosophila serrata , we show that much of the divergence in genetic variance occurred in a single trait combination, a conclusion that could not have been reached by examining variation among the individual elements of the nine G matrices. Divergence in G was primarily in the direction of the major axes of genetic variance within populations, suggesting that genetic drift may be a major cause of divergence in genetic variance among these populations.

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