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Evolutionary potential of hidden genetic variation

Affiliation

  • 1 Linnaeus Centre for Bioinformatics, Biomedical Centre, Box 598, Uppsala University, SE-751 24 Uppsala, Sweden.
  • PMID: 18079017
  • DOI: 10.1016/j.tree.2007.09.014

Evolutionary potential of hidden genetic variation

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Authors

Affiliation

  • 1 Linnaeus Centre for Bioinformatics, Biomedical Centre, Box 598, Uppsala University, SE-751 24 Uppsala, Sweden.
  • PMID: 18079017
  • DOI: 10.1016/j.tree.2007.09.014

Abstract

The ability of a population to respond to natural or artificial selection pressures is determined by the genetic architecture of the selected trait. It is now widely acknowledged that a substantial part of genetic variability can be buffered or released as the result of complex genetic interactions. However, the impact of hidden genetic diversity on phenotypic evolution is still not clear. Here, we argue that a common term to describe the impact of hidden genetic variation on phenotypic change is needed and will help to provide new insights into the contribution of different components of genetic architectures to the evolvability of a character. We introduce the ‘genetic charge’ concept, to describe how the architecture of a trait can be ‘charged’ with potential for evolutionary change that can later be ‘discharged’ in response to selection.

The ability of a population to respond to natural or artificial selection pressures is determined by the genetic architecture of the selected trait. It is now widely acknowledged that a substantial part of genetic variability can be buffered or released as the result of complex genetic interactions. …

Evolutionary potential and constraints in wild populations

Céline Teplitsky

Matthew R. Robinson

Juha Merilä

This chapter asks: How can evolutionary potential be measured? The question is deceptively simple: whilst evolutionary potential is typically defined on a per-trait basis, it has become clear that the complex genetic architecture of quantitative traits requires other ways to quantify evolutionary potential and constraints. This chapter reviews knowledge about multivariate evolutionary potential in the wild and the extent to which genetic covariances, as summarized in the G-matrix, impact evolutionary trajectories of natural populations both in terms of rate and direction. In terms of constraints, genetic covariances among traits can slow down the rate of adaptation, and influence the direction of the response to selection. However, the constraints posed by genetic covariances are insurmountable only if G-matrices are stable. The chapter thus reviews firstly theoretical predictions about the stability of G in relation to selection, migration and drift, and secondly methods available to test differentiation among matrices. To date, a majority of studies imply conservatism of G-matrices; however, a couple of recent studies have revealed that differentiation of G-matrices among wild populations can also be very fast, especially during colonisation of new habitats. Furthermore, as an increasing number of methods have been proposed for comparing G-matrices, we assessed how these methods perform under different hypothetical scenarios. The chapter shows that limited statistical power could often lead to erroneous conclusion of matrix conservatism, suggesting caution is needed in interpreting the results of matrix comparisons. The chapter concludes by identifying areas in need of further research.

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This chapter asks: How can evolutionary potential be measured? The question is deceptively simple: whilst evolutionary potential is typically defined on a per-trait basis, it has become clear that the complex genetic architecture of quantitative traits requires other ways to quantify evolutionary potential and constraints. This chapter reviews knowledge about multivariate evolutionary potential in the wild and the extent to which genetic covariances, as summarized in the G-matrix, impact evolutionary trajectories of natural populations both in terms of rate and direction. In terms of constraints, genetic covariances among traits can slow down the rate of adaptation, and influence the direction of the response to selection. However, the constraints posed by genetic covariances are insurmountable only if G-matrices are stable. The chapter thus reviews firstly theoretical predictions about the stability of G in relation to selection, migration and drift, and secondly methods available to test differentiation among matrices. To date, a majority of studies imply conservatism of G-matrices; however, a couple of recent studies have revealed that differentiation of G-matrices among wild populations can also be very fast, especially during colonisation of new habitats. Furthermore, as an increasing number of methods have been proposed for comparing G-matrices, we assessed how these methods perform under different hypothetical scenarios. The chapter shows that limited statistical power could often lead to erroneous conclusion of matrix conservatism, suggesting caution is needed in interpreting the results of matrix comparisons. The chapter concludes by identifying areas in need of further research. ]]>