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Multilevel Selection 2: Estimating the Genetic Parameters Determining Inheritance and Response to Selection


Reference:

Bijma, P., Muir, W. M., Ellen, E. D., Wolf, J. B. and Van Arendonk, J. A. M., 2007. Multilevel Selection 2: Estimating the Genetic Parameters Determining Inheritance and Response to Selection. Genetics, 175 (1), pp. 289-299.

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Official URL:

http://dx.doi.org/10.1534/genetics.106.062729

Abstract

Interactions among individuals are universal, both in animals and in plants and in natural as well as domestic populations. Understanding the consequences of these interactions for the evolution of populations by either natural or artificial selection requires knowledge of the heritable components underlying them. Here we present statistical methodology to estimate the genetic parameters determining response to multilevel selection of traits affected by interactions among individuals in general populations. We apply these methods to obtain estimates of genetic parameters for survival days in a population of layer chickens with high mortality due to pecking behavior. We find that heritable variation is threefold greater than that obtained from classical analyses, meaning that two-thirds of the full heritable variation is hidden to classical analysis due to social interactions. As a consequence, predicted responses to multilevel selection applied to this population are threefold greater than classical predictions. This work, combined with the quantitative genetic theory for response to multilevel selection presented in an accompanying article in this issue, enables the design of selection programs to effectively reduce competitive interactions in livestock and plants and the prediction of the effects of social interactions on evolution in natural populations undergoing multilevel selection.

Details

Item Type Articles
CreatorsBijma, P., Muir, W. M., Ellen, E. D., Wolf, J. B. and Van Arendonk, J. A. M.
DOI10.1534/genetics.106.062729
DepartmentsFaculty of Science > Biology & Biochemistry
RefereedYes
StatusPublished
ID Code18354

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