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Artificial selection on phenotypically plastic traits.

M Kirkpatrick1, T Bataillon

  • 1Section of Integrative Biology, University of Texas, Austin 78712, USA. kirkp@mail.utexas.edu

Genetical Research
|February 26, 2000
PubMed
Summary
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This study introduces a quantitative genetic framework for analyzing reaction norms, enhancing artificial selection efficiency. The approach leverages environmental information for improved breeding strategies and selection responses.

Area of Science:

  • Quantitative genetics
  • Evolutionary biology
  • Animal breeding

Background:

  • Phenotypic plasticity is a key trait influenced by environmental variables like temperature and nutrition.
  • Understanding phenotypic plasticity can optimize artificial selection for improved traits.

Purpose of the Study:

  • To present a quantitative genetic theory for infinite-dimensional traits, specifically reaction norms.
  • To demonstrate how this framework can enhance the efficiency of artificial selection.

Main Methods:

  • Utilizing quantitative genetic theory for reaction norms.
  • Deriving a selection index for phenotypically plastic traits.
  • Reviewing methods for estimating genetic covariance functions.

Main Results:

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  • The proposed framework offers a natural approach to incorporating environmental effects into selection.
  • It is expected to improve selection responses compared to conventional methods.
  • An index for mass selection of plastic traits was derived.

Conclusions:

  • The reaction norm framework provides a powerful tool for improving artificial selection.
  • This approach can be extended to advanced breeding schemes like best linear unbiased prediction.
  • Efficient estimation of genetic covariance functions is crucial for this methodology.