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Selection limits and strategies.

C C Cockerham1, P M Burrows

  • 1Department of Statistics, North Carolina State University, Raleigh, North Carolina 27650.

Proceedings of the National Academy of Sciences of the United States of America
|January 1, 1980
PubMed
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Maximizing selection limits in finite populations involves truncating at the phenotypic distribution

Area of Science:

  • Quantitative genetics
  • Population genetics
  • Selection theory

Background:

  • Truncation selection is a key method for genetic improvement in finite populations.
  • Understanding selection limits is crucial for maximizing genetic gain.
  • Previous work by Kimura and Crow provides a foundation for selection limit analysis.

Purpose of the Study:

  • To analyze strategies for maximizing the ultimate limit to truncation selection for quantitative traits.
  • To determine optimal truncation points for various phenotypic distributions.
  • To explore sex-specific and mating strategies in dioecious and monoecious populations.

Main Methods:

  • Utilizing the formulation of Kimura and Crow for selection limit analysis.
  • Analyzing phenotypic distributions, including normal, unimodal symmetric, and skewed distributions.

Related Experiment Videos

  • Investigating optimal selection proportions based on distribution characteristics.
  • Examining sex-based selection and mating strategies in different population types.

    • Main Results:

    • The selection limit is maximized by truncating at the mode of the phenotypic distribution.
    • For symmetric distributions, 50% selection is optimal.
    • For skewed distributions, selection proportion depends on whether desired phenotypes are in the long or short tail.
    • Optimal strategies for dioecious and monoecious populations involve specific sex-based and mating approaches.

    Conclusions:

    • Truncation at the phenotypic mode maximizes selection limits.
    • Tailored selection proportions are necessary for skewed distributions.
    • Specific sex and mating strategies enhance selection limits in different population structures.