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Selection response in finite populations

M Wei1, A Caballero, W G Hill

  • 1Institute of Cell, Animal and Population Biology, University of Edinburgh, United Kingdom.

Genetics
|December 1, 1996
PubMed
Summary
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This study presents formulae to predict genetic response to selection, considering factors like genetic drift and inbreeding. Accurate family selection enhances short-term gains but may reduce long-term response and mutation utilization.

Area of Science:

  • Quantitative Genetics
  • Animal Breeding
  • Population Genetics

Background:

  • Predicting genetic response is crucial for effective selection schemes.
  • Factors like genetic drift, linkage disequilibrium, and inbreeding impact response.
  • Understanding variance components is key to accurate predictions.

Purpose of the Study:

  • To derive formulae for predicting genetic response under various selection schemes.
  • To incorporate multiple factors influencing genetic gain.
  • To analyze the long-term implications of selection accuracy.

Main Methods:

  • Developed predictive formulae based on an infinitesimal genetic model.
  • Accounted for genetic drift, Bulmer effect, inbreeding depression, and common environmental variance.

Related Experiment Videos

  • Included initial segregating variance within families and mutational variance.

    • Main Results:

    • Cumulative response to selection (CRt) can be approximated using effective population size (Ne) and variance components.
    • Short-term response (R0) is influenced by selection accuracy, while long-term response depends on Ne, mutational variance, and selection parameters (beta).
    • High-accuracy family selection leads to larger short-term gains but less efficient long-term mutation utilization.

    Conclusions:

    • The derived formulae provide a framework for predicting genetic response.
    • Selection accuracy influences the trade-off between short-term and long-term genetic gains.
    • Optimizing selection schemes requires balancing immediate response with sustainable long-term progress and efficient resource utilization.