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A general framework for marker-assisted selection.

Xin-Sheng Hu1

  • 1Department of Renewable Resources, 751 General Services Building, University of Alberta, Edmonton, AB, Canada T6G 2H1. xin-sheng.hu@ualberta.ca

Theoretical Population Biology
|March 27, 2007
PubMed
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Incorporating non-additive genetic effects into marker-assisted selection (MAS) can boost breeding program efficiency. Phenotype-based marker indices show the highest selection efficiency, especially when non-additive effects are detectable.

Area of Science:

  • Quantitative genetics
  • Plant breeding
  • Genomic selection

Background:

  • Marker-assisted selection (MAS) traditionally focuses on additive genetic effects.
  • Early studies suggested epistatic (non-additive) effects can improve short-term breeding efficiency.
  • Incorporating non-additive effects into MAS theory requires further development.

Purpose of the Study:

  • To extend selection theory for marker-assisted selection (MAS) to include both additive and non-additive genetic effects.
  • To analytically examine different marker indices based on genetic components.
  • To assess the impact of non-additive effects and organelle genomes on selection efficiency.

Main Methods:

  • Extension of Lande and Thompson's theory for MAS.
  • Analytical examination of four marker indices: phenotype-based, general combining ability (GCA)-based, and GCA with reciprocal effects-based.

Related Experiment Videos

  • Consideration of additive-by-additive effects and organelle genome markers.

    • Main Results:

    • Phenotype-based marker indices, incorporating all genetic effects, yield the highest selection efficiency.
    • Indices utilizing non-additive effects show improved efficiency over additive-only markers when transient non-additive effects are present.
    • Marker inclusion from organelle genomes can enhance efficiency, dependent on variance proportions.

    Conclusions:

    • MAS can be improved by including non-additive genetic effects, particularly using phenotype-based marker indices.
    • The magnitude of non-additive variances and their marker explanation are crucial for efficiency gains.
    • Sharing markers across different scoring methods does not improve selection efficiency.