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Genomic selection improves the possibility of applying multiple breeding programs in different environments.

M Slagboom1, M Kargo2, A C Sørensen1

  • 1Department of Molecular Biology and Genetics, Center for Quantitative Genetics and Genomics, Aarhus University, 8830 Tjele, Denmark.

Journal of Dairy Science
|July 22, 2019
PubMed
Summary

A joint breeding program (BP) for dairy cattle offers optimal genetic gain when the genetic correlation between environments is high. Genomic selection enhances genetic gain, even with environment-specific BPs, by facilitating genomic information exchange.

Keywords:
breeding strategydairy cowgenetic gaingenotype by environment interaction

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Area of Science:

  • Animal Breeding and Genetics
  • Genomics
  • Quantitative Genetics

Background:

  • Joint breeding programs (BP) can enhance genetic gain in dairy cattle across different environments, contingent on the genetic correlation (rg) between them.
  • The break-even correlation (rb) defines the threshold rg where a single joint BP yields equivalent genetic gain to two separate environment-specific BPs.
  • Genomic selection introduces new collaboration models, including the exchange of breeding animals and genomic information, impacting breeding strategies.

Purpose of the Study:

  • To determine the break-even correlation (rb) for joint breeding programs under genomic selection.
  • To quantify genetic gain losses associated with suboptimal breeding strategies.
  • To evaluate the influence of genomic data reliability, sample size, and environmental disparities on rb and overall genetic gain.
  • To ascertain the optimal breeding strategy from the perspective of individual environments.

Main Methods:

  • Simulated three breeding strategies: one joint BP, two environment-specific BPs with cross-environment bull selection, and two environment-specific BPs with within-environment bull selection.
  • Calculated the break-even correlation (rb) for genomic selection and compared it to traditional progeny-testing programs.
  • Assessed the impact of varying direct genomic value reliability, the number of genotyped animals, and environmental sizes on rb and genetic gain.
  • Analyzed genetic gain from the viewpoint of both large and small environments.

Main Results:

  • The break-even correlation (rb) was determined to be 0.65, comparable to progeny-testing programs at similar selection intensities.
  • Suboptimal breeding strategies resulted in a maximum genetic gain loss of 24%.
  • Increased reliability of direct genomic values and a larger number of genotyped candidates boosted genetic gain, with minimal impact on rb.
  • Environmental size disparity reduced rb by up to 0.10 points.
  • Large environments favored a single joint BP, while small environments benefited from it only at high rg.
  • Exchange of genomic information, even with restricted animal movement, increased genetic gain, particularly when rg was as low as 0.4.

Conclusions:

  • Genomic selection expands the feasibility of environment-specific breeding programs by enabling effective genomic information exchange.
  • The optimal breeding strategy is context-dependent, influenced by genetic correlation, environmental size, and the specific goals of each breeding entity.
  • Even with moderate genetic correlations, sharing genomic data can significantly improve genetic gain, offering flexibility in breeding program design.