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Simulation studies to optimize genomic selection in honey bees.

Richard Bernstein1,2, Manuel Du3, Andreas Hoppe3

  • 1Institute for Bee Research Hohen Neuendorf, Friedrich-Engels-Str. 32, 16540, Hohen Neuendorf, Germany. richard.bernstein@hu-berlin.de.

Genetics, Selection, Evolution : GSE
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Summary
This summary is machine-generated.

Genomic selection in honey bees requires careful breeding program design. Prioritizing phenotyped breeding queens (BQ) for genotyping and including drone-producing queens (DPQ) maximizes genetic gain and prediction accuracy.

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Area of Science:

  • Animal breeding and genetics
  • Apiculture genomics
  • Quantitative genetics

Background:

  • Genomic selection in honey bees is enabled by SNP chip completion.
  • Existing methods require adaptation for honey bee genetics and breeding infrastructure.
  • Drone-producing queens (DPQ) and breeding queens (BQ) have distinct roles in mating and phenotyping.

Purpose of the Study:

  • Evaluate different breeding program designs for initiating genomic selection in honey bees.
  • Adapt genomic breeding value estimation methods for honey bee specificities.
  • Assess the impact of reference population size and genotyping strategies on genetic gain.

Main Methods:

  • Conducted stochastic simulations to assess breeding value prediction accuracy.
  • Developed a modified genomic relationship matrix incorporating DPQ genotypes.
  • Tested various reference population sizes and annual genotyping numbers.
  • Allocated resources for reference population expansion versus genomic preselection of BQ and DPQ.

Main Results:

  • Genotyping 5000 phenotyped BQ increased prediction accuracy by up to 173%.
  • A minimum of 1000 genotyped queens per year is necessary to start a breeding program.
  • Optimal genetic gain was achieved by combining DPQ preselection with genotyping 10-20% of phenotyped BQ.
  • Maximum genetic gain per genotype requires over 2500 genotyped queens annually and preselection of all BQ and DPQ.

Conclusions:

  • Prioritize genotyping phenotyped BQ to build a robust reference population for effective genomic preselection.
  • Preselecting DPQ and incorporating their genotypes into the genomic relationship matrix maximizes genetic gain.
  • Developed genomic prediction methods are suitable for practical honey bee breeding programs.