A crossbred reference population can improve the response to genomic selection for crossbred performance

Area of Science:

• Animal Breeding and Genetics
• Quantitative Genetics
• Genomic Selection

Background:

• Crossbreeding goals should align with commercial crossbred performance, yet selection often focuses on purebred traits.
• Genomic selection (GS) models incorporating dominance effects can improve purebred selection for crossbred outcomes.
• Optimizing GS requires determining whether marker effects are best estimated from purebred or crossbred data.

Purpose of the Study:

• Compare selection response in crossbreds using purebred versus crossbred training populations in a simulated two-way crossbreeding program.
• Evaluate the impact of accounting for allele line origin in breeding value estimation for GS using crossbred phenotypes.

Main Methods:

• Simulated a two-way crossbreeding program with additive and dominance effects for a trait of interest.
• Animals were selected based on estimated breeding values for crossbred performance.
• Compared GS response using purebred vs. crossbred training data and considered allele origin in prediction models.

Main Results:

• Training on crossbred animals significantly increased selection response in crossbred offspring compared to purebred training.
• Using both crossbred phenotypes and genotypes yielded greater response than using only crossbred phenotypes or parent genotypes.
• Accounting for allele origin improved genomic prediction when parental lines were distantly related; ignoring it was better for closely related lines with small reference populations.

Conclusions:

• Training genomic selection models on crossbred genotypes and phenotypes enhances response in crossbreeding programs.
• Tracing allele origin in crossbreds improves genomic prediction accuracy, provided the reference population is large and parental lines are not closely related.