Integration of genomic information into sport horse breeding programs for optimization of accuracy of selection.

The study focuses on integrating genomic information in horse breeding programs to better select young riding horses. The researchers are trying to improve genetic gain by using these selection criteria which might ultimately reduce generation intervals.

Context and Objective

• The study addresses the need for reliable selection criteria for young riding horses, with the goal of optimizing accuracy of selection and decrease generation intervals. The concept explored is potential genetic gain achieved by incorporating genomic breeding values (GEBVs) into selection strategies for sport horse breeding programs.
• The objective of the research is to evaluate how these new selection strategies impact the accuracy of estimated breeding values for young horses, considering factors like single nucleotide polymorphism (SNP) genotype data and horse performance.

Methods and Scenarios

• The research team applied selection index theory to analyze relevant stages in horse breeding programs. They evaluated the impact of genomic data on the accuracy of breeding value estimates in different scenarios.
• The first scenario considered a low positive correlation (r(mg) = 0.5) between the breeding value estimated from SNP genotype against the actual true breeding value (accuracy of GEBV). This was examined for a low heritability trait (h(2) = 0.15) in a young horse with only information from both parents considered.
• The second scenario involved including ‘own performance’ as a conventional information source in the mentioned index, in addition to SNP information.

Findings and Significance

• The researchers found that incorporating genomic information could potentially double the accuracy of estimated breeding values from 0.27 to 0.54. Including a horse’s performance data, in combination with SNP, information could further increase this accuracy by 40%.
• This research is significant because it illustrates how genomic information can be utilized in decision-making early in a horse’s life, particularly in traits with low heritability. This could therefore help to improve genetic gain and reduce generation intervals in horse breeding programs.
• In another approach, the team also evaluated how utilizing different sources of breeding values (e.g. Estimated Breeding Values (EBVs) from different countries and GEBVs) into an overall index might impact accuracy when altering correlations between traits and accuracies of EBVs. This suggested that using multiple sources of breeding values could be beneficial.