A genomic prediction model for racecourse starts in the Thoroughbred horse.

The research paper discusses the development of a genetic prediction model to ascertain the potential for Thoroughbred horses to start in races. The study proves the hypothesis that traits of durability are inheritable while also exploring specific genes associated with this trait.

Heritability of Durability Traits

• The research group put forward two hypotheses: durability traits in Thoroughbred horses are heritable and genetic data could predict a horse’s potential to start a race.
• ‘Number of 2- and 3-year-old starts’ was selected as the phenotype; the heritability of this characteristic was measured and found to be 0.11 ± 0.02, indicating notable inherited traits. This was based on data from 4,499 horses.

Genomewide Association Study

• The researchers conducted a genome-wide association study to determine which Single Nucleotide Polymorphisms (SNPs) contributed to the trait.
• The study identified certain genes associated with the trait – the neurotrimin (NTM), opioid-binding protein/cell adhesion molecule like (OPCML), and prolylcarboxypeptidase (PRCP).
• NTM is involved in brain development and was shown to have an influential role during the domestication of the horse.
• PRCP has been identified experimentally as an expression quantitative trait locus that mediates the interaction between voluntary exercise and body composition in mice.
• The researchers proposed that the variation in these genes contributes to a horse’s motivation to exercise, affecting their response to training and racing.

Development and Validation of Prediction Model

• The research team designed a Random Forest with Mixed Effects (RFME) model, identifying a set of SNPs that contributed to 24.7% of the heritable variation in the trait.
• The model was validated using an independent validation set consisting of 528 horses.
• Data analysis revealed that groups with a high genetic potential for racing had a significantly smaller percentage of unraced horses (16%) as compared to groups with a low genetic potential for racing (27%).
• Additionally, the group with a high genetic potential for racing demonstrated better racing outcomes than the lower potential group amongst those that raced.
• The research thus concludes that the information from the SNPs included in the model can be used to predict the horses with a greater chance of starting at a racecourse effectively.