Phenotypic Definition Influences Genetic Inference and Predictive Ability for Reining Performance in Quarter Horses Using Random Regression Models.

Reining performance is influenced by subjectivity and competition structure, challenging genetic evaluation. This study estimated genetic parameters for reining performance in Brazilian Quarter Horses using random regression models (RRM) and evaluated how alternative phenotypic definitions affect genetic inference and predictive ability. A dataset comprising 21,165 longitudinal records from 1603 horses was analyzed, comparing within-group rank (RANK) and Blom-transformed rank (BLOM). Model comparison indicated that cubic RRM provided the best fit for both phenotypes. Heritability estimates were low and age-dependent, ranging from 0.01 to 0.17 for RANK and from 0.06 to 0.23 for BLOM. Permanent environmental and rider effects accounted for substantial phenotypic variance. Genetic correlations were higher between adjacent ages and declined across distant ages. RANK showed greater additive genetic stability across ages and slightly higher theoretical accuracy for total EBV among selected stallions. In contrast, BLOM showed greater consistency for the combined additive genetic + permanent environmental component, stronger favorable genetic trends, and better LR-based predictive performance across several age classes. Overall, both rank-based phenotypes were useful and complementary for genetic evaluation of reining performance. BLOM showed modest advantages for several criteria, whereas RANK retained relevant information for representing relative competitive performance on the observed scale.