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Genetic parameter estimates of performance traits in Iranian Thoroughbred race horses using a Bayesian approach
M Taned1, M B Zandi1, S Salek Ardestani1
1Department of Animal Science, Faculty of Agriculture, University of Zanjan, Zanjan, Iran; ZNU Equine Research Center, Faculty of Agriculture, University of Zanjan, Zanjan, Iran.
Background:
Race performance in Thoroughbred horses is influenced by both genetic and environmental factors. Understanding their genetic architecture is essential for designing effective breeding programs.
Objectives:
This study aimed to estimate genetic parameters and trends for key performance traits in Iranian Thoroughbred racehorses.
Methods:
Performance data, including race completion time (RCT), rank at the end of the competition (REC), and average speed (AS), were obtained from the Iranian Equestrian Federation (2002-2021). Pedigree data from 14,391 individuals were analyzed using CFC software. Genetic parameters were estimated using a Bayesian approach via Gibbs sampling with gibbs1f90 for continuous traits (RCT and AS) and thrgibbs1f90 for the categorical trait (REC).
Results:
Heritability estimates were moderate for RCT (0.25) and AS (0.23), and low for REC (0.09). Rider and date/race city effects contributed notably to variation in RCT and AS. Genetic trend analysis showed an unfavorable increase in RCT (0.15 s/year; p = 0.02) and a significant decline in AS (-0.02 m/s/year; p = 0.0001), while the genetic trend for REC was negligible (-0.0004; p = 0.94). Phenotypic trends did not follow the same direction, suggesting strong environmental influences masking genetic changes.
Conclusion:
RCT and AS showed moderate heritability, indicating potential for genetic selection, whereas REC was mainly influenced by environmental factors. Despite stable phenotypic performance, unfavorable genetic trends highlight the need to revise breeding strategies and enhance long-term genetic improvement in Iranian Thoroughbred racehorses.
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