Genomic analysis of gaits and racing performance of the French trotter

The aim was to disentangle gait characteristics from other qualities needed for racing performances with a genomic analysis of French trotters (FT). A sample of 1,390 horses were recruited, from which 46% were genotyped with Illumina chip of 54,602 SNPs, 49% with Affymetrix chip of 670,806 SNPs and 586 had a completed questionnaire on trotting technique. Racing performances cover the period 1996 to 2018. There were 252,368 FT-born; 96,617 qualified and 83,962 which participated in a race. After quality control, 377,611 SNPs were retained and imputed. Questionnaire described trotting technique over 13 questions which were summarized, after principal component analysis in 3 traits: pacer, heavy trot/gallop and other defects. GWAS and genomic evaluation were performed using single-step approach. We found 25 QTL for racing performances and 9 for trotting technique. Only DMRT3 mutation was significant for both traits. To tend to pace avoid the defect at gallop and lead to a better early career for earnings, less percentage of disqualified races at all ages and more harness than under saddle career. This is the portrait of AA genotype at DMRT3. We found 5 other QTL, not linked to gait traits, which might improve selection of genetically independent performance traits of earnings per races and percentage of finished races. For only earnings at different ages and in under saddle or harness races, genomic evaluation remains the best way to predict performances.

Automated summary

The genomic analysis of French trotters aimed to isolate gait characteristics from other factors impacting racing performances. The study identified the significant impact of the DMRT3 mutation on both racing performance and trotting technique, with additional QTLs related to gait traits. Furthermore, the study highlighted additional QTLs unrelated to gait traits that could improve selection for independent performance traits like earnings and finishing rates. The findings underscore the importance of genomic evaluation in predicting horse racing performances, particularly in relation to earnings and race completion rates.