A genome-wide association study of the racing performance traits in Yili horses based on Blink and FarmCPU models.

Racing performance traits are the main indicators for evaluating the performance and value of sport horses. The aim of this study was to identify the key genes for racing performance traits in Yili horses by performing a genome-wide association study (GWAS). Breeding values for racing performance traits were calculated for Yili horses (n = 827) using an animal model. Genome-wide association analysis of racing performance traits in horses (n = 236) was carried out using the Blink, and FarmCPU models in GAPIT software, and genes within the significant regions were functionally annotated. The results of GWAS showed that a total of 24 significant SNP markers (P < 6.05 × 10) and 22 suggestive SNP markers (P < 1.21 × 10) were identified. Among them, the Blink associated 16 significant SNP loci and FarmCPU associated 12 significant SNP loci. A total of 127 candidate genes (50 significant) were annotated. Among these, CNTN6 (motor coordination), NIPA1 (neuronal development), and DCC (dopamine pathway maturation) may be the main candidate genes affecting speed traits. SHANK2 (neuronal synaptic regulation), ISCA1 (mitochondrial protein assembly), and KCNIP4 (neuronal excitability) may be the main candidate genes affecting ranking score traits. A common locus (ECA1: 22698579) was significantly associated with racing performance traits, and the function of the genes at this locus needs to be studied in depth. These findings will provide new insights into the detection and selection of genetic variants for racing performance and will help to accelerate the genetic improvement of Yili horses.