Whole-Genome Resequencing Analysis of Copy Number Variations Associated with Athletic Performance in Grassland-Thoroughbred - Wenqi Ding; Wendian Gong; Tugeqin Bou; Lin Shi; Yanan Lin; Xiaoyuan Shi; Zheng Li; Huize Wu; Manglai Dugarjaviin; Dongyi Bai (Animals)
Copy number variation (CNV) is an important source of genetic variation. However, studies utilizing whole-genome sequencing to investigate CNVs in horse populations and their effects on traits remain relatively limited. This study aims to address the lack of research on the impact of copy number variation (CNV) on racing performance in horse populations, providing new insights for locally bred racing breeds. We analyzed 60 offspring derived from the crossbreeding of Thoroughbred horses and Xilingol horses. These horses were temporarily named “Grassland-Thoroughbred” and were divided into two groups: 30 racing horses and 30 non-racing horses. A total of 89,527 CNVs were identified. After merging overlapping CNVs, 982 copy number variation regions (CNVRs) were recognized, among which the racing horse group (RH) had 29 unique CNVRs, while the non-racing horse group (NR) had 4 unique CNVRs. In addition, a total of 195 genes overlapping with CNVRs were identified. Transcriptomic analysis revealed 120 differentially expressed genes, with MTPN expressed in both CNVR-overlapping genes and mRNA. Both CNVR-overlapping genes and differentially expressed genes were enriched in the MAPK signaling pathway; CNV may affect gene expression through gene dosage effects or regulatory mechanisms. Using Vst statistical analysis, we further screened candidate CNVRs in autosomes that exceeded the 95% differentiation threshold between the RH and NR populations. Several key genes associated with energy metabolism and muscle function were identified, including AGT, IGFN1, IMMPL2, SLC41A3, AOX4, and ACAD11. These findings provide new insights into the genetic structural variation in racing performance and adaptability, fill the gap in CNV studies in the genomics of Grassland-Thoroughbred horses, and offer valuable genomic data for optimizing breeding strategies in native racing horse populations.