Identification of candidate genes for reproductive traits in Xinjiang sheep breeds based on genomic structural variation - Li, Jiaqi; Yiming, Sulaiman; Zheng, Wenxin; Wu, Weiwei; Bi, Jingdong; Li, Fengming; Zhu, Mengting (Frontiers in Veterinary Science, 2025)
Reproductive traits are among the most important economic characteristics in sheep farming. Structural variations (SVs) are extensively distributed across sheep genomes and can directly or indirectly affect gene expression through a variety of mechanisms, leading to phenotypic variation among individuals or breeds. In this study, we characterized genomic SVs and identified candidate genes related to germplasm traits in seven sheep breeds. Based on the genome sequences of 73 ewes, SVs were detected using Delly, Lumpy, and Manta software tools, and the results were integrated using SURVIVOR software, leading to the identification of 107,166 SVs. The proportions of deletions, duplications, insertions, inversions, and translocations were 48.39, 38.41, 6.96, 6.22, and 0.03%, respectively. Regarding SV distribution, the number of SVs per chromosome decreased with increasing chromosome number. Both shared and breed-specific SVs were identified, with the local Tuva sheep breed showing the highest number of breed-specific SVs. Principal component analysis and phylogenetic tree results revealed a close genetic relationship between Hammari and Kabashi sheep. Selection signal analysis, gene annotation, and enrichment analysis led to the identification of potential functional SVs associated with reproductive traits, including FSHR, ADCY5, and MTNR1A. Experimental validation confirmed the regulatory activity of key SVs and their associations with the expression of target genes. This work characterized SVs in seven sheep breeds, identified genes associated with reproductive traits, and preliminarily validated the regulatory relationships between these SVs and their target genes. These findings provide essential data to support the genetic improvement of local sheep breeds in Xinjiang.