Whole-genome resequencing to investigate the genetic diversity and the molecular basis underlying key economic traits in indigenous sheep breeds adapted to hypoxic environments - Tian, Dehong; Han, Buying; Li, Xue; Pei, Quanbang; Zhou, Baicheng; Zhao, Kai (Frontiers in Veterinary Science, 2025)
Under the combined effects of long-term natural selection and artificial domestication, Tibetan sheep on the Qinghai-Tibet Plateau have evolved distinct ecotypes to survive extreme high-altitude conditions, including hypoxia, cold, and low oxygen levels. These ecotypic variations not only serve as an ideal model for studying plateau livestock adaptation but also harbor valuable genetic diversity. However, the lack of comprehensive genetic analyses on their adaptive and phenotypic traits has hindered the effective conservation and utilization of these resources. Using whole-genome resequencing, we systematically studied seven Tibetan sheep breeds, uncovering their genetic structure and diversity. Population analyses, including NJ and maximum likelihood trees, revealed clear genetic differentiation and migration patterns. Selective sweep analyses (Fst and θπ) identified hypoxia-related genes (DOCK8, IGF1R, JAK1, SLC47, TMTC2, and VPS13A) and wool color genes (TCF25, MITF, and MC1R). GWAS further detected candidate genes for body size traits (height, length, weight), enriched in cGMP-PKG, cAMP, and Hedgehog signaling pathways. Integrating GWAS and transcriptomics, we pinpointed key wool trait genes, including WNT16 (non-synonymous mutations), PRKCA, MAP3K8, MMP7, OVOL2 (intergenic SNPs), and COL7A1, KDM8, ZNF385D (intronic SNPs). Notably, HOX family transcription factors were found to critically regulate hair follicle development. These genetic markers offer promising targets for molecular breeding to enhance wool quality and adaptive traits. Our findings provide a genetic basis for understanding Tibetan sheep’s unique adaptations and production traits, supporting future breeding strategies and sustainable utilization of their genetic resources.