Integrating whole-genome resequencing data reveals adaptive selection signatures under extreme environments of goat populations in China.

With the increasing frequency of extreme weather events globally, livestock are facing ever-increasing demands for environmental adaptability. Some goat populations have demonstrated remarkable adaptability under long-term extreme environmental stress, and their genomes retain characteristic genetic imprints formed by adaptive evolution. This study integrated whole-genome resequencing data from 496 individuals from 29 endemic goat populations in China, along with data from 11 environmental factors. Through signal selection analysis and genome-environment association analysis, we identified 262 candidate genes associated with environmental adaptation. Subsequently, we screened Chinese goat populations in extreme environments based on environmental data. We used the FST and θπ methods to scan the genomes of these goat populations. In four extreme environments (high elevation, hot, and arid), 95, 74, and 162 candidate genes were identified, respectively. Based on research related to environmental adaptation, we found that genes such as FGF5, CAMK4, COL4A3BP, and CACNG4 may play important roles in goat adaptation to extreme environments. This study not only deepens our understanding of the evolutionary mechanisms of environmental adaptation in Chinese goats, but also provides important theoretical basis for goat stress resistance breeding and germplasm resource conservation.