Wang Wannian, Cai Ke, Fan Mengdan, Pang Zhixu, Pan Yangyang, Cheng Lifen, Qiao Liying, Wang Ruizhen, Liu Wenzhong, Liu Jianhua
Department of Animal Genetics, Breeding and Reproduction, College of Animal Science, Shanxi Agricultural University, Taigu, 030801, China.
Shanxi Animal Husbandry Technology Extension Service Center, Taiyuan, 030001, China.
BMC Genomics. 2025 Jun 2;26(1):553. doi: 10.1186/s12864-025-11743-2.
The frequent occurrence of extreme climate events globally has elevated the requirements for environmental adaptability in livestock and poultry. Some goat populations have shown strong adaptability in specific extreme environments, and their genomes often leave genetic traces of adaptive evolution. This study integrated global goat single nucleotide polymorphism (SNP) chip data and raster data of 11 environmental variables. We retained 162 native goat populations and analyzed the environmental data of their regions. We detected 23 candidate genes related to environmental adaptation using selection signal analysis and genome-environment association analysis. After that, we screened out goat populations in extreme environments based on environmental data. Then, we used three selection signal analysis methods (F, XPEHH and θπ methods) to detect the genomes of these goat populations. In four different extreme environments (high elevation, hot, cold, and arid), 91, 43, 21, and 115 candidate genes were identified, respectively. Combined with studies related to environmental adaptation, we found that genes such as GULP1, GPC5, GPC6, and PDE4D may play important roles in the adaptation of goats to extreme environments. This study provides new insights into the adaptive mechanism of goats in extreme environments and provides an important theoretical basis for goat breed improvement and stress resistance breeding. At the same time, these findings also provide a reference for the study of the adaptability of other livestock in extreme environments.
全球极端气候事件的频繁发生提高了畜禽对环境适应性的要求。一些山羊群体在特定的极端环境中表现出了很强的适应性,其基因组中往往留下了适应性进化的遗传痕迹。本研究整合了全球山羊单核苷酸多态性(SNP)芯片数据和11个环境变量的栅格数据。我们保留了162个本地山羊群体,并分析了它们所在地区的环境数据。我们通过选择信号分析和基因组-环境关联分析检测到23个与环境适应性相关的候选基因。之后,我们根据环境数据筛选出极端环境中的山羊群体。然后,我们使用三种选择信号分析方法(F、XPEHH和θπ方法)对这些山羊群体的基因组进行检测。在四种不同的极端环境(高海拔、炎热、寒冷和干旱)中,分别鉴定出91、43、21和115个候选基因。结合与环境适应性相关的研究,我们发现GULP1、GPC5、GPC6和PDE4D等基因可能在山羊适应极端环境中发挥重要作用。本研究为山羊在极端环境中的适应机制提供了新的见解,为山羊品种改良和抗逆育种提供了重要的理论依据。同时,这些发现也为其他家畜在极端环境中的适应性研究提供了参考。