Whole-genome resequencing of Chinese indigenous sheep provides insight into the genetic basis underlying climate adaptation

IF 3.6 1区 农林科学 Q1 AGRICULTURE, DAIRY & ANIMAL SCIENCE
Meilin Jin, Huihua Wang, Gang Liu, Jian Lu, Zehu Yuan, Taotao Li, Engming Liu, Zengkui Lu, Lixin Du, Caihong Wei
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Abstract

Chinese indigenous sheep are valuable resources with unique features and characteristics. They are distributed across regions with different climates in mainland China; however, few reports have analyzed the environmental adaptability of sheep based on their genome. We examined the variants and signatures of selection involved in adaptation to extreme humidity, altitude, and temperature conditions in 173 sheep genomes from 41 phenotypically and geographically representative Chinese indigenous sheep breeds to characterize the genetic basis underlying environmental adaptation in these populations. Based on the analysis of population structure, we inferred that Chinese indigenous sheep are divided into four groups: Kazakh (KAZ), Mongolian (MON), Tibetan (TIB), and Yunnan (YUN). We also detected a set of candidate genes that are relevant to adaptation to extreme environmental conditions, such as drought-prone regions (TBXT, TG, and HOXA1), high-altitude regions (DYSF, EPAS1, JAZF1, PDGFD, and NF1) and warm-temperature regions (TSHR, ABCD4, and TEX11). Among all these candidate genes, eight ABCD4, CNTN4, DOCK10, LOC105608545, LOC121816479, SEM3A, SVIL, and TSHR overlap between extreme environmental conditions. The TSHR gene shows a strong signature for positive selection in the warm-temperature group and harbors a single nucleotide polymorphism (SNP) missense mutation located between positions 90,600,001 and 90,650,001 on chromosome 7, which leads to a change in the protein structure of TSHR and influences its stability. Analysis of the signatures of selection uncovered genes that are likely related to environmental adaptation and a SNP missense mutation in the TSHR gene that affects the protein structure and stability. It also provides information on the evolution of the phylogeographic structure of Chinese indigenous sheep populations. These results provide important genetic resources for future breeding studies and new perspectives on how animals can adapt to climate change.
中国土羊的全基因组重测序深入揭示了气候适应的遗传基础
中国土羊是独具特色的宝贵资源。它们分布在中国大陆不同气候的地区,然而,很少有报道根据羊的基因组分析其环境适应性。我们研究了来自 41 个具有表型和地理代表性的中国本土绵羊品种的 173 个绵羊基因组中参与适应极端湿度、海拔和温度条件的变异和选择特征,以确定这些种群环境适应性的遗传基础。根据种群结构分析,我们推断中国土羊分为四个群体:哈萨克羊(KAZ)、蒙古羊(MON)、藏羊(TIB)和云南羊(YUN)。我们还发现了一系列与适应极端环境条件相关的候选基因,如干旱地区(TBXT、TG和HOXA1)、高海拔地区(DYSF、EPAS1、JAZF1、PDGFD和NF1)和暖温地区(TSHR、ABCD4和TEX11)。在所有这些候选基因中,ABCD4、CNTN4、DOCK10、LOC105608545、LOC121816479、SEM3A、SVIL 和 TSHR 这 8 个基因在极端环境条件下有重叠。TSHR基因在暖温组中显示出强烈的正选择特征,其位于7号染色体90,600,001和90,650,001位之间的单核苷酸多态性(SNP)错义突变导致TSHR的蛋白质结构发生变化并影响其稳定性。对选择特征的分析发现了可能与环境适应有关的基因,以及影响TSHR基因蛋白质结构和稳定性的SNP错义突变。该研究还提供了中国本土绵羊种群系统地理结构演变的信息。这些结果为今后的育种研究提供了重要的遗传资源,也为动物如何适应气候变化提供了新的视角。
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来源期刊
Genetics Selection Evolution
Genetics Selection Evolution 生物-奶制品与动物科学
CiteScore
6.50
自引率
9.80%
发文量
74
审稿时长
1 months
期刊介绍: Genetics Selection Evolution invites basic, applied and methodological content that will aid the current understanding and the utilization of genetic variability in domestic animal species. Although the focus is on domestic animal species, research on other species is invited if it contributes to the understanding of the use of genetic variability in domestic animals. Genetics Selection Evolution publishes results from all levels of study, from the gene to the quantitative trait, from the individual to the population, the breed or the species. Contributions concerning both the biological approach, from molecular genetics to quantitative genetics, as well as the mathematical approach, from population genetics to statistics, are welcome. Specific areas of interest include but are not limited to: gene and QTL identification, mapping and characterization, analysis of new phenotypes, high-throughput SNP data analysis, functional genomics, cytogenetics, genetic diversity of populations and breeds, genetic evaluation, applied and experimental selection, genomic selection, selection efficiency, and statistical methodology for the genetic analysis of phenotypes with quantitative and mixed inheritance.
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