Dissecting genomes of multiple yak populations: unveiling ancestry and high-altitude adaptation through whole-genome resequencing analysis.

IF 3.7 2区 生物学 Q2 BIOTECHNOLOGY & APPLIED MICROBIOLOGY BMC Genomics Pub Date : 2025-03-03 DOI:10.1186/s12864-025-11387-2
Sheikh Firdous Ahmad, Munish Gangwar, Amit Kumar, Amod Kumar, Mahesh Shivanand Dige, Girish Kumar Jha, Gyanendra Kumar Gaur, Triveni Dutt
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Abstract

The present study was undertaken to elucidate the population structure and differentiation of Indian yak from Chinese and wild cohorts on genome-wide scale by identifying the selection sweeps and genomic basis of their adaptation across different comparisons while analyzing whole genome sequencing (WGS) data using latest bioinformatics tools. The study included 105 individuals from three distinct yak populations i.e., Indian yak (n = 29); Chinese yak (n = 61) and wild yak (n = 15), hypothesized to be related along the evolutionary timescale. Efficient variant calling and quality control in GATK and PLINK programs resulted in around 1 million (1,002,970) high-quality (LD-independent) SNPs with an average genotyping rate of 96.55%. The PCA, ADMIXTURE and TREEMIX analysis revealed stratification of the yak groups into three distinct clusters. The empirical distribution pattern of minor allele frequency (MAF) of SNPs on genome-wide scale was also elucidated for three yak cohorts revealing unique distribution across five different bins. The selection signature analysis revealed candidate genes that are important for the adaptation of Indian yak against harsh environmental conditions in their habitats. Under iHS analysis, several genes were identified to be under selection pressure in Indian yak including ABCA12, EXOC1, JUNB, KLF1, PRDX2, NANOS3, RFX1, RFX2, and CACNG7. On the other hand, across population analysis revealed the genes like NR2F2, OSBPL10, CIDEC, WFIKKN2, ADCY, THSD7A, ADGRB3, TRPC1, VASH2, and ABHD5 to be part of selective sweeps under these comparisons. A total of 53 genes were found common between intra- and inter-population selection signature analysis of Indian yak. Notably, the genes harbouring the SNPs under selection pressure were significant for adaptation traits including lipidogenesis, energy metabolism, thermogenesis, hair follicle formation, oxidation-reduction reactions, hypoxia and reproduction. These genes may be evaluated as candidate genes for livestock adaptation to harsh environmental conditions and to further the research and application in the present era of climate change.

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解剖多个牦牛种群的基因组:通过全基因组重测序分析揭示祖先和高海拔适应。
本研究利用最新的生物信息学工具分析全基因组测序(WGS)数据,通过确定不同比较中印度牦牛的选择扫描和适应的基因组基础,在全基因组尺度上阐明印度牦牛与中国牦牛和野生牦牛的种群结构和分化。该研究包括来自三个不同牦牛种群的105只个体,即印度牦牛(n = 29);中国牦牛(n = 61)和野生牦牛(n = 15),假设在进化时间尺度上存在关联。在GATK和PLINK项目中,高效的变异调用和质量控制产生了大约100万个高质量(与ld无关)snp,平均基因分型率为96.55%。PCA、admix和TREEMIX分析显示,牦牛种群可分为3个不同的聚类。在三个牦牛群体中,snp的次要等位基因频率(minor allele frequency, MAF)在全基因组尺度上的经验分布模式也得到了阐明,揭示了它们在5个不同箱子中的独特分布。选择特征分析揭示了对印度牦牛适应其栖息地恶劣环境条件很重要的候选基因。通过his分析,确定了ABCA12、EXOC1、JUNB、KLF1、PRDX2、NANOS3、RFX1、RFX2和CACNG7等基因在印度牦牛中处于选择压力。另一方面,跨群体分析显示,在这些比较中,NR2F2、OSBPL10、CIDEC、WFIKKN2、ADCY、THSD7A、ADGRB3、TRPC1、VASH2和ABHD5等基因是选择性扫描的一部分。在对印度牦牛种群内和种群间选择特征分析中,共发现53个共有基因。值得注意的是,在选择压力下携带snp的基因在脂质生成、能量代谢、产热、毛囊形成、氧化还原反应、缺氧和生殖等适应性状中具有重要意义。这些基因可作为家畜适应恶劣环境条件的候选基因,在当前气候变化时代进一步研究和应用。
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来源期刊
BMC Genomics
BMC Genomics 生物-生物工程与应用微生物
CiteScore
7.40
自引率
4.50%
发文量
769
审稿时长
6.4 months
期刊介绍: BMC Genomics is an open access, peer-reviewed journal that considers articles on all aspects of genome-scale analysis, functional genomics, and proteomics. BMC Genomics is part of the BMC series which publishes subject-specific journals focused on the needs of individual research communities across all areas of biology and medicine. We offer an efficient, fair and friendly peer review service, and are committed to publishing all sound science, provided that there is some advance in knowledge presented by the work.
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