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全基因组扫描寻找选择印记揭示了控制萨希瓦尔牛牛奶成分和毛色性状的假定基因组区域和候选基因。

Genome-Wide Scanning for Signatures of Selection Revealed the Putative Genomic Regions and Candidate Genes Controlling Milk Composition and Coat Color Traits in Sahiwal Cattle.

作者信息

Illa Satish Kumar, Mukherjee Sabyasachi, Nath Sapna, Mukherjee Anupama

机构信息

Division of Animal Genetics and Breeding, Indian Council of Agricultural Research-National Dairy Research Institute, Karnal, India.

Artificial Breeding Research Center, Indian Council of Agricultural Research-National Dairy Research Institute, Karnal, India.

出版信息

Front Genet. 2021 Jul 9;12:699422. doi: 10.3389/fgene.2021.699422. eCollection 2021.

Abstract

BACKGROUND

In the evolutionary time scale, selection shapes the genetic variation and alters the architecture of genome in the organisms. Selection leaves detectable signatures at the genomic coordinates that provide clues about the protein-coding regions. Sahiwal is a valuable indicine cattle adapted to tropical environments with desirable milk attributes. Insights into the genomic regions under putative selection may reveal the molecular mechanisms affecting the quantitative and other important traits. To understand this, the present investigation was undertaken to explore signatures of selection in the genome of Sahiwal cattle using a medium-density genotyping INDUS chip.

RESULT

De-correlated composite of multiple selection signals (DCMS), which combines five different univariate statistics, was computed in the dataset to detect the signatures of selection in the Sahiwal genome. Gene annotations, Quantitative Trait Loci (QTL) enrichment, and functional analyses were carried out for the identification of significant genomic regions. A total of 117 genes were identified, which affect a number of important economic traits. The QTL enrichment analysis highlighted 14 significant [False Discovery Rate (FDR)-corrected -value ≤ 0.05] regions on chromosomes BTA 1, 3, 6, 11, 20, and 21. The top three enriched QTLs were found on BTA 6, 20, and 23, which are associated with exterior, health, milk production, and reproduction traits. The present study on selection signatures revealed some key genes related with coat color (, and ), facial pigmentation (), milk fat percent (, and ), sperm membrane integrity (), lactation persistency (, and ), milk yield ( and ), reproduction ( and ), and bovine tuberculosis susceptibility ( and ). Further analysis of candidate gene prioritization identified four hub genes, viz., , and , which play a role in coat color, facial pigmentation, and milk fat percentage in cattle. Gene enrichment analysis revealed significant Gene ontology (GO) terms related to breed-specific coat color and milk fat percent.

CONCLUSION

The key candidate genes and putative genomic regions associated with economic traits were identified in Sahiwal using single nucleotide polymorphism data and the DCMS method. It revealed selection for milk production, coat color, and adaptability to tropical climate. The knowledge about signatures of selection and candidate genes affecting phenotypes have provided a background information that can be further utilized to understand the underlying mechanism involved in these traits in Sahiwal cattle.

摘要

背景

在进化时间尺度上,选择塑造了生物体内的遗传变异并改变了基因组结构。选择在基因组坐标上留下可检测的特征,这些特征为蛋白质编码区域提供线索。 sahiwal牛是一种适应热带环境且具有优良乳品质的珍贵瘤牛品种。对假定选择下的基因组区域的深入了解可能揭示影响数量性状和其他重要性状的分子机制。为了弄清楚这一点,本研究采用中密度基因分型INDUS芯片,对sahiwal牛基因组中的选择特征进行了探索。

结果

在数据集中计算了结合五种不同单变量统计量的多重选择信号去相关复合体(DCMS),以检测sahiwal基因组中的选择特征。对显著基因组区域进行了基因注释、数量性状基因座(QTL)富集和功能分析。共鉴定出117个影响许多重要经济性状的基因。QTL富集分析突出了BTA 1、3、6,、11、20和21号染色体上的14个显著[错误发现率(FDR)校正P值≤0.05]区域。前三个富集的QTL位于BTA 6、20和23号染色体上,与外貌、健康、产奶和繁殖性状相关。本研究对选择特征的研究揭示了一些与毛色(、和)、面部色素沉着()、乳脂率(、和)、精子膜完整性()、泌乳持续性(、和)、产奶量(和)、繁殖(和)以及牛结核病易感性(和)相关的关键基因。对候选基因优先级的进一步分析确定了四个核心基因,即、和,它们在牛的毛色、面部色素沉着和乳脂率方面发挥作用。基因富集分析揭示了与品种特异性毛色和乳脂率相关的显著基因本体(GO)术语。

结论

利用单核苷酸多态性数据和DCMS方法,在sahiwal牛中鉴定出了与经济性状相关的关键候选基因和假定基因组区域。它揭示了对产奶、毛色和热带气候适应性的选择。关于选择特征和影响表型的候选基因的知识提供了背景信息,可进一步用于了解sahiwal牛这些性状的潜在机制。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c926/8299338/0eb3a88fcaab/fgene-12-699422-g001.jpg

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