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Genome-Wide Identification of Natural Selection Footprints in Bos Indicus Using Principal Component Analysis

机译：基于主成分分析的Bos Indicus自然选择足迹的全基因组识别

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Background: To describe natural selection, numerous analytical methods for ascertainingcandidate genomic region have been developed. There is a substantial drive in populationgenomics to identify loci intricate in local adaptation. A potent method to find genomic regionssubject to local adaptation is to genotype numerous molecular markers and look for outlier loci.Methods: In this study, population structure and genome wide footprints scan of natural selection in cattlewas performed using principal component analysis based on alternative individual method assumed inthe PCAdapt R-package. This method was used on the hypothesis that extremely related populationmarkers are also local population adaptation candidates. To test PCAdapt method in cattle, the data ofsixty three animals were collected from four different origins or agro-ecological zones (Achai = 18,Cholistani = 13, Lohani = 19, and Tharparkar = 13) and genotyped using the high density SNPs BeadChip.Results: As expected from the sampling from different zones the principal component result indicated theclear division in these animals into three clusters. K=3 was the optimal number suggested by eigenvalues.Conclusion: The result of this study revealed that the genomic regions harboring signals of the candidategenes were associated with immunity system and muscle formation. Signature of selection detecting inthis study targeted the historical adaptation in these breeds that will be useful in future to understand cattleorigin under different environment.
机译：背景：为了描述自然选择，已经开发了许多确定候选基因组区域的分析方法。人口基因组学在确定局部适应性复杂位点方面有很大的推动力。寻找受局部适应影响的基因组区域的有效方法是对众多分子标记进行基因分型并寻找异常基因座。方法：在这项研究中，使用基于替代个体方法的主成分分析对牛的自然选择进行了种群结构和全基因组足迹扫描在PCAdapt R-package中提供。该方法用于以下假设：与人口相关的标记物也是本地人口适应性候选物。为了测试牛的PCAdapt方法，从四个不同的起源或农业生态区（Achai = 18，Cholistani = 13，Lohani = 19和Tharparkar = 13）收集了六十三只动物的数据，并使用高密度SNPs BeadChip进行了基因分型。结果：正如从不同区域采样所期望的那样，主成分结果表明这些动物清晰地分为三个簇。 K = 3是特征值建议的最佳数目。结论：本研究结果表明，带有候选基因信号的基因组区域与免疫系统和肌肉形成有关。本研究中选择检测的特征是针对这些品种的历史适应性，这将有助于将来了解不同环境下的牛源。

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