The cattle introduced by European conquerors during the Brazilian colonization period were exposed to a process of natural selection in different types of biomes throughout the country, leading to the development of locally adapted cattle breeds. In this study, whole-genome re-sequencing data from indicine and Brazilian locally adapted taurine cattle breeds were used to detect genomic regions under selective pressure. Within-population and cross-population statistics were combined separately in a single score using the de-correlated composite of multiple signals (DCMS) method. Putative sweep regions were revealed by assessing the top 1% of the empirical distribution generated by the DCMS statistics. A total of 33,328,447 biallelic SNPs with an average read depth of 12.4X passed the hard filtering process and were used to access putative sweep regions. Admixture has occurred in some locally adapted taurine populations due to the introgression of exotic breeds. The genomic inbreeding coefficient based on runs of homozygosity (ROH) concurred with the populations’ historical background. Signatures of selection retrieved from the DCMS statistics provided a comprehensive set of putative candidate genes and revealed QTLs disclosing cattle production traits and adaptation to the challenging environments. Additionally, several candidate regions overlapped with previous regions under selection described in the literature for other cattle breeds. The current study reported putative sweep regions that can provide important insights to better understand the selective forces shaping the genome of the indicine and Brazilian locally adapted taurine cattle breeds. Such regions likely harbor traces of natural selection pressures by which these populations have been exposed and may elucidate footprints for adaptation to the challenging climatic conditions.

中文翻译：

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使用全基因组重测序数据对全基因组和巴西本地适应的牛磺酸牛品种的选择特征进行全基因组检测。

欧洲征服者在巴西殖民时期引入的牛在全国各地的不同类型生物群落中经历了自然选择的过程，从而导致了适应当地情况的牛品种的发展。在这项研究中，来自标记和巴西本地适应的牛磺酸牛品种的全基因组重测序数据用于检测选择性压力下的基因组区域。使用多信号去相关复合（DCMS）方法，将种群内和种群间的统计信息分别合并为一个分数。通过评估DCMS统计数据生成的最高1％的经验分布来揭示推定的扫描区域。共有33,328,447个双等位基因SNP，平均读取深度为12。4X通过了硬过滤过程，并用于访问假定的扫描区域。由于外来品种的渗入，在一些当地适应的牛磺酸种群中发生了混合。基于纯合子运行（ROH）的基因组近交系数与种群的历史背景相吻合。从DCMS统计数据中检索到的选择签名提供了一套全面的推定候选基因，并揭示了揭示牛的生产性状和对具有挑战性的环境的适应性的QTL。另外，一些候选区域与文献中描述的其他牛品种的先前选择区域重叠。当前的研究报道了推定的扫掠区域，这些区域可以提供重要的见识，以更好地理解塑造标记和巴西本地适应的牛磺酸牛品种基因组的选择性力量。这些区域可能隐含着自然选择压力的痕迹，这些种群已经暴露在自然选择压力下，并且可能阐明了适应挑战性气候条件的足迹。