The aim of this study was to detect selection signatures considering cows from the German Holstein (GH) and the local dual-purpose black and white (DSN) population, as well as from generated sub-populations. The 4654 GH and 261 DSN cows were genotyped with the BovineSNP50 Genotyping BeadChip. The geographical herd location was used as an environmental descriptor to create the East-DSN and West-DSN sub-populations. In addition, two further sub-populations of GH cows were generated, using the extreme values for solutions of residual effects of cows for the claw disorder dermatitis digitalis. These groups represented the most susceptible and most resistant cows. We used cross-population extended haplotype homozygosity methodology (XP-EHH) to identify the most recent selection signatures. Furthermore, we calculated Wright's fixation index (FST ). Chromosomal segments for the top 0.1 percentile of negative or positive XP-EHH scores were studied in detail. For gene annotations, we used the Ensembl database and we considered a window of 250 kbp downstream and upstream of each core SNP corresponding to peaks of XP-EHH. In addition, functional interactions among potential candidate genes were inferred via gene network analyses. The most outstanding XP-EHH score was on chromosome 12 (at 77.34 Mb) for DSN and on chromosome 20 (at 36.29-38.42 Mb) for GH. Selection signature locations harbored QTL for several economically important milk and meat quality traits, reflecting the different breeding goals for GH and DSN. The average FST value between GH and DSN was quite low (0.068), indicating shared founders. For group stratifications according to cow health, several identified potential candidate genes influence disease resistance, especially to dermatitis digitalis.

中文翻译：

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评估黑白两用和德国荷斯坦牛的选定品系内和之间的选择特征。

这项研究的目的是要考虑来自德国荷斯坦（GH）和当地两用黑白（DSN）种群以及所产生的亚种群的母牛的选择特征。用牛SNP50基因分型BeadChip对4654 GH和261 DSN奶牛进行基因分型。地理位置将畜群用作创建东-DSN和西-DSN子种群的环境描述符。此外，使用奶牛对爪症数字化皮炎的残留效应解决方案的极值，生成了另外两个GH奶牛亚群。这些群体代表最易感和最有抵抗力的母牛。我们使用跨群体扩展单倍型纯合性方法学（XP-EHH）来识别最新的选择特征。此外，我们计算了赖特的注视指数（FST）。详细研究了XP-EHH阴性或阳性XP分数最高的0.1个百分点的染色体片段。对于基因注释，我们使用了Ensembl数据库，并考虑了每个核心SNP下游和上游250 kbp的窗口，该窗口对应于XP-EHH的峰。此外，通过基因网络分析推断潜在候选基因之间的功能相互作用。对于DSN，最杰出的XP-EHH得分在12号染色体上（77.34 Mb），而对于GH，XP-EHH得分最高的是20号染色体（36.29-38.42 Mb）。选择签名的地点具有几个具有重要经济意义的牛奶和肉品质性状的QTL，反映了GH和DSN的不同育种目标。GH和DSN之间的平均FST值很低（0.068），表明创始人是共享的。对于根据母牛健康状况进行的群体分层，