Next generation sequencing reveals the diversity and population-genetic properties of cattle CNVs. Bos taurus

Structural and functional impacts of copy number variations (CNVs) on livestock genomes are not yet well understood. In this study, we have identified 1853 CNV regions (CNVRs) using population-scale sequencing data generated from 75 cattle of 8 breeds (Holstein, Angus, Jersey, Limousin, Romagnola, Brahman, Gir and Nelore). Individual genome sequence coverage ranged from 4 to 30 fold, with a mean of 11.8 fold. A total of 3.1% (87.5 Mb) of the cattle genome is predicted to be copy number variable, representing a substantial increase over the previous estimates (~2%). This dataset was highly correlated with array CGH data (r2 = 0.761) and was validated to be accurate with an estimated 12% false positive rate and a 19% false negative rate based on qPCR and array CGH, respectively. Hundreds of CNVs were found to be either breed specific or differentially variable across breeds, including the RICTOR gene in dairy breeds and the PNPLA3 gene in the beef breeds. In contrast, clusters of the PRP and PAG genes are duplicated in all sequenced animals, implicating that subfunctionalization, neofunctionalization or overdominance play a role in diversifying these fertility related genes. Further population-genetic analyses based on CNVs revealed the population structures of these taurine and indicine breeds and uncovered hundreds of positively selected CNV candidates near important functional genes. These CNV results provide a new glimpse of diverse selections during cattle speciation, domestication, breed formation, and recent genetic improvement. Overall design: 25 animals were analyzed using a custom Nimblegen aCGH chip with 2.1 million probes. The reference animal chosen was L1 Dominette, a Hereford cow of European ancestry. The array was subjected to a dye-swap with the reference sample to test probe intensity fidelity. Single channel intensity data from the array was used in a digital aCGH analysis to compare aCGH copy number estimates to copy number estimates derived from sequence data. Briefly, the reference signal from all analyzed arrays was collected and a median signal intensity was calculated from probe intensities within the BTF3 gene. The copy number of the reference animal was then inferred by division of single channel probe intensities with the median intensity of the BTF3 gene. Next, test sample intensities were normalized by taking the log2 ratio of the test intensity divided by the normalized reference copy number for the probe. CN values derived from sequence data were also normalized in this fashion by taking the log2 of the ratio of NGS CN divided by aCGH reference copy number.

拷贝数变异（copy number variations, CNVs）对畜禽基因组的结构与功能影响，目前尚未得到充分阐释。本研究利用来自8个品种共75头牛的群体规模测序数据，鉴定得到1853个拷贝数变异区域（copy number variation regions, CNVRs），这8个品种分别为荷斯坦（Holstein）、安格斯（Angus）、娟姗（Jersey）、利木赞（Limousin）、罗马诺拉（Romagnola）、婆罗门（Brahman）、吉尔（Gir）以及内洛尔（Nelore）。个体基因组测序覆盖度介于4至30倍之间，平均覆盖度为11.8倍。经预测，牛基因组中总计3.1%（87.5 Mb）的区域存在拷贝数变异，这一比例较此前预估的约2%有显著提升。本数据集与阵列比较基因组杂交（array CGH）数据具有高度相关性（决定系数r²=0.761）；经定量聚合酶链反应（quantitative polymerase chain reaction, qPCR）与阵列比较基因组杂交验证，其准确率较高，假阳性率约为12%，假阴性率约为19%。研究发现数百个CNVs呈现品种特异性或跨品种差异变异特征，其中乳用品种中包含RICTOR基因，肉用品种中包含PNPLA3基因。与之相反，PRP与PAG基因簇在所有测序个体中均发生了重复，这表明亚功能化、新功能化或超显性在这些与繁殖相关的基因多样化过程中发挥了作用。基于CNVs开展的进一步群体遗传学分析，阐明了这些普通牛（taurine）与瘤牛（indicine）品种的群体结构，并在重要功能基因附近发现了数百个受正向选择的CNV候选位点。本CNV研究结果为解析牛物种形成、驯化、品种培育以及近期遗传改良过程中的多样化选择提供了全新视角。实验设计：本研究使用定制的Nimblegen阵列比较基因组杂交芯片（搭载210万个探针）对25个个体进行分析。选取的参考个体为L1 Dominette，一头具有欧洲血统的赫里福德牛。该芯片采用参考样本进行染料交换实验，以验证探针信号强度的可靠性。本研究利用芯片的单通道信号强度数据开展数字化阵列比较基因组杂交分析，以比对阵列比较基因组杂交与测序数据得到的拷贝数估计值。简言之，收集所有分析芯片的参考信号，并基于BTF3基因内的探针信号强度计算中位信号强度。随后，通过将单通道探针信号强度除以BTF3基因的中位信号强度，推断参考个体的拷贝数。接下来，对待测样本的信号强度进行标准化处理：计算每个探针的待测信号强度与标准化后参考个体拷贝数的比值，并取其以2为底的对数。从测序数据得到的拷贝数（CN）值也采用相同方式进行标准化：计算下一代测序（next-generation sequencing, NGS）得到的拷贝数与阵列比较基因组杂交参考拷贝数的比值，并取其以2为底的对数。