Gao Yahui, Jiang Jianping, Yang Shaohua, Hou Yali, Liu George E, Zhang Shengli, Zhang Qin, Sun Dongxiao
Key Laboratory of Animal Genetics and Breeding of Ministry of Agriculture, National Engineering Laboratory of Animal Breeding, College of Animal Science and Technology, China Agricultural University, Beijing, 100193, China.
CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing, 100101, China.
BMC Genomics. 2017 Mar 29;18(1):265. doi: 10.1186/s12864-017-3636-3.
Copy number variations (CNVs) are important and widely distributed in the genome. CNV detection opens a new avenue for exploring genes associated with complex traits in humans, animals and plants. Herein, we present a genome-wide assessment of CNVs that are potentially associated with milk composition traits in dairy cattle.
In this study, CNVs were detected based on whole genome re-sequencing data of eight Holstein bulls from four half- and/or full-sib families, with extremely high and low estimated breeding values (EBVs) of milk protein percentage and fat percentage. The range of coverage depth per individual was 8.2-11.9×. Using CNVnator, we identified a total of 14,821 CNVs, including 5025 duplications and 9796 deletions. Among them, 487 differential CNV regions (CNVRs) comprising ~8.23 Mb of the cattle genome were observed between the high and low groups. Annotation of these differential CNVRs were performed based on the cattle genome reference assembly (UMD3.1) and totally 235 functional genes were found within the CNVRs. By Gene Ontology and KEGG pathway analyses, we found that genes were significantly enriched for specific biological functions related to protein and lipid metabolism, insulin/IGF pathway-protein kinase B signaling cascade, prolactin signaling pathway and AMPK signaling pathways. These genes included INS, IGF2, FOXO3, TH, SCD5, GALNT18, GALNT16, ART3, SNCA and WNT7A, implying their potential association with milk protein and fat traits. In addition, 95 CNVRs were overlapped with 75 known QTLs that are associated with milk protein and fat traits of dairy cattle (Cattle QTLdb).
In conclusion, based on NGS of 8 Holstein bulls with extremely high and low EBVs for milk PP and FP, we identified a total of 14,821 CNVs, 487 differential CNVRs between groups, and 10 genes, which were suggested as promising candidate genes for milk protein and fat traits.
拷贝数变异（CNV）在基因组中很重要且分布广泛。CNV检测为探索人类、动物和植物中与复杂性状相关的基因开辟了一条新途径。在此，我们对可能与奶牛乳成分性状相关的CNV进行了全基因组评估。
在本研究中，基于来自四个半同胞和/或全同胞家系的八头荷斯坦公牛的全基因组重测序数据检测CNV，这些公牛的乳蛋白百分比和脂肪百分比的估计育种值（EBV）极高和极低。每个个体的覆盖深度范围为8.2 - 11.9倍。使用CNVnator，我们共鉴定出14,821个CNV，包括5025个重复和9796个缺失。其中，在高分组和低分组之间观察到487个差异CNV区域（CNVR），其覆盖牛基因组约8.23 Mb。基于牛基因组参考组装（UMD3.1）对这些差异CNVR进行注释，在CNVR内共发现235个功能基因。通过基因本体论和KEGG通路分析，我们发现基因在与蛋白质和脂质代谢、胰岛素/IGF通路 - 蛋白激酶B信号级联、催乳素信号通路和AMPK信号通路相关的特定生物学功能上显著富集。这些基因包括INS、IGF2、FOXO3、TH、SCD5、GALNT18、GALNT16、ART3、SNCA和WNT7A，这意味着它们可能与乳蛋白和脂肪性状相关。此外，95个CNVR与75个已知的与奶牛乳蛋白和脂肪性状相关的QTL（牛QTL数据库）重叠。
总之，基于8头乳蛋白百分比和脂肪百分比EBV极高和极低的荷斯坦公牛的二代测序，我们共鉴定出14,821个CNV、组间487个差异CNVR以及10个基因，这些基因被认为是乳蛋白和脂肪性状有前景的候选基因。
