SNV discovery and functional candidate gene identification for milk composition based on whole genome resequencing of Holstein bulls with extremely high and low breeding values
SNV discovery and functional candidate gene identification for milk composition based on whole genome resequencing of Holstein bulls with extremely high and low breeding values
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基于育种值极高和极低荷斯坦公牛全基因组重测序的SNV发现及乳成分功能候选基因鉴定
DOI：
10.1371/journal.pone.0220629
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发表时间：
2019-08-01
期刊：
影响因子：
3.7
通讯作者：
Sun, Dongxiao
中科院分区：
文献类型：
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作者：
Lin, Shan;Zhang, Hongyan;Sun, Dongxiao
我们使用Illumina重新测序技术对来自四个乳蛋白百分比(PP)和脂肪百分比(FP)极高和极低估计育种值(EBV)的四个半同胞或全同胞家系的8头经过验证的荷斯坦公牛的全部基因组进行了测序。因此，获得了23亿个原始读数，平均有效深度为8.1×。单核苷酸变异体(SNV)召唤后，共鉴定出10,961,243个SNV，其中57,451个SNV在每个家系内EBV高、低的公牛之间显示相反的固定位点(称为共同差异SNV)。接下来，我们根据牛参考基因组对常见的差异SNV进行了注释，观察到45,188个SNV(78.70%)位于基因间隔区，而只有11,871个SNV(20.67%)位于蛋白质编码基因内。在这些差异SNV中，有13,099个位于蛋白质编码基因范围内或接近于5kb以下的蛋白质编码基因，用于奶牛乳成分候选基因的鉴定。通过将2,657个基因与蛋白质和脂肪代谢相关的GO项和途径以及已知的乳蛋白和脂肪性状的数量性状基因座(QTL)进行综合分析，筛选出17个有希望的候选基因：ALG14、ATP2C1、PLD1、C3H1orf85、SNX7、MTHFD2L、CDKN2D、COL5A3、FDX1L、Pin1、FIG4、EXOC7、LASP1、Pgs1、SAO、GPLD1和MGEA5。本研究结果为奶牛的进一步研究和分子育种提供了重要依据。
We have sequenced the whole genomes of eight proven Holstein bulls from the four half-sib or full-sib families with extremely high and low estimated breeding values (EBV) for milk protein percentage (PP) and fat percentage (FP) using Illumina re-sequencing technology. Consequently, 2.3 billion raw reads were obtained with an average effective depth of 8.1×. After single nucleotide variant (SNV) calling, total 10,961,243 SNVs were identified, and 57,451 of them showed opposite fixed sites between the bulls with high and low EBVs within each family (called as common differential SNVs). Next, we annotated the common differential SNVs based on the bovine reference genome, and observed that 45,188 SNVs (78.70%) were located in the intergenic region of genes and merely 11,871 SNVs (20.67%) located within the protein-coding genes. Of them, 13,099 common differential SNVs that were within or close to protein-coding genes with less than 5 kb were chosen for identification of candidate genes for milk compositions in dairy cattle. By integrated analysis of the 2,657 genes with the GO terms and pathways related to protein and fat metabolism, and the known quantitative trait loci (QTLs) for milk protein and fat traits, we identified 17 promising candidate genes: ALG14, ATP2C1, PLD1, C3H1orf85, SNX7, MTHFD2L, CDKN2D, COL5A3, FDX1L, PIN1, FIG4, EXOC7, LASP1, PGS1, SAO, GPLD1 and MGEA5. Our findings provided an important foundation for further study and a prompt for molecular breeding of dairy cattle.