Zhu Hao, Lu Xubin, Jiang Hui, Yang Zhangping, Xu Tianle
Joint International Research Laboratory of Agriculture and Agri-Product Safety, Yangzhou University, Yangzhou 225009, China.
College of Animal Science and Technology, Yangzhou University, Yangzhou 225009, China.
Animals (Basel). 2023 Dec 19;14(1):17. doi: 10.3390/ani14010017.
Milk production traits are the most important quantitative economic traits in dairy cow production; improving the yield and quality of milk is an important way to ensure the production efficiency of the dairy industry. This study carried out a series of in-depth statistical genetics studies and molecular analyses on the Chinese Holstein cows in the Jiangsu Province, such as descriptive statistics and copy number variation analysis. A genetic correlation, phenotypic correlation, and descriptive statistical analysis of five milk production traits (milk yield, milk fat percentage, milk fat yield, milk protein percentage, and milk protein yield) of the dairy cows were analyzed using the SPSS and DMU software. Through quality control, 4173 cows and their genomes were used for genomic study. Then, SNPs were detected using DNA chips, and a copy number variation (CNV) analysis was carried out to locate the quantitative trait loci (QTL) of the milk production traits by Perl program software Penn CNV and hidden Markov model (HMM). The phenotypic means of the milk yield, milk fat percentage, milk fat mass, milk protein percentage, and milk protein mass at the first trimester were lower than those at the other trimesters by 8.821%, 1.031%, 0.930%, 0.003%, and 0.826%, respectively. The five milk production traits showed a significant phenotypic positive correlation ( < 0.01) and a high genetic positive correlation among the three parities. Based on the GGPBovine 100 K SNP data, QTL-detecting research on the fist-parity milk performance of dairy cows was carried out via the CNV. We identified 1731 CNVs and 236 CNVRs in the 29 autosomes of 984 Holstein dairy cows, and 19 CNVRs were significantly associated with the milk production traits ( < 0.05). These CNVRs were analyzed via a bioinformatics analysis; a total of 13 gene ontology (GO) terms and 20 Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways were significantly enriched ( < 0.05), and these terms and pathways are mainly related to lipid metabolism, amino acid metabolism, and cellular catabolic processes. This study provided a theoretical basis for the molecular-marker-assisted selection of dairy cows by developing descriptive statistics on the milk production traits of dairy cows and by locating the QTL and functional genes that affect the milk production traits of first-born dairy cows. The results describe the basic status of the milk production traits of the Chinese Holstein cows in Jiangsu and locate the QTL and functional genes that affect the milk production traits of the first-born cows, providing a theoretical basis for the molecular-marker-assisted selection of dairy cows.
产奶性状是奶牛生产中最重要的数量经济性状；提高牛奶产量和质量是确保奶牛业生产效率的重要途径。本研究对江苏省中国荷斯坦奶牛进行了一系列深入的统计遗传学研究和分子分析，如描述性统计和拷贝数变异分析。使用SPSS和DMU软件对奶牛的五个产奶性状（产奶量、乳脂率、乳脂产量、乳蛋白率和乳蛋白产量）进行了遗传相关性、表型相关性和描述性统计分析。通过质量控制，选取4173头奶牛及其基因组用于基因组研究。然后，使用DNA芯片检测单核苷酸多态性（SNP），并通过Perl程序软件Penn CNV和隐马尔可夫模型（HMM）进行拷贝数变异（CNV）分析，以定位产奶性状的数量性状位点（QTL）。头胎期的产奶量、乳脂率、乳脂质量、乳蛋白率和乳蛋白质量的表型均值分别比其他胎次低8.821%、1.031%、0.930%、0.003%和0.826%。这五个产奶性状在三个胎次间表现出显著的表型正相关（<0.01）和高度的遗传正相关。基于GGPBovine 100K SNP数据，通过CNV对奶牛头胎产奶性能进行了QTL检测研究。我们在984头荷斯坦奶牛的29条常染色体上鉴定出1731个CNV和236个CNVR，其中19个CNVR与产奶性状显著相关（<0.05）。通过生物信息学分析对这些CNVR进行分析；共有13个基因本体（GO）术语和20条京都基因与基因组百科全书（KEGG）通路显著富集（<0.05），这些术语和通路主要与脂质代谢、氨基酸代谢和细胞分解代谢过程有关。本研究通过对奶牛产奶性状进行描述性统计以及定位影响头胎奶牛产奶性状的QTL和功能基因，为奶牛的分子标记辅助选择提供了理论依据。研究结果描述了江苏省中国荷斯坦奶牛产奶性状的基本状况，定位了影响头胎奶牛产奶性状的QTL和功能基因，为奶牛的分子标记辅助选择提供了理论依据。
