Department of Agronomy, Food, Natural Resources, Animals and Environment (DAFNAE), University of Padova, Viale dell'Università 16, 35020 Legnaro, Italy.
Department of Animal Sciences and Department of Biostatistics and Medical Informatics, University of Wisconsin, Madison 53706.
J Dairy Sci. 2017 Nov;100(11):9085-9102. doi: 10.3168/jds.2017-13219. Epub 2017 Aug 24.
The aim of this study was to perform genome-wide associations (GWAS) and gene-set enrichment analyses with protein composition and cheesemaking-related latent variables (factors; F) in a cohort of 1,011 Italian Brown Swiss cows. Factor analysis was applied to identify latent structures of 26 phenotypes related to bovine milk quantity and quality, protein fractions [α-, α-, β-, and κ-casein (CN), β-lactoglobulin, and α-lactalbumin (α-LA)], coagulation and curd firming at time t (CF) measures, and cheese properties [cheese yield (%CY) and nutrients recovery in the curd] of individual cows. Ten orthogonal F were extracted, explaining 74% of the original variability. Factor 1 underlined the %CY characteristics, F2 was related to the CF process parameters, F3 was considered as descriptor of milk and solids yield, whereas F4 underscored the presence of nitrogenous compounds (N) into the cheese. Four more F were related to the milk caseins (F5, F7, F8, and F9) and 1 F was linked to the whey protein (F10); 1 F underlined the udder health status (F6). All cows were genotyped with the Illumina BovineSNP50 Bead Chip v.2 (Illumina Inc., San Diego, CA). Single marker regression GWAS were fitted. Gene-set enrichment analysis was run on GWAS results, using the Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway databases, to reveal ontologies or pathways associated with the F. All F but F3 showed significance in GWAS. Signals in 10 Bos taurus autosomes (BTA) were detected. High peaks on BTA6 (∼87 Mbp) were found for F6, F5, and at the tail of BTA11 (∼104 Mbp) for F4. Gene-set enrichment analyses showed significant results (false discovery rate at 5%) for F8, F1, F4, and F10. For F8, 33 Gene Ontology terms and 3 Kyoto Encyclopedia of Genes and Genomes categories were enriched, including terms related to ion transport and homeostasis, neuron function or part, and GnRH signaling pathway. Our results support the feasibility of factor analysis as a dimension reduction technique in genomic studies and evidenced a potential key role of α-CN in milk quality and composition.
本研究旨在对 1011 头意大利棕色瑞士奶牛进行全基因组关联分析(GWAS)和基因集富集分析,研究对象为蛋白质组成和干酪制作相关的潜在变量(因子;F)。采用因子分析方法,对与牛牛奶量和质量、蛋白质分数[α-、α-、β-、κ-酪蛋白(CN)、β-乳球蛋白和α-乳白蛋白(α-LA)]、凝固和凝乳时的 t 时间(CF)测量值以及奶酪特性[奶酪产量(%CY)和凝乳中营养素回收]相关的 26 个表型进行潜在结构的识别。提取了 10 个正交 F,解释了原始可变性的 74%。因子 1 强调了 %CY 特征,F2 与 CF 过程参数有关,F3 被认为是牛奶和固体产量的描述符,而 F4 则强调了奶酪中含氮化合物(N)的存在。另外 4 个 F 与乳清蛋白(F10)相关,F5、F7、F8 和 F9),1 个 F 与乳蛋白(F6)相关;1 个 F 强调了乳房健康状况(F6)。所有奶牛均采用 Illumina BovineSNP50 Bead Chip v.2(Illumina Inc.,圣地亚哥,CA)进行基因分型。拟合了单标记回归 GWAS。使用基因本体论和京都基因与基因组百科全书途径数据库对 GWAS 结果进行基因集富集分析,以揭示与 F 相关的本体论或途径。所有 F 但 F3 在 GWAS 中均表现出显著意义。在 10 个牛 Taurus 常染色体(BTA)上检测到信号。在 BTA6(约 87 Mbp)上发现了 F6、F5 的高峰值,在 BTA11(约 104 Mbp)的尾部发现了 F4 的高峰值。基因集富集分析显示 F8、F1、F4 和 F10 的结果具有显著意义(假发现率为 5%)。对于 F8,富集了 33 个基因本体论术语和 3 个京都基因与基因组百科全书类别,包括与离子转运和动态平衡、神经元功能或部分以及 GnRH 信号通路相关的术语。我们的结果支持因子分析作为基因组研究中降维技术的可行性,并证明了 α-CN 在牛奶质量和组成中的潜在关键作用。