This study focused on the identification of QTL regions, candidate genes, and network related genes based on the first 3 lactations (LAC3) of milk, fat, and protein yields, and somatic cell score (SCS) in Portuguese Holstein cattle. Additionally, the results were compared with those from only first lactation (LAC1) data. The analyses were performed using the weighted single-step GWAS under an autoregressive test-day (TD) multiple lactations model. A total of 11,434,294 and 4,725,673 TD records from LAC3 and LAC1, respectively, including 38,323 autosomal SNPs and 1338 genotyped animals were used in GWAS analyses. A total of 51 (milk), 5 (fat), 24 (protein), and 4 (SCS) genes were associated to previously annotated relevant QTL regions for LAC3. The CACNA2D1 at BTA4 explained the highest proportion of genetic variance respectively for milk, fat, and protein yields. For SCS, the TRNAG-CCC at BTA14, MAPK10, and PTPN3 genes, both at BTA6 were considered important candidate genes. The accessed network refined the importance of the reported genes. CACNA2D1 regulates calcium density and activation/inactivation kinetics of calcium transport in the mammary gland; whereas TRNAG-CCC, MAPK10, and PTPN3 are directly involved with inflammatory processes widely derived from mastitis. In conclusion, potential candidate genes (TRNAG-CCC, MAPK10, and PTPN3) associated with somatic cell were highlighted, which further validation studies are needed to clarify its mechanism action in response to mastitis. Moreover, most of the candidate genes identified were present in both (LAC3 and LAC1) for milk, fat and protein yields, except for SCS, in which no candidate genes were shared between LAC3 and LAC1. The larger phenotypic information provided by LAC3 dataset was more effective to identify relevant genes, providing a better understanding of the genetic architecture of these traits over all lactations simultaneously.

中文翻译：

---

来自葡萄牙荷斯坦牛测试日多次泌乳的牛奶相关性状的 GWAS 和基因网络。

本研究的重点是基于葡萄牙荷斯坦牛的前 3 个泌乳期 (LAC3) 和体细胞评分 (SCS) 鉴定 QTL 区域、候选基因和网络相关基因。此外，将结果与仅来自第一次泌乳 (LAC1) 数据的结果进行了比较。在自回归测试日 (TD) 多泌乳模型下使用加权单步 GWAS 进行分析。分别来自LAC3和LAC1的11,434,294和4,725,673个TD记录，包括38,323个常染色体SNP和1338个基因型动物用于GWAS分析。共有 51 个（牛奶）、5 个（脂肪）、24 个（蛋白质）和 4 个（SCS）基因与先前注释的 LAC3 相关 QTL 区域相关。该CACNA2D1BTA4 分别解释了牛奶、脂肪和蛋白质产量的最高遗传变异比例。对于 SCS，BTA14、MAPK10和PTPN3基因上的TRNAG-CCC被认为是重要的候选基因。访问的网络完善了报告基因的重要性。CACNA2D1调节钙密度和钙在乳腺中转运的激活/失活动力学；而TRAG-CCC、MAPK10和PTPN3直接参与广泛源自乳腺炎的炎症过程。总之，潜在的候选基因（TRNAG-CCC、MAPK10和PTPN3) 与体细胞相关，需要进一步的验证研究来阐明其响应乳腺炎的机制作用。此外，除了 SCS 之外，大多数已鉴定的候选基因（LAC3 和 LAC1）都存在于牛奶、脂肪和蛋白质产量中，其中 LAC3 和 LAC1 之间没有共享候选基因。LAC3 数据集提供的更大的表型信息更有效地识别相关基因，同时提供对所有哺乳期这些性状的遗传结构的更好理解。