Mastitis is a disease that incurs significant costs in the dairy industry. A promising approach to mitigate its negative effects is to genetically improve the resistance of dairy cattle to mastitis. A meta-analysis of genome-wide association studies (GWAS) across multiple breeds for clinical mastitis (CM) and its indicator trait, somatic cell score (SCS), is a powerful method to identify functional genetic variants that impact mastitis resistance. We conducted meta-analyses of eight and fourteen GWAS on CM and SCS, respectively, using 30,689 and 119,438 animals from six dairy cattle breeds. Methods for the meta-analyses were selected to properly account for the multi-breed structure of the GWAS data. Our study revealed 58 lead markers that were associated with mastitis incidence, including 16 loci that did not overlap with previously identified quantitative trait loci (QTL), as curated at the Animal QTLdb. Post-GWAS analysis techniques such as gene-based analysis and genomic feature enrichment analysis enabled prioritization of 31 candidate genes and 14 credible candidate causal variants that affect mastitis. Our list of candidate genes can help to elucidate the genetic architecture underlying mastitis resistance and provide better tools for the prevention or treatment of mastitis, ultimately contributing to more sustainable animal production.

中文翻译：

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对六个奶牛品种的荟萃分析揭示了抗乳腺炎的生物学相关候选基因


乳腺炎是一种给乳制品行业带来巨大损失的疾病。减轻其负面影响的一个有前途的方法是从基因上提高奶牛对乳腺炎的抵抗力。对多个品种的临床乳腺炎 (CM) 及其指标性状体细胞评分 (SCS) 的全基因组关联研究 (GWAS) 进行荟萃分析，是识别影响乳腺炎抵抗力的功能性遗传变异的有力方法。我们分别使用来自六个奶牛品种的 30,689 和 119,438 只动物，对 CM 和 SCS 的 8 次和 14 次 GWAS 进行了荟萃分析。选择荟萃分析方法以正确解释 GWAS 数据的多品种结构。我们的研究揭示了 58 个与乳腺炎发病率相关的先导标记，其中包括 16 个与之前在动物 QTLdb 中确定的数量性状基因座 (QTL) 不重叠的基因座。基于基因的分析和基因组特征富集分析等 GWAS 后分析技术能够对影响乳腺炎的​​ 31 个候选基因和 14 个可信的候选因果变异进行优先排序。我们的候选基因列表可以帮助阐明乳腺炎抗性的遗传结构，并为预防或治疗乳腺炎提供更好的工具，最终有助于更可持续的动物生产。