对 34,497 头德国荷斯坦奶牛进行孟德尔随机分析,推断产奶量与健康特征之间的因果关系

IF 3.6 1区 农林科学 Q1 AGRICULTURE, DAIRY & ANIMAL SCIENCE
Helen Schneider, Valentin Haas, Ana-Marija Krizanac, Clemens Falker-Gieske, Johannes Heise, Jens Tetens, Georg Thaller, Jörn Bennewitz
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引用次数: 0

摘要

牛爪疾病和乳腺炎是奶牛最重要的健康问题,经常被提及与产奶量有关。虽然许多研究都旨在通过估计遗传相关性来更详细地调查这种联系,但它们并不能提供因果关系的信息。另一种方法是利用基因变异开展孟德尔随机化(MR)研究,调查基因变异介导的暴露对结果性状的影响。目前还没有研究调查奶牛产奶量(MY)与健康性状之间的因果关系。因此,我们利用来自 34,497 头德国荷斯坦奶牛的估算全基因组序列数据,对产奶量和七个健康性状进行了 MR 分析。我们采用了一种使用汇总统计的方法,并剔除了水平多向变异(对两个性状都有影响),从而提高了 MR 研究的功率和无偏性。此外,我们还估算了MY与每个健康性状之间的遗传相关性,以便与我们预期的因果效应估算值进行比较。MY与各健康性状之间的所有遗传相关性均为负,从- 0.303(乳腺炎)到- 0.019(数字皮炎)不等,这表明随着MY的增加,健康状况会下降。唯一不显著的相关性是 MY 与数字皮炎之间的相关性。此外,每种因果关系都是负相关,从- 0.131(乳腺炎)到- 0.034(蹄叶炎)不等,但显著相关的数量减少到 5 个名义显著结果和 2 个整个实验的显著结果。后者是 MY 与乳腺炎和 MY 与数字痰之间的关系。在乳腺炎、数字皮炎和数字痰中发现了水平多向变异。这些变异位于以前报道过的对产奶量和体细胞数有水平多效应的变异内或附近。我们的研究结果证实了奶牛健康性状与 MY 之间已知的负遗传联系。此外,它们还提供了有关因果关系的新信息,例如指出负能量平衡介导了这些性状之间的联系。这些知识有助于更好地理解负遗传相关性是基于多效性、两个性状复合体的因果变异之间的联系,还是确实存在因果关联。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Mendelian randomization analysis of 34,497 German Holstein cows to infer causal associations between milk production and health traits
Claw diseases and mastitis represent the most important health issues in dairy cattle with a frequently mentioned connection to milk production. Although many studies have aimed at investigating this connection in more detail by estimating genetic correlations, they do not provide information about causality. An alternative is to carry out Mendelian randomization (MR) studies using genetic variants to investigate the effect of an exposure on an outcome trait mediated by genetic variants. No study has yet investigated the causal association of milk yield (MY) with health traits in dairy cattle. Hence, we performed a MR analysis of MY and seven health traits using imputed whole-genome sequence data from 34,497 German Holstein cows. We applied a method that uses summary statistics and removes horizontal pleiotropic variants (having an effect on both traits), which improves the power and unbiasedness of MR studies. In addition, genetic correlations between MY and each health trait were estimated to compare them with the estimates of causal effects that we expected. All genetic correlations between MY and each health trait were negative, ranging from − 0.303 (mastitis) to − 0.019 (digital dermatitis), which indicates a reduced health status as MY increases. The only non-significant correlation was between MY and digital dermatitis. In addition, each causal association was negative, ranging from − 0.131 (mastitis) to − 0.034 (laminitis), but the number of significant associations was reduced to five nominal and two experiment-wide significant results. The latter were between MY and mastitis and between MY and digital phlegmon. Horizontal pleiotropic variants were identified for mastitis, digital dermatitis and digital phlegmon. They were located within or nearby variants that were previously reported to have a horizontal pleiotropic effect, e.g., on milk production and somatic cell count. Our results confirm the known negative genetic connection between health traits and MY in dairy cattle. In addition, they provide new information about causality, which for example points to the negative energy balance mediating the connection between these traits. This knowledge helps to better understand whether the negative genetic correlation is based on pleiotropy, linkage between causal variants for both trait complexes, or indeed on a causal association.
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来源期刊
Genetics Selection Evolution
Genetics Selection Evolution 生物-奶制品与动物科学
CiteScore
6.50
自引率
9.80%
发文量
74
审稿时长
1 months
期刊介绍: Genetics Selection Evolution invites basic, applied and methodological content that will aid the current understanding and the utilization of genetic variability in domestic animal species. Although the focus is on domestic animal species, research on other species is invited if it contributes to the understanding of the use of genetic variability in domestic animals. Genetics Selection Evolution publishes results from all levels of study, from the gene to the quantitative trait, from the individual to the population, the breed or the species. Contributions concerning both the biological approach, from molecular genetics to quantitative genetics, as well as the mathematical approach, from population genetics to statistics, are welcome. Specific areas of interest include but are not limited to: gene and QTL identification, mapping and characterization, analysis of new phenotypes, high-throughput SNP data analysis, functional genomics, cytogenetics, genetic diversity of populations and breeds, genetic evaluation, applied and experimental selection, genomic selection, selection efficiency, and statistical methodology for the genetic analysis of phenotypes with quantitative and mixed inheritance.
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