Genome-Wide Association Studies (GWAS) in large human cohorts have identified thousands of loci associated with complex traits and diseases. For identifying the genes and gene-associated variants that underlie complex traits in livestock, especially where sample sizes are limiting, it may help to integrate the results of GWAS for equivalent traits in humans as prior information. In this study, we sought to investigate the usefulness of results from a GWAS on human height as prior information for identifying the genes and gene-associated variants that affect stature in cattle, using GWAS summary data on samples sizes of 700,000 and 58,265 for humans and cattle, respectively. Using Fisher’s exact test, we observed a significant proportion of cattle stature-associated genes (30/77) that are also associated with human height (odds ratio = 5.1, p = 3.1e-10). Result of randomized sampling tests showed that cattle orthologs of human height-associated genes, hereafter referred to as candidate genes (C-genes), were more enriched for cattle stature GWAS signals than random samples of genes in the cattle genome (p = 0.01). Randomly sampled SNPs within the C-genes also tend to explain more genetic variance for cattle stature (up to 13.2%) than randomly sampled SNPs within random cattle genes (p = 0.09). The most significant SNPs from a cattle GWAS for stature within the C-genes did not explain more genetic variance for cattle stature than the most significant SNPs within random cattle genes (p = 0.87). Altogether, our findings support previous studies that suggest a similarity in the genetic regulation of height across mammalian species. However, with the availability of a powerful GWAS for stature that combined data from 8 cattle breeds, prior information from human-height GWAS does not seem to provide any additional benefit with respect to the identification of genes and gene-associated variants that affect stature in cattle.

大型人群的全基因组关联研究（GWAS）已鉴定出数千个与复杂性状和疾病相关的基因座。为了鉴定构成牲畜复杂性状基础的基因和基因相关变体，尤其是在样本量有限的情况下，它可能有助于将GWAS的人类等效性状的结果整合为先验信息。在这项研究中，我们试图利用GWAS的样本量分别为700,000和58,265的人类和女性个体的GWAS汇总数据，来研究GWAS的人类身高结果作为鉴定影响牛身高的基因和基因相关变异的先验信息的有用性。牛，分别。使用Fisher的精确检验，我们观察到很大一部分与牛身高相关的基因（30/77）也与人的身高相关（优势比= 5.1，p = 3.1e-10）。随机抽样测试的结果表明，与身高相关基因的牛直系同源物（以下称为候选基因（C基因））比牛基因组中的随机基因样本更富集牛身材GWAS信号（p = 0.01） 。与随机牛基因中随机抽样的SNPs相比，C基因中随机抽样的SNPs往往也解释了牛身材的遗传变异（高达13.2％）（p = 0.09）。从牛GWAS的C-基因中最显著的SNP的身材并没有解释更多的遗传变异牛身形比内随机牛基因最显著的SNP（p= 0.87）。总之，我们的发现支持了先前的研究，这些研究表明跨哺乳动物物种的身高遗传调控相似。然而，由于有一个强大的GWAS可以将8个牛的数据结合在一起，因此，身高GWAS的先前信息似乎在鉴定影响猪身高的基因和基因相关变体方面没有提供任何额外的好处。牛。