Analytical and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital, Boston, MA 02114, USA.
Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA.
Science. 2023 Mar 31;379(6639):1341-1348. doi: 10.1126/science.abn8455. Epub 2023 Mar 30.
Classical statistical genetics theory defines dominance as any deviation from a purely additive, or dosage, effect of a genotype on a trait, which is known as the dominance deviation. Dominance is well documented in plant and animal breeding. Outside of rare monogenic traits, however, evidence in humans is limited. We systematically examined common genetic variation across 1060 traits in a large population cohort (UK Biobank, = 361,194 samples analyzed) for evidence of dominance effects. We then developed a computationally efficient method to rapidly assess the aggregate contribution of dominance deviations to heritability. Lastly, observing that dominance associations are inherently less correlated between sites at a genomic locus than their additive counterparts, we explored whether they may be leveraged to identify causal variants more confidently.
经典的统计遗传学理论将显性定义为基因型对性状的表现型的纯加性(或剂量)效应的任何偏差,这被称为显性偏差。显性在植物和动物育种中已有充分的记录。然而,除了罕见的单基因性状之外,人类的证据有限。我们在一个大型人群队列(英国生物银行,分析了 361194 个样本)中,对 1060 个性状的常见遗传变异进行了系统检查,以寻找显性效应的证据。然后,我们开发了一种计算效率高的方法,快速评估显性偏差对遗传度的综合贡献。最后,我们观察到,与加性效应相比,基因组位置上的显性关联在不同位点之间的相关性较低,因此我们探讨了是否可以利用它们更有信心地识别因果变异。