A Robust Method Uncovers Significant Context-Specific Heritability in Diverse Complex Traits.

ABSTRACT: Gene-environment interactions (GxE) can be fundamental in applications ranging from functional genomics to precision medicine and is a conjectured source of substantial heritability. However, unbiased methods to profile GxE genome-wide are nascent and, as we show, cannot accommodate general environment variables, modest sample sizes, heterogeneous noise, and binary traits. To address this gap, we propose a simple, unifying mixed model for gene-environment interaction (GxEMM). In simulations and theory, we show that GxEMM can dramatically improve estimates and eliminate false positives when the assumptions of existing methods fail. We apply GxEMM to a range of human and model organism datasets and find broad evidence of context-specific genetic effects, including GxSex, GxAdversity, and GxD

SUBMITTER: Dahl A 

PROVIDER: S-EPMC7042488 | biostudies-literature | 2020 Jan

REPOSITORIES: biostudies-literature