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Genotype-by-environment interactions inferred from genetic effects on phenotypic variability in the UK Biobank.


ABSTRACT: Genotype-by-environment interaction (GEI) is a fundamental component in understanding complex trait variation. However, it remains challenging to identify genetic variants with GEI effects in humans largely because of the small effect sizes and the difficulty of monitoring environmental fluctuations. Here, we demonstrate that GEI can be inferred from genetic variants associated with phenotypic variability in a large sample without the need of measuring environmental factors. We performed a genome-wide variance quantitative trait locus (vQTL) analysis of ~5.6 million variants on 348,501 unrelated individuals of European ancestry for 13 quantitative traits in the UK Biobank and identified 75 significant vQTLs with P < 2.0 × 10-9 for 9 traits, especially for those related to obesity. Direct GEI analysis with five environmental factors showed that the vQTLs were strongly enriched with GEI effects. Our results indicate pervasive GEI effects for obesity-related traits and demonstrate the detection of GEI without environmental data.

SUBMITTER: Wang H 

PROVIDER: S-EPMC6693916 | biostudies-literature | 2019 Aug

REPOSITORIES: biostudies-literature

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Genotype-by-environment interactions inferred from genetic effects on phenotypic variability in the UK Biobank.

Wang Huanwei H   Zhang Futao F   Zeng Jian J   Wu Yang Y   Kemper Kathryn E KE   Xue Angli A   Zhang Min M   Powell Joseph E JE   Goddard Michael E ME   Wray Naomi R NR   Visscher Peter M PM   McRae Allan F AF   Yang Jian J  

Science advances 20190814 8


Genotype-by-environment interaction (GEI) is a fundamental component in understanding complex trait variation. However, it remains challenging to identify genetic variants with GEI effects in humans largely because of the small effect sizes and the difficulty of monitoring environmental fluctuations. Here, we demonstrate that GEI can be inferred from genetic variants associated with phenotypic variability in a large sample without the need of measuring environmental factors. We performed a genom  ...[more]

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