ScienceGeneticsPeer-reviewed journal article
Analysis of genetic dominance in the UK Biobank
Duncan S. PalmeriD, Wei ZhouiD, Liam E. AbbottiD, Emilie M. WigdoriD, Nikolas A. BayaiD, Claire L. ChurchhouseiD, Cotton Seed, Timothy PoterbaiD, Daniel A. KingiD, Masahiro KanaiiD, Alex Bloemendal, Benjamin M. NealeiD
Abstract
Classical statistical genetic theory defines dominance as a deviation from a purely additive effect. Dominance is well documented in model organisms and plant/animal breeding; outside of rare monogenic traits, however, evidence in humans is limited. We evaluated dominance effects in >1,000 phenotypes in the UK Biobank through GWAS, identifying 175 genome-wide significant loci (P < 4.7 x 10-11). Power to detect non-additive loci is low: we estimate a 20-30 fold increase in sample size is required to detect dominance loci to significance levels observed at additive loci. By deriving a new dominance form of LD-score regression, we found no evidence of a dominance contribution to phenotypic variance tagged by common variation genome-wide (median fraction 5.73 x 10-4). We introduce dominance fine-mapping to explore whether the more rapid decay of dominance linkage disequilibrium can be leveraged to find causal variants. These results provide the most comprehensive assessment of dominance trait variation in humans to date.
- organism: human
- assay: GWAS summary statistics
- research focus: fine-mapping
- approach: statistical model
- Citations
- 71
- FWCI
- 11.43
- Field percentile
- top 1%
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