| Title: | Analysis of genetic dominance in the UK Biobank |
| Journal: | Science |
| Published: | 30 Mar 2023 |
| Pubmed: | https://pubmed.ncbi.nlm.nih.gov/36996212/ |
| DOI: | https://doi.org/10.1126/science.abn8455 |
| URL: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10345642 |
| Citations: | 23 (22 in last 2 years) as of 8 Aug 2024 |
Publication 11262
WARNING: the interactive features of this website use CSS3, which your browser does not support. To use the full features of this website, please update your browser.
Abstract
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, N = 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.</p>
12 Authors
- Duncan S Palmer
- Wei Zhou
- Liam Abbott
- Emilie M Wigdor
- Nikolas Baya
- Claire Churchhouse
- Cotton Seed
- Tim Poterba
- Daniel King
- Masahiro Kanai
- Alex Bloemendal
- Benjamin M Neale
1 Application
| Application ID | Title |
|---|---|
| 31063 | Methodological extensions to estimate genetic heritability and shared risk factors for phenotypes of the UK Biobank |
Enabling scientific discoveries that improve human health