Quantifying the contribution of dominance deviation effects to complex trait variation in biobank-scale data

Area of Science:

• Genetics
• Quantitative Trait Analysis
• Bioinformatics

Background:

• The contribution of non-additive genetic effects to complex traits is debated.
• Large-scale biobank datasets enable precise estimation of genetic effects.

Purpose of the Study:

• To develop an efficient method for estimating additive and dominance heritability from genotyped SNPs in unrelated individuals.
• To quantify the contribution of additive and dominance genetic effects to complex traits using UK Biobank data.

Main Methods:

• Developed an efficient method to estimate additive heritability and dominance heritability.
• Applied the method to array and imputed genotypes for 50 quantitative traits in 291,273 UK Biobank participants.
• Accounted for multiple testing in statistical significance assessments.

Main Results:

• Averaged across 50 traits, additive heritability was 21.86% on array SNPs, while dominance heritability was 0.13%.
• Dominance heritability was approximately 0.48% of additive heritability, with similar findings for imputed genotypes.
• No statistically significant evidence for dominance heritability was found, suggesting it unlikely exceeds 1% for analyzed traits.

Conclusions:

• Non-additive genetic effects, specifically dominance, play a limited role in the variation of complex traits.
• The developed method provides unbiased estimates of heritability across various genetic architectures.
• Findings contribute to understanding the genetic basis of complex traits in large, diverse populations.