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

机译:量化优势偏差效应对Biobank级数据复杂性变异的贡献

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摘要

The proportion of variation in complex traits that can be attributed to non-additive genetic effects has been a topic of intense debate. The availability of biobank-scale datasets of genotype and trait data from unrelated individuals opens up the possibility of obtaining precise estimates of the contribution of non-additive genetic effects. We present an efficient method to estimate the variation in a complex trait that can be attributed to additive (additive heritability) and dominance deviation (dominance heritability) effects across all genotyped SNPs in a large collection of unrelated individuals. Over a wide range of genetic architectures, our method yields unbiased estimates of additive and dominance heritability. We applied our method, in turn, to array genotypes as well as imputed genotypes (at common SNPs with minor allele frequency [MAF] > 1%) and 50 quantitative traits measured in 291,273 unrelated white British individuals in the UK Biobank. Averaged across these 50 traits, we find that additive heritability on array SNPs is 21.86% while dominance heritability is 0.13% (about 0.48% of the additive heritability) with qualitatively similar results for imputed genotypes. We find no statistically significant evidence for dominance heritability (p<0.05/50 accounting for the number of traits tested) and estimate that dominance heritability is unlikely to exceed 1% for the traits analyzed. Our analyses indicate a limited contribution of dominance heritability to complex trait variation.
机译:复杂性状的变化比例可以归因于非添加性遗传效应是一个激烈辩论的主题。来自无关个人的基因型和特质数据的生物型数据集的可用性开辟了获得非添加性遗传效应贡献的精确估计的可能性。我们提出了一种有效的方法来估计复杂性状的变异,这些特征可以归因于在大型无关个体中的所有基因分型SNP中的所有基因分型的SNP中的占优势偏差(显性遗传性)效应。在广泛的遗传架构上,我们的方法产生了无偏见的添加剂和优势遗传性的估计。我们采用我们的方法,反过来,以阵列基因型以及估算基因型(在常见SNPs与次要等位基因频率[MAF]> 1%)和在英国生物库291273个无关白英个体测量50个数量性状。在这50个特征上平均,我们发现阵列SNP上的添加剂可遗传性为21.86%,而主导遗传性为0.13%(占添加遗传性的约0.48%),对于抵抗基因型的定性相似。我们发现没有统计遗传性的有明显的证据(P <0.05 / 50核算测试的特征数量),并估计分析的特征不太可能超过1%的遗传性。我们的分析表明,主要遗传性对复杂性特性变异的有限贡献。

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