量化 25 项英国生物库特征中频率相关的遗传结构，揭示负选择的作用。
Quantification of frequency-dependent genetic architectures in 25 UK Biobank traits reveals action of negative selection.
机构信息
Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, 02115, MA, USA.
Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, 02115, MA, USA.
出版信息
Nat Commun. 2019 Feb 15;10(1):790. doi: 10.1038/s41467-019-08424-6.
Understanding the role of rare variants is important in elucidating the genetic basis of human disease. Negative selection can cause rare variants to have larger per-allele effect sizes than common variants. Here, we develop a method to estimate the minor allele frequency (MAF) dependence of SNP effect sizes. We use a model in which per-allele effect sizes have variance proportional to [p(1 - p)], where p is the MAF and negative values of α imply larger effect sizes for rare variants. We estimate α for 25 UK Biobank diseases and complex traits. All traits produce negative α estimates, with best-fit mean of -0.38 (s.e. 0.02) across traits. Despite larger rare variant effect sizes, rare variants (MAF < 1%) explain less than 10% of total SNP-heritability for most traits analyzed. Using evolutionary modeling and forward simulations, we validate the α model of MAF-dependent trait effects and assess plausible values of relevant evolutionary parameters.
理解罕见变异的作用对于阐明人类疾病的遗传基础非常重要。负向选择可能导致罕见变异的每个等位基因效应大小大于常见变异。在这里，我们开发了一种估计 SNP 效应大小的次要等位基因频率（MAF）依赖性的方法。我们使用一种模型，其中每个等位基因的效应大小的方差与 [p(1-p)] 成正比，其中 p 是 MAF，α 的负值意味着罕见变异的效应大小更大。我们针对 25 个英国生物库疾病和复杂特征估计了 α。所有特征都产生了负的 α 估计值，在跨特征的最佳拟合均值为-0.38（s.e. 0.02）。尽管罕见变异的效应大小更大，但在大多数分析的特征中，罕见变异（MAF<1%）解释的 SNP 遗传力不到 10%。使用进化建模和正向模拟，我们验证了 MAF 依赖性特征效应的 α 模型，并评估了相关进化参数的合理值。
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