Variance components analysis has emerged as a powerful tool in complex trait genetics, with applications ranging from heritability estimation to association mapping. While the application of these methods to large-scale genetic datasets can potentially reveal important insights into genetic architecture, existing methods for fitting variance components do not scale well to these datasets. Here, we present a new algorithm for variance components analysis that is accurate and highly efficient, capable of estimating one hundred variance components on a million individuals genotyped at a million SNPs in a few hours. We illustrate the utility of our method in estimating variation in a trait explained by genotyped SNPs (SNP heritability) as well in partitioning heritability across population and functional genomic annotations. Analyzing 22 diverse traits with genotypes from 300, 000 individuals across about 8 million common and low frequency SNPs (minor allele frequency > 0.1%), we observe that the allelic effect size increases with decreasing MAF (minor allele frequency) and LD (linkage disequilibrium) across the analyzed traits consistent with the action of negative selection. Partitioning heritability across 28 functional annotations, we observe enrichment of heritability in FANTOM5 enhancers in asthma, eczema, thyroid and autoimmune disorders.

中文翻译：

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数百万个基因组的有效方差成分分析

方差成分分析已成为复杂性状遗传学中的强大工具，其应用范围从遗传力估计到关联映射。虽然将这些方法应用于大规模遗传数据集可能会揭示重要的遗传结构见解，但现有的用于拟合方差成分的方法却无法很好地适应这些数据集。在这里，我们提出了一种新的方差成分分析算法，该算法准确而高效，能够在几个小时内估算出以一百万个SNP基因型分型的一百万个个体的一百个方差成分。我们说明了我们的方法在估计由基因型SNP（SNP遗传力）解释的性状变异以及在群体和功能基因组注释之间划分遗传力时的效用。分析来自300,000个个体的基因型的22个不同性状，涉及约800万个普通和低频SNP（次要等位基因频率> 0.1％），我们观察到等位基因效应大小随MAF（次要等位基因频率）和LD（连锁不平衡）的降低而增加）与否定选择的行为相一致。通过28个功能注释对遗传力进行划分，我们观察到FANTOM5增强剂在哮喘，湿疹，甲状腺和自身免疫性疾病中的遗传力丰富。我们观察到，在与负选择作用一致的已分析性状中，等位基因效应的大小随MAF（次等位基因频率）和LD（连锁不平衡）的降低而增加。通过28个功能注释对遗传力进行划分，我们观察到FANTOM5增强剂在哮喘，湿疹，甲状腺和自身免疫性疾病中的遗传力丰富。我们观察到，在与负选择作用一致的已分析性状中，等位基因效应的大小随MAF（次等位基因频率）和LD（连锁不平衡）的降低而增加。通过28个功能注释对遗传力进行划分，我们观察到FANTOM5增强剂在哮喘，湿疹，甲状腺和自身免疫性疾病中的遗传力丰富。