近日，美国加州大学洛杉矶分校的Bogdan Pasaniuc和Kathryn S. Burch课题组从生物数据库规模的数据中准确估计SNP遗传力，而不考虑遗传结构。 2019年8月，国际知名学术期刊《自然—遗传学》发表了这一成果。

研究小组表明，表明基因组范围的单核苷酸多态性遗传力可以从生物库规模的数据中准确估计，而不考虑遗传结构，不需要指定遗传力模型或按等位基因频率和/或遗传缺陷率划分单核苷酸多态性。该团队从实际基因型(英国生物库，N=337K)出发，通过分析和大量模拟表明，与现有方法不同，该封闭形式估计方法在广泛的体系结构中是具有鲁棒性的。该研究团队对英国生物库的22个复杂性状的单核苷酸多态性遗传力进行了估计，并且与该模拟结果一致，而现有的生物库规模方法的产量估计值与该理论上合理的方法相差高达30%。

研究人员表示，单核苷酸多态性（SNP）遗传力是研究复杂性状的一个基本量。最近的研究表明，现有的估计全基因组单核苷酸多态性遗传力的方法在假设被违反时会产生偏差。虽然已经提出了各种方法来解释依赖频率和连锁不平衡的遗传结构，但目前还不清楚文献中报道的哪些估计是可靠的。

附：英文原文

Title: Accurate estimation of SNP-heritability from biobank-scale data irrespective of genetic architecture

Author: Kangcheng Hou, Kathryn S. Burch, Arunabha Majumdar, Huwenbo Shi, Nicholas Mancuso, Yue Wu, Sriram Sankararaman, Bogdan Pasaniuc

Issue&Volume: Volume 51 Issue 8

Abstract: SNP-heritability is a fundamental quantity in the study of complex traits. Recent studies have shown that existing methods to estimate genome-wide SNP-heritability can yield biases when their assumptions are violated. While various approaches have been proposed to account for frequency- and linkage disequilibrium (LD)-dependent genetic architectures, it remains unclear which estimates reported in the literature are reliable. Here we show that genome-wide SNP-heritability can be accurately estimated from biobank-scale data irrespective of genetic architecture, without specifying a heritability model or partitioning SNPs by allele frequency and/or LD. We show analytically and through extensive simulations starting from real genotypes (UK Biobank, N=337K) that, unlike existing methods, our closed-form estimator is robust across a wide range of architectures. We provide estimates of SNP-heritability for 22 complex traits in the UK Biobank and show that, consistent with our results in simulations, existing biobank-scale methods yield estimates up to 30% different from our theoretically-justified approach.

DOI: 10.1038/s41588-019-0465-0

Source:https://www.nature.com/articles/s41588-019-0465-0