Simple scaling laws control the genetic architectures of human complex traits
Simple scaling laws control the genetic architectures of human complex traits
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简单的标度法则控制人类复杂性状的遗传结构
DOI：
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发表时间：
2022
期刊：
影响因子：
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通讯作者：
Guy Sella
中科院分区：
文献类型：
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作者：
Yuval B. Simons;H. Mostafavi;Courtney J. Smith;J. Pritchard;Guy Sella
全基因组关联研究表明，复杂性状的遗传结构差异很大，包括在数量、效应大小和显著命中的等位基因频率方面。然而，目前我们缺乏一种原则性的方法来理解特征之间的异同。在这里，我们描述了一个概率模型，该模型结合了突变、漂移和个体位点的稳定选择，以及表型变异的基因组尺度模型。在该模型中，性状的结构来源于突变选择系数的分布和两个尺度参数。我们对来自英国生物银行的95个不同的、高度多基因的数量性状进行了模型拟合。值得注意的是，我们推断所有这些性状的选择系数分布相似。这种共同的分布表明，高多基因性状的结构差异主要来自两个尺度参数：突变靶大小和每个位点的遗传力，它们在性状之间以数量级变化。当考虑到这两个尺度因子时，所有95个特征的结构几乎是相同的。
Genome-wide association studies have revealed that the genetic architectures of complex traits vary widely, including in terms of the numbers, effect sizes, and allele frequencies of significant hits. However, at present we lack a principled way of understanding the similarities and differences among traits. Here, we describe a probabilistic model that combines mutation, drift, and stabilizing selection at individual sites with a genome-scale model of phenotypic variation. In this model, the architecture of a trait arises from the distribution of selection coefficients of mutations and from two scaling parameters. We fit this model for 95 diverse, highly polygenic quantitative traits from the UK Biobank. Notably, we infer similar distributions of selection coefficients across all these traits. This shared distribution implies that differences in architectures of highly polygenic traits arise mainly from the two scaling parameters: the mutational target size and heritability per site, which vary by orders of magnitude across traits. When these two scale factors are accounted for, the architectures of all 95 traits are nearly identical.
DOI：
10.1056/nejmoa1502214
发表时间：
2015-09-03
期刊：
The New England journal of medicine
影响因子：
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作者：
Claussnitzer M;Dankel SN;Kim KH;Quon G;Meuleman W;Haugen C;Glunk V;Sousa IS;Beaudry JL;Puviindran V;Abdennur NA;Liu J;Svensson PA;Hsu YH;Drucker DJ;Mellgren G;Hui CC;Hauner H;Kellis M
通讯作者：
Kellis M