Mosaic patterns of selection in genomic regions associated with diverse human traits

被引:4
|
作者
Abraham, Abin [1 ]
LaBella, Abigail L. [2 ,3 ,4 ,5 ]
Capra, John A. [6 ,7 ]
Rokas, Antonis [2 ,3 ,8 ,9 ]
机构
[1] Vanderbilt Univ, Med Ctr, Nashville, TN 37232 USA
[2] Vanderbilt Univ, Dept Biol Sci, Nashville, TN 37232 USA
[3] Vanderbilt Univ, Evolutionary Studies Initiat, Nashville, TN 37232 USA
[4] Univ North Carolina Charlotte, Dept Bioinformat & Genom, Charlotte, NC USA
[5] North Carolina Res Ctr, Kannapolis, NC USA
[6] Univ Calif San Francisco, Bakar Computat Hlth Sci Inst, San Francisco, CA 94143 USA
[7] Univ Calif San Francisco, Dept Epidemiol & Biostat, San Francisco, CA 94143 USA
[8] Vanderbilt Univ, Sch Med, Dept Biomed Informat, Nashville, TN 37212 USA
[9] Vanderbilt Univ, Vanderbilt Genet Inst, 221 Kirkland Hall, Nashville, TN 37235 USA
来源
PLOS GENETICS | 2022年 / 18卷 / 11期
基金
美国国家卫生研究院; 美国国家科学基金会;
关键词
ALZHEIMERS-DISEASE; HUMAN ADAPTATION; HEIGHT; LOCI; INTROGRESSION; METAANALYSIS; ANNOTATION; PREDICTION; FREQUENCY; VARIANTS;
D O I
10.1371/journal.pgen.1010494
中图分类号
Q3 [遗传学];
学科分类号
071007 ; 090102 ;
摘要
Natural selection shapes the genetic architecture of many human traits. However, the prevalence of different modes of selection on genomic regions associated with variation in traits remains poorly understood. To address this, we developed an efficient computational framework to calculate positive and negative enrichment of different evolutionary measures among regions associated with complex traits. We applied the framework to summary statistics from >900 genome-wide association studies (GWASs) and 11 evolutionary measures of sequence constraint, population differentiation, and allele age while accounting for linkage disequilibrium, allele frequency, and other potential confounders. We demonstrate that this framework yields consistent results across GWASs with variable sample sizes, numbers of trait-associated SNPs, and analytical approaches. The resulting evolutionary atlas maps diverse signatures of selection on genomic regions associated with complex human traits on an unprecedented scale. We detected positive enrichment for sequence conservation among trait-associated regions for the majority of traits (>77% of 290 high power GWASs), which included reproductive traits. Many traits also exhibited substantial positive enrichment for population differentiation, especially among hair, skin, and pigmentation traits. In contrast, we detected widespread negative enrichment for signatures of balancing selection (51% of GWASs) and absence of enrichment for evolutionary signals in regions associated with late-onset Alzheimer's disease. These results support a pervasive role for negative selection on regions of the human genome that contribute to variation in complex traits, but also demonstrate that diverse modes of evolution are likely to have shaped trait-associated loci. This atlas of evolutionary signatures across the diversity of available GWASs will enable exploration of the relationship between the genetic architecture and evolutionary processes in the human genome. Author summary Understanding how evolutionary forces shape patterns of human genomic variation is fundamental for evolutionary genomics and medicine. We developed a novel and very robust computational framework that measures enrichment for evolutionary forces acting on regions associated with variation in diverse complex traits. Application of this framework to more than 900 genome-wide association studies and 11 evolutionary measures, while accounting for potential confounders, generated a comprehensive evolutionary atlas that maps diverse signatures of selection on genomic regions associated with hundreds of complex human traits. Notably, genomic regions associated with human complex traits have been shaped by diverse modes of selection. Combined with the availability of a computational package that can perform these calculations for any set of genomic regions associated with any trait in any organism, this work is a major step forward toward understanding the relationship between genetic architecture and selection.
引用
收藏
页数:20
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