Suppr超能文献

与人类多种特征相关的基因组区域中选择的镶嵌模式。

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

机构信息

Vanderbilt University Medical Center, Vanderbilt University, Nashville, Tennessee, United States of America.

Department of Biological Sciences, Vanderbilt University, Nashville, Tennessee, United States of America.

出版信息

PLoS Genet. 2022 Nov 7;18(11):e1010494. doi: 10.1371/journal.pgen.1010494. eCollection 2022 Nov.

Abstract

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.

摘要

自然选择塑造了许多人类特征的遗传结构。然而,与特征变异相关的基因组区域上不同选择模式的流行程度仍知之甚少。为了解决这个问题,我们开发了一种有效的计算框架,以计算与复杂特征相关的区域中不同进化测量的正富集和负富集。我们将该框架应用于来自>900 项全基因组关联研究(GWAS)和 11 种序列约束、群体分化和等位基因年龄的进化测量的汇总统计数据,同时考虑了连锁不平衡、等位基因频率和其他潜在混杂因素。我们证明,该框架在具有不同样本量、与性状相关的 SNP 数量和分析方法的 GWAS 中产生了一致的结果。由此产生的进化图谱以空前的规模绘制了与复杂人类特征相关的基因组区域上的多种选择信号。我们检测到与性状相关区域的序列保守性存在正富集,大多数性状(290 项高功效 GWAS 中的>77%)都存在这种情况,其中包括生殖性状。许多性状也表现出对群体分化的显著正富集,特别是在头发、皮肤和色素沉着性状中。相比之下,我们在与阿尔茨海默病相关的区域中检测到广泛的平衡选择信号的负富集(51%的 GWAS),并且与晚发性阿尔茨海默病相关的区域中没有进化信号的富集。这些结果支持了在人类基因组中与复杂特征变异相关的区域普遍存在负选择的作用,但也表明不同的进化模式可能已经塑造了与性状相关的基因座。该进化图谱涵盖了各种可用 GWAS,将使人们能够探索人类基因组中遗传结构与进化过程之间的关系。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3762/9671423/8385315b68ac/pgen.1010494.g001.jpg

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验