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基因集的跨 eQTL 图谱分析确定了遗传变异的网络效应。

Trans-eQTL mapping in gene sets identifies network effects of genetic variants.

机构信息

The Committee on Genetics, Genomics and Systems Biology, University of Chicago, Chicago, IL 60637, USA; Department of Medicine, Section of Genetic Medicine, University of Chicago, Chicago, IL 60637, USA.

Department of Medicine, Section of Genetic Medicine, University of Chicago, Chicago, IL 60637, USA.

出版信息

Cell Genom. 2024 Apr 10;4(4):100538. doi: 10.1016/j.xgen.2024.100538. Epub 2024 Apr 1.

Abstract

Nearly all trait-associated variants identified in genome-wide association studies (GWASs) are noncoding. The cis regulatory effects of these variants have been extensively characterized, but how they affect gene regulation in trans has been the subject of fewer studies because of the difficulty in detecting trans-expression quantitative loci (eQTLs). We developed trans-PCO for detecting trans effects of genetic variants on gene networks. Our simulations demonstrate that trans-PCO substantially outperforms existing trans-eQTL mapping methods. We applied trans-PCO to two gene expression datasets from whole blood, DGN (N = 913) and eQTLGen (N = 31,684), and identified 14,985 high-quality trans-eSNP-module pairs associated with 197 co-expression gene modules and biological processes. We performed colocalization analyses between GWAS loci of 46 complex traits and the trans-eQTLs. We demonstrated that the identified trans effects can help us understand how trait-associated variants affect gene regulatory networks and biological pathways.

摘要

几乎所有在全基因组关联研究 (GWAS) 中鉴定出的与性状相关的变异都是非编码的。这些变异的顺式调控作用已经得到了广泛的研究,但由于难以检测跨表达数量性状位点 (eQTL),它们如何影响基因的跨调控一直是较少研究的课题。我们开发了 trans-PCO 来检测遗传变异对基因网络的跨效应。我们的模拟表明,trans-PCO 显著优于现有的跨-eQTL 映射方法。我们将 trans-PCO 应用于两个来自全血的基因表达数据集,DGN(N=913)和 eQTLGen(N=31684),并鉴定出 14985 个与 197 个共表达基因模块和生物过程相关的高质量跨-eSNP 模块对。我们对 46 个复杂性状的 GWAS 位点和跨-eQTL 进行了共定位分析。我们证明,鉴定出的跨效应可以帮助我们了解与性状相关的变异如何影响基因调控网络和生物途径。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9b39/11019359/1dd7f5b8eb88/fx1.jpg

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