Aggregative trans-eQTL analysis detects trait-specific target gene sets in whole blood.
Aggregative trans-eQTL analysis detects trait-specific target gene sets in whole blood.
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DOI：
10.1038/s41467-022-31845-9
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发表时间：
2022-07-26
影响因子：
16.6
通讯作者：
中科院分区：
文献类型：
--
作者：
大规模的遗传关联研究已经发现了许多与性状相关的变异体，了解这些变异体在基因表达下游调控中的作用可以揭示重要的介导生物学机制。在这里，我们提出了ARCHIE，一个基于稀疏典型相关分析方法的汇总统计，以确定由已知的性状相关遗传变异反式调节的基因表达集。模拟研究表明，与标准方法相比，ARCHIE更适合于识别“核心”样基因，通过这些基因可以介导许多其他基因的作用，并且可以捕获遗传关联的疾病特异性模式。通过将ARCHIE应用于eQTLGen联盟的公开汇总统计数据，我们确定了与29个复杂性状的已知遗传变异组具有显著关联的基因集。大约一半（50.7%）的选定基因不具有任何强的反关联，并且不能通过标准方法检测到。我们通过一系列的后续分析，为靶基因的因果基础提供了进一步的证据。这些结果表明，ARCHIE是一个强有力的工具，用于识别基因组的反式调节可能与特定的复杂性状。大规模的遗传关联研究已经确定了许多影响基因表达的性状相关变异。在这里，作者介绍了ARCHIE，一种用于识别基因组的工具，这些基因的调控可能与特定的复杂性状有关。
Large scale genetic association studies have identified many trait-associated variants and understanding the role of these variants in the downstream regulation of gene-expressions can uncover important mediating biological mechanisms. Here we propose ARCHIE, a summary statistic based sparse canonical correlation analysis method to identify sets of gene-expressions trans-regulated by sets of known trait-related genetic variants. Simulation studies show that compared to standard methods, ARCHIE is better suited to identify “core”-like genes through which effects of many other genes may be mediated and can capture disease-specific patterns of genetic associations. By applying ARCHIE to publicly available summary statistics from the eQTLGen consortium, we identify gene sets which have significant evidence of trans-association with groups of known genetic variants across 29 complex traits. Around half (50.7%) of the selected genes do not have any strong trans-associations and are not detected by standard methods. We provide further evidence for causal basis of the target genes through a series of follow-up analyses. These results show ARCHIE is a powerful tool for identifying sets of genes whose trans-regulation may be related to specific complex traits. Large-scale genetic association studies have identified many trait-associated variants that influence gene expression. Here, the authors present ARCHIE, a tool for identifying sets of genes whose regulation may be related to specific complex traits.
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影响因子：
64.8
作者：
Bycroft C;Freeman C;Petkova D;Band G;Elliott LT;Sharp K;Motyer A;Vukcevic D;Delaneau O;O'Connell J;Cortes A;Welsh S;Young A;Effingham M;McVean G;Leslie S;Allen N;Donnelly P;Marchini J
通讯作者：
Marchini J
遗传对人体组织基因表达的影响。
影响因子：
64.8
作者：
GTEx Consortium;Laboratory, Data Analysis &Coordinating Center (LDACC)—Analysis Working Group;Statistical Methods groups—Analysis Working Group;Enhancing GTEx (eGTEx) groups;NIH Common Fund;NIH/NCI;NIH/NHGRI;NIH/NIMH;NIH/NIDA;Biospecimen Collection Source Site—NDRI;Biospecimen Collection Source Site—RPCI;Biospecimen Core Resource—VARI;Brain Bank Repository—University of Miami Brain Endowment Bank;Leidos Biomedical—Project Management;ELSI Study;Genome Browser Data Integration &Visualization—EBI;Genome Browser Data Integration &Visualization—UCSC Genomics Institute, University of California Santa Cruz;Lead analysts:;Laboratory, Data Analysis &Coordinating Center (LDACC):;NIH program management:;Biospecimen collection:;Pathology:;eQTL manuscript working group:;Battle A;Brown CD;Engelhardt BE;Montgomery SB
通讯作者：
Montgomery SB
影响因子：
4.5
作者：
Feng H;Mancuso N;Gusev A;Majumdar A;Major M;Pasaniuc B;Kraft P
通讯作者：
Kraft P
影响因子：
30.8
作者：
Finucane HK;Bulik-Sullivan B;Gusev A;Trynka G;Reshef Y;Loh PR;Anttila V;Xu H;Zang C;Farh K;Ripke S;Day FR;ReproGen Consortium;Schizophrenia Working Group of the Psychiatric Genomics Consortium;RACI Consortium;Purcell S;Stahl E;Lindstrom S;Perry JR;Okada Y;Raychaudhuri S;Daly MJ;Patterson N;Neale BM;Price AL
通讯作者：
Price AL
影响因子：
64.5
作者：
Boyle EA;Li YI;Pritchard JK
通讯作者：
Pritchard JK