Identifying enhancer properties associated with genetic risk for complex traits using regulome-wide association studies.
Identifying enhancer properties associated with genetic risk for complex traits using regulome-wide association studies.
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DOI：
10.1371/journal.pcbi.1010430
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发表时间：
2022-09
影响因子：
4.3
通讯作者：
中科院分区：
文献类型：
--
作者：
复杂性状的遗传风险在参与基因调控的非编码基因组区域（尤其是增强子）中高度丰富。然而，我们缺乏足够的工具来将这些破坏的特征与遗传风险联系起来。在这里，我们提出了 RWAS（调节组广泛关联研究），这是 MAGMA 软件包的一项新应用，用于识别导致疾病遗传风险的增强子的特征。 RWAS 涉及三个步骤：(i) 将基因型 SNP 分配给细胞类型或组织特异性调控特征（例如增强子）； (ii) 测试每个监管特征与可获取全基因组关联研究（GWAS）汇总统计数据的感兴趣特征的关联； (iii) 进行增强子集富集分析，以确定与性状相关的调控元件的定量或分类特征。这些步骤是作为 MAGMA 的一种新颖应用来实现的，MAGMA 是一种最初为基于基因的 GWAS 分析而开发的工具。应用 RWAS 来探究精神分裂症的遗传风险，我们发现了一类与风险相关的富含 AT 的增强子，它们在发育中的大脑中活跃，并含有具有神经发育功能的多种转录因子的结合位点。 RWAS 利用开源软件，我们提供了组织特异性增强子位置和特征的全面注释集合，包括它们的进化保守性、AT 内容以及与数百个 TF 结合位点的共定位。 RWAS 将使研究人员能够表征与 GWAS 汇总统计数据可用的任何感兴趣特征相关的调控元件的特性。增强子是通过转录因子的结合影响基因表达的调节区域。许多遗传性疾病的风险在监管区域（包括增强子）中增加。在本研究中，我们介绍了 MAGMA 软件工具的一种新颖应用，该工具能够测试增强子属性和风险之间的关联，并且我们使用这种方法来确定与精神分裂症风险相关的增强子特征。我们发现与精神分裂症风险相关的增强子在进化上是保守的，并且与不耐受突变的基因有物理接触，其中许多基因具有神经发育功能。风险相关增强子也富含 AT，并含有神经发育转录因子的结合位点。
Genetic risk for complex traits is strongly enriched in non-coding genomic regions involved in gene regulation, especially enhancers. However, we lack adequate tools to connect the characteristics of these disruptions to genetic risk. Here, we propose RWAS (Regulome Wide Association Study), a new application of the MAGMA software package to identify the characteristics of enhancers that contribute to genetic risk for disease. RWAS involves three steps: (i) assign genotyped SNPs to cell type- or tissue-specific regulatory features (e.g., enhancers); (ii) test associations of each regulatory feature with a trait of interest for which genome-wide association study (GWAS) summary statistics are available; (iii) perform enhancer-set enrichment analyses to identify quantitative or categorical features of regulatory elements that are associated with the trait. These steps are implemented as a novel application of MAGMA, a tool originally developed for gene-based GWAS analyses. Applying RWAS to interrogate genetic risk for schizophrenia, we discovered a class of risk-associated AT-rich enhancers that are active in the developing brain and harbor binding sites for multiple transcription factors with neurodevelopmental functions. RWAS utilizes open-source software, and we provide a comprehensive collection of annotations for tissue-specific enhancer locations and features, including their evolutionary conservation, AT content, and co-localization with binding sites for hundreds of TFs. RWAS will enable researchers to characterize properties of regulatory elements associated with any trait of interest for which GWAS summary statistics are available. Enhancers are regulatory regions that influence gene expression via the binding of transcription factors. Risk for many heritable diseases is enriched in regulatory regions, including enhancers. In this study, we introduce a novel application of the MAGMA software tool that enables testing for associations between enhancer attributes and risk, and we use this method to determine the enhancer characteristics that are associated with risk for schizophrenia. We found that enhancers associated with schizophrenia risk are both evolutionarily conserved and in physical contact with mutation-intolerant genes, many of which have neurodevelopmental functions. Risk-associated enhancers are also AT-rich and contain binding sites for neurodevelopmental transcription factors.
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影响因子：
46.9
作者：
Ernst J;Kellis M
通讯作者：
Kellis M
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：
64.8
作者：
Boix CA;James BT;Park YP;Meuleman W;Kellis M
通讯作者：
Kellis M
影响因子：
11
作者：
Clifton NE;Rees E;Holmans PA;Pardiñas AF;Harwood JC;Di Florio A;Kirov G;Walters JTR;O'Donovan MC;Owen MJ;Hall J;Pocklington AJ
通讯作者：
Pocklington AJ
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