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甲基化 QTL 和增强子-靶基因图谱与精神分裂症 GWAS 汇总结果的整合确定了新的基因。

Integration of methylation QTL and enhancer-target gene maps with schizophrenia GWAS summary results identifies novel genes.

机构信息

Department of Statistics, Florida State University, Tallahassee, FL, USA.

Division of Biostatistics, University of Minnesota, Minneapolis, MN, USA.

出版信息

Bioinformatics. 2019 Oct 1;35(19):3576-3583. doi: 10.1093/bioinformatics/btz161.

Abstract

MOTIVATION

Most trait-associated genetic variants identified in genome-wide association studies (GWASs) are located in non-coding regions of the genome and thought to act through their regulatory roles.

RESULTS

To account for enriched association signals in DNA regulatory elements, we propose a novel and general gene-based association testing strategy that integrates enhancer-target gene pairs and methylation quantitative trait locus data with GWAS summary results; it aims to both boost statistical power for new discoveries and enhance mechanistic interpretability of any new discovery. By reanalyzing two large-scale schizophrenia GWAS summary datasets, we demonstrate that the proposed method could identify some significant and novel genes (containing no genome-wide significant SNPs nearby) that would have been missed by other competing approaches, including the standard and some integrative gene-based association methods, such as one incorporating enhancer-target gene pairs and one integrating expression quantitative trait loci.

AVAILABILITY AND IMPLEMENTATION

Software: wuchong.org/egmethyl.html.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

摘要

动机

在全基因组关联研究(GWAS)中发现的大多数与特征相关的遗传变异位于基因组的非编码区域,被认为通过其调节作用发挥作用。

结果

为了解释 DNA 调节元件中富集的关联信号,我们提出了一种新颖而通用的基于基因的关联测试策略,该策略整合了增强子-靶基因对和甲基化数量性状基因座数据与 GWAS 汇总结果;其旨在提高新发现的统计能力,并增强任何新发现的机制解释能力。通过重新分析两个大型精神分裂症 GWAS 汇总数据集,我们证明了所提出的方法可以识别一些重要的新基因(附近没有全基因组显著 SNP),而其他竞争方法(包括标准和一些整合基因的关联方法,例如整合增强子-靶基因对的方法和整合表达数量性状基因座的方法)可能会错过这些基因。

可用性和实现

软件:wuchong.org/egmethyl.html。

补充信息

补充数据可在“Bioinformatics”在线获取。

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