Annotating genetic variants to target genes using H-MAGMA.
Annotating genetic variants to target genes using H-MAGMA.
复制标题
使用 H-MAGMA 将遗传变异注释到目标基因。
DOI：
10.1038/s41596-022-00745-z
复制
发表时间：
2023
期刊：
影响因子：
14.8
通讯作者：
Won,Hyejung
中科院分区：
文献类型：
--
作者：
Sey,NancyYA;Pratt,BrandonM;Won,Hyejung
现代基因组学的一个突出目标是系统地预测与复杂性状相关的非编码变异的功能结果。为了解决这个问题，我们开发了Hi-C耦合的基因组注释多标记分析(H-MAGMA)，它建立在传统的MAGMA-一种基于基因的分析工具，将变体分配给他们的目标基因-通过结合3D染色质配置来分配他们可能的目标基因的变体。应用这种方法，我们确定了与广泛的大脑疾病有关的关键生物学途径，并展示了它在补充其他功能基因组资源方面的有效性，例如基于表达数量性状基因座的变异注释。在这里，我们提供了一个详细的协议，用于通过使用来自成人人脑的染色质相互作用数据来生成H-MAGMA变体基因注释文件。此外，我们提供了一个例子，说明H-MAGMA是如何通过使用帕金森氏病的全基因组关联研究汇总统计来运行的。最后，我们生成了28种组织和细胞类型的变异基因注释文件，希望为研究一系列复杂的遗传疾病的研究人员提供一个资源。对于任何可获得Hi-C数据的单元类型，H-Magma可以在<；2小时内完成。
An outstanding goal in modern genomics is to systematically predict the functional outcome of noncoding variation associated with complex traits. To address this, we developed Hi-C-coupled multi-marker analysis of genomic annotation (H-MAGMA), which builds on traditional MAGMA—a gene-based analysis tool that assigns variants to their target genes—by incorporating 3D chromatin configuration in assigning variants to their putative target genes. Applying this approach, we identified key biological pathways implicated in a wide range of brain disorders and showed its utility in complementing other functional genomic resources such as expression quantitative trait loci–based variant annotation. Here, we provide a detailed protocol for generating the H-MAGMA variant-gene annotation file by using chromatin interaction data from the adult human brain. In addition, we provide an example of how H-MAGMA is run by using genome-wide association study summary statistics of Parkinson’s disease. Lastly, we generated variant-gene annotation files for 28 tissues and cell types, with the hope of contributing a resource for researchers studying a broad set of complex genetic disorders. H-MAGMA can be performed in <2 h for any cell type in which Hi-C data are available.