Matoba Nana, Quiroga Ivana Y, Phanstiel Douglas H, Won Hyejung
Department of Genetics, University of North Carolina; Neuroscience Center, University of North Carolina.
Thurston Arthritis Research Center, University of North Carolina.
J Vis Exp. 2020 Jan 9(155). doi: 10.3791/60428.
Genome-wide association studies (GWAS) have successfully identified hundreds of genomic loci that are associated with human traits and disease. However, because the majority of the genome-wide significant (GWS) loci fall onto the non-coding genome, the functional impact of many remain unknown. Three-dimensional chromatin interactions identified by Hi-C or its derivatives can provide useful tools to annotate these loci by linking non-coding variants to their actionable genes. Here, we outline a protocol to map GWAS non-coding variants to their putative genes using Alzheimer's disease (AD) GWAS and Hi-C datasets from human adult brain tissue. Putative causal single-nucleotide polymorphisms (SNPs) are identified by application of fine-mapping algorithms. SNPs are then mapped to their putative target genes using enhancer-promoter interactions based on Hi-C. The resulting gene set represents AD risk genes, as they are potentially regulated by AD risk variants. To garner further biological insights into molecular mechanisms underlying AD, we characterize AD risk genes using developmental brain expression data and brain single-cell expression profiles. This protocol can be expanded to any GWAS and Hi-C datasets to identify putative target genes and molecular mechanisms underlying various human traits and diseases.
全基因组关联研究（GWAS）已成功鉴定出数百个与人类性状和疾病相关的基因组位点。然而，由于大多数全基因组显著（GWS）位点位于非编码基因组上，许多位点的功能影响仍不明确。通过Hi-C或其衍生技术鉴定的三维染色质相互作用可以提供有用的工具，通过将非编码变异与其可作用的基因联系起来注释这些位点。在这里，我们概述了一种使用来自人类成人大脑组织的阿尔茨海默病（AD）GWAS和Hi-C数据集，将GWAS非编码变异映射到其推定基因的方案。通过应用精细定位算法鉴定推定的因果单核苷酸多态性（SNP）。然后基于Hi-C，利用增强子-启动子相互作用将SNP映射到其推定的靶基因。所得的基因集代表AD风险基因，因为它们可能受AD风险变异的调控。为了进一步深入了解AD潜在的分子机制，我们利用发育中的大脑表达数据和大脑单细胞表达谱对AD风险基因进行表征。该方案可以扩展到任何GWAS和Hi-C数据集，以鉴定各种人类性状和疾病潜在的靶基因和分子机制。
