Enhancer connectome in primary human cells identifies target genes of disease-associated DNA elements

Abstract

The challenge of linking intergenic mutations to target genes has limited molecular understanding of human diseases. Here we show that H3K27ac HiChIP generates high-resolution contact maps of active enhancers and target genes in rare primary human T cell subtypes and coronary artery smooth muscle cells. Differentiation of naive T cells into T helper 17 cells or regulatory T cells creates subtype-specific enhancer–promoter interactions, specifically at regions of shared DNA accessibility. These data provide a principled means of assigning molecular functions to autoimmune and cardiovascular disease risk variants, linking hundreds of noncoding variants to putative gene targets. Target genes identified with HiChIP are further supported by CRISPR interference and activation at linked enhancers, by the presence of expression quantitative trait loci, and by allele-specific enhancer loops in patient-derived primary cells. The majority of disease-associated enhancers contact genes beyond the nearest gene in the linear genome, leading to a fourfold increase in the number of potential target genes for autoimmune and cardiovascular diseases.

BMI1 enhancer polymorphism underlies chromosome 10p12.31 association with childhood acute lymphoblastic leukemia

“…Our analyses support that BMI1 is the gene target of an enhancer element ~180Kb upstream containing SNP rs11591377, with data from recent H3K27ac HiChIP experiments 21 , as well as MethylC-seq patterns of CpG methylation across tissues, suggesting this enhancer is specific to HSCs and early B-cell progenitors. Enhancers are often tissue or cell-type specific (reviewed in Heinz et al .…”

Unveiling the Role of the Most Impactful Cardiovascular Risk Locus through Haplotype Editing

“…Our data suggest that the risk haplotype may contain SNPs that alter the function of enhancers that increase ANRIL expression (compared to the non-risk haplotype) because deleting the risk (but not non-risk) haplotype (ANRIL exons 10-19) reduces expression of the remaining upstream ANRIL exons (1-9) (Figure 5). Intriguingly, a recent paper examining long-range chromatin interactions showed that non-coding candidate regulatory regions within the 9p21.3 risk haplotype associated more strongly with the ANRIL enhancer (and also with the nearby CDKN2B enhancer) compared to the analogous region in the non-risk haplotype (Mumbach et al, 2017). This mechanism could explain at least part of the phenotype we observe, since we can mimic several key cellular and molecular phenotypes in NN KO cells via ANRIL overexpression.…”

High‐resolution mapping of cancer cell networks using co‐functional interactions

“…Understanding the complex biological underpinnings of human disease has long been a goal of network biologists (Barabási & Oltvai, ; Barabási et al , ). Because genes vary in their role and importance across diverse cell types, it has become increasingly clear that characterizing tissue‐ and cell type‐specific regulation of chromatin accessibility (Roadmap Epigenomics Consortium et al , ; Breeze et al , ), chromosome looping (Javierre et al , ; Mumbach et al , ), and gene expression (GTEx Consortium et al , ) will be central to developing a coherent understanding of disease etiology. Differences in biological pathway importance across tissues are especially vexing when modeling diseases such as cancer that specifically exploit tissue‐specific pathways and preferentially acquire mutations to regulate them.…”