Lineage-Specific Genome Architecture Links Enhancers and Non-coding Disease Variants to Target Gene Promoters

Abstract

SummaryLong-range interactions between regulatory elements and gene promoters play key roles in transcriptional regulation. The vast majority of interactions are uncharted, constituting a major missing link in understanding genome control. Here, we use promoter capture Hi-C to identify interacting regions of 31,253 promoters in 17 human primary hematopoietic cell types. We show that promoter interactions are highly cell type specific and enriched for links between active promoters and epigenetically marked enhancers. Promoter interactomes reflect lineage relationships of the hematopoietic tree, consistent with dynamic remodeling of nuclear architecture during differentiation. Interacting regions are enriched in genetic variants linked with altered expression of genes they contact, highlighting their functional role. We exploit this rich resource to connect non-coding disease variants to putative target promoters, prioritizing thousands of disease-candidate genes and implicating disease pathways. Our results demonstrate the power of primary cell promoter interactomes to reveal insights into genomic regulatory mechanisms underlying common diseases.

Enhancer-gene maps in the human and zebrafish genomes using evolutionary linkage conservation

“…The challenges of predicting long-distance regulatory interactions Most methods currently employed to predict long-range regulatory interactions in the human genome rely on specific cell lines [26][27][28][29][30][31]33 . These methods usually differ in their approach and the cell types or tissues they study, which might limit expectations to observe overlap in 290 their predictions, especially given that most enhancers are tissue-specific 29,[54][55][56] .…”

“…These methods usually differ in their approach and the cell types or tissues they study, which might limit expectations to observe overlap in 290 their predictions, especially given that most enhancers are tissue-specific 29,[54][55][56] . It is therefore interesting to observe that when comparing these methods with one another, the level of agreement between eQTLs-based predictions ranges from 10% to 48% (between 10% and 16% for ESCs and NECs cells, between 38% and 48% for CD34 and GM12878 cells).…”

“…Methods that have been developed to address this problem fall in three broad categories. The first uses 35 chromosomal conformation capture techniques to identify physical interaction between two loci in the genome [25][26][27][28][29][30] , but it is not clear which of these interactions are linked to a regulatory role. The second measures the correlation of transcription activity between noncoding sequences and nearby genes 31,32 , assuming the two are signatures of a coordinated regulatory function.…”

Variation in Genome-wide NF-kappaB RELA Binding Sites upon Microbial Stimuli and Identification of a Virus Response Profile

“…In addition, differentially bound peaks seemed less likely to occur at promoters compared to non-DB peaks and binding of RELA was observed at promoters of non-regulated genes suggesting the importance of 16, 2018; enhancers. Enhancers has been shown to be especially important in cell-type specific gene expression regulation 31 , they could play a particular role in stimulus-specific expression as well.…”

Twenty-First Century Glucocorticoid Receptor Molecular Biology

“…This indicates that although loss and gain of TAD loops can occur naturally as cells adapt their gene expression landscape, it is not an obligate step in gene activation/repression. Indeed, Hi-C results obtained in parallel in eight primary human hematopoietic cell types show high correspondence [68].…”