Abstract
The human genome is tightly packaged into chromatin whose functional output depends on both one-dimensional (1D) local chromatin states and three-dimensional (3D) genome organization. Currently, chromatin modifications and 3D genome organization are measured by distinct assays. An emerging question is whether it is possible to deduce 3D interactions by integrative analysis of 1D epigenomic data and associate 3D contacts to functionality of the interacting loci. Here we present EpiTensor, an algorithm to identify 3D spatial associations within topologically associating domains (TADs) from 1D maps of histone modifications, chromatin accessibility and RNA-seq. We demonstrate that active promoter–promoter, promoter–enhancer and enhancer–enhancer associations identified by EpiTensor are highly concordant with those detected by Hi-C, ChIA-PET and eQTL analyses at 200 bp resolution. Moreover, EpiTensor has identified a set of interaction hotspots, characterized by higher chromatin and transcriptional activity as well as enriched TF and ncRNA binding across diverse cell types, which may be critical for stabilizing the local 3D interactions.
Highlights
The human genome is tightly packaged into chromatin whose functional output depends on both one-dimensional (1D) local chromatin states and three-dimensional (3D) genome organization
As most of the interactions are within topologically associating domains (TAD), we constrain our analysis within TADs and show that promoter– enhancer, promoter–promoter and enhancer–enhancer associations within identified from EpiTensor are highly concordant with those from Hi-C, ChIA-PET and eQTL experiments
We demonstrate these hotspots having higher chromatin and transcriptional activity across cell types are preferably bound by TFs and lncRNAs, and are enriched with TF motifs
Summary
The human genome is tightly packaged into chromatin whose functional output depends on both one-dimensional (1D) local chromatin states and three-dimensional (3D) genome organization. Chromosome conformation capture (3C)-based methods, including 4C and 5C, have been developed to detect physical contacts in the 3D space[2] These assays are not designed to measure 3D interactions in the entire genome. The epigenomic state of a specific locus is defined by the combination of epigenomic signals, which leads to linear segmentation of the genome; sequencing reads of epigenomic modifications are typically visualized as different tracks in a genome browser[8,9] Such 1D representation and interpretation of epigenomic data neglect the important impacts of the 3D organization of chromosomes in the cell[10]. EpiTensor identified a set of interaction hotspots that have many interacting partners We demonstrate these hotspots having higher chromatin and transcriptional activity across cell types are preferably bound by TFs and lncRNAs, and are enriched with TF motifs
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