Chromatin interaction networks revealed unique connectivity patterns of broad H3K4me3 domains and super enhancers in 3D chromatin

Asa Thibodeau,Dong-Guk Shin,Duygu Ucar,Eladio J Márquez,Paola Vera-Licona

doi:10.1038/s41598-017-14389-7

Asa Thibodeau, Dong-Guk Shin + Show 3 more

Open Access

https://doi.org/10.1038/s41598-017-14389-7

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Abstract

Broad domain promoters and super enhancers are regulatory elements that govern cell-specific functions and harbor disease-associated sequence variants. These elements are characterized by distinct epigenomic profiles, such as expanded deposition of histone marks H3K27ac for super enhancers and H3K4me3 for broad domains, however little is known about how they interact with each other and the rest of the genome in three-dimensional chromatin space. Using network theory methods, we studied chromatin interactions between broad domains and super enhancers in three ENCODE cell lines (K562, MCF7, GM12878) obtained via ChIA-PET, Hi-C, and Hi-CHIP assays. In these networks, broad domains and super enhancers interact more frequently with each other compared to their typical counterparts. Network measures and graphlets revealed distinct connectivity patterns associated with these regulatory elements that are robust across cell types and alternative assays. Machine learning models showed that these connectivity patterns could effectively discriminate broad domains from typical promoters and super enhancers from typical enhancers. Finally, targets of broad domains in these networks were enriched in disease-causing SNPs of cognate cell types. Taken together these results suggest a robust and unique organization of the chromatin around broad domains and super enhancers: loci critical for pathologies and cell-specific functions.

Highlights

Cell-type-specific functions of super enhancers and broad domains have been extensively studied and well established across diverse cell types and organisms[1,2,3,4], where their distinct epigenomic profiles were instrumental in their discovery
This study utilizes advanced computational methods to uncover how broad domains and super enhancers interact in the 3D chromatin space, in particular, whether they are associated with distinct connectivity patterns, whether these patterns are conserved across cell types and assays, and whether they are predictive of the cell-specific nature of promoters and enhancers
Using machine learning models based on support vector machines (SVM)[16,17], we showed that these chromatin connectivity patterns can effectively discriminate broad domains from regular promoters and super enhancers from regular enhancers

Summary

Introduction

Cell-type-specific functions of super enhancers and broad domains have been extensively studied and well established across diverse cell types and organisms[1,2,3,4], where their distinct epigenomic profiles were instrumental in their discovery. An alternative method has been developed, HiChIP12, to detect protein-centric chromatin interactions[12] using 100-fold less input material, providing an opportunity to generate such maps in primary human cells and tissues These datasets, the ones capturing protein-mediated promoter and enhancer interactions enable genomewide study of chromatin interactions between broad domains and super enhancers. This study utilizes advanced computational methods to uncover how broad domains and super enhancers interact in the 3D chromatin space, in particular, whether they are associated with distinct connectivity patterns, whether these patterns are conserved across cell types and assays, and whether they are predictive of the cell-specific nature of promoters and enhancers. We studied the clinical relevance of these annotated chromatin interaction networks by demonstrating that enhancers targeting broad domains harbor more SNPs associated to diseases of the cognate cell type

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