Dataset Information

A compendium of promoter-centered long-range chromatin interactions in the human genome.

ABSTRACT: A large number of putative cis-regulatory sequences have been annotated in the human genome, but the genes they control remain poorly defined. To bridge this gap, we generate maps of long-range chromatin interactions centered on 18,943 well-annotated promoters for protein-coding genes in 27 human cell/tissue types. We use this information to infer the target genes of 70,329 candidate regulatory elements and suggest potential regulatory function for 27,325 noncoding sequence variants associated with 2,117 physiological traits and diseases. Integrative analysis of these promoter-centered interactome maps reveals widespread enhancer-like promoters involved in gene regulation and common molecular pathways underlying distinct groups of human traits and diseases.

SUBMITTER: Jung I

PROVIDER: S-EPMC6778519 | biostudies-literature | 2019 Oct

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

A compendium of promoter-centered long-range chromatin interactions in the human genome.

Jung Inkyung I Schmitt Anthony A Diao Yarui Y Lee Andrew J AJ Liu Tristin T Yang Dongchan D Tan Catherine C Eom Junghyun J Chan Marilynn M Chee Sora S Chiang Zachary Z Kim Changyoun C Masliah Eliezer E Barr Cathy L CL Li Bin B Kuan Samantha S Kim Dongsup D Ren Bing B

Nature genetics 20190909 10

A large number of putative cis-regulatory sequences have been annotated in the human genome, but the genes they control remain poorly defined. To bridge this gap, we generate maps of long-range chromatin interactions centered on 18,943 well-annotated promoters for protein-coding genes in 27 human cell/tissue types. We use this information to infer the target genes of 70,329 candidate regulatory elements and suggest potential regulatory function for 27,325 noncoding sequence variants associated w ...[more]

PMID: 31501517

Similar Datasets

Project description:MotivationPromoter-centered chromatin interactions, which include promoter-enhancer (PE) and promoter-promoter (PP) interactions, are important to decipher gene regulation and disease mechanisms. The development of next-generation sequencing technologies such as promoter capture Hi-C (pcHi-C) leads to the discovery of promoter-centered chromatin interactions. However, pcHi-C experiments are expensive and thus may be unavailable for tissues/cell types of interest. In addition, these experiments may be underpowered due to insufficient sequencing depth or various artifacts, which results in a limited finding of interactions. Most existing computational methods for predicting chromatin interactions are based on in situ Hi-C and can detect chromatin interactions across the entire genome. However, they may not be optimal for predicting promoter-centered chromatin interactions.ResultsWe develop a supervised multi-modal deep learning model, which utilizes a comprehensive set of features such as genomic sequence, epigenetic signal, anchor distance, evolutionary features and DNA structural features to predict tissue/cell type-specific PE and PP interactions. We further extend the deep learning model in a multi-task learning and a transfer learning framework and demonstrate that the proposed approach outperforms state-of-the-art deep learning methods. Moreover, the proposed approach can achieve comparable prediction performance using predefined biologically relevant tissues/cell types compared to using all tissues/cell types in the pretraining especially for predicting PE interactions. The prediction performance can be further improved by using computationally inferred biologically relevant tissues/cell types in the pretraining, which are defined based on the common genes in the proximity of two anchors in the chromatin interactions.Availability and implementationhttps://github.com/lichen-lab/DeepPHiC.Supplementary informationSupplementary data are available at Bioinformatics online.

Project description:In multicellular organisms, transcription regulation is one of the central mechanisms modelling lineage differentiation and cell-fate determination. Transcription requires dynamic chromatin configurations between promoters and their corresponding distal regulatory elements. It is believed that their communication occurs within large discrete foci of aggregated RNA polymerases termed transcription factories in three-dimensional nuclear space. However, the dynamic nature of chromatin connectivity has not been characterized at the genome-wide level. Here, through a chromatin interaction analysis with paired-end tagging approach using an antibody that primarily recognizes the pre-initiation complexes of RNA polymerase II, we explore the transcriptional interactomes of three mouse cells of progressive lineage commitment, including pluripotent embryonic stem cells, neural stem cells and neurosphere stem/progenitor cells. Our global chromatin connectivity maps reveal approximately 40,000 long-range interactions, suggest precise enhancer-promoter associations and delineate cell-type-specific chromatin structures. Analysis of the complex regulatory repertoire shows that there are extensive colocalizations among promoters and distal-acting enhancers. Most of the enhancers associate with promoters located beyond their nearest active genes, indicating that the linear juxtaposition is not the only guiding principle driving enhancer target selection. Although promoter-enhancer interactions exhibit high cell-type specificity, promoters involved in interactions are found to be generally common and mostly active among different cells. Chromatin connectivity networks reveal that the pivotal genes of reprogramming functions are transcribed within physical proximity to each other in embryonic stem cells, linking chromatin architecture to coordinated gene expression. Our study sets the stage for the full-scale dissection of spatial and temporal genome structures and their roles in orchestrating development.

Dataset Information

A compendium of promoter-centered long-range chromatin interactions in the human genome.

Publications

A compendium of promoter-centered long-range chromatin interactions in the human genome.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets