The 3D Genome Browser: a web-based browser for visualizing 3D genome organization and long-range chromatin interactions

Fan Song,Yanli Wang,Lijun Zhang,Ming Hu,Yun Li,Ting Wang,Feng Yue,Mayank N. K. Choudhary,Jie Xu,Daofeng Li,Ross Hardison,Da Kuang,Bo Zhang

doi:10.1186/s13059-018-1519-9

Abstract

Here, we introduce the 3D Genome Browser, http://3dgenome.org, which allows users to conveniently explore both their own and over 300 publicly available chromatin interaction data of different types. We design a new binary data format for Hi-C data that reduces the file size by at least a magnitude and allows users to visualize chromatin interactions over millions of base pairs within seconds. Our browser provides multiple methods linking distal cis-regulatory elements with their potential target genes. Users can seamlessly integrate thousands of other omics data to gain a comprehensive view of both regulatory landscape and 3D genome structure.

Highlights

The three-dimensional (3D) organization of mammalian genomes plays an essential role in gene regulation [1,2,3,4]
Several recent high-throughput technologies based on chromatin conformation capture (3C) [7] have emerged and have provided an unprecedented opportunity to study the genome spatial organization in a genome-wide fashion
To further examine the predicted promoter-enhancer linkages, we explored the linkage data by DNase I hypersensitive sites (DHS) in this region, which represents another method of linking distal regulatory element with their target genes

Summary

Introduction

The three-dimensional (3D) organization of mammalian genomes plays an essential role in gene regulation [1,2,3,4]. At the DNA level, distal regulatory elements such as enhancers have been shown to be in spatial proximity to their target genes. Topologically associating domains (TADs) have been suggested to be the basic unit of mammalian genome organization [5, 6]. Several recent high-throughput technologies based on chromatin conformation capture (3C) [7] have emerged (such as Hi-C [8], ChIA-PET [9], Capture-C [10], Capture Hi-C [11], PLAC-Seq [12], and HiChIP [13]) and have provided an unprecedented opportunity to study the genome spatial organization in a genome-wide fashion.

Methods

Results

Conclusion