Constructing 3D interaction maps from 1D epigenomes

Yun Zhu, Zhao Chen, Kai Zhang, Mengchi Wang, David Medovoy, John W. Whitaker, Bo Ding, Nan Li, Lina Zheng and Wei Wang ()
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Yun Zhu: University of California at San Diego
Zhao Chen: University of California at San Diego
Kai Zhang: University of California at San Diego
Mengchi Wang: University of California at San Diego
David Medovoy: University of California at San Diego
John W. Whitaker: University of California at San Diego
Bo Ding: University of California at San Diego
Nan Li: University of California at San Diego
Lina Zheng: University of California at San Diego
Wei Wang: University of California at San Diego

Nature Communications, 2016, vol. 7, issue 1, 1-11

Abstract: 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.

Date: 2016
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DOI: 10.1038/ncomms10812

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