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Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/21376

Title: CTCF-Mediated Human 3D Genome Architecture Reveals Chromatin Topology for Transcription
Authors: Tang, Zhonghui
Luo, Oscar Junhong
Li, Xingwang
Zheng, Meizhen
Jufen Zhu, Jacqueline
Szala, Przemyslaw
Trzaskoma, Pawel
Magalska, Adriana
Wlodarczyk, Jakub
Ruszczycki, Blazej
Michalski, Paul
Piecuch, Emaly
Wang, Ping
Wang, Danjuan
Zhongyuan Tian, Simon
Penrad-Mobayed, May
Sachs, Laurent M.
Ruan, Xiaoan
We, Chia-Lin
Liu, Edison T.
Wilczynski, Grzegorz M.
Plewczynski, Dariusz
Li, Guoliang
Ruan, Yijun
Issue Date: 2015
Citation: CELL, 163 (7), p. 1611-1627
Abstract: Spatial genome organization and its effect on transcription remains a fundamental question. We applied an advanced chromatin interaction analysis by paired-end tag sequencing (ChIA-PET) strategy to comprehensively map higher-order chromosome folding and specific chromatin interactions mediated by CCCTC-binding factor (CTCF) and RNA polymerase II (RNAPII) with haplotype specificity and nucleotide resolution in different human cell lineages. We find that CTCF/cohesin-mediated interaction anchors serve as structural foci for spatial organization of constitutive genes concordant with CTCF-motif orientation, whereas RNAPII interacts within these structures by selectively drawing cell-type-specific genes toward CTCF foci for coordinated transcription. Furthermore, we show that haplotype variants and allelic interactions have differential effects on chromosome configuration, influencing gene expression, and may provide mechanistic insights into functions associated with disease susceptibility. 3D genome simulation suggests a model of chromatin folding around chromosomal axes, where CTCF is involved in defining the interface between condensed and open compartments for structural regulation. Our 3D genome strategy thus provides unique insights in the topological mechanism of human variations and diseases.
URI: http://hdl.handle.net/1942/21376
DOI: 10.1016/j.cell.2015.11.024
ISI #: 000366854200010
ISSN: 0092-8674
Category: A1
Type: Journal Contribution
Validation: ecoom, 2017
Appears in Collections: Research publications

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