Literature DB >> 22265404

Extensive promoter-centered chromatin interactions provide a topological basis for transcription regulation.

Guoliang Li1, Xiaoan Ruan, Raymond K Auerbach, Kuljeet Singh Sandhu, Meizhen Zheng, Ping Wang, Huay Mei Poh, Yufen Goh, Joanne Lim, Jingyao Zhang, Hui Shan Sim, Su Qin Peh, Fabianus Hendriyan Mulawadi, Chin Thing Ong, Yuriy L Orlov, Shuzhen Hong, Zhizhuo Zhang, Steve Landt, Debasish Raha, Ghia Euskirchen, Chia-Lin Wei, Weihong Ge, Huaien Wang, Carrie Davis, Katherine I Fisher-Aylor, Ali Mortazavi, Mark Gerstein, Thomas Gingeras, Barbara Wold, Yi Sun, Melissa J Fullwood, Edwin Cheung, Edison Liu, Wing-Kin Sung, Michael Snyder, Yijun Ruan.   

Abstract

Higher-order chromosomal organization for transcription regulation is poorly understood in eukaryotes. Using genome-wide Chromatin Interaction Analysis with Paired-End-Tag sequencing (ChIA-PET), we mapped long-range chromatin interactions associated with RNA polymerase II in human cells and uncovered widespread promoter-centered intragenic, extragenic, and intergenic interactions. These interactions further aggregated into higher-order clusters, wherein proximal and distal genes were engaged through promoter-promoter interactions. Most genes with promoter-promoter interactions were active and transcribed cooperatively, and some interacting promoters could influence each other implying combinatorial complexity of transcriptional controls. Comparative analyses of different cell lines showed that cell-specific chromatin interactions could provide structural frameworks for cell-specific transcription, and suggested significant enrichment of enhancer-promoter interactions for cell-specific functions. Furthermore, genetically-identified disease-associated noncoding elements were found to be spatially engaged with corresponding genes through long-range interactions. Overall, our study provides insights into transcription regulation by three-dimensional chromatin interactions for both housekeeping and cell-specific genes in human cells.
Copyright © 2012 Elsevier Inc. All rights reserved.

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Year:  2012        PMID: 22265404      PMCID: PMC3339270          DOI: 10.1016/j.cell.2011.12.014

Source DB:  PubMed          Journal:  Cell        ISSN: 0092-8674            Impact factor:   41.582


  33 in total

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  642 in total

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4.  Computational Approaches for Mining GRO-Seq Data to Identify and Characterize Active Enhancers.

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Authors:  Suhas S P Rao; Miriam H Huntley; Neva C Durand; Elena K Stamenova; Ivan D Bochkov; James T Robinson; Adrian L Sanborn; Ido Machol; Arina D Omer; Eric S Lander; Erez Lieberman Aiden
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Review 9.  Enhancer deregulation in cancer and other diseases.

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