An Oestrogen Receptor α-bound Human Chromatin Interactome

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Abstract

Genomes are organized into high-level 3-dimensional structures, and DNA elements separated by long genomic distances could functionally interact. Many transcription factors bind to regulatory DNA elements distant from gene promoters. While distal binding sites have been shown to regulate transcription by long-range chromatin interactions at a few loci, chromatin interactions and their impact on transcription regulation have not been investigated in a genome-wide manner. Therefore, we developed Chromatin Interaction Analysis by Paired-End Tag sequencing (ChIA-PET) for de novo detection of global chromatin interactions, and comprehensively mapped the chromatin interaction network bound by oestrogen receptor α (ERα) in the human genome. We found that most high-confidence remote ERα binding sites are anchored at gene promoters through long-range chromatin interactions, suggesting that ERα functions by extensive chromatin looping to bring genes together for coordinated transcriptional regulation. We propose that chromatin interactions constitute a primary mechanism for regulating transcription in mammalian genomes.

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Most cited references 19

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Chromosome Conformation Capture Carbon Copy (5C): a massively parallel solution for mapping interactions between genomic elements.

Josée Dostie, Todd A Richmond, Ramy Arnaout … (2006)

Physical interactions between genetic elements located throughout the genome play important roles in gene regulation and can be identified with the Chromosome Conformation Capture (3C) methodology. 3C converts physical chromatin interactions into specific ligation products, which are quantified individually by PCR. Here we present a high-throughput 3C approach, 3C-Carbon Copy (5C), that employs microarrays or quantitative DNA sequencing using 454-technology as detection methods. We applied 5C to analyze a 400-kb region containing the human beta-globin locus and a 100-kb conserved gene desert region. We validated 5C by detection of several previously identified looping interactions in the beta-globin locus. We also identified a new looping interaction in K562 cells between the beta-globin Locus Control Region and the gamma-beta-globin intergenic region. Interestingly, this region has been implicated in the control of developmental globin gene switching. 5C should be widely applicable for large-scale mapping of cis- and trans- interaction networks of genomic elements and for the study of higher-order chromosome structure.

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Genome-wide analysis of estrogen receptor binding sites.

Jason Carroll, Clifford Meyer, Jun. Song … (2006)

The estrogen receptor is the master transcriptional regulator of breast cancer phenotype and the archetype of a molecular therapeutic target. We mapped all estrogen receptor and RNA polymerase II binding sites on a genome-wide scale, identifying the authentic cis binding sites and target genes, in breast cancer cells. Combining this unique resource with gene expression data demonstrates distinct temporal mechanisms of estrogen-mediated gene regulation, particularly in the case of estrogen-suppressed genes. Furthermore, this resource has allowed the identification of cis-regulatory sites in previously unexplored regions of the genome and the cooperating transcription factors underlying estrogen signaling in breast cancer.

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Quantitative analysis of chromosome conformation capture assays (3C-qPCR).

Hélène Hagege, Petra Klous, Caroline Braem … (2007)

Chromosome conformation capture (3C) technology is a pioneering methodology that allows in vivo genomic organization to be explored at a scale encompassing a few tens to a few hundred kilobase-pairs. Understanding the folding of the genome at this scale is particularly important in mammals where dispersed regulatory elements, like enhancers or insulators, are involved in gene regulation. 3C technology involves formaldehyde fixation of cells, followed by a polymerase chain reaction (PCR)-based analysis of the frequency with which pairs of selected DNA fragments are crosslinked in the population of cells. Accurate measurements of crosslinking frequencies require the best quantification techniques. We recently adapted the real-time TaqMan PCR technology to the analysis of 3C assays, resulting in a method that more accurately determines crosslinking frequencies than current semiquantitative 3C strategies that rely on measuring the intensity of ethidium bromide-stained PCR products separated by gel electrophoresis. Here, we provide a detailed protocol for this method, which we have named 3C-qPCR. Once preliminary controls and optimizations have been performed, the whole procedure (3C assays and quantitative analyses) can be completed in 7-9 days.

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Author and article information

Journal

Journal ID (nlm-journal-id): 0410462

Journal ID (pubmed-jr-id): 6011

Journal ID (nlm-ta): Nature

Title: Nature

ISSN (Print): 0028-0836

ISSN (Electronic): 1476-4687

Publication date Nihms-submitted: 16 September 2009

Publication date (Print): 5 November 2009

Publication date PMC-release: 5 May 2010

Volume: 462

Issue: 7269

Pages: 58-64

Affiliations

[1 ]Genome Institute of Singapore, Agency for Science, Technology and Research, Singapore

[2 ]Department of Molecular Biology, Nijmegen Centre for Molecular Life Sciences, Radboud University, The Netherlands

[3 ]Department of Computer Science, School of Computing, National University of Singapore, Singapore

[4 ]Department of Biochemistry, Yong Loo Lin School of Medicine, National University of Singapore, Singapore

[5 ]School of Biological Sciences, Nanyang Technological University, Singapore

Author notes

Correspondence and requests for materials should be addressed to Y.R. ( ruanyj@ 123456gis.a-star.edu.sg ) or E.C. ( cheungcwe@ 123456gis.a-star.edu.sg ).

[* ] Corresponding authors: Yijun Ruan, PhD Genome Institute of Singapore, 60 Biopolis, Singapore 138672 T. 65 6478 8073; F. 65 6478 9059; ruanyj@ 123456gis.a-star.edu.sg Edwin Cheung, PhD Genome Institute of Singapore, 60 Biopolis, Singapore 138672 T. 65 6478 8184; F. 65 6478 9003; cheungcwe@ 123456gis.a-star.edu.sg

Author contributions M.J.F. and Y.R. conceptualized the ChIA-PET strategy. M.J.F., E.C. and Y.R. designed the experiments. M.J.F., M.H.L., Y.F.P., J.L., A.H., P.H.M., E.G.Y.C., P.Y.Y.H., W-J.W., Y.H., Y.L., P.Y.T., P.Y.C., K.D.S.A.W., B.Z., K.S.L., S.C.L., J.S.Y., R.J., K.V.D., J.S.T., Y.K.L., T.H., H.G.S., X.R., and V.C-R. performed experiments. M.J.F., X.H., Y.B.M., Y.L.O, S.V., H-S.O., P.N.A., V.B.V., Y.K.L., R.K.M.K., G.B., H.G.S., X.R., V.C-R., W-K.S., C-L.W., E.C., and Y.R. analyzed experimental data. E.T.L., E.C., and C-L.W. commented on the manuscript drafts; M.J.F. and Y.R. wrote the paper.

Article

Manuscript ID: nihpa145406

DOI: 10.1038/nature08497

PMC ID: 2774924

PubMed ID: 19890323

SO-VID: 0da7e138-42e1-44cd-9e70-e710d7c336e4

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