edoc

Modeling of epigenome dynamics identifies transcription factors that mediate Polycomb targeting

Arnold, Phil and Schöler, Anne and Pachkov, Mikhail and Balwierz, Piotr J. and Jørgensen, Helle and Stadler, Michael B. and van Nimwegen, Erik and Schübeler, Dirk. (2013) Modeling of epigenome dynamics identifies transcription factors that mediate Polycomb targeting. Genome research, Vol. 23. S. 60-73.

Full text not available from this repository.

Official URL: http://edoc.unibas.ch/dok/A6043860

Downloads: Statistics Overview

Abstract

Although changes in chromatin are integral to transcriptional reprogramming during cellular differentiation, it is currently unclear how chromatin modifications are targeted to specific loci. To systematically identify transcription factors (TFs) that can direct chromatin changes during cell fate decisions, we model the relationship between genome-wide dynamics of chromatin marks and the local occurrence of computationally predicted TF binding sites. By applying this computational approach to a time course of Polycomb-mediated H3K27me3 marks during neuronal differentiation of murine stem cells, we identify several motifs that likely regulate the dynamics of this chromatin mark. Among these, the sites bound by REST and by the SNAIL family of TFs are predicted to transiently recruit H3K27me3 in neuronal progenitors. We validate these predictions experimentally and show that absence of REST indeed causes loss of H3K27me3 at target promoters in trans, specifically at the neuronal progenitor state. Moreover, using targeted transgenic insertion, we show that promoter fragments containing REST or SNAIL binding sites are sufficient to recruit H3K27me3 in cis, while deletion of these sites results in loss of H3K27me3. These findings illustrate that the occurrence of TF binding sites can determine chromatin dynamics. Local determination of Polycomb activity by REST and SNAIL motifs exemplifies such TF based regulation of chromatin. Furthermore, our results show that key TFs can be identified ab initio through computational modeling of epigenome data sets using a modeling approach that we make readily accessible.
Faculties and Departments:05 Faculty of Science > Departement Biozentrum > Computational & Systems Biology > Bioinformatics (van Nimwegen)
UniBasel Contributors:van Nimwegen, Erik
Item Type:Article, refereed
Bibsysno:Link to catalogue
Publisher:Cold Spring Harbor Laboratory Press
ISSN:1088-9051
Note:Publication type according to Uni Basel Research Database: Journal article
Related URLs:
Identification Number:
Last Modified:24 May 2013 09:03
Deposited On:01 Feb 2013 08:42

Repository Staff Only: item control page