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Inference of interactions between chromatin modifiers and histone modifications: from ChIP-Seq data to chromatin-signaling

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Perner,  Juliane
IMPRS for Computational Biology and Scientific Computing - IMPRS-CBSC (Kirsten Kelleher), Dept. of Computational Molecular Biology (Head: Martin Vingron), Max Planck Institute for Molecular Genetics, Max Planck Society;

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Lasserre,  Julia
Dept. of Computational Molecular Biology (Head: Martin Vingron), Max Planck Institute for Molecular Genetics, Max Planck Society;

Kinkley,  Sarah
Max Planck Society;

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Vingron,  Martin
Gene regulation (Martin Vingron), Dept. of Computational Molecular Biology (Head: Martin Vingron), Max Planck Institute for Molecular Genetics, Max Planck Society;

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Chung,  Ho-Ryun
Computational Epigenetics (Ho-Ryun Chung), Independent Junior Research Groups (OWL), Max Planck Institute for Molecular Genetics, Max Planck Society;

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Zitation

Perner, J., Lasserre, J., Kinkley, S., Vingron, M., & Chung, H.-R. (2014). Inference of interactions between chromatin modifiers and histone modifications: from ChIP-Seq data to chromatin-signaling. Nucleic Acids Research (London), 42(22), 13689-13695. doi:10.1093/nar/gku1234.


Zitierlink: https://hdl.handle.net/11858/00-001M-0000-0025-2127-8
Zusammenfassung
Chromatin modifiers and histone modifications are components of a chromatin-signaling network involved in transcription and its regulation. The interactions between chromatin modifiers and histone modifications are often unknown, are based on the analysis of few genes or are studied in vitro. Here, we apply computational methods to recover interactions between chromatin modifiers and histone modifications from genome-wide ChIP-Seq data. These interactions provide a high-confidence backbone of the chromatin-signaling network. Many recovered interactions have literature support; others provide hypotheses about yet unknown interactions. We experimentally verified two of these predicted interactions, leading to a link between H4K20me1 and members of the Polycomb Repressive Complexes 1 and 2. Our results suggest that our computationally derived interactions are likely to lead to novel biological insights required to establish the connectivity of the chromatin-signaling network involved in transcription and its regulation.