Genome Biology (Nov 2019)
CRUP: a comprehensive framework to predict condition-specific regulatory units
- Anna Ramisch,
- Verena Heinrich,
- Laura V. Glaser,
- Alisa Fuchs,
- Xinyi Yang,
- Philipp Benner,
- Robert Schöpflin,
- Na Li,
- Sarah Kinkley,
- Anja Römer-Hillmann,
- John Longinotto,
- Steffen Heyne,
- Beate Czepukojc,
- Sonja M. Kessler,
- Alexandra K. Kiemer,
- Cristina Cadenas,
- Laura Arrigoni,
- Nina Gasparoni,
- Thomas Manke,
- Thomas Pap,
- John A. Pospisilik,
- Jan Hengstler,
- Jörn Walter,
- Sebastiaan H. Meijsing,
- Ho-Ryun Chung,
- Martin Vingron
Affiliations
- Anna Ramisch
- Department of Computational Molecular Biology, Max Planck Institute for Molecular Genetics
- Verena Heinrich
- Department of Computational Molecular Biology, Max Planck Institute for Molecular Genetics
- Laura V. Glaser
- Department of Computational Molecular Biology, Max Planck Institute for Molecular Genetics
- Alisa Fuchs
- Otto-Warburg-Laboratory, Computational Epigenomics, Max Planck Institute for Molecular Genetics
- Xinyi Yang
- Otto-Warburg-Laboratory, Computational Epigenomics, Max Planck Institute for Molecular Genetics
- Philipp Benner
- Department of Computational Molecular Biology, Max Planck Institute for Molecular Genetics
- Robert Schöpflin
- Department of Computational Molecular Biology, Max Planck Institute for Molecular Genetics
- Na Li
- Otto-Warburg-Laboratory, Computational Epigenomics, Max Planck Institute for Molecular Genetics
- Sarah Kinkley
- Otto-Warburg-Laboratory, Computational Epigenomics, Max Planck Institute for Molecular Genetics
- Anja Römer-Hillmann
- Institute of Musculoskeletal Medicine, University Hospital Münster
- John Longinotto
- Department of Epigenetics, Max Planck Institute of Immunobiology and Epigenetics
- Steffen Heyne
- Department of Epigenetics, Max Planck Institute of Immunobiology and Epigenetics
- Beate Czepukojc
- Department of Pharmacy, Pharmaceutical Biology, University of Saarland
- Sonja M. Kessler
- Department of Pharmacy, Pharmaceutical Biology, University of Saarland
- Alexandra K. Kiemer
- Department of Pharmacy, Pharmaceutical Biology, University of Saarland
- Cristina Cadenas
- Leibniz-Institut für Arbeitsforschung (ifADo)
- Laura Arrigoni
- Department of Epigenetics, Max Planck Institute of Immunobiology and Epigenetics
- Nina Gasparoni
- Department of Genetics, University of Saarland
- Thomas Manke
- Department of Epigenetics, Max Planck Institute of Immunobiology and Epigenetics
- Thomas Pap
- Institute of Musculoskeletal Medicine, University Hospital Münster
- John A. Pospisilik
- Department of Epigenetics, Max Planck Institute of Immunobiology and Epigenetics
- Jan Hengstler
- Leibniz-Institut für Arbeitsforschung (ifADo)
- Jörn Walter
- Department of Genetics, University of Saarland
- Sebastiaan H. Meijsing
- Department of Computational Molecular Biology, Max Planck Institute for Molecular Genetics
- Ho-Ryun Chung
- Otto-Warburg-Laboratory, Computational Epigenomics, Max Planck Institute for Molecular Genetics
- Martin Vingron
- Department of Computational Molecular Biology, Max Planck Institute for Molecular Genetics
- DOI
- https://doi.org/10.1186/s13059-019-1860-7
- Journal volume & issue
-
Vol. 20,
no. 1
pp. 1 – 23
Abstract
Abstract We present the software Condition-specific Regulatory Units Prediction (CRUP) to infer from epigenetic marks a list of regulatory units consisting of dynamically changing enhancers with their target genes. The workflow consists of a novel pre-trained enhancer predictor that can be reliably applied across cell types and species, solely based on histone modification ChIP-seq data. Enhancers are subsequently assigned to different conditions and correlated with gene expression to derive regulatory units. We thoroughly test and then apply CRUP to a rheumatoid arthritis model, identifying enhancer-gene pairs comprising known disease genes as well as new candidate genes.
Keywords
- Enhancer prediction
- Enhancer dynamics
- Gene regulation
- Epigenetics
- Random forest
- Differential analysis
