1
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Maji RK, Czepukojc B, Scherer M, Tierling S, Cadenas C, Gianmoena K, Gasparoni N, Nordström K, Gasparoni G, Laggai S, Yang X, Sinha A, Ebert P, Falk-Paulsen M, Kinkley S, Hoppstädter J, Chung HR, Rosenstiel P, Hengstler JG, Walter J, Schulz MH, Kessler SM, Kiemer AK. Alterations in the hepatocyte epigenetic landscape in steatosis. Epigenetics Chromatin 2023; 16:30. [PMID: 37415213 DOI: 10.1186/s13072-023-00504-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/19/2023] [Accepted: 06/21/2023] [Indexed: 07/08/2023] Open
Abstract
Fatty liver disease or the accumulation of fat in the liver, has been reported to affect the global population. This comes with an increased risk for the development of fibrosis, cirrhosis, and hepatocellular carcinoma. Yet, little is known about the effects of a diet containing high fat and alcohol towards epigenetic aging, with respect to changes in transcriptional and epigenomic profiles. In this study, we took up a multi-omics approach and integrated gene expression, methylation signals, and chromatin signals to study the epigenomic effects of a high-fat and alcohol-containing diet on mouse hepatocytes. We identified four relevant gene network clusters that were associated with relevant pathways that promote steatosis. Using a machine learning approach, we predict specific transcription factors that might be responsible to modulate the functionally relevant clusters. Finally, we discover four additional CpG loci and validate aging-related differential CpG methylation. Differential CpG methylation linked to aging showed minimal overlap with altered methylation in steatosis.
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Affiliation(s)
- Ranjan Kumar Maji
- Institute for Cardiovascular Regeneration, Goethe-University, 60590, Frankfurt, Germany
- German Centre for Cardiovascular Research (DZHK), Partner Site Rhine-Main, 60590, Frankfurt, Germany
| | - Beate Czepukojc
- Department of Pharmacy, Pharmaceutical Biology, Saarland University, 66123, Saarbrücken, Germany
| | - Michael Scherer
- Centre for Genomic Regulation (CRG), Barcelona Institute of Science and Technology (BIST), 08003, Barcelona, Spain
| | - Sascha Tierling
- Department of Genetics, Saarland University, 66123, Saarbrücken, Germany
| | - Cristina Cadenas
- IfADo: Leibniz Research Centre for Working Environment and Human Factors, Dortmund, Germany
| | - Kathrin Gianmoena
- IfADo: Leibniz Research Centre for Working Environment and Human Factors, Dortmund, Germany
| | - Nina Gasparoni
- Department of Genetics, Saarland University, 66123, Saarbrücken, Germany
| | - Karl Nordström
- Department of Genetics, Saarland University, 66123, Saarbrücken, Germany
| | - Gilles Gasparoni
- Department of Genetics, Saarland University, 66123, Saarbrücken, Germany
| | - Stephan Laggai
- Department of Pharmacy, Pharmaceutical Biology, Saarland University, 66123, Saarbrücken, Germany
| | - Xinyi Yang
- Institute of Medical Bioinformatics and Biostatistics, Philipps University of Marburg, 35032, Marburg, Germany
| | - Anupam Sinha
- Institute of Clinical Molecular Biology, Christian-Albrechts-University, 24105, Kiel, Germany
| | - Peter Ebert
- Core Unit Bioinformatics, Medical Faculty, Heinrich Heine University, 40225, Düsseldorf, Germany
- Department of Computational Biology and Applied Algorithmics, Max Planck Institute for Informatics, 66123, Saarbrücken, Germany
| | - Maren Falk-Paulsen
- Institute of Clinical Molecular Biology, Christian-Albrechts-University, 24105, Kiel, Germany
| | - Sarah Kinkley
- Department of Computational Molecular Biology, Max Planck Institute for Molecular Genetics, 14195, Berlin, Germany
| | - Jessica Hoppstädter
- Department of Pharmacy, Pharmaceutical Biology, Saarland University, 66123, Saarbrücken, Germany
| | - Ho-Ryun Chung
- Institute of Medical Bioinformatics and Biostatistics, Philipps University of Marburg, 35032, Marburg, Germany
| | - Philip Rosenstiel
- Institute of Clinical Molecular Biology, Christian-Albrechts-University, 24105, Kiel, Germany
| | - Jan G Hengstler
- IfADo: Leibniz Research Centre for Working Environment and Human Factors, Dortmund, Germany
| | - Jörn Walter
- Department of Genetics, Saarland University, 66123, Saarbrücken, Germany
| | - Marcel H Schulz
- Institute for Cardiovascular Regeneration, Goethe-University, 60590, Frankfurt, Germany.
- German Centre for Cardiovascular Research (DZHK), Partner Site Rhine-Main, 60590, Frankfurt, Germany.
- Department of Computational Biology and Applied Algorithmics, Max Planck Institute for Informatics, 66123, Saarbrücken, Germany.
- Excellence Cluster on Multimodal Computing and Interaction, Saarland University, 66123, Saarbrücken, Germany.
| | - Sonja M Kessler
- Department of Pharmacy, Pharmaceutical Biology, Saarland University, 66123, Saarbrücken, Germany.
- Institute of Pharmacy, Experimental Pharmacology for Natural Sciences, Martin Luther University Halle-Wittenberg, Halle, Germany.
- Halle Research Centre for Drug Therapy (HRCDT), Halle, Germany.
| | - Alexandra K Kiemer
- Department of Pharmacy, Pharmaceutical Biology, Saarland University, 66123, Saarbrücken, Germany.
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2
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Gianmoena K, Gasparoni N, Jashari A, Gabrys P, Grgas K, Ghallab A, Nordström K, Gasparoni G, Reinders J, Edlund K, Godoy P, Schriewer A, Hayen H, Hudert CA, Damm G, Seehofer D, Weiss TS, Boor P, Anders HJ, Motrapu M, Jansen P, Schiergens TS, Falk-Paulsen M, Rosenstiel P, Lisowski C, Salido E, Marchan R, Walter J, Hengstler JG, Cadenas C. Epigenomic and transcriptional profiling identifies impaired glyoxylate detoxification in NAFLD as a risk factor for hyperoxaluria. Cell Rep 2021; 36:109526. [PMID: 34433051 DOI: 10.1016/j.celrep.2021.109526] [Citation(s) in RCA: 22] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/13/2020] [Revised: 05/12/2021] [Accepted: 07/22/2021] [Indexed: 02/07/2023] Open
Abstract
Epigenetic modifications (e.g. DNA methylation) in NAFLD and their contribution to disease progression and extrahepatic complications are poorly explored. Here, we use an integrated epigenome and transcriptome analysis of mouse NAFLD hepatocytes and identify alterations in glyoxylate metabolism, a pathway relevant in kidney damage via oxalate release-a harmful waste product and kidney stone-promoting factor. Downregulation and hypermethylation of alanine-glyoxylate aminotransferase (Agxt), which detoxifies glyoxylate, preventing excessive oxalate accumulation, is accompanied by increased oxalate formation after metabolism of the precursor hydroxyproline. Viral-mediated Agxt transfer or inhibiting hydroxyproline catabolism rescues excessive oxalate release. In human steatotic hepatocytes, AGXT is also downregulated and hypermethylated, and in NAFLD adolescents, steatosis severity correlates with urinary oxalate excretion. Thus, this work identifies a reduced capacity of the steatotic liver to detoxify glyoxylate, triggering elevated oxalate, and provides a mechanistic explanation for the increased risk of kidney stones and chronic kidney disease in NAFLD patients.
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Affiliation(s)
- Kathrin Gianmoena
- Department of Toxicology, Leibniz-Research Centre for Working Environment and Human Factors at the TU Dortmund (IfADo), 44139 Dortmund, Germany
| | - Nina Gasparoni
- Department of Genetics, Saarland University, 66123 Saarbrücken, Germany
| | - Adelina Jashari
- Department of Toxicology, Leibniz-Research Centre for Working Environment and Human Factors at the TU Dortmund (IfADo), 44139 Dortmund, Germany
| | - Philipp Gabrys
- Department of Toxicology, Leibniz-Research Centre for Working Environment and Human Factors at the TU Dortmund (IfADo), 44139 Dortmund, Germany
| | - Katharina Grgas
- Department of Toxicology, Leibniz-Research Centre for Working Environment and Human Factors at the TU Dortmund (IfADo), 44139 Dortmund, Germany
| | - Ahmed Ghallab
- Department of Toxicology, Leibniz-Research Centre for Working Environment and Human Factors at the TU Dortmund (IfADo), 44139 Dortmund, Germany; Department of Forensic and Veterinary Toxicology, Faculty of Veterinary Medicine, South Valley University, 83523 Qena, Egypt
| | - Karl Nordström
- Department of Genetics, Saarland University, 66123 Saarbrücken, Germany
| | - Gilles Gasparoni
- Department of Genetics, Saarland University, 66123 Saarbrücken, Germany
| | - Jörg Reinders
- Department of Toxicology, Leibniz-Research Centre for Working Environment and Human Factors at the TU Dortmund (IfADo), 44139 Dortmund, Germany
| | - Karolina Edlund
- Department of Toxicology, Leibniz-Research Centre for Working Environment and Human Factors at the TU Dortmund (IfADo), 44139 Dortmund, Germany
| | - Patricio Godoy
- Department of Toxicology, Leibniz-Research Centre for Working Environment and Human Factors at the TU Dortmund (IfADo), 44139 Dortmund, Germany
| | - Alexander Schriewer
- Department of Analytical Chemistry, Institute of Inorganic and Analytical Chemistry, University of Münster, 48149 Münster, Germany
| | - Heiko Hayen
- Department of Analytical Chemistry, Institute of Inorganic and Analytical Chemistry, University of Münster, 48149 Münster, Germany
| | - Christian A Hudert
- Department of Pediatric Gastroenterology, Hepatology and Metabolic Diseases, Charité-University Medicine Berlin, 13353 Berlin, Germany
| | - Georg Damm
- Department of Hepatobiliary Surgery and Visceral Transplantation, University of Leipzig, 04103 Leipzig, Germany; Department of General-, Visceral- and Transplantation Surgery, Charité University Medicine Berlin, 13353 Berlin, Germany
| | - Daniel Seehofer
- Department of Hepatobiliary Surgery and Visceral Transplantation, University of Leipzig, 04103 Leipzig, Germany; Department of General-, Visceral- and Transplantation Surgery, Charité University Medicine Berlin, 13353 Berlin, Germany
| | - Thomas S Weiss
- University Children Hospital (KUNO), University Hospital Regensburg, 93053 Regensburg, Germany
| | - Peter Boor
- Institute of Pathology and Department of Nephrology, University Clinic of RWTH Aachen, 52074 Aachen, Germany
| | - Hans-Joachim Anders
- Department of Medicine IV, Renal Division, University Hospital, Ludwig-Maximilians-University Munich, 80336 Munich, Germany
| | - Manga Motrapu
- Department of Medicine IV, Renal Division, University Hospital, Ludwig-Maximilians-University Munich, 80336 Munich, Germany
| | - Peter Jansen
- Maastricht Centre for Systems Biology, University of Maastricht, 6229 Maastricht, the Netherlands
| | - Tobias S Schiergens
- Biobank of the Department of General, Visceral and Transplant Surgery, Ludwig-Maximilians-University Munich, 81377 Munich, Germany
| | - Maren Falk-Paulsen
- Institute of Clinical Molecular Biology (IKMB), Kiel University and University Hospital Schleswig Holstein, Campus Kiel, 24105 Kiel, Germany
| | - Philip Rosenstiel
- Institute of Clinical Molecular Biology (IKMB), Kiel University and University Hospital Schleswig Holstein, Campus Kiel, 24105 Kiel, Germany
| | - Clivia Lisowski
- Institute of Experimental Immunology, University Hospital Bonn, Rheinische-Friedrich-Wilhelms University Bonn, 53127 Bonn, Germany
| | - Eduardo Salido
- Hospital Universitario de Canarias, Universidad La Laguna, CIBERER, 38320 Tenerife, Spain
| | - Rosemarie Marchan
- Department of Toxicology, Leibniz-Research Centre for Working Environment and Human Factors at the TU Dortmund (IfADo), 44139 Dortmund, Germany
| | - Jörn Walter
- Department of Genetics, Saarland University, 66123 Saarbrücken, Germany
| | - Jan G Hengstler
- Department of Toxicology, Leibniz-Research Centre for Working Environment and Human Factors at the TU Dortmund (IfADo), 44139 Dortmund, Germany
| | - Cristina Cadenas
- Department of Toxicology, Leibniz-Research Centre for Working Environment and Human Factors at the TU Dortmund (IfADo), 44139 Dortmund, Germany.
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3
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Nordström KJV, Schmidt F, Gasparoni N, Salhab A, Gasparoni G, Kattler K, Müller F, Ebert P, Costa IG, Pfeifer N, Lengauer T, Schulz MH, Walter J. Unique and assay specific features of NOMe-, ATAC- and DNase I-seq data. Nucleic Acids Res 2020; 47:10580-10596. [PMID: 31584093 PMCID: PMC6847574 DOI: 10.1093/nar/gkz799] [Citation(s) in RCA: 22] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/06/2019] [Revised: 08/31/2019] [Accepted: 09/11/2019] [Indexed: 01/01/2023] Open
Abstract
Chromatin accessibility maps are important for the functional interpretation of the genome. Here, we systematically analysed assay specific differences between DNase I-seq, ATAC-seq and NOMe-seq in a side by side experimental and bioinformatic setup. We observe that most prominent nucleosome depleted regions (NDRs, e.g. in promoters) are roboustly called by all three or at least two assays. However, we also find a high proportion of assay specific NDRs that are often ‘called’ by only one of the assays. We show evidence that these assay specific NDRs are indeed genuine open chromatin sites and contribute important information for accurate gene expression prediction. While technically ATAC-seq and DNase I-seq provide a superb high NDR calling rate for relatively low sequencing costs in comparison to NOMe-seq, NOMe-seq singles out for its genome-wide coverage allowing to not only detect NDRs but also endogenous DNA methylation and as we show here genome wide segmentation into heterochromatic B domains and local phasing of nucleosomes outside of NDRs. In summary, our comparisons strongly suggest to consider assay specific differences for the experimental design and for generalized and comparative functional interpretations.
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Affiliation(s)
| | - Florian Schmidt
- Department of Computational Biology and Applied Algorithmics, Max Planck Institute for Informatics, 66123 Saarbrücken, Germany.,Excellence Cluster on Multimodal Computing and Interaction, Saarland University, 66123 Saarbrücken, Germany
| | - Nina Gasparoni
- Department of Genetics, Saarland University, 66123 Saarbrücken, Germany
| | | | - Gilles Gasparoni
- Department of Genetics, Saarland University, 66123 Saarbrücken, Germany
| | - Kathrin Kattler
- Department of Genetics, Saarland University, 66123 Saarbrücken, Germany
| | - Fabian Müller
- Department of Computational Biology and Applied Algorithmics, Max Planck Institute for Informatics, 66123 Saarbrücken, Germany
| | - Peter Ebert
- Department of Computational Biology and Applied Algorithmics, Max Planck Institute for Informatics, 66123 Saarbrücken, Germany
| | - Ivan G Costa
- Institute for Computational Genomics, Joint Research Center for Computational Biomedicine, RWTH Aachen University Medical School, 52074 Aachen, Germany
| | | | - Nico Pfeifer
- Department of Computational Biology and Applied Algorithmics, Max Planck Institute for Informatics, 66123 Saarbrücken, Germany
| | - Thomas Lengauer
- Department of Computational Biology and Applied Algorithmics, Max Planck Institute for Informatics, 66123 Saarbrücken, Germany
| | - Marcel H Schulz
- Department of Computational Biology and Applied Algorithmics, Max Planck Institute for Informatics, 66123 Saarbrücken, Germany.,Excellence Cluster on Multimodal Computing and Interaction, Saarland University, 66123 Saarbrücken, Germany
| | - Jörn Walter
- Department of Genetics, Saarland University, 66123 Saarbrücken, Germany
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4
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Ramisch A, Heinrich V, Glaser LV, Fuchs A, Yang X, Benner P, Schöpflin R, Li N, Kinkley S, Römer-Hillmann A, Longinotto J, Heyne S, Czepukojc B, Kessler SM, Kiemer AK, Cadenas C, Arrigoni L, Gasparoni N, Manke T, Pap T, Pospisilik JA, Hengstler J, Walter J, Meijsing SH, Chung HR, Vingron M. CRUP: a comprehensive framework to predict condition-specific regulatory units. Genome Biol 2019; 20:227. [PMID: 31699133 PMCID: PMC6839171 DOI: 10.1186/s13059-019-1860-7] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/11/2018] [Accepted: 10/14/2019] [Indexed: 02/06/2023] Open
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.
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Affiliation(s)
- Anna Ramisch
- Department of Computational Molecular Biology, Max Planck Institute for Molecular Genetics, Berlin, 14195, Germany
| | - Verena Heinrich
- Department of Computational Molecular Biology, Max Planck Institute for Molecular Genetics, Berlin, 14195, Germany
| | - Laura V Glaser
- Department of Computational Molecular Biology, Max Planck Institute for Molecular Genetics, Berlin, 14195, Germany
| | - Alisa Fuchs
- Otto-Warburg-Laboratory, Computational Epigenomics, Max Planck Institute for Molecular Genetics, Berlin, 14195, Germany
| | - Xinyi Yang
- Otto-Warburg-Laboratory, Computational Epigenomics, Max Planck Institute for Molecular Genetics, Berlin, 14195, Germany
| | - Philipp Benner
- Department of Computational Molecular Biology, Max Planck Institute for Molecular Genetics, Berlin, 14195, Germany
| | - Robert Schöpflin
- Department of Computational Molecular Biology, Max Planck Institute for Molecular Genetics, Berlin, 14195, Germany
| | - Na Li
- Otto-Warburg-Laboratory, Computational Epigenomics, Max Planck Institute for Molecular Genetics, Berlin, 14195, Germany
| | - Sarah Kinkley
- Otto-Warburg-Laboratory, Computational Epigenomics, Max Planck Institute for Molecular Genetics, Berlin, 14195, Germany
| | - Anja Römer-Hillmann
- Institute of Musculoskeletal Medicine, University Hospital Münster, Münster, 48149, Germany
| | - John Longinotto
- Department of Epigenetics, Max Planck Institute of Immunobiology and Epigenetics, Freiburg, 78108, Germany
| | - Steffen Heyne
- Department of Epigenetics, Max Planck Institute of Immunobiology and Epigenetics, Freiburg, 78108, Germany
| | - Beate Czepukojc
- Department of Pharmacy, Pharmaceutical Biology, University of Saarland, Saarbrücken, 66041, Germany
| | - Sonja M Kessler
- Department of Pharmacy, Pharmaceutical Biology, University of Saarland, Saarbrücken, 66041, Germany
- Department of Pharmacology and Toxicology for Natural Science, Institute of Pharmacy, Martin Luther University Halle-Wittenberg, Halle (Saale), 06120, Germany
| | - Alexandra K Kiemer
- Department of Pharmacy, Pharmaceutical Biology, University of Saarland, Saarbrücken, 66041, Germany
| | - Cristina Cadenas
- Leibniz-Institut für Arbeitsforschung (ifADo), Dortmund, 44139, Germany
| | - Laura Arrigoni
- Department of Epigenetics, Max Planck Institute of Immunobiology and Epigenetics, Freiburg, 78108, Germany
| | - Nina Gasparoni
- Department of Genetics, University of Saarland, Saarbrücken, 66123, Germany
| | - Thomas Manke
- Department of Epigenetics, Max Planck Institute of Immunobiology and Epigenetics, Freiburg, 78108, Germany
| | - Thomas Pap
- Institute of Musculoskeletal Medicine, University Hospital Münster, Münster, 48149, Germany
| | - John A Pospisilik
- Department of Epigenetics, Max Planck Institute of Immunobiology and Epigenetics, Freiburg, 78108, Germany
| | - Jan Hengstler
- Leibniz-Institut für Arbeitsforschung (ifADo), Dortmund, 44139, Germany
| | - Jörn Walter
- Department of Genetics, University of Saarland, Saarbrücken, 66123, Germany
| | - Sebastiaan H Meijsing
- Department of Computational Molecular Biology, Max Planck Institute for Molecular Genetics, Berlin, 14195, Germany
| | - Ho-Ryun Chung
- Otto-Warburg-Laboratory, Computational Epigenomics, Max Planck Institute for Molecular Genetics, Berlin, 14195, Germany
| | - Martin Vingron
- Department of Computational Molecular Biology, Max Planck Institute for Molecular Genetics, Berlin, 14195, Germany.
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5
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Behjati Ardakani F, Kattler K, Nordström K, Gasparoni N, Gasparoni G, Fuchs S, Sinha A, Barann M, Ebert P, Fischer J, Hutter B, Zipprich G, Imbusch CD, Felder B, Eils J, Brors B, Lengauer T, Manke T, Rosenstiel P, Walter J, Schulz MH. Integrative analysis of single-cell expression data reveals distinct regulatory states in bidirectional promoters. Epigenetics Chromatin 2018; 11:66. [PMID: 30414612 PMCID: PMC6230222 DOI: 10.1186/s13072-018-0236-7] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/02/2018] [Accepted: 10/26/2018] [Indexed: 01/12/2023] Open
Abstract
Background Bidirectional promoters (BPs) are prevalent in eukaryotic genomes. However, it is poorly understood how the cell integrates different epigenomic information, such as transcription factor (TF) binding and chromatin marks, to drive gene expression at BPs. Single-cell sequencing technologies are revolutionizing the field of genome biology. Therefore, this study focuses on the integration of single-cell RNA-seq data with bulk ChIP-seq and other epigenetics data, for which single-cell technologies are not yet established, in the context of BPs. Results We performed integrative analyses of novel human single-cell RNA-seq (scRNA-seq) data with bulk ChIP-seq and other epigenetics data. scRNA-seq data revealed distinct transcription states of BPs that were previously not recognized. We find associations between these transcription states to distinct patterns in structural gene features, DNA accessibility, histone modification, DNA methylation and TF binding profiles. Conclusions Our results suggest that a complex interplay of all of these elements is required to achieve BP-specific transcriptional output in this specialized promoter configuration. Further, our study implies that novel statistical methods can be developed to deconvolute masked subpopulations of cells measured with different bulk epigenomic assays using scRNA-seq data. Electronic supplementary material The online version of this article (10.1186/s13072-018-0236-7) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Fatemeh Behjati Ardakani
- Excellence Cluster for Multimodal Computing and Interaction, Saarland Informatics Campus, Saarland University, Campus E1 7, Saarbrücken, 66123, Germany.,Department of Computational Biology and Applied Algorithmics, Max Planck Institute for Informatics, Saarland Informatics, Campus E 4, Saarbrücken, 66123, Germany.,Graduate School of Computer Science, Saarland University, Campus E1 3, Saarbrücken, 66123, Germany
| | - Kathrin Kattler
- Department of Genetics, University of Saarland, Campus A2 4, Saarbrücken, 66123, Germany
| | - Karl Nordström
- Department of Genetics, University of Saarland, Campus A2 4, Saarbrücken, 66123, Germany
| | - Nina Gasparoni
- Department of Genetics, University of Saarland, Campus A2 4, Saarbrücken, 66123, Germany
| | - Gilles Gasparoni
- Department of Genetics, University of Saarland, Campus A2 4, Saarbrücken, 66123, Germany
| | - Sarah Fuchs
- Department of Genetics, University of Saarland, Campus A2 4, Saarbrücken, 66123, Germany
| | - Anupam Sinha
- Institute of Clinical Molecular Biology, Christian-Albrechts-University, Rosalind-Franklin-Str. 12, Kiel, 24105, Germany
| | - Matthias Barann
- Institute of Clinical Molecular Biology, Christian-Albrechts-University, Rosalind-Franklin-Str. 12, Kiel, 24105, Germany
| | - Peter Ebert
- Department of Computational Biology and Applied Algorithmics, Max Planck Institute for Informatics, Saarland Informatics, Campus E 4, Saarbrücken, 66123, Germany.,Graduate School of Computer Science, Saarland University, Campus E1 3, Saarbrücken, 66123, Germany
| | - Jonas Fischer
- Excellence Cluster for Multimodal Computing and Interaction, Saarland Informatics Campus, Saarland University, Campus E1 7, Saarbrücken, 66123, Germany.,Department of Computational Biology and Applied Algorithmics, Max Planck Institute for Informatics, Saarland Informatics, Campus E 4, Saarbrücken, 66123, Germany.,Graduate School of Computer Science, Saarland University, Campus E1 3, Saarbrücken, 66123, Germany
| | - Barbara Hutter
- Applied Bioinformatics, Deutsches Krebsforschungszentrum, Berliner-Str. 41, Heidelberg, 69120, Germany
| | - Gideon Zipprich
- Data Management and Genomics IT, Deutsches Krebsforschungszentrum, Im Neuenheimer Feld 280, Heidelberg, 69120, Germany
| | - Charles D Imbusch
- Applied Bioinformatics, Deutsches Krebsforschungszentrum, Berliner-Str. 41, Heidelberg, 69120, Germany
| | - Bärbel Felder
- Data Management and Genomics IT, Deutsches Krebsforschungszentrum, Im Neuenheimer Feld 280, Heidelberg, 69120, Germany
| | - Jürgen Eils
- Data Management and Genomics IT, Deutsches Krebsforschungszentrum, Im Neuenheimer Feld 280, Heidelberg, 69120, Germany
| | - Benedikt Brors
- Applied Bioinformatics, Deutsches Krebsforschungszentrum, Berliner-Str. 41, Heidelberg, 69120, Germany
| | - Thomas Lengauer
- Department of Computational Biology and Applied Algorithmics, Max Planck Institute for Informatics, Saarland Informatics, Campus E 4, Saarbrücken, 66123, Germany
| | - Thomas Manke
- Max Planck Institute of Immunobiology and Epigenetics, Stübeweg 51, Freiburg, 79108, Germany
| | - Philip Rosenstiel
- Institute of Clinical Molecular Biology, Christian-Albrechts-University, Rosalind-Franklin-Str. 12, Kiel, 24105, Germany
| | - Jörn Walter
- Department of Genetics, University of Saarland, Campus A2 4, Saarbrücken, 66123, Germany
| | - Marcel H Schulz
- Excellence Cluster for Multimodal Computing and Interaction, Saarland Informatics Campus, Saarland University, Campus E1 7, Saarbrücken, 66123, Germany. .,Department of Computational Biology and Applied Algorithmics, Max Planck Institute for Informatics, Saarland Informatics, Campus E 4, Saarbrücken, 66123, Germany. .,Institute for Cardiovascular Regeneration, Goethe University, Theodor-Stern-Kai 7, Frankfurt am Main, 60590, Germany. .,German Center for Cardiovascular Research, Partner site Rhein-Main, Frankfurt am Main, 60590, Germany.
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6
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Schmidt F, Gasparoni N, Gasparoni G, Gianmoena K, Cadenas C, Polansky JK, Ebert P, Nordström K, Barann M, Sinha A, Fröhler S, Xiong J, Dehghani Amirabad A, Behjati Ardakani F, Hutter B, Zipprich G, Felder B, Eils J, Brors B, Chen W, Hengstler JG, Hamann A, Lengauer T, Rosenstiel P, Walter J, Schulz MH. Combining transcription factor binding affinities with open-chromatin data for accurate gene expression prediction. Nucleic Acids Res 2017; 45:54-66. [PMID: 27899623 PMCID: PMC5224477 DOI: 10.1093/nar/gkw1061] [Citation(s) in RCA: 68] [Impact Index Per Article: 9.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/27/2016] [Revised: 10/18/2016] [Accepted: 10/24/2016] [Indexed: 12/21/2022] Open
Abstract
The binding and contribution of transcription factors (TF) to cell specific gene expression is often deduced from open-chromatin measurements to avoid costly TF ChIP-seq assays. Thus, it is important to develop computational methods for accurate TF binding prediction in open-chromatin regions (OCRs). Here, we report a novel segmentation-based method, TEPIC, to predict TF binding by combining sets of OCRs with position weight matrices. TEPIC can be applied to various open-chromatin data, e.g. DNaseI-seq and NOMe-seq. Additionally, Histone-Marks (HMs) can be used to identify candidate TF binding sites. TEPIC computes TF affinities and uses open-chromatin/HM signal intensity as quantitative measures of TF binding strength. Using machine learning, we find low affinity binding sites to improve our ability to explain gene expression variability compared to the standard presence/absence classification of binding sites. Further, we show that both footprints and peaks capture essential TF binding events and lead to a good prediction performance. In our application, gene-based scores computed by TEPIC with one open-chromatin assay nearly reach the quality of several TF ChIP-seq data sets. Finally, these scores correctly predict known transcriptional regulators as illustrated by the application to novel DNaseI-seq and NOMe-seq data for primary human hepatocytes and CD4+ T-cells, respectively.
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Affiliation(s)
- Florian Schmidt
- Cluster of Excellence for Multimodal Computing and Interaction, Saarland Informatics Campus, Saarland University, Saarbrücken, 66123, Germany
- Computational Biology & Applied Algorithmics, Max Planck Institute for Informatics, Saarland Informatics Campus, Saarbrücken, 66123, Germany
| | - Nina Gasparoni
- Department of Genetics, University of Saarland, Saarbrücken, 66123, Germany
| | - Gilles Gasparoni
- Department of Genetics, University of Saarland, Saarbrücken, 66123, Germany
| | - Kathrin Gianmoena
- Leibniz Research Centre for Working Environment and Human Factors IfADo, Dortmund, 44139, Germany
| | - Cristina Cadenas
- Leibniz Research Centre for Working Environment and Human Factors IfADo, Dortmund, 44139, Germany
| | - Julia K Polansky
- Experimental Rheumatology, German Rheumatism Research Centre, Berlin, 10117, Germany
| | - Peter Ebert
- Computational Biology & Applied Algorithmics, Max Planck Institute for Informatics, Saarland Informatics Campus, Saarbrücken, 66123, Germany
- International Max Planck Research School for Computer Science, Saarland Informatics Campus, Saarbrücken, 66123, Germany
| | - Karl Nordström
- Department of Genetics, University of Saarland, Saarbrücken, 66123, Germany
| | - Matthias Barann
- Institute of Clinical Molecular Biology, Christian-Albrechts-University, Kiel, 24105, Germany
| | - Anupam Sinha
- Institute of Clinical Molecular Biology, Christian-Albrechts-University, Kiel, 24105, Germany
| | - Sebastian Fröhler
- Berlin Institute for Medical Systems Biology, Max-Delbrück Center for Molecular Medicine, Berlin, 13092, Germany
| | - Jieyi Xiong
- Berlin Institute for Medical Systems Biology, Max-Delbrück Center for Molecular Medicine, Berlin, 13092, Germany
| | - Azim Dehghani Amirabad
- Cluster of Excellence for Multimodal Computing and Interaction, Saarland Informatics Campus, Saarland University, Saarbrücken, 66123, Germany
- Computational Biology & Applied Algorithmics, Max Planck Institute for Informatics, Saarland Informatics Campus, Saarbrücken, 66123, Germany
- International Max Planck Research School for Computer Science, Saarland Informatics Campus, Saarbrücken, 66123, Germany
| | - Fatemeh Behjati Ardakani
- Cluster of Excellence for Multimodal Computing and Interaction, Saarland Informatics Campus, Saarland University, Saarbrücken, 66123, Germany
- Computational Biology & Applied Algorithmics, Max Planck Institute for Informatics, Saarland Informatics Campus, Saarbrücken, 66123, Germany
| | - Barbara Hutter
- Applied Bioinformatics, Deutsches Krebsforschungszentrum, Heidelberg, 69120, Germany
| | - Gideon Zipprich
- Data Management and Genomics IT, Deutsches Krebsforschungszentrum, Heidelberg, 69120, Germany
| | - Bärbel Felder
- Data Management and Genomics IT, Deutsches Krebsforschungszentrum, Heidelberg, 69120, Germany
| | - Jürgen Eils
- Data Management and Genomics IT, Deutsches Krebsforschungszentrum, Heidelberg, 69120, Germany
| | - Benedikt Brors
- Applied Bioinformatics, Deutsches Krebsforschungszentrum, Heidelberg, 69120, Germany
| | - Wei Chen
- Berlin Institute for Medical Systems Biology, Max-Delbrück Center for Molecular Medicine, Berlin, 13092, Germany
| | - Jan G Hengstler
- Leibniz Research Centre for Working Environment and Human Factors IfADo, Dortmund, 44139, Germany
| | - Alf Hamann
- International Max Planck Research School for Computer Science, Saarland Informatics Campus, Saarbrücken, 66123, Germany
| | - Thomas Lengauer
- Computational Biology & Applied Algorithmics, Max Planck Institute for Informatics, Saarland Informatics Campus, Saarbrücken, 66123, Germany
| | - Philip Rosenstiel
- Institute of Clinical Molecular Biology, Christian-Albrechts-University, Kiel, 24105, Germany
| | - Jörn Walter
- Department of Genetics, University of Saarland, Saarbrücken, 66123, Germany
| | - Marcel H Schulz
- Cluster of Excellence for Multimodal Computing and Interaction, Saarland Informatics Campus, Saarland University, Saarbrücken, 66123, Germany
- Computational Biology & Applied Algorithmics, Max Planck Institute for Informatics, Saarland Informatics Campus, Saarbrücken, 66123, Germany
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Durek P, Nordström K, Gasparoni G, Salhab A, Kressler C, de Almeida M, Bassler K, Ulas T, Schmidt F, Xiong J, Glažar P, Klironomos F, Sinha A, Kinkley S, Yang X, Arrigoni L, Amirabad A, Ardakani F, Feuerbach L, Gorka O, Ebert P, Müller F, Li N, Frischbutter S, Schlickeiser S, Cendon C, Fröhler S, Felder B, Gasparoni N, Imbusch C, Hutter B, Zipprich G, Tauchmann Y, Reinke S, Wassilew G, Hoffmann U, Richter A, Sieverling L, Chang HD, Syrbe U, Kalus U, Eils J, Brors B, Manke T, Ruland J, Lengauer T, Rajewsky N, Chen W, Dong J, Sawitzki B, Chung HR, Rosenstiel P, Schulz M, Schultze J, Radbruch A, Walter J, Hamann A, Polansky J. Epigenomic Profiling of Human CD4+ T Cells Supports a Linear Differentiation Model and Highlights Molecular Regulators of Memory Development. Immunity 2016; 45:1148-1161. [DOI: 10.1016/j.immuni.2016.10.022] [Citation(s) in RCA: 130] [Impact Index Per Article: 16.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/30/2015] [Revised: 06/22/2016] [Accepted: 07/22/2016] [Indexed: 12/21/2022]
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