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Characterization of Labelled Regulatory Elements in Embryonic Stem Cells and Macrophages Using Quantitative and Qualitative Methods

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Characterization of Labelled Regulatory Elements in Embryonic Stem Cells and Macrophages Using Quantitative and Qualitative Methods THESIS FOR THE DEGREE OF DOCTOR OF PHILOSOPHY (PHD) Characterization of labelled regulatory elements in embryonic stem cells and macrophages using quantitative and qualitative methods by Attila Horváth UNIVERSITY OF DEBRECEN DOCTORAL SCHOOL OF MOLECULAR CELL AND IMMUNE BIOLOGY DEBRECEN, 2019 THESIS FOR THE DEGREE OF DOCTOR OF PHILOSOPHY (PHD) Characterization of labelled regulatory elements in embryonic stem cells and macrophages using quantitative and qualitative methods by Attila Horváth Supervisor: Prof. Dr. László Nagy Co-Supervisor: Dr. Benedek Nagy UNIVERSITY OF DEBRECEN DOCTORAL SCHOOL OF MOLECULAR CELL AND IMMUNE BIOLOGY DEBRECEN, 2019 2 TABLE OF CONTENT 1. ABBREVIATIONS ..................................................................................................................................... 6 2. INTRODUCTION .................................................................................................................................... 10 Transcription regulation in Eukaryotes ......................................................................................................... 10 The concept of enhancer ............................................................................................................................. 12 Identification of enhancer regions................................................................................................................ 13 Histone modifications .................................................................................................................................. 13 Classification of enhancer states based on epigenetic signatures .................................................................. 14 3. LITERATURE REVIEW ............................................................................................................................ 16 3.1. Computational methods for modeling genomics data ........................................................................ 16 Introduction to Machine learning methods .................................................................................................. 16 Random Forest ............................................................................................................................................ 16 Support Vector Regression........................................................................................................................... 17 Network motifs............................................................................................................................................ 17 Turing machine and Finite State Automata................................................................................................... 19 3.2. Macrophages: as model system for the study of enhancer formation ................................................. 22 3.3. PU.1 is a master regulator of macrophages ........................................................................................ 23 Regulation of macrophage enhancers in the context of polarizations signals ................................................ 25 3.4. Embryonic stem cells: a model system to study developmental enhancers .......................................... 28 3.5. OCT4 as one of the master regulators of pluripotency ........................................................................ 29 4. AIMS AND HYPOTHESES ....................................................................................................................... 31 5. MATERIALS AND METHODS.................................................................................................................. 34 3 Differentiation of bone marrow derived macrophages ................................................................................. 34 Embryonic stem cell culture ......................................................................................................................... 34 Ligands and Treatment ................................................................................................................................ 34 siRNA knockdown ........................................................................................................................................ 34 Microarray analysis ...................................................................................................................................... 35 RT-qPCR ...................................................................................................................................................... 35 ChIP-seq ...................................................................................................................................................... 36 Western blot analysis .................................................................................................................................. 36 GRO-seq ...................................................................................................................................................... 36 ChIP-seq, GRO-seq and ATAC-seq analyses ................................................................................................... 36 Machine learning ......................................................................................................................................... 38 Data Availability ........................................................................................................................................... 39 Author contributions to the wet-lab experiments......................................................................................... 39 6. RESULTS ............................................................................................................................................... 40 6.1. Random Forest classification hints the existence of low accessible TF binding sites in macrophages .... 40 6.2. PU.1-labelled regulatory elements are widespread in the macrophage genome.................................. 46 6.3. Key transcriptional regulators of macrophage form labelled regulatory elements ............................... 51 6.4. The role of PU.1 and IRF8 co-LREs in cellular response to IL-4 ............................................................. 54 6.5. IRF8 maintains low accessible chromatin structure at a subset of labelled regulatory elements .......... 58 6.6. Labelled regulatory elements are dynamically utilized by macrophage polarization signals................. 60 6.7. Modelling enhancer states using Nondeterministic Finite State Automata .......................................... 69 6.8. OCT4-LREs in the context of RA-induced neurogenesis ........................................................................ 71 6.9. Modelling OCT4-related transcriptional circuits using network motifs................................................. 79 4 7. DISCUSSION ......................................................................................................................................... 82 8. SUMMARY ........................................................................................................................................... 86 9. ÖSSZEFOGLALÁS ................................................................................................................................... 88 10. TABLE OF FIGURES................................................................................................................................ 90 11. REFERENCES ......................................................................................................................................... 93 12. LIST OF KEYWORDS ............................................................................................................................ 105 13. KULCSSZAVAK LISTÁJA ....................................................................................................................... 106 14. ACKNOWLEDGEMENTS ...................................................................................................................... 107 15. APPENDIX........................................................................................................................................... 108 5 1. ABBREVIATIONS AP-1 activator protein 1 APC antigen presenting cell Arg1 arginase 1 AUC area under the curve BMDM bone marrow-derived macrophages BRE B recognition element cDNA Complementary DNA CEBP CCAAT/enhancer binding protein ChIP-seq chromatin immunoprecipitation sequencing CTCF CCCTC-binding Factor CTF collaborating transcription factor DKO double knock-out DMEM Dulbecco's Modified Eagle's Medium DNA deoxyribonucleic acid DPE downstream promoter element EC enhancer cluster EICE Ets-IRF composite element EGR early growth response protein eRNA enhancer RNA ESC embryonic stem cell ETV E26 transformation-specific FAIRE formaldehyde-assisted isolation of regulatory elements 6 FBS fetal bovine serum FC fold-change FDR false discovery rate FSA finite state automaton GB gene body GRO-seq global run-on sequencing H3K27ac histone H3 lysine 27 acetylation H3K4me1 histone H3 lysine 4 mono-methylation Hbegf heparin-binding EGF-like growth factor IGV integrative genomics viewer IL12B interleukin-12B IL1B interleukin-1B IL-4 interleukin-4 Inr initiator IRF interferon regulatory factor ISRE interferon stimulated response element LDTF lineage determining transcription factor LIF leukemia inhibitory factor lncRNA long non-coding RNA LPS lipopolysaccharide LRE labelled regulatory element
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