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Semelhante a Integrative Analysis of Epigenomics and Expression Data in an Immune Cell Proliferation System
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Integrative Analysis of Epigenomics and Expression Data in an Immune Cell Proliferation System
- 1. Integrative Analysis of Epigenomics and Expression data in an Immune Cell Proliferation System Esteban Ballestar Chromatin and Disease Group Cancer Epigenetics and Biology Programme (PEBC) Bellvitge Medical Research Institute (IDIBELL) Barcelona, Barcelona Spain eballestar@idibell.org PEBC COST‐STATEGRA Workshop
- 2. DNA methylation is the most studied epigenetic modification Methyl group introduced in the 5’ position of cytosine In CG dinucleotides Methylation of promoter CpG islands leads to transcriptional silencing y p p p g Gene DNA repeats Promoter & CpG is land Body of the gene HDAC HDAC HDAC MBD MBD MBD E1 E2 E3 x SILENCING GENE EXPRESSION Inactive X‐chromosome, imprinted and tissue‐specific genes Maintained by M i t i d b DNA methyltransferases. Id tit of active d th lt f Identity f ti demethylases th l controversial
- 4. Histone post‐translational modifications K4 K9 R17 K27 K36 H3 K9 K14 K18 K23 R3 K20 H4 Activation K79 K5 K8 K12 K16 Repression R i Acetylation Phosphorylation Methylation Ubiquitylation
- 5. Interplay between epigenetic modifications and miRNAs in gene regulation Transcriptional control T i i l l Epigenetics + transcription factors TF p promoter miRNA gene g Post‐transcriptional control miRNAs + RNA binding proteins TF mature miRNA promoter protein gene mature mRNA
- 6. DNA methylation in changes in cancer Normal cell Normal cell Gene DNA repeats Promoter & CpG island Body of the gene •Unmethylated CpG •Methylated CpG E1 E2 E3 GENE EXPRESSION Cancer cell C ll E1 E2 E3 x GENE SILENCING Aberrant DNA Global DNA hypermethylation of tumor hypermethylation of tumor hypomethylation suppressor genes Chromosomal Chromosomal Gene repression instability
- 7. DNA methylation changes in different models of immune disease‐related disease: predominance of DNA hypomethylation h th l ti • ICF syndrome is a rare autosomal recessive disease characterized by a variable immunodeficiency, mild facial anomalies, and centromeric decondensation— chromosomal instability involving chromosomes 1, 9, and 16, (1, 2). Hypomethylation of the satellite 2 and satellite 3 regions of chromosomes 1, 9, and 16 (3). • Autoimmune diseases are characterized by the breakdown of immune tolerance to specific self‐antigens. Two basic types: systemic (systemic lupus erythematosus, rheumatoid arthritis and psoriasis) and organ‐specific (Sjögren’s syndrome, type 1 diabetes and multiple sclerosis). Analysis of different lymphocyte subsets have revealed a predominance of DNA hypomethylation/overexpression in key genes for immune function.
- 8. ICF syndrome: mutations in DNMT3b and hypomethylation PNAS 96, 14412–14417 (1999) Decrease of DNA methylation level of 42%, profound changes occurring in inactive heterochromatic regions, satellite repeats and transposons. Transcriptional active loci and ribosomal RNA repeats escape global hypomethylation. Despite a genome‐wide loss of DNA methylation the epigenetic landscape and crucial regulatory structures are conserved. [Heyn et al (2012) Epigenetics]
- 9. Genetic Elements Hypomethylated in autoimmune diseases Ballestar (2011) Nat. Rev. Rheumatol
- 10. MZ twins discordant for autoimmune diseases to investigate the role of DNA methylation in pathogenesis y p g Collection of MZ twins discordant for several AI diseases: SLE, RA, DM PBMC Clinically caracterized samples: age, activity, tissue damage Fred Miller, Environmental Autoimmunity Group, NIEHS, NIH Methylation Arrays 807 CpG‐containing gene promoter probes Selected genes fall into various classes: tumor suppressor genes oncogenes genes involved in DNA repair cell cycle control differentiation differentiation apoptosis X‐linked imprinted genes
- 11. A set of genes display DNA hypomethylation in SLE with respect to healthy twins MATCHED CONTROLS HEALTHY TWINS SLE TWINS TRIP6 TM7SF3 LCN2 IL10 ERCC3 MMP8 THPO MAP3K8 CSF3 MST1R AGXT SOD3 LCN2 PI3 CSF1R TNFRSF1AM PO NOTCH4 RARA EMR3 GRB7 GRB10 CARD15 IFNGR2 CD82 CARD15 STAT5A GFI1 SEPT9 LTB4R HGF SPI1 PECAM1 PADI4 MMP9 PECAM1 TIE1 SLC5A5 MPL SYK SLC22A18 S100A2 CD9 CSF3R LMO2 SPI1 LMO2 DCHR24 HOXB2 MMP14 EPHA2 VAMP8 AIM2 SPDEF ‐6.0 ‐5.4 ‐4.7 ‐4.1 ‐3.5 ‐2.8 ‐2.2 ‐1.6 ‐0.32 0.95 1.6 2.2 2.8 3.5 4.1 4.7 5.4 6.0 Javierre et al (2010) Genome Res
- 12. DNA methylation changes associated with conversion of resting B cells to proliferating lymphoblasts p g y p Resting B cell EBV LCLs Primary Infection continuous B cell proliferation (naïve hosts, immunocompromised) type III latency l Latency Cancer: Burkitt Lymphoma, Hodking Lymphoma, Diffuse large‐cell lymphoma (DLBCL), Nasopharyngeal C i N h l Carcinoma Autoimmune Diseases: Systemic Lupus Erithematosus, Rheumatoid Arthritis, Multiple Sclerosis
- 13. EBV‐mediated B cell to LCL transformation associates with promoter hypomethylation RBL LCL M F M F CCL3L1 1.0 1.0 Beta Value LCL F1 FCER2 Ls SLAMF7 Beta Value LCL 0.8 08 0.8 BLNK IL25 0.6 0.6 IRS2 0.4 0.4 TRAF1 0.2 0.2 TAP1 CD19 0.0 0.0 IL21 0.0 0.2 0.4 0.6 0.8 1.0 0.0 0.2 0.4 0.6 0.8 1.0 Beta Value RBLs Beta Value RBL F1 COLEC12 1.0 1.0 Beta Value LC L Male Beta Value LC F2 0.8 0.8 CL MAP3K7IP1 BLK 0.6 0.6 CCR7 0.4 0.4 0.2 0.2 TCL1A 0.0 0.0 CD1C 0.0 0.2 0.4 0.6 0.8 1.0 00 02 04 06 08 10 0.0 0.2 0.4 0.6 0.8 1.0 00 02 04 06 08 10 CD80 Beta Value RBL Male Beta Value RBL F2 CD79A Beta Value LC Female 1.0 1.0 Beta Value LCL F3 0.8 0.8 CL LCK 0.6 0.6 e 0.4 0.4 0.2 0.2 DOK3 0.0 0.0 0.0 0.2 0.4 0.6 0.8 1.0 0.0 0.2 0.4 0.6 0.8 1.0 -3 0 3 27K Beta V l B Value RBL F RB Female l Beta Value B t V l RBL F3 256 genes hypomethylated in LCLs (FDR ≤ 0.05 & Fold‐change ≥ 2) Hernando et al (2013) Genome Biol.
- 14. No changes in DNA methylation in repeats in EBV‐mediated B cell to LCL transformation Hernando et al (2013) Genome Biol.
- 15. Pyrosequencing confirms promoter hypomethylation
- 16. Potential pathways to DNA demethylation • DNA hypomethylation associated with inefficient/defective maintenance of DNA methylation throughout replication cycles • Active DNA demethylation
- 17. Potential pathways to DNA demethylation
- 18. Demethylation occurs as cell start to proliferate
- 19. AID not involved in demethylation in RBL to LCL conversion -LMB +LMB DAPI Anti-HA MERGE DAPI Anti-HA MERGE OCK MO AID WT A BLNK CCL3L1 CD19 TSS TSS TSS +149 bp +119 bp +87 bp +122 bp +122 bp +122 bp 3 2 2 1,5 1,5 2 1 1 1 0,5 0,5 0 0 0
- 20. Demethylation does not occur in CD40L/IL40 stimulated cells
- 21. Hypomethylated genes are relevant to B cell function
- 22. Hypomethylated genes display binding motifs for NFkB subunits and other hematopoietic TFs
- 23. ChIP‐seq analysis reveals binding of NFkB and Pol II to hypomethylated promoters
- 24. Binding of additional TF to hypomethylated promoters
- 26. DNMTs are less efficient in maintaining DNA methylation in eucrhomatic sites as proliferation starts Hernando et al (2013) Genome Biol.
- 27. Hypomethylated genes undergo further upregulation
- 28. Demethylating agents promote transformation and proliferation
- 29. Conclusions • Transformation of resting B cells into proliferating lymphoblasts involves hypomethylation of around 250 genes. No hypermethylation is detected. • A significant group of those 250 hypomethylated genes are already highly expressed in B cells, are bound by NFkB RELA and REL and other B cell specific transcription factors and their expression levels do not change during this process. • Hypomethylation does not appear to occur through an active process and it is likely that is associated with the inefficient maintenance of DNA methylation at active regions (it does not occur at repetitive heterochromatic regions) • Demethylation may contribute to the efficiency of the process by further enhancing gene upregulation of certain genes
- 30. Chromatin and Disease Group, IDIBELL, Barcelona Spain Environmental Autoimmunity, NIEHS, NIH, Bethesda Laura Ciudad Terry O’Hanlon Henar Hernando Lisa G. Rider Virginia Rodríguez Fred Miller Roser Vento Lorenzo de la Rica University of Oklahoma José Urquiza Amr Sawalha (U Michigan) Lluís Pons John Harley (CCHMC) Javier Rodríguez‐Ubreva Computational Medicine Unit, Karolinska Institutet, Stokholm, Sweden Leiden University Medical Center David Gómez‐Cabrero René Toes Jesper Tegnér University of Birmingham Claire Shannon‐Lowe Claire Shannon‐Lowe Broad Institute Fatima Al‐Shahrour INNPACTO, SAF FUNDACIÓN RAMÓN ARECES PEBC