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Integrative Analysis of Epigenomics and Expression data in an Immune Cell Proliferation System data in an Immune Cell Proliferation System Esteban Ballestar Esteban Ballestar Chromatin and Disease Group Chromatin and Disease Group Cancer Epigenetics and Biology Programme (PEBC) Bellvitge Medical Research Institute (IDIBELL) Barcelona Spain Barcelona, Spain [email protected] P P E E BC BC P P E E BC BC COSTSTATEGRA Workshop

Integrative Analysis of Epigenomics and miRNA data in Immune System Models

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Page 1: Integrative Analysis of Epigenomics and miRNA data in Immune System Models

Integrative Analysis of Epigenomics and Expression data in an Immune Cell Proliferation Systemdata in an Immune Cell Proliferation System

Esteban BallestarEsteban Ballestar

Chromatin and Disease GroupChromatin and Disease GroupCancer Epigenetics and Biology Programme (PEBC)

Bellvitge Medical Research Institute (IDIBELL)Barcelona SpainBarcelona, Spain

[email protected]

PPEEBCBCPPEEBCBC

COST‐STATEGRA Workshop

Page 2: Integrative Analysis of Epigenomics and miRNA data in Immune System Models

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

Gene

Promoter &

DNA repeatsGene

Promoter &

DNA repeatsGene

Promoter &

DNA repeats

y p p p g

CpG is land Body of the geneCpG is land Body of the geneCpG is land Body of the gene

HDACMBDHDACMBDMBD

HDACMBDHDACMBDMBD

HDACMBDHDACMBDMBD

GENE EXPRESSION

E1 E2 E3

GENE EXPRESSION

E1 E2 E3

GENE EXPRESSION

E1E1 E2 E3

GENE SILENCINGx GENE SILENCINGxE1 E2 E3E1E1 E2 E3

Inactive X‐chromosome, imprinted and tissue‐specific genes

M i t i d b DNA th lt f Id tit f ti d th lMaintained by DNA methyltransferases. Identity of active demethylasescontroversial

Page 3: Integrative Analysis of Epigenomics and miRNA data in Immune System Models

Molecular anatomy of CpG sites in chromatin and their roles in gene expression

Jones (2012) Nat. Rev. Genet

Page 4: Integrative Analysis of Epigenomics and miRNA data in Immune System Models

Histone post‐translational modifications

H3

K9 K27K4 K36R17

H3

K20R3

K14K18 K23K9

H4

K20

K79R i

Activation

Acetylation

Phosphorylation

K8 K12 K16K5 Repression

Phosphorylation

Methylation

Ubiquitylation

Page 5: Integrative Analysis of Epigenomics and miRNA data in Immune System Models

Interplay between epigenetic modifications

T i i l l

Interplay between epigenetic modificationsand miRNAs in gene regulation

Transcriptional controlEpigenetics + transcription factors

miRNA genemiRNA genepromoterpromoter

TFTF

Post‐transcriptional controlmiRNAs + RNA binding proteins

ggpp

mature miRNA

protein geneprotein genepromoterpromoter

TFTF

mature mRNA

Page 6: Integrative Analysis of Epigenomics and miRNA data in Immune System Models

DNA methylation in changes in cancer

Normal cellGene

Promoter & CpG island Body of the gene

DNA repeats

•Unmethylated CpG

Normal cell

C ll

E1 E2 E3 •Methylated CpG

GENE EXPRESSION

Cancer cell

GENE SILENCING

E1 E2 E3

x

Aberrant  DNA hypermethylation of tumor

Global DNA hypomethylation

x

hypermethylation of tumor suppressor genes

hypomethylation

ChromosomalGene repression

Chromosomal instability

Page 7: Integrative Analysis of Epigenomics and miRNA data in Immune System Models

DNA methylation changes in different models of immunedisease‐related disease: predominance of DNAh th l tihypomethylation

• ICF syndrome is a rare autosomal recessive disease characterized by a variableimmunodeficiency, mild facial anomalies, and centromeric decondensation—chromosomal instability involving chromosomes 1, 9, and 16, (1, 2). Hypomethylation ofthe satellite 2 and satellite 3 regions of chromosomes 1, 9, and 16 (3).

• Autoimmune diseases are characterized by the breakdown of immune tolerance tospecific self‐antigens. Two basic types: systemic (systemic lupus erythematosus,rheumatoid arthritis and psoriasis) and organ‐specific (Sjögren’s syndrome, type 1diabetes and multiple sclerosis). Analysis of different lymphocyte subsets have revealed apredominance of DNA hypomethylation/overexpression in key genes for immunefunction.

Page 8: Integrative Analysis of Epigenomics and miRNA data in Immune System Models

ICF syndrome: mutations in DNMT3b and hypomethylation

PNAS 96, 14412–14417 (1999)

Decrease of DNA methylation level of 42%, profound changes occurring ininactive heterochromatic regions, satellite repeats and transposons.Transcriptional active loci and ribosomal RNA repeats escape globalhypomethylation. Despite a genome‐wide loss of DNA methylation theepigenetic landscape and crucial regulatory structures are conserved.[Heyn et al (2012) Epigenetics]

Page 9: Integrative Analysis of Epigenomics and miRNA data in Immune System Models

Genetic Elements Hypomethylated in autoimmune diseases

Ballestar (2011) Nat. Rev. Rheumatol

Page 10: Integrative Analysis of Epigenomics and miRNA data in Immune System Models

MZ twins discordant for autoimmune diseases to investigate the role of DNA methylation in pathogenesis

Collection of MZ twins discordant for several AI diseases: SLE, RA, DMPBMC

y p g

PBMCClinically caracterized samples: age, activity, tissue damageFred 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 differentiationdifferentiation apoptosis X‐linked imprinted genes

Page 11: Integrative Analysis of Epigenomics and miRNA data in Immune System Models

A set of genes display DNA hypomethylation in SLE with respect to healthy twins

TRIP6TM7SF3LCN2IL10ERCC3MMP8THPO

MATCHED CONTROLS HEALTHY TWINS SLE TWINS

THPOMAP3K8CSF3MST1RAGXTSOD3LCN2PI3CSF1RTNFRSF1AMPONOTCH4RARAEMR3GRB7GRB10CARD15IFNGR2CD82CARD15STAT5AGFI1SEPT9LTB4RHGFSPI1PECAM1PADI4MMP9MMP9PECAM1TIE1SLC5A5MPLSYKSLC22A18S100A2CD9CSF3RLMO2SPI1LMO2DCHR24HOXB2MMP14EPHA2VAMP8AIM2SPDEFSPDEF

‐6.0 ‐5.4 ‐4.7 ‐4.1 ‐2.8‐3.5 ‐1.6‐2.2 0.95 1.6 2.2 2.8 4.13.5 5.44.7 6.0‐0.32

Javierre et al (2010) Genome Res

Page 12: Integrative Analysis of Epigenomics and miRNA data in Immune System Models

DNA methylation changes associated with conversion of resting B cells to proliferating lymphoblastsp g y p

Resting B cell LCLsEBV

Primary Infection continuous B cell proliferation (naïve hosts, immunocompromised)

ltype III latency

Latency Cancer:  Burkitt Lymphoma, Hodking Lymphoma, Diffuse large‐cell lymphoma (DLBCL), N h l C iNasopharyngeal Carcinoma

Autoimmune Diseases: Systemic Lupus Erithematosus, Rheumatoid Arthritis, MultipleSclerosis

Page 13: Integrative Analysis of Epigenomics and miRNA data in Immune System Models

EBV‐mediated B cell to LCL transformation associates with promoter hypomethylation

RBL LCL

M F M FCCL3L1FCER2SLAMF7 F1Ls

1.0

0 8

1.0

SLAMF7

BLNKIL25IRS2

TRAF1TAP1 B

eta

Valu

e LC

L

Bet

a Va

lue

LCL 0.8

0.6

0.2

0.4

0.8

0.6

0.2

0.4

CD19IL21

COLEC12

MAP3K7IP1 CL

F2

L M

ale 1.0

0.8

1.0

0.8

Beta Value RBLs Beta Value RBL F1

0.00.2 1.00.80.60.0 0.4

0.00.2 1.00.80.60.0 0.4

BLK

CCR7

CD1C

TCL1A

MAP3K7IP1

Bet

a Va

lue

LC

Bet

a Va

lue

LC 0.6

0.2

0.0

0.4

0 2 1 00 80 60 0 0 4

0.6

0.2

0.0

0.4

0 2 1 00 80 60 0 0 4

CD79A

LCK

CD80

CL

Fem

ale

e LC

L F3

1.0

0.8

0.6

1.0

0.8

0.6

Beta Value RBL Male Beta Value RBL F20.2 1.00.80.60.0 0.4 0.2 1.00.80.60.0 0.4

DOK3

B V l RB F l

Bet

a Va

lue

LC

Bet

a Va

lue

B t V l RBL F3

0.2

0.0

0.4

0.2 1.00.80.60.0 0.4

0.2

0.0

0.4

0.2 1.00.80.60.0 0.427K

256 genes hypomethylated in LCLs (FDR ≤ 0.05 & Fold‐change ≥ 2)

0-3 3 Beta Value RBL Female Beta Value RBL F327K

Hernando et al (2013) Genome Biol.

Page 14: Integrative Analysis of Epigenomics and miRNA data in Immune System Models

No changes in DNA methylation in repeats in EBV‐mediatedB cell to LCL transformation

Hernando et al (2013) Genome Biol.

Page 15: Integrative Analysis of Epigenomics and miRNA data in Immune System Models

Pyrosequencing confirms promoter hypomethylation

Page 16: Integrative Analysis of Epigenomics and miRNA data in Immune System Models

Potential pathways to DNA demethylation

• DNA hypomethylation associated with inefficient/defective maintenance of DNAmethylation throughout replication cycles

• Active DNA demethylation

Page 17: Integrative Analysis of Epigenomics and miRNA data in Immune System Models

Potential pathways to DNA demethylation

Page 18: Integrative Analysis of Epigenomics and miRNA data in Immune System Models

Demethylation occurs as cell start to proliferate

Page 19: Integrative Analysis of Epigenomics and miRNA data in Immune System Models

AID not involved in demethylation in RBL to LCL conversionAID not involved in demethylation in RBL to LCL conversion

MERGEMERGEDAPI Anti-HA

-LMB

DAPI Anti-HA

+LMB

OC

KM

OA

ID W

TA

CD19

+87 bp+122 bp

TSS

BLNK

TSS

+149 bp+122 bp

CCL3L1

TSS

+119 bp+122 bp

3 2 2

0

1

2

3

0

0,5

1

1,5

2

0

0,5

1

1,5

2

Page 20: Integrative Analysis of Epigenomics and miRNA data in Immune System Models

Demethylation does not occur in CD40L/IL40 stimulated cells

Page 21: Integrative Analysis of Epigenomics and miRNA data in Immune System Models

Hypomethylated genes are relevant to B cell function

Page 22: Integrative Analysis of Epigenomics and miRNA data in Immune System Models

Hypomethylated genes display binding motifs for NFkBsubunits and other hematopoietic TFs

Page 23: Integrative Analysis of Epigenomics and miRNA data in Immune System Models

ChIP‐seq analysis reveals binding of NFkB and Pol II tohypomethylated promoters

Page 24: Integrative Analysis of Epigenomics and miRNA data in Immune System Models

Binding of additional TF to hypomethylated promoters

Page 25: Integrative Analysis of Epigenomics and miRNA data in Immune System Models

Nucleic Acids Res 39, 874–888 (2011). 

Mol Cell Biol 29, 5366‐5376 (2009) 

Page 26: Integrative Analysis of Epigenomics and miRNA data in Immune System Models

DNMTs are less efficient in maintaining DNA methylation ineucrhomatic sites as proliferation starts

Hernando et al (2013) Genome Biol.

Page 27: Integrative Analysis of Epigenomics and miRNA data in Immune System Models

Hypomethylated genes undergo further upregulationHypomethylated genes undergo further upregulation

Page 28: Integrative Analysis of Epigenomics and miRNA data in Immune System Models

Demethylating agents promote transformation andDemethylating agents promote transformation andproliferation

Page 29: Integrative Analysis of Epigenomics and miRNA data in Immune System Models

Conclusions

• Transformation of resting B cells into proliferating lymphoblasts involveshypomethylation of around 250 genes. No hypermethylation is detected.

• A significant group of those 250 hypomethylated genes are already highly expressed inB cells, are bound by NFkB RELA and REL and other B cell specific transcription factorsand their expression levels do not change during this process.

• Hypomethylation does not appear to occur through an active process and it is likelythat is associated with the inefficient maintenance of DNA methylation at active regions(it does not occur at repetitive heterochromatic regions)(it does not occur at repetitive heterochromatic regions)

• Demethylation may contribute to the efficiency of the process by further enhancinggene upregulation of certain genesgene upregulation of certain genes

Page 30: Integrative Analysis of Epigenomics and miRNA data in Immune System Models

Chromatin and Disease Group, IDIBELL, Barcelona SpainLaura CiudadHenar HernandoVirginia RodríguezRoser Vento

Environmental Autoimmunity, NIEHS, NIH, BethesdaTerry O’HanlonLisa G. RiderFred Miller

Lorenzo de la RicaJosé UrquizaLluís PonsJavier Rodríguez‐Ubreva

Computational Medicine Unit, Karolinska Institutet, Stokholm, Sweden

University of OklahomaAmr Sawalha (U Michigan)John Harley (CCHMC)

Computational Medicine Unit, Karolinska Institutet, Stokholm, SwedenDavid Gómez‐CabreroJesper Tegnér

Leiden University Medical CenterRené Toes

University of BirminghamClaire Shannon‐Lowe

INNPACTO, SAF

Claire Shannon‐Lowe

Broad InstituteFatima Al‐Shahrour

FUNDACIÓN

PPEEBCBCPPEEBCBC

FUNDACIÓN RAMÓN ARECES