June 2006Page 1

LOCATION ANALYSIS (ChIP-on-chip)

Regulation of Human ES CellsJune 2006

June 2006Page 2

Mammalian Development

Cell 125, 301-313, April 21, 2006.

Richard Young, Professor of Biology, MIT

June 2006Page 3

Overview: Control of embryonic stem cells

• ES cells must remain pluripotent until signalled to differentiate

• Polycomb group proteins (PcG) repress genes previously found to control segment identity in drosophila by modifying chromatin

• PcG proteins assemble Polycomb Repressive Complexes (PRCs) – required to repress developmental genes so that cells are pluripotent

• Specifically, PRC2 plays a role in histone methylation for gene silencing

June 2006Page 4

The role of PRC2 and its components

What does PRC2 do?

• Represses developmental genes in ES cells to maintain pluripotency

• Catalyzes methylation of histone H3 lysine-27 in nucleosomes: associated genes are thus silenced through repressed chromatin state

• Contains subunits EED, EZH2, and SUZ12 critical for PRC2 for the methyltransferase activity

RING1

BMI1

hPc2

PRC1

NH4-ARTKQTARKSTGGKAPRKQLATKAARKSAPATG

EED

EZH2SUZ12

PRC2

H3

June 2006Page 5

Goals of methodology to confirm PRC2 role

• DNA segments bound by RNA pol 2 or SUZ12 isolated using ChIP-on-chip (Agilent)

• SUZ12 mapped genome-wide to understand how PRC2 needed for self- renewal and pluripotency

• RNA pol II also mapped as control and reference to PRC2 occupation

0 25

210

215

0

25

210

215

Human embryonicstem cells (H9)

Whole genome arrays4.6 million features

Scatter plot(ChIP / reference)

ChIP

53130000 5314000

Fold

Enrich

ment (I

P/W

CE

)

SMCX

Chromosomal position (bp)

53135000

2

6

0

4

Promoters bound byRNA polymerase II or Suz12

June 2006Page 6

Genome-wide binding of SUZ12 and RNA polymerase II

RNA pol 2 enrichment ratios• Bound at 87% known genes• 4% false positive PCR-confirmed

SUZ12 enrichment ratios• Associated with 1,893 promoters of 22,500 genes (8%)• 95% of bound sites within 1 kb of known transcriptional start sites• 40% within 1kb of CpG Islands• 3% false positive

June 2006Page 7

Suz12 & Pol II are mutually exclusive

0

0.5

1

1.5

2

2.5

3

3.5

4

4.5

5

177885000 177900000 177915000

0

1

2

3

4

5

6

7

8

182340000 182360000 182380000 182400000

NEUROD1

HNRPA3

Fo

ld E

nric

hm

en

tF

old

En

rich

me

nt

Pol IISuz12

Pol IISuz12

Pol II30%

Neither

Both1.9%

Suz12 6.5%

Lee et. al., Cell 2006

June 2006Page 8

PRC2 occupies key developmental regulators confirmed by SUZ12 occupation

Development

Reg. of Transcription

Morphogenesis

Organogenesis

Neurogenesis

Cell-cell signaling

Protein transport

Cell cycle

Resp.to DNA damage

DNA metabolism

Protein biosynthesis

RNA metabolism

1E-20 1E-40 1E-601E0

Suz12RNA Pol II

• SUZ12 mainly occupies genes that control development and transcription

• RNA pol II occupies genes controlling broader cell proliferation functions

June 2006Page 9

SUZ12 binds multitude of developmental transcription factor families

Transcription factor families include:

• HOX

• HOX co-factors (MEIS/EVX)

• FOX

• NEUROD

• Myogenic basic domain (MYO)

• GATA binding protein

• LIM homeobox (LHX)

• Distal-less homeobox

• SRY box (SOX)

• RUNX, PAX, SIX, POU

GATA

ATOH

LHX

POU

IRX

DLX

SIX

NEUROD

BHLHB

PAX

FOX

HOX

SOX

TBX

NKX

HES

EBF

RUNX

MYO

CDX

MEIS/EVX

CDX2

MYOD1

NEUROG2

NEUROD1

MEIS1

EBF

PAX3

SOX21

T

OLIG2

GATA4

FOXA1

Transcription factor family membersoccupied by PRC2

Red circles: Individual TFsWhite ovals: TF with defined role in development

June 2006Page 10

Suz12 covers large domains over HOX clusters

Pol II

Suz12

• High portion of developmental regulator genes bound by SUZ12 in extended regions

• SUZ12 binding ~100kb across HOX A-D clusters

• Unrelated genes not bound

• Thus, PRC2 favors binding to developmental regulator genes

June 2006Page 11

Targets of PRC2 shared with key ES cell regulators

RNAP2

SUZ12

• OCT4, SOX, NANOG previously reported to play critical role in differentiation (Boyer et. al. 2005)

• Subset of dev. regulator genes almost all occupied by PRC2 as well

• Further support to link between PRC2 binding and repression of dev regulators and ES cell pluripotency

June 2006Page 12

Suz12 occupied genes in ES cells are poised for expression during differentiation

• Genes bound by SUZ12 more likely to be activated during differentiation than genes that are not bound

• Indicative that genes once bound by SUZ12 are preferentially activated as ES cells differentiate

June 2006Page 13

Loss of PRC2 in differentiated cells

In muscle, PRC2 is lost from genes encoding regulators of muscle development…

…but maintained at genes encoding developmental regulators for other cell types.

June 2006Page 14

Regulation of ES cell pluripotency by Polycomb

PRC2 maintains ES cell pluripotency by repressing key developmental regulators.

• PRC2 localizes to the promoters of hundreds of genes encoding known developmental regulators.

• SUZ12 component was mapped using ChIP-on-chip to indicate PRC2 role

• PRC2 is associated with methylation at H3K27 and transcriptional repression genome-wide.

• Genes bound by PRC2 become activated as ES cells differentiate.

• In differentiated cells, there is a loss of PRC2 at genes that play a role in specifying the identity of that tissue.

June 2006Page 15

Master Regulators of Mammalian Transcription

Embryonic stem cellsOCT4, NANOG, SOX2 Polycomb

Brain and Spinal CordSOX1-18, OCT6, MeCP2 CBP, NGN, NEURODCerebrumCerebellumGanglia & nerves

Circulatory SystemMyocardin, GATA4, TBX5, NKX2.5, MEF2, HANDHeart Vascular system

Digestive SystemHNF1, HNF4, HNF6, CBP, PGC1, FOXA, PDX1, GATA, EsophagusStomachIntestinesLiverPancreas

Urinary SystemHNF1B, HNF4, CDX, FTFC/EBP, FOXA, GATAKidneyUrinary tract

Respiratory SystemHNF-3, NKX2.1 and GATA6AirwaysLungs

Reproductive OrgansER, SF1, DAX1, C/EBPOvaryUterusBreastTestis

Skeletal and MuscularMYOD, MEF2, MRF4, MYF5MyogeninBoneMuscleCartilage

Hematopoietic SystemTAL1, LMO1, LMO2, E2A, XBP1, AML1, MLL1, PU.1, C/EBPBone marrowBloodEmbryonic Liver

Immune SystemSTAT1, STAT3 STAT5, NFB family, IRF1, IRF3, IRF5ThymusSpleenLymph nodes

Sensory OrgansSOX1-18, OCT6, PAX3,PAX6, NGN, SKIN1EyeEarOlfactorySkinTongue

June 2006Page 16

ChIP-on-chip: The Agilent AdvantageFlexibility

• Rapid custom design iteration and turnaround with inkjet technology

• Over 9 species for whole genome and focused microarrays

• Wide range of array formats

• Analysis software and visualization tools and support

Commitment

• Dedicated ChIP-on-chip in-house expertise and support

Quality

• Unique, unmatched probe design – Tm-balanced format,optimal spacing deliver enhanced specificity and sensitivity

June 2006Page 17

Microarray format flexibility

244k

15k

105k

Standard 1 x3 slide

Multi-pak Capability

e.g. C. elegans whole genome

244k

100 bp

200 bp

300 bp

3

2

1

number of slidesprobesspacing

44k

June 2006Page 18

Agilent ChIP-on-chip:Human, Mouse, Rat Arrays

Promoter arrays: approx. -5.5kb to +2.5kb around transcription start sites for ~17,000 RefSeq genes

- Human hg17- Mouse mm7 Whole genome sets- HumanDatabases (customization) – 100 bp tiled probes across genome- Human hg17, hg18 available soon- Mouse mm7-Rat, Rn 3.1

Analyze protein-DNA binding events and protein structure/function in mammalian systems

June 2006Page 19

Agilent ChIP-on-chip:Model Organism Arrays

Model whole genome tiled arrays and tiled databases - Yeast (S. cerevisiae)- Plant (A. thaliana), ath1- Round Worm (C. elegans), Ce2- Fly (D. melanogaster), dm2Shared design:- Yeast (S. pombe)Model promoter arrays- Zebrafish (D. rerio), zv4

Compare protein-DNA binding events and protein structure/function

between model organisms and human systems

June 2006Page 20

Agilent CpG ChIP-on-chip:Exploring DNA methylation

CpG

CpG

CpGCpG

CpG

CpGCpG

CpG

CpG

Tiled arrays with 60-oligomer probes spaced ~100 bp apart

Uses the CpG island probes defined by Gardiner-Garden and Frommer from UCSC hg17/NCBI release 35 (May 2004 build)

Compatible with methylated DNA immunoprecipation method (Keshet et. al, 2006) and possibly other methods

June 2006Page 21

Genome wide detection of DNA methylation

Restriction enzyme based approaches

Advantages• Specific• Sensitive

Disadvantages• Limited to RE sites• Complex data analysis• Reference

Antibody based method (mDIP)Advantages

• Unbiased• Simpler data analysis• Genomic reference

Disadvantages• Cross reactivity• Sensitivity ?

CH3

CH3

CH3

CH3

digest

CH3

CH3

fragment

June 2006Page 22

eArraySelf-service custom array design

Upload and print your own designs (60-mers)

Select Agilent-designed probes for your genomic regions

RAPID Turnaround: 2-3 week delivery

http://earray.chem.agilent.com

June 2006Page 23

Features:

User control over analysis steps and parameters

Multiple output formats & reports

Quality Control report

Peak detection visualization

Support for replicates

Compatibility with UCSC Genome Browser

Windows or Macintosh platforms

Coming soon: ChIP/CGH Analytics plus support for methylation

Software: ChIP AnalyticsProcess spot intensities to determine binding sites

Agilent Scan

Axon Scan

Agilent FE

GenePix

Chip Analytics

Ver 1.2

June 2006Page 24

Summary

Dedication

Expertise

Flexibility

Conduct your experiments today

June 2006Page 25

Agilent’s Strength

Commitment• Acquired seminal intellectual property• Provide local application scientist support• Customer trainings & workshops (EMBL,

CSHL, and Agilent)

Quality• Highest sensitivity in industry• Feature quality (size, physical oligo,

optimized 60-mers)• Validated probe selection process• NO complex statistical manipulations• Easy to use analysis software

Flexibility• Conduct experiments TODAY • Rapid custom array design leveraging eArray• Multiple array formats on 1x3 glass slide• Density of up to 440,000 (future) features on a single

slide

June 2006Page 26

APPENDIX

June 2006Page 27

Where the proteome meets the genome

Binding Protein

June 2006Page 28

Chromatin Immunoprecipitation (ChIP)

TFDNA

TFDNA

Cross-link protein to DNA

With formaldehyde

Randomly shear DNA

By sonication

TFDNA

Precipitate DNA-protein

Complex with anti-TF Antibody

TFTF TF

TF Reverse Cross-linking

Purify DNA

Enriched, TF bound

DNA

June 2006Page 30

GENE XGENE YTF

ChIP-enrichment of DNA vs. total DNA input

Total DNA input (WCE)

Enriched DNA (IP)

Note: chromatin DNA fragments

are ~100 - 500 bp

June 2006Page 31

“ChIP on chip” / Location Analysis

GENE XGENE YTF

Chromosome position

En

ric

hm

en

t

1x

Cy5 / Cy3

June 2006Page 32

High Accuracy Location Analysis Start with optimal probe design

Goals:• Construct a database of high-quality

probes spanning the genome. • Provide tools to select probes onto arrays

for particular applications.

Methodology

• Tile 60-mers at 1-bp spacing across non-RepeatMasked genome (1.3B probes).

• Reduce 10-fold by thermodynamic scores (130M probes).

• Homology search against the genome using ProbeSpec (custom homology search tool designed for probe matching).

• Reduce 10-fold using thermodynamic and homology scores (13M probes).

• Re-score homology using MegaBlast (catches gapped alignments).

Notes

• Probe scoring model is trained on XY/XX or other model systems.

• Down-selection uses Pairwise Reduction to balance probe spacing with probe quality.

June 2006Page 33

Probe Design

List of Probes Find smallest interval Remove worst of pair< N

Advantages

• Balances spacing with performance

• Scoring is easily tuned

• Robust to genome perturbations

ACTG

Pairwise Reduction

Location Analysis

Select regions based on TSS, merge

overlapping regions.

CGH

Select entire chromosomes, apply spatial bias to over-represent desirable sub-regions (genes,

promoters, CpG islands, etc).

ARRAY DESIGN1. Select regions2. Select all probes in regions3. Apply Pairwise Reduction to

achieve desired probe count or coverage

June 2006Page 34

Probe DesignChoosing the best probes

• Agilent’s proven platform

• 60-mers, robust hybridization

Increasingly constrained region …

… limited chances of finding a well-behaved probe

• Probe optimization criteria:

• Uniqueness (homology)

• Tm

• Self-structure

Probes

Net effect: Constrained regions Restricted probe performance Noisier system

More probes ≠ more accurate measurements. One well chosen 60mer gives greater measurement accuracy than the statistical average of multiple “noisy” probes

June 2006Page 35

Recent presentationsGraves Lab, Huntsman InstituteSystems Biology, Cold Spring Harbor Laboratory, Mar. 23-26, 2006

June 2006Page 36

Recent presentationsMyers Lab, Stanford UniversityThe Biology of Genomes, Cold Spring Harbor Laboratory, May 10-14, 2006

June 2006Page 37

Recent presentationsHuang Lab, Ohio State UniversityAACR, Washington DC, Apr. 1-5, 2006

June 2006Page 38

Working with leaders50+ Customers & Growing…

Agilent Technologies expands microarray technology agreement to National Cancer Institute extramural researchersAccess to emerging techniques enables more scientists to study cancer from multiple perspectives, speed progress toward 2015 goal

PALO ALTO, Calif., Dec. 1, 2005 Citing growing demand for emerging microarray applications that complement gene expression studies, Agilent Technologies Inc. (NYSE: A) today announced the extension of its technology access program to National Cancer Institute (NCI) extramural researchers. The NCI funds approximately 4,500 research grants a year.

NCI extramural researchers can now obtain Agilent's microarray solutions for comparative genomic hybridization (CGH), ChIP-on-chip (also known as location analysis), and gene expression under the agreement. NCI's intramural Center for Cancer Research (CCR) already has access to the Agilent microarray technology.

"The NCI's goal is to eliminate the suffering and death due to cancer by 2015, and growing numbers of researchers realize that this can't be achieved using gene expression data alone," said Fran DiNuzzo, Agilent Life Science and Chemical Analysis vice president and general manager, Integrated Biology Solutions. "We're focused on providing the genomics tools to help scientists study pathways from multiple perspectives, link applications with well-designed bioinformatics systems, and thus reach useful discoveries faster."

Microarray-based CGH is being recognized as a powerful technique for pinpointing genomic gains and losses associated with cancer and other genetic-based diseases. A paper in the December 2004 issue of the Proceedings of the National Academy of Sciences (PNAS) demonstrates that oligonucleotide arrays designed for CGH provide a robust and precise platform for detecting chromosomal alterations with high sensitivity, even in complex samples such as those used by oncology investigators.

ChIP-on-chip is an emerging microarray application for determining where proteins bind to regulatory regions of DNA. The September 2005 issue of Cell published a paper by professor Richard Young's laboratory at the Whitehead Institute, validating the effectiveness of this technique by examining key transcriptional regulators of stem cells. The prior month's issue described the utility of location analysis in producing high-resolution maps of histone acetylation and methylationin yeast. This technique is important, as changes in chromatin structure play an important role in the silencing of certain genes in cancer, and histone deacetylase inhibitors have demonstrated anti-cancer effect.

"We observe very impressive enrichment upon immunoprecipitation with these microarrays, and the dynamic range of the signal in the IP channel is excellent -- the background signal is extremely low," said Dr. Brian Dynlacht, director of Genomics Program for New York University's Cancer Institute, an NCI extramural researcher referring to his use of Agilent's mammalian location analysis microarrays.

The technology access program includes Agilent reagents, catalog and custom microarrays, instrumentation, and software. In addition to providing promotional pricing, the program encourages broad publication of scientific results. It is designed to facilitate collaborations between academic, governmental and commercial researchers.

Agilent Technologies expands microarray technology agreement to National Cancer Institute extramural researchersAccess to emerging techniques enables more scientists to study cancer from multiple perspectives, speed progress toward 2015 goal

PALO ALTO, Calif., Dec. 1, 2005 Citing growing demand for emerging microarray applications that complement gene expression studies, Agilent Technologies Inc. (NYSE: A) today announced the extension of its technology access program to National Cancer Institute (NCI) extramural researchers. The NCI funds approximately 4,500 research grants a year.

NCI extramural researchers can now obtain Agilent's microarray solutions for comparative genomic hybridization (CGH), ChIP-on-chip (also known as location analysis), and gene expression under the agreement. NCI's intramural Center for Cancer Research (CCR) already has access to the Agilent microarray technology.

"The NCI's goal is to eliminate the suffering and death due to cancer by 2015, and growing numbers of researchers realize that this can't be achieved using gene expression data alone," said Fran DiNuzzo, Agilent Life Science and Chemical Analysis vice president and general manager, Integrated Biology Solutions. "We're focused on providing the genomics tools to help scientists study pathways from multiple perspectives, link applications with well-designed bioinformatics systems, and thus reach useful discoveries faster."

Microarray-based CGH is being recognized as a powerful technique for pinpointing genomic gains and losses associated with cancer and other genetic-based diseases. A paper in the December 2004 issue of the Proceedings of the National Academy of Sciences (PNAS) demonstrates that oligonucleotide arrays designed for CGH provide a robust and precise platform for detecting chromosomal alterations with high sensitivity, even in complex samples such as those used by oncology investigators.

ChIP-on-chip is an emerging microarray application for determining where proteins bind to regulatory regions of DNA. The September 2005 issue of Cell published a paper by professor Richard Young's laboratory at the Whitehead Institute, validating the effectiveness of this technique by examining key transcriptional regulators of stem cells. The prior month's issue described the utility of location analysis in producing high-resolution maps of histone acetylation and methylationin yeast. This technique is important, as changes in chromatin structure play an important role in the silencing of certain genes in cancer, and histone deacetylase inhibitors have demonstrated anti-cancer effect.

"We observe very impressive enrichment upon immunoprecipitation with these microarrays, and the dynamic range of the signal in the IP channel is excellent -- the background signal is extremely low," said Dr. Brian Dynlacht, director of Genomics Program for New York University's Cancer Institute, an NCI extramural researcher referring to his use of Agilent's mammalian location analysis microarrays.

The technology access program includes Agilent reagents, catalog and custom microarrays, instrumentation, and software. In addition to providing promotional pricing, the program encourages broad publication of scientific results. It is designed to facilitate collaborations between academic, governmental and commercial researchers.

FRANK HOLSTEGE

STEPHEN BELL

RICK YOUNG

ERIN O’SHEA, ANDREW McMAHON

TREY IDEKER, CHRIS GLASS

BRIAN DYNLACHT

BONITA BREWER

RICK MYERS

NAFTALI KAMINSKI

TIM HUANG

FRANCOIS ROBERT

KLAUS KAESTNER

BRAD CAIRNS

GUOPING FAN

WING WONG

JEAN-PIERRE ISSA

June 2006Page 39

DNA methylation

Methylation of C5 of cytosine in CG dinucleotide

– DNA methyltransferases

– Post-replication maintenance (DNMT 1)

– de novo (DNMT3A & DNMT3B)

Gene regulation

– embryonic development

– genomic imprinting

– gene silencing - cancer

CpG islands

– regions of high CG, generally un-methylated, 1% of human genome

– promoter associated

Chromatin stability

June 2006Page 40

Array Roadmap‘MASTER’ TILING DATABASES (~100bp)

Species # Probes

Agilent Designed

Human 13M

Mouse 13M

Rat 10M

Arabidopsis ~750K

C. elegans ~725K

P. aeruginosa TBD

Cryptoccocus TBD

OTHER GENOME DATASETS

Customer Designed

Species Coverage

S. cereveisiae 40K (~266bp)

Drosophila13.8M genome

(~250bp)

Zebrafish11K annotated genes (~250bp)

S. pombe TBD

All Genome Databases will be loaded in eArray v4.5

MAR APR MAY JUN JUL AUG

Catalog & custom 44K designs (100µ)

Early Access 185K designs (60µ)• Hu promoter• Mo promoter• Hu CpG Island• Custom

Catalog 244K (60µ)• Hu promoter• Mo promoter• Hu CpG Island• Hu, Mo, & model

organism WG• Yeast WG (4x44)

Custom 244k & multi-array formats

• 1x244K• 2x110K• 4x44K

DRAFT

DEC

Early Access 440K (30µ) & multi-array formats

*Feature size in parenthesis

June 2006Page 41

22k 44k 185k

1.9k11k

244k

44k

Multi-pak

2001 2002 2003 2004 2005 2006 2007

Existing

Future

July ‘06 Early ‘07

Agilent microarray formats timeline

79k

440k

105k 189k

27k15k

June 2006Page 42

Agilent ChIP-on-chip:Major Applications

• Identify transcription factor and DNA-binding protein targets

• Characterize transcription, DNA replication, and DNA repair events

• Map chromatin modifications such as DNA methylation

• Determine modality and interactions between therapeutic compounds and target genes

• Validate and augment existing gene expression data with true binding events

June 2006Page 43

Available 244K Array Designs: Summary

Array Type Part Number # slides # arrays per slide

# samples Description:

Yeast G4491A 1 1 5 • Probes for ~12 MB of the genome • Probes spacing 50 nt on average

Yeast 4-pack (4x44K) G4493A 1 4 20 • Probes for ~12 MB of the genome • Probes spacing 290 nt on average

Human Expanded Promoter 2-set

G4489A 2 1 5 • ~17,000 best defined human transcripts• Coverage: -5.5k to +2.5k region. Approx. 25

probes/gene.

Mouse Expanded Promoter 2-set

G4490A 2 1 5 • ~17,000 best defined mouse transcripts• Coverage: -5.5k to +2.5k region. Approx. 25

probes/gene

Human CpG Islands G4492A 1 1 5 • 27,800 CpG Islands on 1 array

MADE TO ORDER: Agilent Unrestricted

AMADIDS

G4495A 1 1 1 • Order single slides from sets• Order Human ENCODE, Drosophila,

Arabidopsis, Zebrafish, C. elegans

Custom 1x244K G4496A 1 1 1 • Create your own array

Custom 4x44K G4497A 1 4 4 • Create your own array

June 2006Page 44

Model organism and made-to-order arraysArray Type # slides in

setSource Format Part number Design IDs Description:

Drosophila WG 2 dm2 244k G4495A 14816-17 • Drosophila whole genome on 2-array set with 233 nt average tiling density

C. Elegans WG 2 ce2 244k G4495A 14793-94 • C. elegans whole genome on 2-array set with 182 nt average tiling density

Arabidopsis WG 2 ath1 244k G4495A 14798-99 • Arabidopsis whole genome on 2-array set with 212 nt average tiling density

Zebrafish (share) proximal promoter

2 zv4 44k G4475A 013834-35 • Probes cover -1.5kb to +.5kb from the tss and represent 11,000 transcripts

Zebrafish (share) expanded promoter

9 zv4 44k G4475A 013824-32 • Probes cover -9kb to +3kb from the tss and represent 11,000 transcripts

S. Pombe WG (share)

1 Sanger, Sep 2004

44k TBD TBD • Whole genome 44K array, shared

Human ENCODE 1 Human ENCODE

244k G4495A 14792 • 153K probes covering ENCODE regions on single slide