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LOCATION ANALYSIS (ChIP-on-chip) Regulation of Human ES Cells June 2006

LOCATION ANALYSIS (ChIP-on-chip) Regulation of Human ES Cells June 2006. Mammalian Development. Richard Young, Professor of Biology, MIT. Cell 125, 301-313, April 21, 2006. Overview: Control of embryonic stem cells. ES cells must remain pluripotent until signalled to differentiate

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LOCATION ANALYSIS (ChIP-on-chip) Regulation of Human ES Cells June 2006

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  1. LOCATION ANALYSIS (ChIP-on-chip) Regulation of Human ES Cells June 2006

  2. Mammalian Development Richard Young, Professor of Biology, MIT Cell 125, 301-313, April 21, 2006.

  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

  4. BMI1 RING1 hPc2 PRC1 NH4-ARTKQTARKSTGGKAPRKQLATKAARKSAPATG H3 EED SUZ12 EZH2 PRC2 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

  5. ChIP Human embryonic stem cells (H9) Scatter plot (ChIP / reference) Whole genome arrays 4.6 million features Promoters bound by RNA polymerase II or Suz12 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

  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

  7. Suz12 6.5% Both 1.9% Pol II 30% Neither NEUROD1 HNRPA3 Suz12 & Pol II are mutually exclusive Pol II Suz12 Fold Enrichment Pol II Suz12 Fold Enrichment Lee et. al., Cell 2006

  8. Development Reg. of Transcription Morphogenesis Organogenesis Neurogenesis Cell-cell signaling Protein transport Cell cycle Resp.to DNA damage DNA metabolism Protein biosynthesis RNA metabolism 1E0 1E-20 1E-40 1E-60 Suz12 RNA Pol II PRC2 occupies key developmental regulators confirmed by SUZ12 occupation • SUZ12 mainly occupies genes that control development and transcription • RNA pol II occupies genes controlling broader cell proliferation functions

  9. Transcription factor family members occupied by PRC2 HOX OLIG2 CDX2 IRX BHLHB CDX MEIS/EVX MEIS1 T TBX DLX MYO MYOD1 HES FOX FOXA1 NEUROG2 ATOH NEUROD EBF NEUROD1 GATA EBF POU RUNX GATA4 PAX SOX NKX LHX SIX SOX21 PAX3 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 Red circles: Individual TFs White ovals: TF with defined role in development

  10. Pol II Suz12 Suz12 covers large domains over HOX clusters • 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

  11. RNAP2 SUZ12 Targets of PRC2 shared with key ES cell regulators • 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

  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

  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.

  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.

  15. Master Regulators of Mammalian Transcription Embryonic stem cells OCT4, NANOG, SOX2 Polycomb Brain and Spinal Cord SOX1-18, OCT6, MeCP2 CBP, NGN, NEUROD Cerebrum Cerebellum Ganglia & nerves Circulatory System Myocardin, GATA4, TBX5, NKX2.5, MEF2, HAND Heart Vascular system Digestive System HNF1, HNF4, HNF6, CBP, PGC1, FOXA, PDX1, GATA, Esophagus Stomach Intestines Liver Pancreas Urinary System HNF1B, HNF4, CDX, FTF C/EBP, FOXA, GATA Kidney Urinary tract Respiratory System HNF-3, NKX2.1 and GATA6 Airways Lungs Reproductive Organs ER, SF1, DAX1, C/EBPb Ovary Uterus Breast Testis Skeletal and Muscular MYOD, MEF2, MRF4, MYF5 Myogenin Bone Muscle Cartilage Hematopoietic System TAL1, LMO1, LMO2, E2A, XBP1, AML1, MLL1, PU.1, C/EBP Bone marrow Blood Embryonic Liver Immune System STAT1, STAT3 STAT5, NFB family, IRF1, IRF3, IRF5 Thymus Spleen Lymph nodes Sensory Organs SOX1-18, OCT6, PAX3, PAX6, NGN, SKIN1 Eye Ear Olfactory Skin Tongue

  16. ChIP-on-chip: The Agilent Advantage • Flexibility • 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

  17. 244k 44k Microarray format flexibility Standard 1 x3 slide Multi-pak Capability 105k 15k e.g. C. elegans whole genome number of slides probes spacing 244k 100 bp 3 200 bp 2 300 bp 1

  18. Agilent ChIP-on-chip:Human, Mouse, Rat Arrays • Analyze protein-DNA binding events and protein structure/function in mammalian systems • Promoter arrays: approx. -5.5kb to +2.5kb around transcription start sites for ~17,000 RefSeq genes • - Human hg17 • Mouse mm7 • Whole genome sets • Human • Databases (customization) – 100 bp tiled probes across genome • Human hg17, hg18 available soon • Mouse mm7 • Rat, Rn 3.1

  19. Agilent ChIP-on-chip:Model Organism Arrays • Compare protein-DNA binding events and protein structure/function between model organisms and human systems • Model whole genome tiled arrays and tiled databases • - Yeast (S. cerevisiae) • Plant (A. thaliana), ath1 • Round Worm (C. elegans), Ce2 • Fly (D. melanogaster), dm2 • Shared design: • Yeast (S. pombe) • Model promoter arrays • - Zebrafish (D. rerio), zv4

  20. CpG CpG CpG CpG CpG CpG CpG CpG CpG Agilent CpG ChIP-on-chip:Exploring DNA methylation • 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

  21. Genome wide detection of DNA methylation CH3 • 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 ? digest CH3 CH3 CH3 fragment CH3 CH3

  22. eArraySelf-service custom array design • Upload and print your own designs (60-mers) • Select Agilent-designed probes for your genomic regions http://earray.chem.agilent.com RAPID Turnaround: 2-3 week delivery

  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 Agilent FE Chip Analytics Ver 1.2 Axon Scan GenePix

  24. Summary • Dedication • Expertise • Flexibility • Conduct your experiments today

  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

  26. APPENDIX

  27. Binding Protein Where the proteome meets the genome

  28. TF TF TF TF Chromatin Immunoprecipitation (ChIP) TF DNA Cross-link protein to DNA With formaldehyde TF DNA Randomly shear DNA By sonication TF DNA Precipitate DNA-protein Complex with anti-TF Antibody Enriched, TF bound DNA Reverse Cross-linking Purify DNA

  29. TF Note: chromatin DNA fragments are ~100 - 500 bp GENE Y GENE X ChIP-enrichment of DNA vs. total DNA input Enriched DNA (IP) Total DNA input (WCE)

  30. TF GENE Y GENE X “ChIP on chip” / Location Analysis Cy5 / Cy3 Enrichment 1x Chromosome position

  31. 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. • 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). 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.

  32. Advantages • Balances spacing with performance • Scoring is easily tuned • Robust to genome perturbations 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 DESIGN • Select regions • Select all probes in regions • Apply Pairwise Reduction to achieve desired probe count or coverage Probe Design Pairwise Reduction < N List of Probes Remove worst of pair Find smallest interval ACTG

  33. Agilent’s proven platform 60-mers,robust hybridization Probe DesignChoosing the best probes • Probe optimization criteria: • Uniqueness (homology) • Tm • Self-structure Increasingly constrained region … Probes … limited chances of finding a well-behaved probe 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

  34. Recent presentations Graves Lab, Huntsman Institute Systems Biology, Cold Spring Harbor Laboratory, Mar. 23-26, 2006

  35. Recent presentations Myers Lab, Stanford University The Biology of Genomes, Cold Spring Harbor Laboratory, May 10-14, 2006

  36. Recent presentations Huang Lab, Ohio State University AACR, Washington DC, Apr. 1-5, 2006

  37. Working with leaders50+ Customers & Growing… RICK YOUNG RICK MYERS TIM HUANG ERIN O’SHEA, ANDREW McMAHON TREY IDEKER, CHRIS GLASS FRANCOIS ROBERT BRIAN DYNLACHT WING WONG BRAD CAIRNS JEAN-PIERRE ISSA GUOPING FAN NAFTALI KAMINSKI KLAUS KAESTNER BONITA BREWER FRANK HOLSTEGE STEPHEN BELL

  38. 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

  39. DRAFT Array Roadmap MAR APR MAY JUN JUL AUG DEC Catalog & custom 44K designs (100µ) Early Access 440K (30µ) & multi-array formats • 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 All Genome Databases will be loaded in eArray v4.5 *Feature size in parenthesis

  40. Agilent microarray formats timeline 22k 44k 185k 244k 440k 2001 2002 2003 2004 189k 105k 11k 1.9k 44k 79k 15k 27k Existing Future July ‘06 Early ‘07 2005 2006 2007 Multi-pak

  41. 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

  42. Available 244K Array Designs: Summary

  43. Model organism and made-to-order arrays

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