1. Vidyadhar Karmarkar Genomics and Bioinformatics 414 Life Sciences Building, Huck Institute of Life Sciences

2. Felsenfeld and Groudine (2003) Nature 421, 448-453 Chromosomal Packaging 2.9 million bp in haploid human genome 1.5% human genome codes for proteins 20,000 human genes Chromatin

3. Promoter 5’ UTR ATG Exons Stop 3’ UTR Poly A Signal Introns Gene Structure

4. Transcription – A quick review http://www.msu.edu/course/lbs/ 145/smith/s02/graphics/ campbell_17.7.gif

5. Hanlon and Lieb (2004) Curr. Opin. Gen. & Dev. 14:697-705 Single TF-Multiple Responses

6. Transcriptome Research Tag-based Microarrays chIP-chip Computational Traditional

7. Limitations of current methods in Transcriptome Research Are in vitro and not in vivo Gel-shift assays poor predictors of TF’s actual binding site Computational approaches frustrating DNA-footprinting and chIP-qtPCR reveals limited information -Buck and Lieb (2004) Genomics 83:349-360 RNA level measurement - an indirect indicator of TF activity – Hanlon and Lieb (2004) Curr. Opin. Gen. Dev. 14:697-705

8. Basic steps in chIP Fixation Sonication Immunoprecipitation Analysis of IP-ed DNA Das et al (2004) Biotechniques 37(6) 961-969

9. Advantages of chIP Information about in vivo location of TF binding sites on the DNA Captures information from living cells Powerful tool in genomics when coupled to cloning and microarrays Das et al (2004) Biotechniques 37(6) 961-969

10. chIP-chip Buck and Lieb (2004) Genomics 83:349-360 chIP Das et al (2004) Biotechniques 37(6) 961-969

11. Summary of chIP-chip Employs the strategy of enriching the TF-target sites by immunoprecipitating followed by microarray to detect the level of enrichment Sikder and Kodadek (2005) Curr. Opin. Chem. Biol. 9:38-45

12. Types of DNA microarrays Types: Mechanically spotted cDNA/amplicons Mechanically spotted oligos In situ synthesis of oligos Buck and Lieb (2004) Genomics 83:349-360 Most of these arrays made from transcribed genomic regions

13. Promoter region is not transcribed TF binding sites mapped: Outside the predicted promoter region (Cawley et al 2002 Genome Res. 12:1749-1755; Martone et al 2003 PNAS 100:12247-12252; Euskirchen 2004 Mol. Cell. Biol. 24:3804-3814) In coding and non-coding regions (Martone et al 2003 PNAS 100:12247-12252; Euskirchen 2004 Mol. Cell. Biol. 24:3804-3814) Choosing chip for chIP

14. On separate arrays enrichment at any given spot is relative to sequences on same array Whole genome arrays reveals enrichment of ORFs relative to intergenic regions Hanlon and Lieb (2004) Curr. Opin. Gen. & Dev. 14:697-705

15. Maximizing TF-target identification Arrays that tile across an entire regulatory region of interest (Horak et al 2002 PNAS 99:2924-2929) –Comprehensive but specific to the regulatory region –Limited information CpG island microarray (Weinmann et al 2002 Genes & Dev 16:235-244) –Less # of primers => reduced cost –Unbiased coverage of large portion of genome –Requires sequence information on identity of clones –Low cost but highly informative option to whole genome arrays

16. ‘DNA tiling arrays’ (whole genome arrays) representing all intergenic regions and predicted coding sequences (Iyer et al 2001 Nature 409:533-538) - Successfully used in yeast (Buck and Lieb 2004 Genomics 83:349-360) –Costly and technically challenging to make in organisms with large genomes Maximizing TF-target identification

17. Resolution of chIP-chip within 1-2 kb and exact site of DNA-protein interaction unknown Programs to analyze chIP-chip data: –MDScan (Liu et al 2002 Nature Biotech. 20:835- 839) –MOTIF REGRESSOR (Conlon et al 2003 PNAS 100 (6):3339-3344) Computational Validation of chIP-chip data

18. Drawbacks of chIP-chip chIP is technically challenging Promiscuous crosslinking by formaldehyde Resolution dependant on: –Sheared DNA fragment size, –length and spacing of arrayed DNA elements used to detect IP elements Cost of making arrays Buck and Lieb (2004) Genomics 83:349-360

19. Possible complications with chIP-chip Differential formation of DNA-protein crosslinks Variable epitiope accessibility Hanlon and Lieb (2004) Curr. Opin. Gen. & Dev. 14:697-705 Legend:

20. Normalization of chIP-chip data Mistaking ubiquitous modification to be uniform distribution Mistaking promoter associated modification to be uniform distribution Hanlon and Lieb (2004) Curr. Opin. Gen. & Dev. 14:697-705

21. Conclusion chIP-chip is efficient method for TF-target identification Computational and biochemical validation of chIP-chip data required to pinpoint the exact site of TF-DNA interaction chIP-CpG arrays are cost effective alternative to chIP-WG arrays

22. Future Prospects Novel insights in genomics of pathogenesis, development, apoptosis, cell cycle, genome stability and epigenetic silencing, chromatin remodelling High-throughput method for genome annotation and cross-validation of previous data