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Vidyadhar Karmarkar Genomics and Bioinformatics 414 Life Sciences Building, Huck Institute of Life Sciences Chromosomal Packaging Chromatin 2.9 million bp in haploid human genome 1.5% human genome codes for proteins 20,000 human genes Felsenfeld and Groudine (2003) Nature 421, 448-453 Gene Structure 5’ UTR Promoter Introns ATG 3’ UTR Exons Stop Poly A Signal Transcription – A quick review http://www.msu.edu/course/lbs/ 145/smith/s02/graphics/ campbell_17.7.gif Single TF-Multiple Responses Hanlon and Lieb (2004) Curr. Opin. Gen. & Dev. 14:697-705 Transcriptome Research chIP-chip Traditional Tag-based Microarrays Computational 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 Basic steps in chIP Fixation Sonication Immunoprecipitation Analysis of IP-ed DNA Das et al (2004) Biotechniques 37(6) 961-969 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 chIP Das et al (2004) Biotechniques 37(6) 961-969 chIP-chip Buck and Lieb (2004) Genomics 83:349-360 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 Types of DNA microarrays Types: • Mechanically spotted cDNA/amplicons • Mechanically spotted oligos • In situ synthesis of oligos Most of these arrays made from transcribed genomic regions Buck and Lieb (2004) Genomics 83:349-360 Choosing chip for chIP 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 • 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 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 16:235-244) – – – – (Weinmann et al 2002 Genes & Dev 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 Maximizing TF-target identification • ‘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 Computational Validation of chIP-chip data • 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. 20:835839) – MOTIF REGRESSOR (Conlon et al 2003 PNAS 100 (6):3339-3344) 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 Possible complications with chIP-chip Differential formation of DNA-protein crosslinks Variable epitiope accessibility Legend: Hanlon and Lieb (2004) Curr. Opin. Gen. & Dev. 14:697-705 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 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 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