Vidyadhar Karmarkar Genomics and Bioinformatics

414 Life Sciences Building, Huck Institute of Life Sciences

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

Promoter

5’ UTR

ATG

Exons

Stop

3’ UTR

Poly A Signal

Introns

Gene Structure

Transcription – A quick review

http://www.msu.edu/course/lbs/145/smith/s02/graphics/campbell_17.7.gif

Hanlon and Lieb (2004) Curr. Opin. Gen. & Dev. 14:697-705

Single TF-Multiple Responses

Transcriptome Research

Tag-based

Microarrays

chIP-chip

Computational

Traditional

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-chip

Buck and Lieb (2004) Genomics 83:349-360

chIP

Das et al (2004) Biotechniques37(6) 961-969

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

Buck and Lieb (2004) Genomics 83:349-360

Most of these arrays made from transcribed genomic regions

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

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 (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

• ‘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

• 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

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

Hanlon and Lieb (2004) Curr. Opin. Gen. & Dev. 14:697-705

Legend:

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