1. Postgenomics FUNCTIONAL GENOMICS DNA Chips and Microarrays CSUS, Nov 15, 2001 Zeljka Smit-McBride zsmcbride@ucdavis.edu University of California, Davis

2. Central Dogma of Molecular Biology DNA makes RNA makes PROTEIN

3. LEVEL OF SINGLE GENE ANALYSIS DNA RNA PROTEIN RNA PROTEIN TRANSCRIPTION TRANSLATION

4. LEVEL OF THE WHOLE GENOME ANALYSIS GENOME RNA PROTEIN TRANSCRIPTOME PROTEOME TRANSCRIPTION TRANSLATION

5. EFFECT OF mRNA OVEREXPRESSION NORMALOVEREXPRESSED

6. THE -OME AND -OMICS GENOMICS: study of GENOME; how many GENES, physical map, sequence of their DNA, structure… FUNCTIONAL GENOMICS: study of TRANSCRIPTOME; which, when, where and how much mRNA expressed… PROTEOMICS: study of PROTEOME; which PROTEINS, when, where and how much…

7. What is functional genomics ? To understand the relationship between genotype (a particular set of genes) and phenotype (a set of features of the whole organism), we need to look at the function of the entire genome. This is reflected in the cellular expression pattern of mRNA. This is the area of study of functional genomics.

8. New technology - Microarrays robotic engineering pin technology molecular biology DNA sequencing computers optical technology laser technology informatics Able to look at gene expression programs on a very large scale Advancements in several technologies:

9. Orderly grid or matrix of genes we know exactly which gene is at each spot What is microarray?

10. Custom microarray

11. DNA microarrays DNA microarrays are microscopic groups of thousands of DNA molecules of known sequence attached to a solid surface. Traditional Spoted arrays - cDNA DNA chip – oligonucleotides synthesized in situ

12. What is cDNA ? Genomic DNA hnRNA mRNA cDNA protein Exon 1Exon 2Exon 3 splicing Reverse transcription transcription

13. DNA on the slide after hybridization Duggan, et al, Nature Genetics Supplement, Vol21, Jan 1999

14. Components of the of functional genomics analysis RNA sample preparation Array generation and sample analysis Data handling and analysis - bioinformatics

15. The front end - from sample to RNA Bowtell, DDL, Nature Genetics Supplement, Vol 21, Jan 1999, pp 25-32

16. Middleware: making and using microarrays Bowtell, DDL, Nature Genetics Supplement, Vol 21, Jan 1999, pp 25-32

17. Back end: moving and handling data Bowtell, DDL, Nature Genetics Supplement, Vol 21, Jan 1999, pp 25-32

18. Important principles from molecular biology DNA makes RNA makes PROTEIN Genetic Code A=T and G=C Complementary strands hybridize Genomic DNA vs mRNA vs cDNA

19. Gene expression analysis using DNA microarrays DNA microarray TEP 1 cDNA mRNA P.O.Brown & D.Botstein, Nature Genetics Supplement, Vol 21, Jan 1999, pp 33-37

20. we know exactly which gene is at each spot based on color of each spot after the experiment we can tell which gene expressions have changed After hybridization... RED - OVEREXPRESSED GREEN - UNDEREXPRESSED YELLOW - NO CHANGE

21. Applied Genomics Exploiting the human genome Molecular diagnostics of cancer SNPs and Personal pills Pharmacogenomics and new drugs Structural genomics and new targets and many more

22. Gene expression in Molecular Diagnostics

23. Molecular Classification of Malignant Melanoma

24. A chip of a different flavor GeneChip

25. GeneChip Expression Analysis Process GeneChip expression analysis probe array Each probe cell contains millions of copies of a specific oligonucleotide probe Biotinylated RNA target from experi- mental sample Streptavidin- phycoerythrin conjugate Image of hybridized probe array

26. Oligonucleotide Arrays Southern et al, Nature Genetics Suppl., Vol 21, Jan 1999

27. Light directed oligonucleotide synthesis Lipshutz, R.J., Fodor, S.P.A., Gingeras, T.R. & D. LockhartNature Genetics Supl., Vol 21, Jan 1999, pp. 20-24

28. GeneChip Expression Array Design Perfect match probe cells Mismatch probe cells mRNA DNA probe pairs Reference Sequence Lipshutz, RJ, Fodor, SPA, Gingeras, TR & DJ Lockhart, Nature Genetics Supplement, Vol 21, Jan 1999, pp 20-24 Fluorescence Intensity Image Perfect Match Oligo Mismatch Oligo

29. Gene expression oligonucleotide array performance characteristics

30. SNP - single nucleotide polymorphism Variations in the gene sequence, resulting in the amino acid change in the protein, which results in the altered function Genotyping of oncogenes - cancer causing or permitting genes Identifying and genotyping drug response gene variants

31. Genotyping Arrays 120,000 probes for 3,000 biallelic loci Allele A Allele B Mismatch Perfect Match Mismatch Genotype A/AB/B A/B

32. High throughput VistaArray microarrays platform for SNPs genotyping Array (256 elements) Array platform (96 arrays/plate)

33. Evans, WE & Relling, MV, Science, Vol 286, Oct 15, 1999 Pharmacogenomics Translating functional genomics into rational therapeutics

34. Structural Genomics - High Throughput Protein Structure Determination

35. The Exponential Growth of Biological Information NCBI, Aug 2001

36. The Gene Machine grows 16 96-deep well plates The Q-bot picks 3,000 colonies/hour The Eppendorf manifold does 384 minipreps at a time PCR reactions set up with a Beckman biomek 2000 Tetrads run 384 PCR reactions at a time ABI 3700 runs 8 96-well plates/day

37. Birth of a new scientific discipline: Bioinformatics

38. Bioinformatics is: Trying to Swim in a Sea of Data A A A G T G C T G A T C T T T C T C G A T C T A T A G C “Now we’ve done it! Now, we’ll really need big computers to help us make sense out of this!”

39. BIO INFORMATICS BIOLOGY COMPUTER SCIENCE INFORMATION TECHNOLOGY

40. TRANSLATION INITIATION FACTORS eIFs- NOVEL MECHANISM OF ONCOGENESIS

41. OVEREXPRESSION OF TRANSLATION INITIATION FACTORS IN CANCER BREAST, BLADDER, PROSTATE, LYMPHOMAS HEAD&NECK, COLON BREAST, LUNGS OESOPHAGUS PROSTATE T-CELL LEUKEMIA MELANOMA eIF2 LYMPHOMAS

42. TRANSLATION INITIATION FACTORS - NOVEL MECHANISM OF ONCOGENESIS FUTURE DIRECTIONS PROSTATE CANCER –DETECTION MARKERS FOR EARLIEST CANCER STAGES MARKERS FOR THE RISK OF METASTASIS TUMOR PROGRESSION MARKERS –TREATMENT NOVEL THERAPEUTIC TARGETS –MECHANISM HYPOTHESIS - ROLE IN INCURABLE ANDROGEN INDEPENDENT PROSTATE CANCER STAGE

43. Where to from here?

44. Sci.Am., Aug 2001

45. E-cell The Self-surviving Cell Model TRENDs in Biotechnology,Vol 19, No 6, June 2001

46. Conclusions There is life after genomics revolution ! Genome information exploitation ! Pharmaceutical industry can move faster - design better drugs, utilize more targets Massive move toward automation and high- throughput sample analysis Expression profiling is painting the functional picture of the physiology of the cell and eventually tissue, organism...

47. On-line Resources NCBI-http://www.ncbi.nlm.nih.gov/ Stanford- http://genome-www.stanford.edu/ Affymetrix- http://www.affymetrix.com Silicon Genetics- http:www.signetics.com/GeneSpring/ Brown Lab, Stanford University- http://cmgm.stanford.edu/pbrown/explore MicroArray Project, NIH- http://www.nhgri.nih.gov/ E-cell- http://www.e-cell.org/

48. THE END