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Postgenomics FUNCTIONAL GENOMICS DNA Chips and Microarrays

Postgenomics FUNCTIONAL GENOMICS DNA Chips and Microarrays. CSUS, Nov 15, 2001 Zeljka Smit-McBride zsmcbride@ucdavis.edu University of California, Davis. Central Dogma of Molecular Biology. DNA makes RNA makes PROTEIN. LEVEL OF SINGLE GENE ANALYSIS. RNA. PROTEIN. TRANSCRIPTION.

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Postgenomics FUNCTIONAL GENOMICS DNA Chips and Microarrays

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  1. PostgenomicsFUNCTIONAL GENOMICSDNA 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 RNA PROTEIN TRANSCRIPTION TRANSLATION PROTEIN DNA RNA

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

  5. EFFECT OF mRNA OVEREXPRESSION NORMAL OVEREXPRESSED

  6. THE -OME AND -OMICS GENOMICS: study of GENOME; how many GENES, physical map, sequence of their DNA, structure… FUNCTIONAL GENOMICS: study ofTRANSCRIPTOME; 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. robotic engineering pin technology molecular biology DNA sequencing computers optical technology laser technology informatics New technology - Microarrays • Able to look at gene expression programs • on a very large scale • Advancements in several technologies:

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

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

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

  20. After hybridization... RED - OVEREXPRESSED • 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 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 Biotinylated RNA target from experi- mental sample Each probe cell contains millions of copies of a specific oligonucleotide probe GeneChip expression analysis probe array 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 mRNA DNA probe pairs Reference Sequence Perfect Match Oligo Mismatch Oligo Fluorescence Intensity Image Perfect match probe cells Mismatch probe cells Lipshutz, RJ, Fodor, SPA, Gingeras, TR & DJ Lockhart, Nature Genetics Supplement, Vol 21, Jan 1999, pp 20-24

  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 Mismatch Perfect Match Perfect Match Mismatch Allele A Allele B Genotype A/A B/B A/B 120,000 probes for 3,000 biallelic loci

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

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

  34. Structural Genomics- High Throughput Protein Structure Determination

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

  36. The Q-bot picks 3,000 colonies/hour The Gene Machine grows 16 96-deep well plates PCR reactions set up with a Beckman biomek 2000 The Eppendorf manifold does 384 minipreps at a time 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 G A A G T G A C G T A A T T C T A T T G C A C C T T C T “Now we’ve done it! Now, we’ll really need big computers to help us make sense out of this!”

  39. BIOLOGY BIO INFORMATICS INFORMATION TECHNOLOGY COMPUTER SCIENCE

  40. TRANSLATION INITIATION FACTORS eIFs-NOVEL MECHANISM OF ONCOGENESIS

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

  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

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