1. The Central Dogma

2. Life - a recipe for making proteins DNA protein RNA Translation Transcription

3. ATCTTTTTCGGCTTTTTTTAGTATCCACAGAGGTTATCGACAACATTTTCACA TTACCAACCCCTGTGGACAAGGTTTTTTCAACAGGTTGTCCGCTTTGTGGAT AAGATTGTGACAACCATTGCAAGCTCTCGTTTATTTTGGTATTATATTTGTGT TTTAACTCTTGATTACTAATCCTACCTTTCCTCTTTATCCACAAAGTGTGGAT AAGTTGTGGATTGATTTCACACAGCTTGTGTAGAAGGTTGTCCACAAGTTGT GAAATTTGTCGAAAAGCTATTTATCTACTATATTATATGTTTTCAACATTTAAT GTGTACGAATGGTAAGCGCCATTTGCTCTTTTTTTGTGTTCTATAACAGAGA AAGACGCCATTTTCTAAGAAAAGGAGGGACGTGCCGGAAGATGGAAAATAT ATTAGACCTGTGGAACCAAGCCCTTGCTCAAATCGAAAAAAAGTTGAGCAA ACCGAGTTTTGAGACTTGGATGAAGTCAACCAAAGCCCACTCACTGCAAGG CGATACATTAACAATCACGGCTCCCAATGAATTTGCCAGAGACTGGCTGGAG TCCAGATACTTGCATCTGATTGCAGATACTATATATGAATTAACCGGGGAAGA ATTGAGCATTAAGTTTGTCATTCCTCAAAATCAAGATGTTGAGGACTTTATGC CGAAACCGCAAGTCAAAAAAGCGGTCAAAGAAGATACATCTGATTTTCCTCA AAATATGCTCAATCCAAAATATACTTTTGATACTTTTGTCATCGGATCTGGAA ACCGATTTGCACATGCTGCTTCCCTCGCAGTAGCGGAAGCGCCCGCGAAAG CTTACAACCCTTTATTTATCTATGGGGGCGTCGGCTTAGGGAAAACACACTT AATGCATGCGATCGGCCATTATGTAATAGATCATAATCCTTCTGCCAAAGTGG TTTATCTGTCTTCTGAGAAATTTACAAACGAATTCATCAACTCTATCCGAGAT AATAAAGCCGTCGACTTCCGCAATCGCTATCGAAATGTTGATGTGCTTTTGA TAGATGATATTCAATTTTTAGCGGGGAAAGAACAAACCCAGGAAGAATTTTT CCATACATTTAACACATTACACGAAGAAAGCAAACAAATCGTCATTTCAAGT GACCGGCCGCCAAAGGAAATTCCGACACTTGAAGACAGATTGCGCTCACGT TTTGAATGGGGACTTATTACAGATATCACACCGCCTGATCTAGAAACGAGAA TTGCAATTTTAAGAAAAAAGGCCAAAGCAGAGGGCCTCGATATTCCGAACG AGGTTATGCTTTACATCGCGAATCAAATCGACAGCAATATTCGGGAACTCGA AGGAGCATTAATCAGAGTTGTCGCTTATTCATCTTTAATTAATAAAGATATTA ATGCTGATCTGGCCGCTGAGGCGTTGAAAGATATTATTCCTTCCTCAAAACC GAAAGTCATTACGATAAAAGAAATTCAGAGGGTAGTAGGCCAGCAATTTAAT ATTAAACTCGAGGATTTCAAAGCAAAAAAACGGACAAAGTCAGTAGCTTTTC CGCGTCAAATCGCCATGTACTTATCAAGGGAAATGACTGATTCCTCTCTTCC TAAAATCGGTGAAGAGTTTGGAGGACGTGATCATACGACCGTTATTCATGCG CATGAAAAAATTTCAAAACTGCTGGCAGATGATGAACAGCTTCAGCAGCATG TAAAAGAAATTAAAGAACAGCTTAAATAGCAGGACCGGGGATCAATCGGGG AAAGTGTGAATAACTTTTCGGAAGTCATACACAGTCTGTCCACATGTGGATA GGCTGTGTTTCCTGTCTTTTTCACAACTTATCCACAAATCCACAGGCCCTAC TATTACTTCTACTATTTTTTATAAATATATATATTAATACATTATCCGTTAGGAG GATAAAAATGAAATTCACGATTCAAAAAGATCGTCTTGTTGAAAGTGTCCAA GATGTATTAAAAGCAGTTTCATCCAGAACCACGATTCCCATTCTGACTGGTA TTAAAATTGTTGCATCAGATGATGGAGTATCCTTTACAGGGAGTGACTCAGA TATTTCTATTGAATCCTTCATTCCAAAAGAAGAAGGAGATAAAGAAATCGTC ACTATTGAACAGCCCGGAAGCATCGTTTTACAGGCTCGCTTTTTTAGTGAAA TTGTAAAAAAATTGCCGATGGCAACTGTAGAAATTGAAGTCCAAAATCAGTA TTTGACGATTATCCGTTCTGGTAAAGCTGAATTTAATCTAAACGGACTGGAT GCTGATGAATATCCGCACTTGCCGCAGATTGAAGAGCATCATGCGATTCAGA TCCCAACTGATTTGTTAAAAAATCTAATCAGACAAACAGTATTTGCAGTGTC CACCTCAGAAACACGCCCTATCTTGACAGGTGTAAACTGGAAAGTGGAGCA AAGTGAATTATTATGCACTGCAACGGATAGCCACCGTCTTGCATTAAGAAAG GCGAAACTTGATATTCCAGAAGACAGATCTTATAACGTCGTGATTCCGGGAA AAAGTTTAACTGAACTCAGCAAGATTTTAGATGACAACCAGGAACTTGTAGA TATCGTCATCACAGAAACCCAAGTTCTGTTTAAAGCGAAAAACGTCTTGTTC TTCTCACGGCTTCTGGACGGGAATTATCCAGACACAACCAGCCTGATTCCGC AAGACAGCAAAACAGAAATCATTGTGAACACAAAAGAATTCCTTCAGGCCAT TGATCGTGCATCTCTTTTAGCTAGAGAGGGACGCAACA DNA

4. The Central Dogma

5. Hybridization A A A T T G G C C T A T G A T G C C A A A T T G G C C T A T G A T G C C

6. Introduction to Microarrays

7. Microarrays - The Concept Measure the level of transcript from a very large number of genes in one go CELL RNA

8. Microarrays - The Technologies Stanford Microarrays Affymetrix

9. Why? RNA

10. How? gene specific DNA probes labeled target gene mRNA

11. Stanford Microarrays

12. Coating glass slides Deposition of probes Post-processing Hybridization

13. Coating 1. Rinse of slides:NaOH and EtOH 2. Wash with water 2 h - shaking 3. Coat slides:poly-L-lycine 1 h - shaking 4. Wash and dry

14. Making Microarrays 1. Produce probes 2. Print by the use of a robot oligos cDNA library PCR products

15. Spotting - Mechanical deposition of probes

16. 16-pin microarrayer

18. Microarrayer

19. Making Microarrays 1. Produce probes 2. Print by the use of a robot oligos cDNA library PCR products 3. Post-process: rehydrate snap dry UV-cross link block surface

20. Sample preparation 1. Design experiment Question? Replicates? Test? 2. Perform experiment 4. Label RNA Amplification? Direct or indirect? Label? wild type mutant 3. Precipitate RNA Eukaryote/prokaryote? Cell wall?

21. mRNA cDNA Cy3-cDNACy5-cDNA SAMPLE CONTROL Stanford microarrays DESIGN and ORDER PROBES

22. Affymetrix GeneChip ® oligonucleotide array 11 to 20 oligonucleotide probes for each gene On-chip synthesis of 25 mers ~20.000 genes per chip good quality data – low variance

23. Catalog Arrays Human Mouse Rat Arabidopsis C. elegans Canine Drosophila E. coli P. aeruginosa Plasmodium/Anopheles Vitis vinifera (Grape) Xenopus laevis Yeast Zebrafish NimbleExpress™ Array Program

24. Fluidic Station and Scanner

25. The Affymetrix Genechip ®

26. TTT T T T T T T T A A A A A A A AAA Photolithography in situ synthesis Spacers bound to surface with photolabile protection groups Mask #1 Mask #2

27. Photolithography - Micromirrors NimbleExpress™ Array Program

28. Oligonucleotide Synthesis Detritylisation (Deblock A solution) O O B P N CEO NPPOC Oxidation (Oxidizer) O O B O O B P O CEOO NPPOC Addition (Amidite) O O B O O B P O CEO NPPOC Photo-Deprotection (Deblock L) O O B P N CEO NPPOC

29. Capping of uncoupled amidites O O B O O B P O CEOO NPPOC O O B O O B P O CEOO O O B O O B P O CEOO O O B O O B P O CEOO O O B O O B P O CEOO HO

30. The Affymetrix GeneChip ® A gene is represented like this: - Perfect Match (PM) - MisMatch (MM) PM MM PM: CGATCAATTGCACTATGTCATTTCT MM: CGATCAATTGCAGTATGTCATTTCT

31. The Technologies - Costs - Flexibility - Data Quality Affymetrix Spotter

32. Facility setup: Stanford Microarrays < 100,000 USD Affymetrix< 250,000 USD The Technologies - Cost Cost pr. array Stanford Microarrays 30-50 USD Affymetrix 300-400 USD NimbleExpress™ Array Program - a bit more expensive

33. NimbleExpress™ Array Program - 282,000 unique features (probes) - Design fee: 3,000 USD - 800 USD/array (minimum 10) - few weeks before delivery - can be run on the Affymetrix equipment

34. The Technologies - Flexibility Stanford microarrays: Are flexible, but new probes must be ordered each time Affymetrix arrays: Are not flexible, unless you order the NimbleExpress™ chip

35. The Technologies - Data Quality Reproducibility of data: (Pearson’s correlation coefficient) Stanford microarrays: 0.80 - 0.95 Affymetrix:  0.95

36. The Technologies - Choice of Stanford microarrays: If you work with unsequenced species Low budget Affymetrix: Only sequenced species High data quality

37. Analysis of Data Normalization: Linear or non-linear

38. Is it worth it? Number of known positives Number of significantly affected genes Qspline normalization Linear normalization Known positives versus the total number of significantly affected genes at 5 different cutoffs in the TnrA experiment

39. Analysis of Data Normalization: Linear or non-linear Statistical test: student’s t-test ANalysis Of VAriance (ANOVA) Analysis: Principle Component Analysis (PCA) Clustering and visualization

40. Break - 15 minuttes After break: - introduce yourself - why are you here?