1. Introduction to
Microarrays

2. The Central Dogma

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

4. ATCTTTTTCGGCTTTTTTTAGTATCCACAGAGGTTATCGACAACATTTTCACATTACCAACCCCTGTGGACAAGGTTTTTTCAACAGGTTGTCCGCTTTGTGGATAAGATTGTGACAACCATTGCAAGCTCTCGTTTATTTTGGTATTATATTTGTGTTTTAACTCTTGATTACTAATCCTACCTTTCCTCTTTATCCACAAAGTGTGGATAAGTTGTGGATTGATTTCACACAGCTTGTGTAGAAGGTTGTCCACAAGTTGTGAAATTTGTCGAAAAGCTATTTATCTACTATATTATATGTTTTCAACATTTAATGTGTACGAATGGTAAGCGCCATTTGCTCTTTTTTTGTGTTCTATAACAGAGAAAGACGCCATTTTCTAAGAAAAGGAGGGACGTGCCGGAAGATGGAAAATATATTAGACCTGTGGAACCAAGCCCTTGCTCAAATCGAAAAAAAGTTGAGCAAACCGAGTTTTGAGACTTGGATGAAGTCAACCAAAGCCCACTCACTGCAAGGCGATACATTAACAATCACGGCTCCCAATGAATTTGCCAGAGACTGGCTGGAGTCCAGATACTTGCATCTGATTGCAGATACTATATATGAATTAACCGGGGAAGAATTGAGCATTAAGTTTGTCATTCCTCAAAATCAAGATGTTGAGGACTTTATGCCGAAACCGCAAGTCAAAAAAGCGGTCAAAGAAGATACATCTGATTTTCCTCAAAATATGCTCAATCCAAAATATACTTTTGATACTTTTGTCATCGGATCTGGAAACCGATTTGCACATGCTGCTTCCCTCGCAGTAGCGGAAGCGCCCGCGAAAGCTTACAACCCTTTATTTATCTATGGGGGCGTCGGCTTAGGGAAAACACACTTAATGCATGCGATCGGCCATTATGTAATAGATCATAATCCTTCTGCCAAAGTGGTTTATCTGTCTTCTGAGAAATTTACAAACGAATTCATCAACTCTATCCGAGATAATAAAGCCGTCGACTTCCGCAATCGCTATCGAAATGTTGATGTGCTTTTGATAGATGATATTCAATTTTTAGCGGGGAAAGAACAAACCCAGGAAGAATTTTTCCATACATTTAACACATTACACGAAGAAAGCAAACAAATCGTCATTTCAAGTGACCGGCCGCCAAAGGAAATTCCGACACTTGAAGACAGATTGCGCTCACGTTTTGAATGGGGACTTATTACAGATATCACACCGCCTGATCTAGAAACGAGAATTGCAATTTTAAGAAAAAAGGCCAAAGCAGAGGGCCTCGATATTCCGAACGAGGTTATGCTTTACATCGCGAATCAAATCGACAGCAATATTCGGGAACTCGAAGGAGCATTAATCAGAGTTGTCGCTTATTCATCTTTAATTAATAAAGATATTAATGCTGATCTGGCCGCTGAGGCGTTGAAAGATATTATTCCTTCCTCAAAACCGAAAGTCATTACGATAAAAGAAATTCAGAGGGTAGTAGGCCAGCAATTTAATATTAAACTCGAGGATTTCAAAGCAAAAAAACGGACAAAGTCAGTAGCTTTTCCGCGTCAAATCGCCATGTACTTATCAAGGGAAATGACTGATTCCTCTCTTCCTAAAATCGGTGAAGAGTTTGGAGGACGTGATCATACGACCGTTATTCATGCGCATGAAAAAATTTCAAAACTGCTGGCAGATGATGAACAGCTTCAGCAGCATGTAAAAGAAATTAAAGAACAGCTTAAATAGCAGGACCGGGGATCAATCGGGGAAAGTGTGAATAACTTTTCGGAAGTCATACACAGTCTGTCCACATGTGGATAGGCTGTGTTTCCTGTCTTTTTCACAACTTATCCACAAATCCACAGGCCCTACTATTACTTCTACTATTTTTTATAAATATATATATTAATACATTATCCGTTAGGAGGATAAAAATGAAATTCACGATTCAAAAAGATCGTCTTGTTGAAAGTGTCCAAGATGTATTAAAAGCAGTTTCATCCAGAACCACGATTCCCATTCTGACTGGTATTAAAATTGTTGCATCAGATGATGGAGTATCCTTTACAGGGAGTGACTCAGATATTTCTATTGAATCCTTCATTCCAAAAGAAGAAGGAGATAAAGAAATCGTCACTATTGAACAGCCCGGAAGCATCGTTTTACAGGCTCGCTTTTTTAGTGAAATTGTAAAAAAATTGCCGATGGCAACTGTAGAAATTGAAGTCCAAAATCAGTATTTGACGATTATCCGTTCTGGTAAAGCTGAATTTAATCTAAACGGACTGGATGCTGATGAATATCCGCACTTGCCGCAGATTGAAGAGCATCATGCGATTCAGATCCCAACTGATTTGTTAAAAAATCTAATCAGACAAACAGTATTTGCAGTGTCCACCTCAGAAACACGCCCTATCTTGACAGGTGTAAACTGGAAAGTGGAGCAAAGTGAATTATTATGCACTGCAACGGATAGCCACCGTCTTGCATTAAGAAAGGCGAAACTTGATATTCCAGAAGACAGATCTTATAACGTCGTGATTCCGGGAAAAAGTTTAACTGAACTCAGCAAGATTTTAGATGACAACCAGGAACTTGTAGATATCGTCATCACAGAAACCCAAGTTCTGTTTAAAGCGAAAAACGTCTTGTTCTTCTCACGGCTTCTGGACGGGAATTATCCAGACACAACCAGCCTGATTCCGCAAGACAGCAAAACAGAAATCATTGTGAACACAAAAGAATTCCTTCAGGCCATTGATCGTGCATCTCTTTTAGCTAGAGAGGGACGCAACAAATTGCCGATGGCAACTGTAGAAATTGAAGTCCAAAATCAGTATTTGACGATTATCCGTTCTGGTAAAGCTGAATTTAATCTAAACGGACTGGATGCTGATGAATATCCGCACTTGCCGCAGATTGAAGAGCATCATGCGATTCAGATCCCAACTGATTTGTTAAAAAATCTAATCAGACAAACAGTATTTGCAGTGTCCACCTCAGAAACACGCCCTATCTTGACAGGTGTAAACTGGAAAGTGGAGCAAAGTGAATTATTATGCACTGCAACGGATAGCCACCGTCTTGCATTAAGAAAGGCGAAACTTGATATTCCAGAAGACAGATCTTATAACGTCGTGATTCCGGGAAAAAGTTTAACTGAACTCAGCAAGATTTTAGATGACAACCAGGAACTTGTAGATATCGTCATCACAGAAACCCAAGTTCTGTTTAAAGCGAAAAACGTCTTGTTCTTCTCACGGCTTCTGGACGGGAATTATCCAGACACAACCAGCCTGATTCCGCAAGACAGCAAAACAGAAATCATTGTGAACACAAAAGAATTCCTTCAGGCCATTGATCGTGCATCTCTTTTAGCTAGAGAGGGACGCAACACAGACACAACCAGCCTGATTCCGCAAGACAGCAAAACAGAAATCATTGTGAACACAAAAGAATTCCTTCAGGCCATTGATCGTGCATCTCTTTTAGCTAGAGAGGGACGCAACAAAGAATTCCTTCAGGCCATTGATCGTGCATCTCTTTTAGCTAGAGAGGGACGCAACATTGTGA
DNA

5. The Central Dogma

6. Hybridization A T G C T A G C A T G C

7. Introduction to
Microarrays

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

9. Microarrays - The Technologies
Stanford Microarrays
High-density

10. Why?
RNA

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

12. Stanford-type Microarrays

13. Stanford-type Microarrays
Coating glass slides
Deposition of probes
Post-processing
Hybridization

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

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
1. Produce probes
2. Print by the use of a robot
3. Post-process:
rehydrate
snap dry
UV-cross link
block surface

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

21. Stanford microarrays DESIGN and ORDER PROBES SAMPLE CONTROL mRNA cDNA
Cy3-cDNA
Cy5-cDNA

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

23. Catalog Arrays Human E. coli Mouse P. aeruginosa 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. Photolithography Mask #2 Mask #1
in situ synthesis T A
Mask #2
Mask #1 T A
Spacers bound to surface with photolabile protection groups

27. Photolithography - Micromirrors
NimbleExpress™ Array Program
manufactured on Iceland by NimbleGen Systems Inc.

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

29. NimbleGen Systems Inc. ~380.000 probes/array
They do most of the practical work

30. The Technologies - Flexibility
Stanford microarrays: Are flexible, but new probes must be ordered each time High-density: Are not flexible, ....unless you order the NimbleExpress™ chip or use the NimbleGen Systems

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

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

33. 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