The Central Dogma

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

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

The Central Dogma

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

Introduction to Microarrays

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

Microarrays - The Technologies Stanford Microarrays Affymetrix

Why? RNA

How? gene specific DNA probes labeled target gene mRNA

Stanford Microarrays

Coating glass slides Deposition of probes Post-processing Hybridization

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

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

Spotting - Mechanical deposition of probes

16-pin microarrayer

Microarrayer

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

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?

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

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

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

Fluidic Station and Scanner

The Affymetrix Genechip ®

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

Photolithography - Micromirrors NimbleExpress™ Array Program

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

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

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

The Technologies - Costs - Flexibility - Data Quality Affymetrix Spotter

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

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

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

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

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

Analysis of Data Normalization: Linear or non-linear

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

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

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