1. Microarray Technology and Applications

2. Analysis of Gene Expression • Examine expression during development or in different tissues • Compare genes expressed in normal vs. diseased states • Analyze response of cells exposed to drugs or different physiological conditions

3. Monitoring Changes in Genomic DNA • Identify mutations • Examine genomic instability such as in certain cancers and tumors (gene amplifications, translocations, deletions) • Identify polymorphisms (SNPs) • Diagnosis: chips have been designed to detect mutations in p53, HIV, and the breast cancer gene BRCA-1

4. Applications in Medicine • Gene expression studies • Gene function for cell state change in various conditions (clustering, classification) • Disease diagnosis (classification) • Inferring regulatory networks • Pathogen analysis (rapid genotyping)

5. Applications in Drug Discovery • Drug Discovery • Identify appropriate molecular targets for therapeutic intervention (small molecule / proteins) • Monitor changes in gene expression in response to drug treatments (up / down regulation) • Analyze patient populations (SNPs) and response • Targeted Drug Treatment • Pharmacogenomics: individualized treatments • Choosing drugs with the least probable side effects

6. Generating DNA Sequence automated sequencer chromatogram files software pipeline base calling quality clipping vector clipping contig assembly output >GENE01 ACCTGTCAGTGTCAACTGCTTCAATAGCTAATGCTAGGCTCGATAATCGCTGGCCTCAGCTCAGTCTAGCATTACGATTACGGAGACCTATGCTTTAGCTAGTAGGAACCTCAGCTCAGTACCTGTCAGTGTCAACTGCTTCAATAGCTAATGCTACTC

7. What Is Microarray Technology? • Different Approaches

8. Oligoarrays vs. Spotted Arrays • Oligoarrays • Shorter nucleotides • Higher feature density • Used for SNP detection • Perfect match and mismatch (A,T,C,G) • More expensive to prepare • Higher per unit cost production • Not manufactured in as high numbers

17. Spotted Array Experiment 1. Prepare sample. 4. Print microarray. Test Reference 2. Label with fluorescent dyes. 5. Hybridize to microarray. 3. Combine cDNAs. 6. Scan.

18. cDNA Array Sample Preparation

21. Axon Instruments Scanner • GenPix 4000

22. Choice of Microarray System • cDNA arrays (Affymetrix) • Oligonucleotide chips • cRNA arrays (Applied Biosystems) • SNP arrays Applied Biosystems)

23. cDNA Arrays: Advantages • Non-redundant clone sets are available for numerous organisms (humans, mouse, rats, drosophila, yeast, c.elegans, arabidopsis) • Prior knowledge of gene sequence is not necessary: good choice for gene discovery • Large cDNA size is great for hybridization • Glass or membrane spotting technology is readily available

24. Membrane cDNA microarray

25. cDNA Arrays: Disadvantages • Processing cDNAs to generate “spotting-ready” material is cumbersome • Low density compared to oligonucleotide arrays • cDNAs may contain repetitive sequences (like Alu in humans) • Common sequences from gene families (ex: zinc fingers) are present in all cDNAs from these genes: potential for cross-hybridization • Clone authentication can be difficult

26. cDNA Microarray Slide

28. 50um Affymetrix Microarrays Raw image 1.28cm ~107 oligonucleotides, half Perfectly Match mRNA (PM), half have one Mismatch (MM) Raw gene expression is intensity difference: PM - MM

29. Affymetrix • Probe Array (Photolithography) • Synthesis of probe

30. Affymetrix System

32. Microarrays: An Example • Leukemia: Acute Lymphoblastic (ALL) vs Acute Myeloid (AML), Golub et al, Science, v.286, 1999 • 72 examples (38 train, 34 test), about 7,000 genes • well-studied (CAMDA-2000), good test example ALL AML Visually similar, but genetically very different

33. Tumor Cell Analysis

34. Microarray Data Life Cycle Biological Question Sample Preparation Data Analysis & Modeling Microarray Detection Microarray Reaction

35. Spotted cDNA Array Production

36. Hybridization Process

37. Microarray Data Processing normalization quality & intensity filtering background correction expression ratios (treated / control)

38. What genes are up-regulated, down-regulated, co-regulated, not-regulated? Microarray Analysis • Gene discovery • Pattern discovery • Inferences about biological processes • Classification of biological processes

39. Identifying Differential Expression SAM Significance Analysis of Microarrays Tusher et al., PNAS 2001 http://www-stat.stanford.edu/~tibs/SAM/index.html

40. Diauxic shift • respiration <- fermentation Monitoring Cell Differentiation

41. Advanced Questions in Microarray Analysis • e.g. can we correlate patterns in other types of data with the microarray results? • cis-elements • protein domains • protein-protein interactions • orthologous genes • gene ontologies • textual associations

42. Arrayer Hardware Scanner Software Procedures • Preparation • Target DNA (reference and test samples) • Slides • Reaction(Droplet or Pin Spotting) • Hybridization • Scanning • Analysis • Image processing • Data mining • Modeling

43. The Basic System Computational Tasks • Gene set selection • Probe design • Image analysis • Normalization of chip, sample…. • …more….

44. A Typical GeneChip Array Experiment Target Preparation Isolate total RNA from tissue Deposition of oligo probes on GeneChip Synthesis of cDNA & addition of T7 promoter Biotin-labeling of cRNA & purification Hybridization to GeneChip Data Mining Interesting genes Image acquisition & analysis Pattern Recognition Pathways

45. Summary • Microarray process • Microarray applications • From genes to pathways • Haplotyping and SNP mapping • Using microarrays and medicine