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
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
Stanford/
Pat Brown
Affymetrix
How DNA sequences are laid down
Spotting
Photolithography
Length of DNA sequences
cDNA(Complete sequences)
Oligonucleotides

8. Oligoarrays vs. Spotted Arrays
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. Affymetrix Microarrays
Raw image
1.28cm
50um
~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. Microarray Analysis
What genes are up-regulated, down-regulated, co-regulated, not-regulated?
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

40. Monitoring Cell Differentiation
Diauxic shift
respiration <- fermentation

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

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