Download - DNA Microarrays M. Ahmad Chaudhry, Ph. D. Director Microarray Facility University of Vermont
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DNA MicroarraysDNA Microarrays
M. Ahmad Chaudhry, Ph. D.M. Ahmad Chaudhry, Ph. D.
Director Microarray FacilityDirector Microarray Facility
University of VermontUniversity of Vermont
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Outline of the lectureOutline of the lecture
• Overview of Micoarray Technology• Types of Microarrays• Manufacturing
• Instrumentation and Softwares• Data analysis
• Applications
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• Mainly used in gene discovery
Microarray DevelopmentMicroarray Development
• Widely adopted
• Relatively young technology
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Evolution & IndustrializationEvolution & Industrialization
• 1994- First cDNAs arrays were developed at Stanford University.
• 1996- Commercialization of arrays
• 1997-Genome-wide Expression Monitoring in S. cerevisiae
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• Microarrays are simply small glass or silicon slides upon the surface of which are arrayed thousands of genes (usually between 500-20,000)
• Via a conventional DNA hybridization process, the level of expression/activity of genes is measured
• Data are read using laser-activated fluorescence readers
• The process is “ultra-high throughput”
What are Microarrays?What are Microarrays?
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Why use Microarrays?Why use Microarrays?• What genes are Present/Absent in a cell?
• What genes are Present/Absent in the experiment vs. control?
• Which genes have increased/decreased expression in experiment vs. control?
• Which genes have biological significance?
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Why analyze so many genes?Why analyze so many genes?
• Just because we sequenced a genome doesn’t mean we know anything about the genes. Thousands of genes remain without an assigned function.
• Patterns/clusters of expression are more predictive than looking at one or two prognostic markers – can figure out new pathways
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The 6 steps of a DNA microarray The 6 steps of a DNA microarray experiment (1-3)experiment (1-3)
1. Manufacturing of the microarray
2. Experimental design and choice of reference: what to compare to what?
3. Target preparation (labeling) and hybridization
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The 6 steps of a microarray experiment (4-6)The 6 steps of a microarray experiment (4-6)
4. Image acquisition (scanning) and quantification (signal intensity to numbers)
5. Database building, filtering and normalization
6. Statistical analysis and data mining
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GENE EXPRESSION ANALYSIS WITH MICROARRAYS
DNA Chips
Miniaturized, high density arrays of oligos (Affymetrix Inc.)
Printed cDNA or Oligonucleotide Arrays Robotically spotted cDNAs or Oligonucleotides • Printed on Nylon, Plastic or Glass surface
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Affymetrix MicroarraysAffymetrix Microarrays
Involves Fluorescently tagged cRNA • One chip per sample• One for control• One for each experiment
Glass Slide Microarrays Involves two dyes/one chip
• Red dye• Green dye• Control and experiment on same chip
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Gene Chip Technology Affymetrix Inc
Miniaturized, high density arrays of oligos 1.28-cm by 1.28-cm (409,000 oligos)
Manufacturing Process
Solid-phase chemical synthesis and Photolithographic fabrication techniques employed in semiconductor industry
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Selection of Expression ProbesSelection of Expression ProbesSet of oligos to be synthesized is defined, based on its ability to Set of oligos to be synthesized is defined, based on its ability to hybridize to the target genes of interesthybridize to the target genes of interest
Probes
Sequence
Perfect Match
MismatchChip
5’ 3’
Computer algorithms are used to design photolithographic masks for use in manufacturing
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• Each gene is represented on the probe array by multiple probe pairs
• Each probe pair consists of a perfect match and a mismatch oligonucleotide
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Photolithographic SynthesisPhotolithographic Synthesis
Manufacturing ProcessManufacturing ProcessProbe arrays are manufactured by light-directed chemical Probe arrays are manufactured by light-directed chemical synthesis process which enables the synthesis of hundreds of synthesis process which enables the synthesis of hundreds of thousands of discrete compounds in precise locationsthousands of discrete compounds in precise locations
Lamp
Mask Chip
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Affymetrix Wafer and Chip FormatAffymetrix Wafer and Chip Format
1.28cm
20 - 50 µm
20 - 50 µm
Millions of identical oligonucleotide
probes per feature
49 - 400 chips/wafer
up to ~ 400,000 features/chip
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Creating TargetsCreating Targets
Reverse Transcriptase
in vitro transcription
mRNA
cDNA
Target
cRNA
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RNA-DNA HybridizationRNA-DNA Hybridization
probe setsDNA
(25 base oligonucleotides of known sequence)
TargetsRNA
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Non-Hybridized Targets are Washed AwayNon-Hybridized Targets are Washed Away
“probe sets” (oligo’s)
Targets(fluorescently tagged)
Non-bound ones are washed away
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Target PreparationTarget Preparation
cDNA
Wash & Stain
Scan
Hybridize
(16 hours)
mRNAAAAA
B B B B
Biotin-labeled transcripts Fragment
(heat, Mg2+)
Fragmented cRNA
B B
B
B
IVT(Biotin-UTPBiotin-CTP)
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GeneChipGeneChip®® Expression Analysis Expression Analysis
Hybridization and StainingHybridization and Staining
Array
cRNA Target
Hybridized Array
Streptravidin-phycoerythrinconjugate
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InstrumentationAffymetrix GeneChip System
3000-7G Scanner450 Fluidic Station
640 Hybridization Oven
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Currently Available GeneChips
B. subtilis
Barley Genome Array
Bovine Genome Array
C. elegans Genome Array
Canine Genome Array
Chicken Genome Array
Drosophila Genome Arrays
E. coli Genome Arrays
Human Genome Arrays
Maize Genome Array
Mouse Genome Arrays
P. aeruginosa Genome Array
Plasmodium/Anopheles Genome Array
Porcine Genome Array
Rat Genome Arrays
Rice Genome Array
Soybean Genome Array
Sugar Cane Genome Array
Vitis vinifera (Grape) Array
Wheat Genome Array
Xenopus laevis Genome Array
Yeast Genome Arrays
Zebrafish Genome Array
Arabidopsis Genome Arrays
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Custom GeneChips
Affymetrix offers over 120 prokaryotic arrays that are manufactured by Nimblegen Inc.
Custom GeneChips are also available for both Eukaryotic and Prokaryotic systems.
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Quality Control IssuesQuality Control Issues
• RNA purity and integrity• cDNA synthesis efficiency• Efficient cRNA synthesis, labeling and
fragmentation• Target evaluation with Test Chips
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GENE EXPRESSION ANALYSIS WITH MICROARRAYS
DNA Chips
Miniaturized, high density arrays of oligos (Affymetrix Inc.)
Printed cDNA or Oligonucleotide Arrays Robotically spotted cDNAs or Oligonucleotides • Printed on Nylon, Plastic or Glass surface
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Microarray of thousands of genes on a glass slide
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Spotted arraysSpotted arrays
1 nanolitre spots90-120 um diameter
384 well source plate
chemically modified slides
steel
spotting pin
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TheThe processprocessBuilding the chip:
MASSIVE PCR PCR PURIFICATION and PREPARATION
PREPARING SLIDES PRINTING
RNA preparation:
CELL CULTURE AND HARVEST
RNA ISOLATION
cDNA PRODUCTION
Hybing the chip: POST PROCESSING
ARRAY HYBRIDIZATION
PROBE LABELING
DATA ANALYSIS
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Building the chipBuilding the chip
Arrayed Library(96 or 384-well plates of bacterial glycerol stocks)
PCR amplificationDirectly from colonies withSP6-T7 primers in 96-well plates
Consolidate into 384-well plates
Spot as microarrayon glass slides
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Sample preparationSample preparation
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HybridizationHybridizationBinding of cDNA target samples to cDNA probes on the slideBinding of cDNA target samples to cDNA probes on the slide
cover
slip
Hybridize for
5-12 hours
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LABEL
3XSSC
HYB CHAMBER
ARRAY
SLIDE
LIFTERSLIP
SLIDE LABEL
• Humidity• Temperature• Formamide
(Lowers the Tm)
Hybridization chamberHybridization chamber
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Expression profiling with DNA microarraysExpression profiling with DNA microarrays
cDNA “A”Cy5 labeled
cDNA “B”Cy3 labeled
Hybridization Scanning
Laser 1 Laser 2
+
Analysis Image Capture
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Image analysisImage analysis
• The raw data from a cDNA microarray experiment consist of pairs of image files, 16-bit TIFFs, one for each of the dyes.
• Image analysis is required to extract measures of the red and green fluorescence intensities for each spot on the array.
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Image analysisImage analysis
GenePix
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Image analysisImage analysis
1. Addressing. Estimate location of spot centers.
2. Segmentation. Classify pixels as foreground (signal) or background.
3. Information extraction. For each spot on the array and each dye
• signal intensities;• background intensities; • quality measures.
R and G for each spot on the array.
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Biological Question
Sample PreparationMicroarray
Life Cycle
Data Analysis & Modelling
Microarray Reaction
MicroarrayDetection
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Spotted cDNA microarraysSpotted cDNA microarraysAdvantages• Lower price and flexibility• Simultaneous comparison of two related
biological samples (tumor versus normal, treated versus untreated cells)
• ESTs allow discovery of new genes
Disadvantages• Needs sequence verification• Measures the relative level of expression
between 2 samples
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Data Pre-processingData Pre-processing
Filtering – Background subtraction – Low intensity spots– Saturated spots – Low quality spots (ghost spots, dust
spots etc)
Normalization– Housekeeping genes/ control genes
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Affymetrix Software for Microarray Data Analysis
• Microarray Suite 5 • Micro DB • Data Mining Tool (DMT)• NetAffx
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Affymetrix Microarray Suite - Data AnalysisAffymetrix Microarray Suite - Data Analysis
Absolute Analysis –whether transcripts are Present or not (uses data from one probe array experiment).
Comparison Analysis –determine the relative change in transcripts (uses data from two probe array experiments).
Intensities for each experiment are compared to a baseline/control.
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Microarray data analysisMicroarray data analysis
Scatter plots
• Intensities of experimental samples versus normal samples
• Quick look at the changes and overall quality of microarray
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Normal vs. NormalNormal vs. Normal Normal vs. TumorNormal vs. Tumor
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Lung Tumor: Lung Tumor: Up-RegulatedUp-Regulated
Lung Tumor: Lung Tumor: Down-RegulatedDown-Regulated
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Microarray data analysisMicroarray data analysis
Supervised versus unsupervised analysis
– Clustering: organization of genes that are similar to each other
– Statistical analysis: how significant are the results?
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Hierarchical clusteringHierarchical clustering • Unsupervised: no assumption on
samples
• The algorithm successively joins gene expression profiles to form a dendrogram based on their pair-wise similarities.
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Cluster analysis of genes in G1 and G2
Chaudhry et. al., 2002
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Publicly Available Softwares
GenMAPP
Visualize gene expression data on maps representing biological pathways and groupings of genes.
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Microarray ApplicationsMicroarray Applications• Identify new genes implicated in disease progression and
treatment response (90% of our genes have yet to be ascribed a function)
• Assess side-effects or drug reaction profiles
• Extract prognostic information, e.g. classify tumors based on hundreds of parameters rather than 2 or 3.
• Identify new drug targets and accelerate drug discovery and testing
• ???
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Microarray Technology - ApplicationsMicroarray Technology - Applications
• Gene Discovery-– Assigning function to sequence– Discovery of disease genes and drug targets– Target validation
• Genotyping– Patient stratification (pharmacogenomics)– Adverse drug effects (ADE)
• Microbial ID
The List Continues To Grow….
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Microarray FutureMicroarray Future
• Must go beyond describing differentially expressed genes
• Inexpensive, high-throughput, genome- wide scan is the end game for research applications
• Protein microarrays (Proteomics)
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Microarray FutureMicroarray Future
• Publications are now being focused on biology rather than technology
• SNP analysis –Faster, cheaper, as accurate as sequencing–Disease association studies–Population surveys
• Chemicogenomics–Dissection of pathways by compound application–Fundamental change to lead validation
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Microarray FutureMicroarray Future
• Diagnostics– Tumor classification– Patient stratification– Intervention therapeutics
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ConclusionConclusion
• Technology is evolving rapidly.• Blending of biology, automation, and
informatics.• New applications are being pursued
– Beyond gene discovery into screening, validation, clinical genotyping, etc.
• Microarrays are becoming more broadly available and accepted.– Protein Arrays– Diagnostic Applications
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W.W.W resourcesW.W.W resources
• Complete guide to “microarraying” http://cmgm.stanford.edu/pbrown/mguide/
• http://www.microarrays.org– Parts and assembly instructions for printer and
scanner;– Protocols for sample prep;– Software;– Forum, etc.
• Animation: http://www.bio.davidson.edu/courses/genomics/chip/chip.html