Microarray Technology

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Presentation transcript:

Microarray Technology Microarray Outreach Program Vermont Genetics Network University of Vermont

Outline of the lecture Overview of Microarray Technology Types of Microarrays Manufacturing Instrumentation and Software Data Analysis-Basic Applications

Microarray Development Mainly used in gene discovery Widely adopted Relatively young technology

Evolution & Industrialization 1989: First Affymetrix Genechip Prototype 1994: First Commercial Affymetrix Genechip 1994- First cDNAs arrays were developed at Stanford University. 1994: First Commercial Scanner-Affymetrix 1996- Commercialization of arrays 1997-Genome-wide Expression Monitoring in S. cerevisiae

What are Microarrays? Microarrays are simply small glass or silicon slides upon the surface of which are arrayed thousands of features (usually between 500 up to a million) Using a conventional hybridization process, the level of expression of genes is measured (for instance) Microarrays are read using laser-based fluorescence scanners The process is “high throughput”

Why use Microarrays? Determine what genes are active in a cell and at what levels Compare the gene expression profiles of a control vs treated Determine what genes have increased or decreased in during an experimental condition Determine which genes have biological significance in a system Discovery of new genes, pathways, and cellular trafficking

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 or clusters of genes are more informative regarding total cellular function than looking at one or two genes – can figure out new pathways

The six steps in development of a DNA microarray experiment Manufacturing of the microarray Experimental design and choice of reference: what to compare to what? Target (sample) preparation and hybridization 4. Image acquisition (scanning) and quantification of gene expression

Database building, filtering, and normalization 6. Bioinformatics: Statistical analysis, data mining, pathway analysis

Types of Microarrays -Expression Arrays -Protein microarrays (Proteomics) -Resequencing arrays -CGH arrays- Comparative genomic hybridization -SNP Arrays -Antibody Arrays -Exon arrays-Alternative splice variant detection -Tissue Arrays

C) Tissue Section Slide Microarray Formats A) Cartridge-based Spotted Electronic B) Spotted Glass Slide C) Tissue Section Slide

Cartridge-based Chips -Miniaturized, high density arrays of DNA oligos within a plastic housing -One sample=One chip (Affymetrix, Agilent, Applied Biosystems…) - Generally used with expression and DNA arrays

Cartridge-based Expression Microarrays Involves Fluorescently tagged biotinylated cRNA -One chip per sample -Uses single fluorescent dye -More expensive Affymetrix GeneChip Image

Uses cDNA, Oligonucleotide, protein, antibody Spotted Glass Arrays Uses cDNA, Oligonucleotide, protein, antibody -Robotically spotted cDNAs or Oligonucleotides - Printed on Nylon, Plastic, or Glass microscope slide BD’s Antibody Array Agilent:Oligonucleotide Array

Involves two dyes on the same slide Spotted cDNA and Oligo Glass Arrays: Involves two dyes on the same slide Red dye-Cy5 Green dye-Cy3 Control and experimental cDNA on same chip

Electroniconically Addressable Microarrays Nanogen- Nanochip Motorola- eSensor Chip

Expression Arrays Most common type of microarray Spotted glass, cartridge, and electronic Involves extracting RNA from a sample and converting it to cDNA by priming off of the Poly A tail of mRNA for eukaryotes and using random hexamers for prokaryotes [WHY?] Measures the amount and type of mRNA transcripts Provides information on whether genes are up or down regulated in a specific condition Can find novel changes in ESTs for specific conditions

Protein Microarrays True protein microarrays are evolving very slow and only a few exist. Technology is not straight forward due to inherent characteristic of proteins [e.g. available ligands, folding, drying…] Most are designed to detect antibodies or enzymes in a biological system Protein is on the microarray Some detect protein-protein interaction by surface plasmon resonance other use a fluorescence based approach

Protein Microarrays The Invitrogen Human Protein Microarray is a high-density microarray It contains thousands of unique human proteins [kinases, phophatases, GPCRs, nuclear receptors, and proteases]

Antibody Arrays -Assay hundreds of native proteins simultaneously -Compare protein abundances in a variety of biological samples -GenTel and BD biosciences -Antibody or ligand is on the microarray

Antibody Arrays-labeling scheme

SNP, Genotyping, and DNA Mapping Arrays Targets DNA not RNA like expression Requires amplification of target DNA Uses multiple probes sets to determine base change at a specific nucleotide position in the genomic DNA. Use thousand of oligos that “tile” or span the genomic DNA for characterization. Provides sequence and genotyping data including LOH, Linkage analysis and single nucleotide polymorphisms

Resequencing Arrays [Affy] Enable the analysis of up to 300,000+ bases of double-stranded sequence (600,000 bases total) on a single Affy array Used for large-scale resequencing of organisms genome and organelles Faster and cheaper than sequencing but very limited to few organisms and/or organelles Large potential

Exon Arrays-Alternative splice variant detection Probes are designed for hybridizing to individual exons of genomic DNA Tissue or development specific splicing leads to normal or expected protein diversity Defective splicing can lead to disease

CGH Arrays- Comparative Genomic Hybridization Provides DNA and chromosomal information DNA Copy number and allele-specific information Determine regions of chromosomal deletion (LOH) or amplification Enables the identification of critical gene(s) that have altered copy number and may be responsible for the development and progression of a particular disease.

Slide based “spotted” tissues (not really) Tissue Arrays Slide based “spotted” tissues (not really)

Assembling Tissue Arrays Coring of embedded paraffin tissues and plugging or inserting into new paraffin block Sectioning and deposition onto a slide

GeneChip Technology Affymetrix Inc Miniaturized, high density arrays of 1,300,000 DNA oligos 1-cm by 1-cm Manufacturing Process: Solid-phase chemical synthesis and Photolithographic fabrication techniques employed in semiconductor industry WE WILL DISCUSS THIS IN DETAIL IN ANOTHER PPT

cDNA Array Microarray of thousands of Oligos on a glass slide Printed cDNA or Oligonucleotide Arrays Robotically spotted cDNAs (50mer) or Oligonucleotides (70mers) vs. Affymetrix’s that uses 25mers Printed on Nylon, Plastic, or Glass surface cDNA Array Microarray of thousands of Oligos on a glass slide

Spotted arrays steel spotting pin chemically modified slides 384 well source plate chemically modified slides 1 nanolitre spots 90-120 um diameter

The process Building the chip: RNA preparation: Hybing the chip: MASSIVE PCR PCR PURIFICATION and PREPARATION PREPARING SLIDES PRINTING RNA preparation: CELL CULTURE AND HARVEST RNA ISOLATION cDNA PRODUCTION Hybing the chip: ARRAY HYBRIDIZATION PROBE LABELING DATA ANALYSIS POST PROCESSING

bacterial glycerol stocks) Building the chip PCR amplification Directly from colonies with SP6-T7 primers in 96-well plates Consolidate into 384-well plates Arrayed Library (96 or 384-well plates of bacterial glycerol stocks) Slide 4 Ideally, you will have a slides consist of all genes in the genomeThe design of the array / template is an imporatnt bioinformatics question. As you are only able to detect expression of genes on this template. Spot as microarray on glass slides

Hybridization chamber 3XSSC HYB CHAMBER ARRAY LIFTERSLIP SLIDE LABEL SLIDE LABEL Humidity Temperature Formamide (Lowers the Tm)

Expression profiling with cDNA microarrays cDNA “B” Cy3 labeled cDNA “A” Cy5 labeled Laser 1 Laser 2 Hybridization Scanning Slide 5 You will have another sample of interests consists of a portion of the genes and the questions is to find out what genes are being expressed in this sample. The simplified version of the experiments is to label the sample with a color dye hybridize the sample on the slides and scan the slides under some laser to see which spots that light up. This provides a list of genes and it’s corresponding expression levels in our samples. Our interest is on comparing the expression levels between the two samples. + Analysis Image Capture

Image analysis of cDNA array

Spotted cDNA microarrays Advantages -Lower price and flexibility -Simultaneous comparison of two related biological samples (tumor versus normal, treated versus untreated cells) Disadvantages -Needs sequence verification -Measures the relative level of expression between 2 samples -Features can come off the surface-poor adhesion -Labor Intensive, requires designated staff and equipment - Data is can be variable

Microarray data analysis Scatter plots, significance analysis, clustering, pathway analysis… to name a few Intensities of experimental samples versus normal samples Quick look at the changes and overall quality of microarray

Normal vs. Normal Normal vs. Tumor

Bioinformatics : Microarray data analysis Often is a stand alone dept. within an institute (such as the case at UVM), but works very closely with a microarray facility A whole field by itself Involves extensive knowledge of gene ontology, biochemical pathways, gene annotation, cell signaling, cellular trafficking , …. Uses special software such as Spotfire, Genesifter, Genespring…to name a few.

Validating Microarray Expression Data Microarray data are not stand alone results and requires validation by second method Microarray data is only semi-quantitative because of a limited dynamic range. True quantitative results must be determined with another technique such as Quantitative real-time PCR

Microarray Validation Two types of validation 1] Validating the instrument data using the same RNA (confirming a result) And most importantly 2] Validating the biological phenomenon with new samples same experiment conditions Methods Northern Blots, RPA’s, Immunohistochemistry,Western Blot, in silico PCR- i.e.Quantitative real-time PCR **DNA mapping Arrays or CGH may also help indicate where or why a change is occuring

Microarray 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

Microarray 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

Microarray Future Diagnostics -[Affy, Nanogen only at this time] Disease detection Tumor classification Patient stratification Intervention therapeutics Treatment and Customized Medicine Clinical arrays currently available are the AmpliChip CYP450 by Affymetrix and Roche. Used for predictive phenotyping in defects of the cytochrome P450 Genes

Conclusion 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, tissue arrays, etc Diagnostic Applications

W.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