PowerPoint PresentationOverviewSlide 3Slide 4Slide 5Slide 6Slide 7Slide 8Slide 9Fabrication of “Spotted Arrays”Slide 11Slide 12Slide 13Slide 14Slide 15Slide 16Slide 17Slide 18Slide 19Slide 20Slide 21Layout of the cDNA MicroarraysSlide 23Slide 24Practical Problems 1Practical Problems 2Practical Problems 3Practical Problems 4Practical Problems 5Slide 30Slide 31Normalization - lowessNormalisation - print-tip-groupSlide 34Slide 35Slide 36Slide 37Slide 38Advantages of Our DesignSlide 40Introduction to Microarray Analysis and TechnologyDave Lin - November 5, 2001OverviewOverview—Why Biologists care about Genomics—Why statisticians/computer scientists —may care about genomics•Preprocessing issues•Sources of variability in constructing microarrays•Postprocessing issues•Analysis of dataWhat makes one cell different from another? liver vs. brainCancerous vs. non-cancerousTreatment vs. controlOld Days 100,000 genes in mammalian genomeeach cell expresses 15,000 of these geneseach gene is expressed at a different levelestimated total of 100,000 copies of mRNA/cell1-5 copies/cell - “rare” -~30% of all genes10-200 copies/cell - “moderate”200 copies/cell and up - “abundant”Cells can be defined by:Complement of Genes (which genes are expressed)How much of each gene is expressed (quantity)What makes one cell different from another?Try and find genes that are differentially expressedStudy the function of these genesFind which genes interact with your favorite geneExtremely time-consuming.Huge amounts of effort expended to find individual genes that may differ between two conditionsGenomics. Almost useless term-defines many different concepts and applications.Microarrays-massively parallel analysis of gene expression-screen an entire genome at once-find not only individual genes that differ,but groups of genes that differ.-find relative expression level differences-how quantitative can they be?Microarrays-Based on old techniquemany flavors- majority are of two essential varietiescDNA Arrays printing on glass slidesminiaturization, throughputfluorescence based detection Affymetrix Arraysin situ synthesis of oligonucleotideswill not consider Affymetrix arrays further.Department of Statistics, University of California, Berkeley, and Division of Genetics and Bioinformatics, The Walter and Eliza Hall Institute of Medical Research,THE PROCESSTHE PROCESSBuilding the Chip:MASSIVE PCRPCR PURIFICATIONand PREPARATIONPREPARING SLIDES PRINTINGPreparing RNA:CELL CULTUREAND HARVESTRNA ISOLATIONcDNA PRODUCTIONHybing the Chip:POST PROCESSINGARRAY HYBRIDIZATIONPROBE LABELINGDATA ANALYSISDepartment of Statistics, University of California, Berkeley, and Division of Genetics and Bioinformatics, The Walter and Eliza Hall Institute of Medical Research,MASSIVE PCRPCR PURIFICATION and PREPARATIONPREPARING SLIDESPRINTINGBuilding the Chip:Full yeast genome = 6,500 reactions IPA precipitation +EtOH washes + 384-well formatThe arrayer: high precision spotting device capable of printing 10,000 products in 14 hrs, with a plate change every 25 minsPolylysine coating for adhering PCR products to glass slidesPOST PROCESSINGChemically converting the positive polylysine surface to prevent non-specific hybridizationFabrication of “Spotted Arrays”Fabrication of “Spotted Arrays”20,000Precipitations 20,000 resuspensionsConsolidate forprintingSpot on Glass SlidesArrayed LibraryNormalized/Subtracted20,000 PCRreactionsDepartment of Statistics, University of California, Berkeley, and Division of Genetics and Bioinformatics, The Walter and Eliza Hall Institute of Medical Research,Printing ApproachesPrinting ApproachesNon - Contact• Piezoelectric dispenser• Syringe-solenoid ink-jet dispenserContact (using rigid pin tools, similar to filterarray)• Tweezer• Split pin• Micro spotting pinDepartment of Statistics, University of California, Berkeley, and Division of Genetics and Bioinformatics, The Walter and Eliza Hall Institute of Medical Research,Micro Spotting pinMicro Spotting pinDepartment of Statistics, University of California, Berkeley, and Division of Genetics and Bioinformatics, The Walter and Eliza Hall Institute of Medical Research,Microarray GridderMicroarray GridderDepartment of Statistics, University of California, Berkeley, and Division of Genetics and Bioinformatics, The Walter and Eliza Hall Institute of Medical Research,Practical ProblemsPractical Problems— Surface chemistry: uneven surface may lead to high background.— Dipping the pin into large volume -> pre-printing to drain ofexcess sample.— Spot variation can be due to mechanical diference between pins.Pins could be clogged during the printing process.— Spot size and density depends on surface and solutionproperties.— Pins need good washing between samples to prevent samplecarryover.Department of Statistics, University of California, Berkeley, and Division of Genetics and Bioinformatics, The Walter and Eliza Hall Institute of Medical Research,Hybing the Chip:ARRAY HYBRIDIZATIONPROBE LABELINGDATA ANALYSISCy3 and Cy5 RNA samples are simultaneously hybridized to chip. Hybs are performed for 5-12 hours and then chips are washed.Two RNA samples are labelled with Cy3 or Cy5 monofunctional dyes via a chemical coupling to AA-dUTP. Samples are purified using a PCR cleanup kit.Ratio measurements are determined via quantification of 532 nm and 635 nm emission values. Data are uploaded to the appropriate database where statistical and other analyses can then be performed.Labeling of RNAs with Cy3 or Cy5Two general methods-Dye conjugated nucleotide-Amino-allyl indirect labelingDirect labeling of RNAAAAAAAARNATTTTTTTTCCAACCTATGGTTCy5-dUTPGGTTGGATACCcDNAcDNA synthesis+orCy3-dUTPAAAAAAATTTTTTTTCCAACCTATGGGGTTGGATACCIndirect labeling of RNATModified nucleotideCy3 GGTTGGATACCadditioncDNA synthesisDye effect issuesDirect methodUnequal incorporation of Cy5 vs. Cy3Very poor overall incorporation of direct-conjugatednucleotide = more starting RNA for labeling.Indirect methodPresumably less bias in initial incorporation of activated nucleotide, but not clear if more or lessdye is addedBoth MethodsCy3 fluoresces more brightly than Cy5labeling is very highly sequence dependentDepartment of Statistics, University of California, Berkeley, and Division of Genetics and Bioinformatics, The Walter and Eliza Hall Institute of Medical Research,Micrograph of a portion of hybridization probe from a yeast mciroarray (after