STAT530lecture3IntroMicroarray - STAT 530 STAT Introduction...

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Unformatted text preview: STAT 530 STAT Introduction to Microarray Microarray Ping Ma Ping Microarray High throughput gene expression platforms – SAGE – Microarrays: cDNA and oligonucleotide arrays Microarray analysis: – Very low level: image analysis – Low level: normalization • Dye swap • Linear scaling • Loess: reference set • More next lecture… Ping Ma STAT530 2 Ping Ma STAT 530 1 Central Dogma of Molecular Biology DNA replication DNA RNA Translation Protein Folded with function Physiology Reverse transcription Transcription Ping Ma STAT530 3 Differential Expression Understand expression level of genes under different conditions – Cell types (brain vs. liver) – Developmental (fetal vs. adult) – Response to stimulus (rich vs poor media) – Gene activity (wild vs. mutant) – Disease states (healthy vs. diseased) Ping Ma STAT530 4 Ping Ma STAT 530 2 High Throughput Gene Expression Technologies Measure gene expression: quasi-estimate of the protein level and cell state High throughput: measure mRNA level of every gene in the genome Formats: – Serial Analysis of Gene Expression (SAGE) – Microarrays: spotted and cDNA microarrays oligonucleotide arrays Ping Ma STAT530 5 SAGE Serial Analysis of Gene Expression Earliest high throughput gene expression experiment Velculescu et al, Science 1995. Ping Ma STAT530 6 Ping Ma STAT 530 3 SAGE data Ping Ma STAT530 7 SAGE data A SAGE experiment: SAGE ---sampling a handful of colored balls from a sampling big bag and then estimating the proportion of balls of each color. balls Statistical model: Bin(n,pi) Statistical Bin(n,p Ping Ma STAT530 8 Ping Ma STAT 530 4 SAGE modeling SAGE count :Yi(t) be the count of tag i in library SAGE be t, and Yii(t) ~ Poisson(λi(t)θi). and Y Poisson( ). The expected count λi(t)θi consists of two consists factors: ---θi iis the expected sum of counts of transcript i --- s (tag i) over all libraries ---λi(t) iis the contribution of transcript i in library s t to the sum θi expressed in percentage. expressed Ping Ma STAT530 9 SAGE Advantage: – Sensitive for low expression genes – Does not require prior sequence info, detect unknown genes Disadvantage: – 10-14 bp may not uniquely map to one gene – Does not have commercial product, therefore not as well supported and widely used Ping Ma STAT530 10 Ping Ma STAT 530 5 Microarrays Grow cells at certain condition, collect mRNA and convert to labeled cDNA/cRNA Microarray has high density sequence specific probes with known location for each gene/RNA Sample hybridized to microarray probes by DNA complementarity, wash non-specific binding Check sample mRNA value by labeled signals at each probe location Ping Ma STAT530 11 Spotted cDNA Arrays Pat Brown Lab, Stanford University Robotic spotting of cDNA clones in high density format Spot size about 100 microns One probe per gene Ping Ma STAT530 12 Ping Ma STAT 530 6 Spotted cDNA Arrays Competing hybridization – Control – Sample Detection – Green: high control – Red: high sample – Yellow: equally high – Black: equally low Ping Ma STAT530 13 cDNA Microarrays Ping Ma STAT530 14 Ping Ma STAT 530 7 Why Competing Hybridization? Probes not spotted evenly, DNA concentration in PCR not the same Ping Ma STAT530 15 Animation cDNA cDNA Printing Printing Ping Ma STAT530 16 Ping Ma STAT 530 8 Oligonucleotide Arrays GeneChip® by Affymetrix Parallel synthesis of oligonucleotide probes (25mer) on a slide using photolithographic methods Feature size about 20 microns (now 5 microns) Multiple probes per gene One-color arrays Ping Ma STAT530 17 Affymetrix GeneChip Probes Ping Ma STAT530 18 Ping Ma STAT 530 9 cRNA Sample Preparation Ping Ma STAT530 19 cRNA Sample Preparation Ping Ma STAT530 20 Ping Ma STAT 530 10 Labeled cRNA Samples Hybridize to DNA Probes on GeneChip Ping Ma STAT530 21 Shining Laser Light Causes Tagged Fragments to Glow Ping Ma STAT530 22 Ping Ma STAT 530 11 Perfect Match (PM) vs MisMatch (MM) (control for cross hybridization) Ping Ma STAT530 23 Array Platform Comparisons cDNA microarrays: – Two-color assay, comparative hybridization – Cheaper ($50-$200 / chip) – Flexibility of custom-made array: do not need whole sequence Oligonucleotide GeneChip: – One-color assay, absolute expression level – A little more expensive ($400-500 / chip) price drop according to Moore’s Law – Automated: better quality control, less variability – Easier to compare results from different experiments Many more commercial array platforms – Agilent, ABI, Amgen, NimbleGen… – Many use long oligo probes: 30-70 nt Ping Ma STAT530 24 Ping Ma STAT 530 12 Motivation of Exon Array Motivation Exon Global analyses of mammalian transcriptomes suggest transcriptomes suggest that alternative splicing is an important and prevalent form of transcript variation in many species Genome-wide analyses of expressed sequences indicate Genome wide that 40–60% of human genes have multiple splice that 60% forms Since alternative splicing has been largely ignored throughout the probe design of traditional expression microarrays, these findings have motivated the microarrays these development of a new generation of microarray microarray platforms, which use probes targeting individual exons platforms, exons to interrogate pre-mRNA splicing at the genomic scale mRNA Ping Ma STAT530 25 Exon Array Ping Ma STAT530 26 Ping Ma STAT 530 13 Probes in Exon Array Probes Exon On Exon arrays, up to four probes are selected from Exon arrays, each putative exonic region. exonic region. In addition to probes targeting each exon supported by exon supported RefSeq mRNA evidence (core probes), Exon arrays RefSeq mRNA Exon arrays also have probes that target exons supported solely by exons supported expressed sequence tag evidence (extended probes) or by purely computational predictions (full probes). over 6.5 million probes on the Human Exon 1.0 array Exon 1.0 Ping Ma STAT530 27 No mismatch in Exon arrays No Exon arrays In contrast to the 3' approach of using MM probes to measure non-specific hybridization, probes specific Exon arrays have no MM probes and instead Exon arrays include a set of probes designed to detect hybridization due to pure background. Ping Ma STAT530 28 Ping Ma STAT 530 14 ...
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This note was uploaded on 11/21/2010 for the course STAT STAT530 taught by Professor Ma during the Spring '07 term at University of Illinois, Urbana Champaign.

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