Presentation on theme: "Introduction to DNA Microarrays Michael F. Miles, M.D., Ph.D. Depts. of Pharmacology/Toxicology and Neurology and the Center for Study of Biological Complexity."— Presentation transcript:
Introduction to DNA Microarrays Michael F. Miles, M.D., Ph.D. Depts. of Pharmacology/Toxicology and Neurology and the Center for Study of Biological Complexity email@example.com 225-4054
Biological Regulation: “You are what you express” Levels of regulation Methods of measurement Concept of genomics
Regulation of Gene Expression Transcriptional –Altered DNA binding protein complex abundance or function Post-transcriptional –mRNA stability –mRNA processing (alternative splicing) Translational –RNA trafficking –RNA binding proteins Post-translational –Many forms!
Regulation of Gene Expression Genes are expressed when they are transcribed into RNA Amount of mRNA indicates gene activity Some genes expressed in all tissues -- but are still regulated! Some genes expressed selectively depending on tissue, disease, environment Dynamic regulation of gene expression allows long term responses to environment
Acute Drug Use Mesolimbic dopamine ? Other Reinforcement Intoxication Chronic Drug Use Compulsive Drug Use “Addiction” ?Synaptic Remodeling Persistent Gene Exp. Tolerance Dependence Sensitization Altered Signaling Gene Expression ?Synaptic Remodeling
Progress in Studies on Gene Regulation 19601970198019902000 mRNA, tRNA discovered Nucleic acid hybridization, protein/RNA electrophoresis Molecular cloning; Southern, Northern & Western blots; 2-D gels Subtractive Hybridization, PCR, Differential Display, MALDI/TOF MS Genome Sequencing DNA/Protein Microarrays
A Bit of History ~1992-1996: Oligo arrays developed by Fodor, Stryer, Lockhart, others at Stanford/Affymetrix and Southern in Great Britain ~1994-1995: cDNA arrays usually attributed to Pat Brown and Dari Shalon at Stanford who first used a robot to print the arrays. In 1994, Shalon started Synteni which was bought by Incyte in 1998. However, in 1982 Augenlicht and Korbin proposed a DNA array (Cancer Research) and in 1984 they made a 4000 element array to interrogate human cancer cells. (Rejected by Science, Nature and the NIH)
Comparative Hybridization with Spotted cDNA Microarrays
Synthesis of High Density Oligonucleotide Arrays by Photolithography/Photochemistry
GeneChip Features Parallel analysis of >30K human, rat or mouse genes/EST clusters with 15-20 oligos (25 mer) per gene/EST entire genome analysis (human, yeast, mouse) 3-4 orders of magnitude dynamic range (1-10,000 copies/cell) quantitative for changes >25% ?? SNP analysis
Oligonucleotide Array Analysis AAAA Oligo(dT)-T7 Total RNA Rtase/ Pol II dsDNA AAAA-T7 TTTT-T7 CTP-biotin T7 pol TTTT-5’ 5’ Biotin-cRNA Hybridization Steptavidin- phycoerythrin Scanning PM MM
Stepwise Analysis of Microarray Data Low-level analysis -- image analysis, expression quantitation Primary analysis -- is there a change in expression? Secondary analysis -- what genes show correlated patterns of expression? (supervised vs. unsupervised) Tertiary analysis -- is there a phenotypic “trace” for a given expression pattern?
Position Dependent Nearest Neighbor (PDNN) - 2003 Zhang, Miles and Aldape, (2003) A model of molecular interactions on short oligogonucleotide microarrays: implications for probe design and data analysis. Nature Biotech. In Press.
“Lowess” normalization, Pin-specific Profiles After Print-tip Normalization Slide Normalization: Pieces and Pins See also: Schuchhardt, J. et al., NAR 28: e47 (2000) http://www.ipam.ucla.edu/publications/fg2000/fgt_tspeed9.pdf
Sources of Variability Target Preparation –Group target preps Chip Run –Minor, BUT… –Be aware of processing order Chip Lot –Stagger lots across experiment if necessary Chip Scanning Order –Cross and block chip scanning order
Array Analysis: Conclusions Be careful! Assess quality control parameters rigorously Single arrays or experiments are of limited value Normalization and weighting for noise are critical procedures Across investigator/platform/species comparisons will most easily be done with relative data