1. Introduction to DNA Microarrays: Functional Mining of Array Patterns Michael F. Miles, M.D., Ph.D. Depts. of Pharmacology/Toxicology and Neurology and the Center for Study of Biological Complexity mfmiles@vcu.edu 225-4054

2. Tertiary Analysis: Connecting Function with Expression Patterns Annotation –UniGene/Swiss-Prot, SOURCE, CARS Biased functional assessment –Functional group interrogation Manual, GenMAPP, GeneSpring Non-biased functional queries –PubGen –MAPPFinder, DAVID/Ease, GEPAS, others –Cytoscape Overlaying genomics and genetics –WebQTL

3. CARS: A Curated Annotation Database Tool

5. Tertiary Analysis: Connecting Function with Expression Patterns Annotation –UniGene/Swiss-Prot, SOURCE, CARS Biased functional assessment –Functional group interrogation Manual, GenMAPP, GeneSpring Non-biased functional queries –PubGen –MAPPFinder, DAVID/Ease, GEPAS, others –Cytoscape Overlaying genomics and genetics –WebQTL

6. Mirnics et al., Neuron 28:53, 2000 Microarray Analysis of Gene Expression in Prefrontal Cortex of Schizophrenics

8. Distribution of Expressed Genes across Seven Frontal Cortex Comparisons Percent of ChangeALL FrontalMYELGLUPSYNAPOPCell cycleAlcRes (44029)(120)(50)(511)(618)(752)(733) <=-1.90.74.22.01.20.31.11.4 -1.6 to -1.891.98.36.02.01.52.73.3 -1.59 to 1.5994.975.886.093.996.094.792.0 1.6 to 1.891.84.26.02.52.11.22.3 >=1.90.77.50.00.40.20.41.1 Chi-square, p<NA<<0.00010.00020.950.940.930.72 Functional Hierarchy Statistics in Alcoholic Brain Tissue (Frontal Cortex) Courtesy of Dr. Adron Harris, UT at Austin

9. Non-biased (semi) Functional Group Analysis: GenMAPP

10. Tertiary Analysis: Connecting Function with Expression Patterns Annotation –UniGene/Swiss-Prot, SOURCE, CARS Biased functional assessment –Functional group interrogation Manual, GenMAPP, GeneSpring Non-biased functional queries –PubGen –MAPPFinder, DAVID/Ease, GEPAS, others –Cytoscape Overlaying genomics and genetics –WebQTL

11. Efforts to Integrate Diverse Biological Databases with Expression Information: PubGen www.PubGen.org

12. Tertiary Analysis: Connecting Function with Expression Patterns Annotation –UniGene/Swiss-Prot, SOURCE, CARS Biased functional assessment –Functional group interrogation Manual, GenMAPP, GeneSpring Non-biased functional queries –PubGen –MAPPFinder, DAVID/Ease, GEPAS, others –Cytoscape Overlaying genomics and genetics –WebQTL

14. Expression of Aldh9a1 Across BxD RI Lines

15. WebQTL Allows Definition of Genetic “Linkage” for Expression Patterns

16. Expression Profiling: “It is possible that the expression profile could serve as a universal phenotype … Using a comprehensive database of reference profiles, the pathway(s) perturbed by an uncharacterized mutation would be ascertained by simply asking which expression patterns in the database its profile most strongly resembles … it should be equally effective at determining consequences of pharmaceutical treatments and disease states” Hughes et al. Cell 102:109-126 (2000)

17. Use of Expression Profile “Compendium” to Characterize Gene or Drug Function Hughes et al. Cell 102:109-126 (2000) established error model profiled large number of mutants/drugs under highly controlled conditions statistical treatment of expression patterns verified array results with biochemical/phenotypic assays Key features:

18. Correlation in Expression Profiles of Drugs/Genes Affecting Same Pathways cup5 and vma8, components of H+/ATPase complex Unrelated gene mutants HMG CoA- reductase mutant vs. lovastatin, an inhibitor of HMG2 Red symbols = significant change (p<0.05) in both treatments Hughes et al. Cell 102:109-126 (2000)

19. Assigning Function to Uncharacterized Genes by Expression Profiles Hughes et al. Cell 102:109-126 (2000)

20. Expression Networks Expression Profiling Pharmacology Genetics Behavior Prot-Prot Interactions Ontology HomoloGene BioMed Lit Relations