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
225-4054
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
CARS: A Curated Annotation Database Tool
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
Mirnics et al., Neuron 28:53, 2000
Microarray Analysis of Gene Expression in Prefrontal Cortex of Schizophrenics
0
2
4
6
8
10
12
S-Score
Ribosomal
Total
p< 10-33 (Chi-Square)
Distribution of Expressed Genes across Seven Frontal Cortex Comparisons
Percent of Change ALL Frontal MYEL GLU PSYN APOP Cell cycleAlcRes
(44029) (120) (50) (511) (618) (752) (733)
<=-1.9 0.7 4.2 2.0 1.2 0.3 1.1 1.4-1.6 to -1.89 1.9 8.3 6.0 2.0 1.5 2.7 3.3-1.59 to 1.59 94.9 75.8 86.0 93.9 96.0 94.7 92.0
1.6 to 1.89 1.8 4.2 6.0 2.5 2.1 1.2 2.3>=1.9 0.7 7.5 0.0 0.4 0.2 0.4 1.1
Chi-square, p< NA <<0.0001 0.0002 0.95 0.94 0.93 0.72
Functional Hierarchy Statistics in Alcoholic Brain Tissue(Frontal Cortex)
Courtesy of Dr. Adron Harris, UT at Austin
Non-biased (semi) Functional Group Analysis: GenMAPP
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
Efforts to Integrate Diverse Biological Databases
with Expression Information: PubGen
www.PubGen.org
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
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Expression of Aldh9a1 Across BxD RI Lines
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WebQTL Allows Definition of Genetic “Linkage” for Expression Patterns
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)
Use of Expression Profile “Compendium” to Characterize Gene or Drug Function
Hughes et al. Cell 102:109-126 (2000)
established error modelprofiled large number of mutants/drugs under highly controlled conditionsstatistical treatment of expression patternsverified array results with biochemical/phenotypic assays
Key features:
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 treatmentsHughes et al. Cell 102:109-126 (2000)
Assigning Function to Uncharacterized Genes by Expression Profiles
Hughes et al. Cell 102:109-126 (2000)
Expression Networks
Expression Profiling
Pharmacology Genetics
Behavior
Prot-Prot
Interactions
OntologyHomoloGene
BioMed Lit
Relations