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Microarrays and Their Uses Brad Windle, Ph.D. 628-1956 [email protected] Profile A set of data or characteristics pertaining to an item Profiles are sometimes referred to as Signatures or Fingerprints Cellular Profiles Gene/Protein Sequence Protein Structure Protein Expression Gene Expression SNPs Protein States Structural Genomic Cell State Drug Response Drug Structure Methylation Misc Data Metabolitics Disease Cellular Profiles Gene/Protein Sequence Protein Structure Drug Structure Protein Expression Gene Expression SNPs Protein States Structural Genomic Drug Response Methylation Misc Data Metabolitics Profiles Have Two Sides Gene s / Samples Sample 1 Gene 1 1 Gene s / Samples Sample 1 Sample 2 GeneGene 21 1 5 2 Gene 2 5 3 3 23 23 65 GeneGene 3 Gene 4 2 1 Gene 4 2 Sample 2 Sample 3 2 3 Sample 3 Sample 4 33 17 32 17 22 23 65213 21 3 1 3 Sample 4 32 22 23 3 A gene profile across samples and a sample profile across genes Microarrays and Gene Expression Profiling What do we want to know? The smaller picture What genes went up or down under an experimental condition? The bigger picture Are cells or tissues related based on the genes they express? For an experimental cell model, are there conditions that are similar based on changes in gene expression? For certain experimental conditions, are there genes that show similar patterns of change (co-regulated)? How did we use to do this? Probe for 1 gene Analyze ~10 samples Now with Microarrays Analyzing 1 gene for 10 samples Analyzing thousands of genes for 1 sample Spotting Arrays Affymetrix cDNA synthesis labeling Gene Expression Profiling cell or condition of interest control or reference cell hybridize to microarray Applications of Gene Expression Profiling Tissue or Tumor Classification Gene Classification Drug Classification Drug Target Identification Drug Response Prediction Ross et al Nature Genetics 24:227 (2000) The Color Map Cells 12345abcde Genes 1 2 3 4 a d c d Ross et al Nature Genetics 24:227 (2000) Alizadeh et al. Nature 403:503 (2000) Alizadeh et al. Nature 403:503 (2000) Gene Expression Array Genomic Content Array Methylation Array (Chromatin Array) Replication Array SNP Array Structural Genomic Profiling Comparative Genomic Hybridization (CGH) cell with losses or gains hybridize to metaphase chromosomes normal cell Genome Representation Profiling Using Arrays Normal Label DNA Cancer Label DNA BAC or Oligo Array CG H Detection mainly for cancer and inherited deletions Tumor suppressor genes are deleted Oncogenes are amplified Methylation Profiling me CCGG GGCC me PCR linkers CCGG GGCC me me PCR Amplify / Label Hpa II / PCR Amplify/ Label hybridize to array CpG Island Array Profile cells based on methylation state cell-type profiles Differences in the methylated state of cancers Compare methylation profiles to gene expression profiles Replication Profiling Synchronized cells in G1/S time BrdU Labeling cDNA or BAC Array Profiling Transcription Factor-Interactive DNA Immuno-precipitate w/ Ab to protein Chromatin IP or ChIP total genomic DNA Combinatorial Elements Regulating Transcription Single Nucleotide Polymorphism (SNPs) Profile Personal fingerprint Profile a small town Figure out who’s related to who What chromosomes came from whom What regions came from whom Figure out what meiotic exchanges occurred Pharmacogenomics - SNPs that affect disease and reaction to drugs The ProfileData Sources Gene expression DNA microarrays, oligo or PCR, 20-30,000 genes Structural genomics DNA microarrays, BACs, ~one per 1Mb Methylation DNA microarrays, upstream sequences, CpG islands SNPs DNA microarray, oligos, millions of SNP sites Protein expression Ab microarray, 2D gels, chromatographics Protein states 2D gels, <1000 proteins resolved Drug response brute force, 70,000 compounds screened Metabolitics chromatographics DNA/protein sequence Sequencing, <20 people sequenced, brute force Drug structure in silico Protein structure 3D crystallography, NMR, brute force Questions?