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Parallel human genome analysis: Microarray-based expression monitoring of 1000 genes Mark Schena, Dari Shalon, Renu Heller, Andrew Chai, Patrick O. Brown,

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Presentation on theme: "Parallel human genome analysis: Microarray-based expression monitoring of 1000 genes Mark Schena, Dari Shalon, Renu Heller, Andrew Chai, Patrick O. Brown,"— Presentation transcript:

1 Parallel human genome analysis: Microarray-based expression monitoring of 1000 genes Mark Schena, Dari Shalon, Renu Heller, Andrew Chai, Patrick O. Brown, and Ronald W. Davis

2 Goals Goals To detect the expression of thousands of genes simultaneously To detect the expression of thousands of genes simultaneously Gene expression studies – expression patterns of genes provide clues to function by comparison Gene expression studies – expression patterns of genes provide clues to function by comparison Gene discovery studies Gene discovery studies Use the microarray assay to identify Use the microarray assay to identify Known and novel heat shock genes Known and novel heat shock genes Phorbol-ester regulated genes Phorbol-ester regulated genes Schena et. al

3 Types of Microarrays Photolithography – using oligos Photolithography – using oligos Spotting – using cDNAs/ESTs Spotting – using cDNAs/ESTs

4 Schena et. al Human cDNA from human T mRNA transformed by the Epstein Barr Virus with 5’ amino acid modification, amplified by PCR, and arrayed onto silyated microscope slides Human cDNA from human T mRNA transformed by the Epstein Barr Virus with 5’ amino acid modification, amplified by PCR, and arrayed onto silyated microscope slides Probes labeled with fluorescin and Cy5-dCTP are hybridized to 1056-element array and scanned Probes labeled with fluorescin and Cy5-dCTP are hybridized to 1056-element array and scanned Verify expression patterns with RNA Blot Verify expression patterns with RNA Blot Array elements that display differential expression patterns are sequenced Array elements that display differential expression patterns are sequenced Compare sequence to Informatics databases Compare sequence to Informatics databases Methods

5 Schena et. al, Figure 1 Monitoring of heat shock response in control (37 o )and treated Jurkat (43 o,human T) cells Monitoring of heat shock response in control (37 o )and treated Jurkat (43 o, human T) cells - Array contains 10 Arabidopsis controls, 1046 human blood cDNAs -White box indicates altered fluorescence: -Red boxes indicate activation -Green boxes indicate repression Hybridization signals observed for > 95% of human cDNA elements Comparative expression finds altered fluorescence in 17 array elements

6 Schena et. al, Figure 2 Elemental displays of activated and repressed genes  Fluorescin labeled probes from (+) heat-shock and (+) phobol ester cells are compared to Cy5-labeled untreated probes  Data is the average of the ratios from the 2 hybridizations  17 elements have a 2-fold alteration in fluorescence  Intensity of fluorescnece is a measure of mRNA abundance

7 Schena et. al, Table 1  14/17 clones matched; proximal and distal ends map to same gene  Hsp90, dnaJ, polyubiquitin, tcp-1 are highly induced  Novel sequences (B7-B9) have 2-fold induction

8 Schena et. al, Table 2 Correlation of human gene expression from microarray analysis is confirmed by RNA blot analyses

9 Schena et. al, Figure 3 Microarrays measure expression in human tissues Bone marrow, brain, prostate, and heart Expression levels in genes correlates with expression level in tissues

10 Advantages Small hybridization volumes using cDNA provides specificity not possible with oligo-based arrays Small hybridization volumes using cDNA provides specificity not possible with oligo-based arrays High array densities High array densities Incorporation of fluorescence labeling and detection Incorporation of fluorescence labeling and detection High throughput: sequence-based methods require serial processing High throughput: sequence-based methods require serial processing Rich number of ESTs makes for more powerful arrays Rich number of ESTs makes for more powerful arrays Schena et. al

11 Disadvantages Cost Cost Commercial availability of microarrays Commercial availability of microarrays

12 Conclusions Microarrays are useful for gene discovery in the absence of sequence information Microarrays are useful for gene discovery in the absence of sequence information Parallel assays can monitor gene expression for thousands of genes Parallel assays can monitor gene expression for thousands of genes Allows high throughput human genome expression and gene discovery Allows high throughput human genome expression and gene discovery Allows for rapid mechanistic examination of hormones, drugs, elicitors, and other small molecules Allows for rapid mechanistic examination of hormones, drugs, elicitors, and other small molecules Potential capacities for patient screening Potential capacities for patient screening Sensitivities of microarrays allows for functional analysis of transcription factors, kinases, growth factors Sensitivities of microarrays allows for functional analysis of transcription factors, kinases, growth factors Schena et. al


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