1. An Introduction to DNA Microarrays Jack Newton University of Alberta newton@cs.ualberta.ca

2. DNA Microarrays Overview Introduction to DNA Microarrays DNA Microarray Analysis DNA Microarray Data Characteristics

3. DNA Microarrays What are DNA Microarrays? A recent technology that can measure the expression level of thousands of genes at once A large number of DNA fragments are attached in a systematic way to a solid substrate

4. DNA Microarrays DNA Microarray Image Reference cDNA Experimental cDNA Upregulated Downregulated Gene GTF4

5. DNA Microarrays How DNA Microarrays Work ATGCAAT TGACTGC AGTCGTG GTCTGAT T A A G T C GGene TEF4: …… A G T C T A A G T C G

6. DNA Microarrays How DNA Microarrays Work DNA microarrays measure gene expression levels by measuring mRNA abundance Cambell, Neil (1996). Biology. Benjamin/Cummings Publishing.

7. DNA Microarrays DNA Microarrays and Gene Expression Traditional view of gene expression: – A single gene codes for a single protein Modern view of gene expression: – A single gene may code for several proteins as a result of alternate splicing of mRNA and post-translational modifications – Genes act in concert, not in isolation Thus, we need to observe genes acting together, not in isolation

8. DNA Microarrays From Gene Science to Genome Science DNA Microarrays allow us to see the gene expression levels for tens of thousands of genes at once. A microarray of 50,000 unique cDNAs allows the expression monitoring of the entire human genome in a single hybridization.

9. DNA Microarrays DNA Microarray Analysis What kinds of questions do we want to ask? – What genes have similar function? – What regulatory pathways exist? – Can we subdivide experiments or genes into meaningful classes? – Can we correctly classify an unknown experiment or gene into a known class? – Can we make better treatment decisions for a cancer patient based on his or her gene expression profile?

10. DNA Microarrays Characteristics of DNA Microarray Data Extremely high dimensionality – Experiment = (gene 1, gene 2, …, gene N ) – Gene = (experiment 1, experiment 2, …, experiment M ) – N is often on the order of 10 4 – M is often on the order of 10 1 Noisy data – Normalization and thresholding are important Missing data – For some experiments a given gene may have failed hybridizing

11. DNA Microarrays Characteristics of DNA Microarray Data (Continued) > 8.0 > 1.7 > 2.8 > 1.7 1:1 > 4.8 > 2.8 > 4.8 > 8.0 Gene 1 Gene 2 Gene 3 Gene 4 Experiment 1Experiment 2Experiment 6Experiment 4Experiment 5Experiment 3Experiment 7Experiment 8Experiment 9Experiment 10 Gene 5 Gene 10,000 ……

12. DNA Microarrays Application: Clustering Eisen et al. formulated a method to group genes with similar patterns of expression together. Provides scientists with an invaluable tool to visualize and interpret DNA microarray data. A recently published article in Nature applied this technique to breast cancer research.

13. DNA Microarrays Application: Clustering Perou, Charles M., et al. Nature, 406, 747-752, 2000.

14. DNA Microarrays Application: Clustering Clustering analysis identified four distinct tumor types that had not previously been reported. Previous studies examining the same genes one at a time did not reveal that certain groups of genes play an important role in tumor development. “When you look at one gene at a time, you can't see relationships between genes and groups of genes.” – M. Perou, co-author of study.