1. Microarrays and Other High-Throughput Methods BMI/CS 576 www.biostat.wisc.edu/bmi576/ Colin Dewey cdewey@biostat.wisc.edu Fall 2010

2. One High-Throughput Method: Microarrays one common HT study type: measuring RNA abundances what is varied: individuals, strains, cell types, environmental conditions, disease states, etc. what is measured: RNA quantities for thousands of genes, exons or other transcribed sequences genes mRNAs

3. More High-Throughput Methods varied: individuals, strains, cell types, environmental conditions, disease states, etc. measured: RNA quantities technology: microarrays, RNA-seq varied: same as above measured: protein quantities technology: 2D gel electrophoresis + mass spec varied: same as above measured: small molecule quantities technology: 2D gel electrophoresis + mass spec

4. More High-Throughput Methods varied: single (or pairs) genes knocked out measured: some “reporter” quantity of interest technology: deletion libraries   varied: individuals measured: variation at specific genome locations technology: SNP chips, next- generation sequencing

5. High-Throughput Methods for Detecting Interactions varied: cell types, environmental conditions etc. measured: protein-DNA interactions technology: chip-ChIP, ChIP- Seq varied: measured: protein-protein interactions technology: two-hybrid systems, mass spec

6. HT Output for most of these methods, we can think of the output as a 2D matrix in which –rows are gene/protein/small- molecule measurements –columns are individuals/strains/cell- types/treatments etc.

7. Microarrays microarrays provide a tool for answering a wide range of questions about the dynamics of cells –how active are various genes in different cell/tissue types? –how does the activity level of various genes change under different conditions? stages of a cell cycle environmental conditions disease states knockout experiments –what genes seem to be regulated together? can also be used to answer questions about static properties (e.g. genotyping), but we’ll focus on the former class of questions

8. Microarrays a.k.a. DNA chips, gene chips, DNA arrays etc. two general types that are popular –spotted arrays (pioneered by Pat Brown @ Stanford) –oligonucleotide arrays (pioneered by Affymetrix Inc.) both based on the same basic principles –anchoring pieces of DNA to glass/nylon/silicon slides –complementary hybridization

9. Complementary Hybridization AGCGGTTCGAATACC TCGCGAAGCTAGACA CCGAAATAGCCAGTA UCGCCAAGCUUAUGG due to Watson-Crick base pairing, complementary single- stranded DNA/RNA molecules hybridize (bond to each other)

10. Complementary Hybridization AGCGGTTCGAATACC one way to do it in practice –put (a large part of ) the actual gene sequence on array –convert mRNA to cDNA using reverse transcriptase UCGCCAAGCUUAUGG TCGCCAAGCTTATGG actual gene cDNA mRNA reverse transcriptase

11. Spotted Arrays robot puts little spots of DNA on glass slides each spot is DNA analog of one of the mRNAs we want to measure

12. Spotted Arrays two samples (reference and test) of mRNA are reverse transcribed to cDNA, labeled with fluorescent dyes and allowed to hybridize to array test reference mRNAcDNA

13. Spotted Arrays lasers applied to the arrays yield an emission for each fluorescent dye

15. Spotted Arrays we can’t detect the absolute amount of mRNA present for a given gene, but we can measure amount relative to a reference sample typically we have a set of measurements where red is the test expression level, and green is the reference level for gene G in the i th experiment

16. Oligonucleotide Arrays most common are Affymetrix’s GeneChips™

17. Oligonucleotide Arrays instead of putting entire genes on an array, put sets of DNA oligonucleotides (fixed length sequences, typically 25-60 nucleotides in length) oligos are synthesized on the chip –Affymetrix uses a photolithography process similar to that used to make semiconductor chips –there are other processes; Nimblegen (in Madison) uses an array of 786,000 tiny mirrors + photo deposition chemistry mRNA samples are processed separately on individual arrays, instead of in pairs

18. Oligonucleotide Arrays given a gene to be measured, select different n-mers for the gene can also select n-mers for noncoding regions of the genome selection criteria –specificity –hybridization properties –ease of manufacturing gene 25-mers

19. Oligonucleotide Arrays put each of these n-mers on the chip Affymetrix also puts a slight variant (that differs only at the middle base) of each next to it –this supposedly helps factor out false hybridizations the measurements for a gene are derived from these separate n-mer measurements –present/absent calls –numerical quantity proportional to amount of mRNA present

20. RNA-Seq Sequencing technology is rapidly advancing Idea: sequencing is so cheap we can directly sequence mRNAs “digital gene expression”

21. RNA-Seq Mortazavi et al., Nature Methods, 2008

22. RNA-Seq vs. Microarrays Mortazavi et al., Nature Methods, 2008

23. Several Computational Tasks identifying differential expression: which genes have different expression levels across two groups clustering genes: which genes seem to be regulated together clustering samples: which treatments/individuals have similar profiles classifying genes: to which functional class does a given gene belong classifying samples: to which class does a given sample belong –e.g., does this patient have ALL or AML –e.g., does this chemical act like an AHR agonist, or a PCB or …