Uses of Microarrays in Research

Anne RosenwaldGeorgetown University

PubMed Articles

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DNA Arrays

Protein Arrays

Microarrays in Research:A Survey of PubMed

Schena, Shalon, Davis, and Brown (1995) Science 270, 467

Differential expression of 45 Arabidopsis genes!

Recent Microarray Papers: I. New Techniques/Applications

Transcriptional regulatory networks in Saccharomyces cerevisiae Lee et al. (2002) Science 298 799-804 “ChIP-on-chip”

Recent Microarray Papers: I. New Techniques/Applications

5,000 RNAi experiments on a chip Lehner and Fraser (2004) Nat Methods 1, 103

RNA living-cell microarrays for loss-of-function screens in Drosophila melanogaster cells Wheeler et al. (2004) Nat Methods 1, 127

Spots on chip contain dsRNA Chip incubated with Drosophila cells Cells induced to “take-up” RNA

Are cells alive or dead? Do cells have phosphorylated Akt? Do cells have altered actin fibrils?

Recent Microarray Papers: II. Improved Methods for Analysis/Access

Reproducibility and statistical rigor outbred organisms (i.e. humans) do different platforms give the same

answers?

Tools for analysis MAGIC Tool! (many others….)

Tools for access and annotation GeneCruiser

http://www.broad.mit.edu/cancer/genecruiser Liefeld et al. Bioinformatics (2005) 21, 3681 Uses Affymetrix-generated data incorporates GO terms and links info with

SwissProt, RefSeq, LocusLink, etc. Primarily for mouse and human data

GEO (Gene Expression Omnibus) http://www.ncbi.nlm.nih.gov/geo/ Barrett et al. (2007) NAR 35, D760 Also heavily weighted to mouse and human data

Recent Microarray Papers: II. Improved Methods for Analysis/Access

Tools for access and annotation (cont). Stanford Microarray Database

http://genome-www5.stanford.edu/ Links to Caryoscope – a way to look at

gene expression data in a whole genome context

http://dahlia.stanford.edu:8080/caryoscope/index.html

Recent Microarray Papers: II. Improved Methods for Analysis/Access

Mutational change: compare “wild type” to mutant Tissue-specific gene expression Environmental change: compare same organism in two

different environments Development: compare different stages along a

particular lineage Therapeutics: compare in cells/tissues treated with and

without the drug of interest Investigate changes in gene copy number Investigate differences in methylation: Epigenetics Disease: compare affected with normal

2006 papers with term “microarray” = 19226 Of those, also with term “cancer” = 5561 (29%)

Recent Microarray Papers: III. Scientific Endeavors

Recent Microarray Papers: III. New Scientific Endeavors

Transgenic C. elegans as a model in Alzheimer's research Curr Alzheimer Res. 2005 Jan;2(1):37-45.

Compared wild type worms with worms expressing human A

Behavior and the limits of genomic plasticity: power and replicability in microarray analysis of honeybee brains Genes Brain Behav. 2005 Jun;4(4):267-71

Compared bees with long-standing behavioral differences (nursers v. foragers)

Compared recently hatched bees beginning to express behavioral differences (nursers v. foragers v. gravetenders)

Beyond Microarrays

Ivakhno (2007) FEBS J. 10, 2439

Some basic yeast biology

Yeast come in two mating types MATa MAT

Can live either as haploids or as diploids diploids referred to as MATa/ haploids are either MATa or MAT

sporulation/meiosisMATa/

MATa MAT

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mating

General website for Saccharomyces (SGD) http://www.yeastgenome.org/

Materials available ~5500 genes cloned with tags for purification TAP-tagged fusion collections GFP-tagged fusion collections Insertional mutant collections Knockout collections

Most of these available from OpenBiosystems www.openbiosystems.com

Yeast resources

The yeast knockout collection

Yeast knockout resources MATa/ heterozygous diploids (entire genome) MATa haploids (non-essentials) MAT haploids (non-essentials) MATa/ homozygous diploids (non-essentials)*

Yeast knockout website http://www-sequence.stanford.edu/group/yeast_delet

ion_project/deletions3.html

*I have this collection, so if there’s a mutant you want, let me know.

The yeast knockout collection

http://www-sequence.stanford.edu/group/yeast_deletion_project/deletions3.html

Using the knockouts for microarrays

A Robust Toolkit for Functional Profiling of the Yeast Genome Pan et al. (2004) Mol Cell 16, 487

Takes advantage of the MATa/ heterozygous diploid collection identifies synthetic lethal interactions via diploid-based

synthetic lethality analysis by microarrays (“dSLAM”)

Uses dSLAM to identify those strains that upon knockout of a query gene, show growth defects synthetic lethal (the new double mutant = dead) synthetic fitness (the new double mutant = slow

growth)

Step 1: Creating the haploid convertible heterozygotes

Important point:This HIS3 gene is only expressed in MATa haploids, not in MAThaploids or MATa/ diploids

So in other words, can select against MATa/ diploids to ensure you’re looking at only haploids later on.

Step 2: Inserting the query mutation

Knockout one copy of your gene of interest (“Your Favorite Gene”) with URA3

Step 3: Make new haploids and select for strains of interest

Sporulate to get new haploids

Select on –his medium to ensure only haploids survive (no diploids)

selects against query mutation so genotype is xxx::KanMX YFG1

selects for query mutation so genotype is xxx::KanMX yfg1::URA3

Reminder about YKO construction

U1 D1

U2 D2

Using common oligos U1 and U2 (or D1 and D2) amplifies the UPTAG (or DNTAG) sequence unique to each of the KOs

Step 4: Prepare genomic DNA and do PCR with common TAG sequences

Step 4: Prepare genomic DNA and do PCR with common TAG sequences

The two different conditions are labeled with two different colors**

The labeled DNA is then incubated with a TAG microarray

**The PCR reactions create a mixture of TAGs (representing all the strains in the pool), since each KO has a unique set of identifier tags (UPTAG and DNTAG) bounded by common oligonucleotides

Evidence this really works – part I

Strains

x-axis y-axis

XXX/xxx::KanMXCAN1/CAN1

XXX/xxx::KanMXCAN1/can1::MFA1pr-HIS3

On average, the intensity is the same before and after 1 copy of the CAN1 gene is knocked out

Evidence this really works – part II

Strainsx-axis y-axis

DIPLOIDSXXX/xxx::KanMX

CAN1/can1::MFA1pr-HIS3

HAPLOIDSXXX or xxx::KanMXcan1::MFA1pr-HIS3

Red spots illustrate that fraction of the strains with KOs in essential genes, so when haploid, not present in pool

Another variation: Drug sensitivity

Another variation: Drug sensitivity

Summary

If you can compare two different conditions and you have a way to stick things to slides, some sort of microarray is possible!