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Uses of Microarrays in Research

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Title: Uses of Microarrays in Research


1
Uses of Microarrays in Research
  • Anne Rosenwald
  • Georgetown University

2
Microarrays in ResearchA Survey of PubMed
3
Recent Microarray Papers I. New
Techniques/Applications
  • Transcriptional regulatory networks in
    Saccharomyces cerevisiae
  • Lee et al. (2002) Science 298 799-804
  • ChIP-on-chip

4
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?

5
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.)

6
Recent Microarray Papers II. Improved Methods
for Analysis/Access
  • 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

7
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.edu8080/caryoscope/index.h
    tml

8
Recent Microarray Papers III. Scientific
Endeavors
  • 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)

9
Recent Microarray Papers III. New Scientific
Endeavors
  • Transgenic C. elegans as a model in Alzheimer's
    research
  • Curr Alzheimer Res. 2005 Jan2(1)37-45.
  • Compared wild type worms with worms expressing
    human Ab
  • Behavior and the limits of genomic plasticity
    power and replicability in microarray analysis of
    honeybee brains
  • Genes Brain Behav. 2005 Jun4(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)

10
Beyond Microarrays
Ivakhno (2007) FEBS J. 10, 2439
11
Some basic yeast biology
  • Yeast come in two mating types
  • MATa
  • MATa
  • Can live either as haploids or as diploids
  • diploids referred to as MATa/a
  • haploids are either MATa or MATa

sporulation/meiosis
mating
MATa/a

MATa
MATa
12
Yeast resources
  • 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

13
The yeast knockout collection
  • Yeast knockout resources
  • MATa/a heterozygous diploids (entire genome)
  • MATa haploids (non-essentials)
  • MATa haploids (non-essentials)
  • MATa/a 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 theres a mutant
you want, let me know.
14
The yeast knockout collection
http//www-sequence.stanford.edu/group/yeast_delet
ion_project/deletions3.html
15
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/a 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)

16
Step 1 Creating the haploid convertible
heterozygotes
Important point This HIS3 gene is only expressed
in MATa haploids, not in MATa haploids or MATa/a
diploids So in other words, can select against
MATa/a diploids to ensure youre looking at only
haploids later on.
17
Step 2 Inserting the query mutation
Knockout one copy of your gene of interest (Your
Favorite Gene) with URA3
18
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
xxxDKanMX YFG1
selects for query mutation so genotype is
xxxDKanMX yfg1URA3
19
Reminder about YKO construction
20
Step 4 Prepare genomic DNA and do PCR with
common TAG sequences
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
21
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
22
Evidence this really works part I
On average, the intensity is the same before and
after 1 copy of the CAN1 gene is knocked out
Strains
x-axis
y-axis
XXX/xxxDKanMX CAN1/CAN1
XXX/xxxDKanMX CAN1/can1DMFA1pr-HIS3
23
Evidence this really works part II
Red spots illustrate that fraction of the strains
with KOs in essential genes, so when haploid, not
present in pool
Strains
x-axis
y-axis
DIPLOIDS XXX/xxxDKanMX CAN1/can1DMFA1pr-HIS3
HAPLOIDS XXX or xxxDKanMX can1DMFA1pr-HIS3
24
Another variation Drug sensitivity
25
Another variation Drug sensitivity
26
Summary
  • If you can compare two different conditions and
    you have a way to stick things to slides, some
    sort of microarray is possible!
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