Transcript Microarrays - University of Vermont

Vermont Genetics Network
Microarray Outreach Program
Large Scale Gene
Expression with
DNA Microarrays
Vermont Genetics Network (VGN)
Founded at the University of Vermont in 2001 through an NIH
BRIN grant and renewed in 2005 through an NIH INBRE
grant
Purpose:
• Encourage biomedical research in Vermont
• Create a “network” of researchers and students
• Give outreach lectures to 4-year institutions
• Provide research grants to faculty and students
• Mentoring for students interested in research
VGN Microarray Outreach Program
•Develop microarray outreach module.
•Introduce microarray technology to VT colleges.
•Team of scientists to serve as instructors
Tim Hunter, Pat Reed, Janet Murray, Scott Tighe
Why Gene Expression using Microarray?
• Up and coming modern technology- complicated
• Not affordable to all colleges
• Well adapted mini coarse with a “big picture”
• Can use many model organisms
• Employs large scale bioinfomatics-one of VGN’s goals
Desired Outcomes of Microarray module
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Learn new techniques that are state of the art
Improve laboratory skills
Build self confidence
Creates new opportunities:
• Internships
• Job offers due to experience in new technology
• Build contact networks
Microarrays
What are Microarrays?
• Microarrays are simply small glass or silicon slides upon the
surface of which are arrayed thousands of features (usually
between 500 up to 7.5 million)
• Using a conventional hybridization process, the level of
expression of genes is measured
• Microarrays are read using laser-based fluorescence
scanners
What are Microarrays?
Instrumentation
Affymetrix GeneChip System
3000-7G Scanner
450 Fluidic Station
640 Hybridization Oven
Affymetrix GeneChip
$400 each
$300,000
Arabidopsis ATH1 Genome Array
This GeneChip contains 500,000 DNA oligos comprising 24,000 genes
-
The image on the left is
a full scan of the
GeneChip while the
image on the right is a
1000X zoom of a small
area.
Why use Microarrays?
• What genes are Present/Absent in a cell?
• What genes are Present/Absent in the experiment vs.
control?
• Which genes have increased/decreased expression in
experiment vs. control?
• Which genes have biological significance?
Microarray Applications
• Identify new genes implicated in disease progression and
treatment response (90% of our genes have yet to be ascribed a
function)
• Assess side-effects or drug reaction profiles
• Extract prognostic information, e.g. classify tumors based on
hundreds of parameters rather than 2 or 3.
• Identify new drug targets and accelerate drug discovery and
testing
Microarray Applications
• Gene Discovery– Assigning function to sequence
– Discovery of disease genes and drug targets
– Target validation
• Genotyping
– Patient stratification (pharmacogenomics)
– Adverse drug effects (ADE)
• Microbial ID
Why analyze so many genes?
• Just because we sequenced a genome doesn’t mean we know
anything about the genes. Thousands of genes remain without
an assigned function.
• Patterns/clusters of expression are more predictive than
looking at one or two prognostic markers – can figure out new
pathways
The 2008 Marlboro Experiments
• What is your experiment
• What is your question or hypothesis
• What is your organism
• Will you be able to keep the study system stable and
comparable
• How many duplicates/samples will be enough
Experimental Design
Is this a “fishing expedition” or a hypothesis-based experiment?
Choice of reference (control):
Common reference, Non-treated, Wildtype
As important as the experimental samples
Number of replicates (required!!!):
How many are needed ?
How many are affordable?
Pooling of samples???
Scatter plots reveal changes between samples
Normal vs. Normal
Normal vs. Treated
UP
Down
Laboratory Procedures and Considerations
The Central Dogma
DNA (genes)
messenger RNA
Protein (effector molecules)
[Expressed Genes = mRNA]
Consider the characteristics of your model organism!
E. coli
Yeast
Human
~ 1 x 3 m
~ 5 m dia.
~ 1.7 m
1 chromosome
16 chromosomes
23 chromosomes
4 x 10 6 bp
12 x 10 6 bp
3.3 x 10 9 bp
~ 4,377 genes
~ 5,726 genes
~ 30, 000 genes
Arabidopsis Characteristics….
• How many chromosomes?
• What is expected RNA yields?
• What are the problems that investigators encounter routinely?
• What genes do you expect will change?
• Check the databases:
http://www.arabidopsis.org/
Netaffx-Affymetrix
First step –Get good total RNA
• Five types of RNA
– Ribosomal- [rRNA-5s, 5.8s 16s, 18s, 25s 28s]
– Transfer[tRNA]-protein synthesis]
– Messager[mRNA-Poly adenylated]
– Micro[miRNA-RNA control]
– Small Nuclear- [snRNA]
We need total RNA –We need the rRNA as an indicator of quality
Creating Targets
mRNA
Reverse Transcriptase
1st Strand
cDNA
2nd Strand
cDNA
in vitro transcription
cRNA
GeneChip
The steps of a
microarray
experiment
Quality Control Is Very Important because
microarray is very expensive!
• RNA purity and integrity
Nanodrop spec
Bioanalyzer
• cDNA synthesis efficiency
• Efficient cRNA synthesis, labeling, and
fragmentation
• Target evaluation with Test Chips
RNA-DNA Hybridization, Staining, and Scanning
Labeled
sample
Inject and Hyb 16hr
Stain and scan
Examine and Analyze…..
Data Analysis:
Data analysis is
difficult and time
consuming and can
takes weeks and
months due to the
amount of data
General Techniques and Guidelines for Extracting Total RNA
Why Total RNA?
• Not all transcripts have poly A tail
• RNA assessment is more determinative due to rRNA
subunit peaks when running a gel or Bioanalyzer
• Recovery of special RNA’s such as MiRNA
• mRNA recovery kits also recover rRNA anyway
General RNA Handling
Reagents and Equipment-Considerations:
All reagents MUST be RNase-free
Use gloves that are periodically treated with RNase Zap
Perform as must work in a hood
Biosafety
Laminar flow
PCR hood
DO NOT use a fume hood
Use aerosol resistent pipet tips
Prepare all surfaces and pipets by treating with RNAse Zap
All utensils [scissors, scalpels, tweezers] should be scrubbed clean, sprayed
with RNase Zap, soaked in ETOH and flame sterilized before a surgery
General RNA Handling
Prepare daily aliquots of RNase-free water. I aliquot 10-20 tubes each
week and discard half way through the day.
Diethylpyrocarbonate [DEPC]-treated water is NOT an inhibitor for
RNases, but rather DEPC is a chemical added to water to eliminate
RNases. After autoclaving [or when purchased], no DEPC resides in
the water.
When opening and closing tubes, be careful not to bump the inner rim of
your tubes.
RNA Extraction Systems
RNA Isolation and Purification Systems-[Column-based]
RNeasy Micro kit [74004]
Small elution volumes 10-15ul for 10ug
Good for FACS samples, LCM, or limited cell
On-column DNase treatment
RNeasy Mini Kit [74104]
Standard Elution volume of 30-50ul for 100ug
General use column
On column DNase treatment
Lipid or Fiber kits too
RNeasy Midi and Maxi Kit
Large elution volumes 150-800ul for 1mg of RNA
USB Corp Prep-Easy Kit [78766]
A knock off of the RNeasy Mini kit
Elution volume of 30ul
Cheaper than RNeasy and comes with DNase
Zymo Corp
Not recommended-poor recoveries in our hands
RNA Isolation and Purification Systems-[Column-based]
• RNeasy and USB system are a 4M guanidine isothiocyanate [GCN]
chaotopic salt system that strongly denatures RNases-no phenol
• RNA is precipitated with ethanol and bound to silica [Si-O-H],
washed, and eluted with water.
PROS
Easy to perform
No precipitation rxn
Very clean RNA
Can extract in RLT Buffer
DNase on the column
Compatible with FastPrep
sample
Compatible with Shedder column
CONS
Will not isolate MiRNA
Will not isolate RNA <200bp
Lower yield than Trizol
Lipids can interfere and inhibit
Poor storage integrity at -80
Abrasives can end up in final
Heavy DNA contamination –bad
[neutrophils, PMN]
Salts may be left behind
Silica Columns-how they work
Once water is introduced, the electrostatic bond is
“broken” and RNA is immediately released back into the
“polar” water
Silica Column-based Applications [RNeasy]…continued
Multiple applications of the same elution water increases yield
Be sure not to “spin-out” your DNase before adding RW1
Do not spin with column with cap “open” as described in directions
The final dry spin can be done for 3 minutes
Some columns allow a final rinse with 80% ETOH to reduce salt
carryover- Ask your tech support
260/280 ratios are often above 2.00
Can add 0.5ul of Superase™ to collection tube if imparitive-Under
special circumstances
If using MinElute or MicroElute columns-be aware of the o-ring-it catches and
retains liquid that can get into your final sample
Extracting RNA
Extracting RNA from Tissue- Types of homogenization
• Traditional mortor and pestle with LN2
• Liquid Nitrogen is not always RNase-free
• Difficult to make sterile and RNase-free
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Poly-tron with new tips or RNase-free blades
• Not optimized for very small quantities
• Sometimes difficult to make RNase-free
• Mini motorized pestle
• With or without abrasive
• All RNase-free disposable
• Impactor [bio-pulverizer]
• French Press
• Biomasher columns
Extracting RNA from Tissue- Types of homogenization
• FastPrep System and Mini-bead beater
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Automated, fast, RNase-free
Uses screw cap 2ml tubes, 15ml and 50ml and
optional abrasive for homogenizing tough tissue
Excellent for bacterial extractions
Beware:
Some beads are silica-based and can bind nucleic acids in the presence of binding
buffers
Quality Control of RNA
Quality Control of RNA
• Consider running an RNase-free gel
– Look for gDNA
– Look for rRNA bands
• We use the E-gel routinely
– Fast, RNase-free agarose gel
Quality Control of RNA
• Measuring your RNA on the Nanodrop
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Good RNA
RNA prep
with mostly
gDNA from
Neutrophils
Look carefully at the trace!
Can not distinguish DNA from RNA
Can not distinguish degraded RNA from “good” RNA
Quantitative interferences can lead to questionable downstream
results
Quality Control of RNA
Good vs Degraded RNA
Thing are not always as they appear- These look great on the nanodrop… but….
are they?
Quality Control of RNA ….expected yield?
• Expected yield is very important!!!
We see apx 500
ng of RNA per
1mg of tissue
• Just getting “enough” RNA is not always ok
• Actively growing mammalian cells contain 1-10 pg/cell
• Calculate your expected RNA recovery
• If you are way below your expected yield than….
– Selectively recovered RNA from weak or apoptotic cells
– Selectively recovered RNA from G0 or G2M
***Will significantly impact gene expression data***
Problematic Nanodrop Traces
Sample is NOT 183 ng/ul most likely much less
272 nm peak is skewing data
260
272
How will this affect
downstream processes
such as RT-qPCR if
one assumes equal
RNA input to a cDNA
reaction?
Marlboro 2007….the fun has just begun
How do you use this thing?....
Oh, no…where’s my RNA?
Sites that have participated:
Marlboro College
St. Michael’s College
Johnson State College
Middlebury College
Green Mountain College
Norwich University
Castleton State College
Lyndon State College
University of Vermont