Microarrays
A snapshot that captures the activity
pattern of thousands of genes at once.
Custom spotted arrays
Affymetrix GeneChip
Microarray Process
Practical Applications of Microarrays
Gene Target Discovery
By allowing scientists to compare diseased cells with normal cells, arrays can
be used to discover sets of genes that play key roles in diseases. Genes that
are either overexpressed or underexpressed in the diseased cells often
present excellent targets for therapeutic drugs.
Pharmacology and Toxicology
Arrays can provide a highly sensitive indicator of a drug’s activity
(pharmacology) and toxicity (toxicology) in cell culture or test animals.
This information can then be used to screen or optimize drug candidates
prior to launching costly clinical trials.
Diagnostics
Array technology can be used to diagnose clinical conditions by detecting
gene expression patterns associated with disease states in either biopsy
samples or peripheral blood cells.
Microarray Platforms
•Oligonucleotide-based arrays
•25mers spotted on a glass wafer, Affymetrix
GeneChip arrays
•Custom spotted 50-80mers generated from
known sequences.
•cDNA
•Inserts from cDNA libraries
•PCR products generated from gene specific or
universal primers
GeneChip Instrument System
®
Fluidics
Station
Scanner made by
Hewlett-Packard
Computer
Workstation
GeneChip Probe Array
®
GeneChip Probe Arrays
®
GeneChip Probe Array
Hybridized Probe Cell
Single stranded, fluorescently
labeled DNA target
Oligonucleotide probe
1.28cm
*
*
*
*
*
24µm
Each probe cell or feature contains
millions of copies of a specific
oligonucleotide probe
Over 250,000 different probes
complementary to genetic
information of interest
Image of Hybridized Probe Array
Synthesis of Ordered
Oligonucleotide Arrays
Light
(deprotection)
Mask
OOOOO
TTOOO
HO HO O O O
T–
Substrate
Light
(deprotection)
Mask
CATAT
AGCTG
TTCCG
TTCCO
TTOOO
C–
Substrate
REPEAT
Probe Tiling Strategy
Gene Expression
(25-mer)
Gene Expression
Tiling Strategy
[
]
[
]
[
[
Uninduced
]
]
[
]
[
]
Induced
40 separate hybridization events are involved in
determining the presence or absence of a transcript
80 separate hybridization events are involved determining
differential gene expression of a transcript between two
samples
Starting material for Microarrays
Platform
Affymetrix
Poly (A)+ mRNA
Total RNA
~2 mg
~10 mg
Spotted arrays
Poly (A) +
Total RNA
~0.4 – 2 mg
10 -100 mg
Experimental Design
Biotin - labeled
cRNA transcript
Cells
B
+
Poly (A)
RNA
Or
Total RNA
IVT
cDNA
Biotin-UTP
Biotin-CTP
B
B
B
B
B
B
Fragment
heat, Mg2+
B
Hybridize
B
B
B
B
Wash & Stain
Scan
(8 minutes)
(75 minutes)
(16 hours)
Biotin - labeled cRNA
fragments
Add Oligo B2 &
Staggered Spike
Controls
Normalization and Scaling
Non-biological factors can contribute to the variability of data
in many biological assays, therefore it is important to minimize
the non-biological differences. Factors that may contribute to
variation include:
•Amount and quality of target hybridized to array
•Amount of stain applied
•Experimental variables
The data can be normalized from:
•a limited group of probe sets
•all probe sets
Thus the normalization of the array is multiplied by a
Normalization Factor (NF) to make its Average Intensity
equivalent to the Average Intensity of the baseline array.
Normalization and Scaling
Average intensity of an array is calculated by averaging all
the Average Difference values of every probe set on the array,
excluding the highest 2% and lowest 2% of the values.
Data Processing:
•Analytical Spreadsheet can Handle Millions of Rows
or Columns
•Scaling & Normalization (e.g. standardize, log-scale,
log & linear scale, power)
•Sort rows by Value or by Similarity to Prototype (find
genes most similar to
specified prototype)
•Missing Data Handling (e.g. analysis, casewise
deletion, imputation)
Cluster and Tree View
Microarray Process
Products used for spotting
Easy-To-Spot™ Products (Incyte Genomics)
•Every clone is sequence-verified prior to PCR
• PCR products are purified to remove excess salts,
unincorporated nucleotides, primers, and particulates
• Quality controlled production process with failure rate1 of less
than 10%
• 8,734 PCR products from sequenced-verified clones from the
UniGene database from NCBI, average length is greater than
500 nucleotides
•Between 1-3 ug of DNA per well. Enough to fabricate 500 to 1,000
arrays
• Corresponding clones available for purchase for further research
Indirect labeling
Simple, highly sensitive technique
requires less starting RNA, and
creates evenly labeled DNA
without dye bias.
•Uniform incorporation of
fluorescent dyes produces more
reliable signals
•High sensitivity to detect lowcopy signals
•Requires only 10 to 20 µg of
total RNA or 0.4 to 1 µg of polyA
RNA
Clontech
Atlas™ Glass Fluorescent Labeling Kit
Stratagene
FairPlay™ Microarray Labeling Kit
Array Ready Oligo set
(Operon Technologies)
Complete Yeast Genome Oligo Set
• Optimized 70-mer oligonucleotides for each of the 6,307 open reading
frames (ORFs) of Saccharomyces cerevisiae from the Saccharomyces
Genome Database (SGD) at Stanford University
•The amount of sample provided with each set is sufficient to print
between 2000 and 6000 slides, depending on the printing procedure
used.
Human Genome Oligo Set
•This Array-Ready Oligo Set™ contains arrayable 70-mers
representing 13,971 well-characterized human genes from the
UniGene database. This database is located at the National Center
for Biotechnology Information.
•All 70-mer oligonucleotides in the Human Genome Oligo Set were
designed from the representative sequences in the UniGene
database, Hs build #119. The set also contains 29 controls.
GeneMachine Omni Grid Arrayer
Printing Pin
Axon GenePix4000A Scanner
• 10mm pixel size
• Simultaneously scans array
slides at two wavelengths
• User-selectable laser power
• User-selectable focus poisitions
GenePix Pro Features
• Auto Align
Before Auto Align
After Auto Align
GenePix Pro Features
•Feature Viewer
P = pixel intensity
F = feature intensity
B = background intensity
Rp = ratio of pixel intensities
Rm = ratio of means
mR = median of ratios
rR = regression ratio
GenePix Pro Features
•Feature Pixel Plot
GenePix Pro Features
•Histogram
GenePix Pro Features
•Scatter Plot
Spotted glass slide microarrays
Advantages
Low cost per array
Custom gene selection
Any species
Competitive hybridization
Open architecture
Disadvantages
Clone management
Clone cost
Quality control
Affymetrix GeneChip system
Advantages
Stream line production
Large number of genes and ESTs/chip
Several number of species
Disadvantages
System cost
GeneChip cost
Propietary system
Limits on customizing
GeneCards Database
Challenges in analyzing Microarray Data
•Amount of DNA in spot is not consistant
•Spot contamination
•cDNA may not be proportional to that in the tissue
•Low hybridization quality
•Measurement errors
•Spliced variants
•Outliers
•Data are high-dimensional “multi-variant”
•Biological signal may be subtle, complex, non linear,
and buried in a cloud of noise
•Normalization
•Comparison across multiple arrays, time points, tissues,
treatments
•How do you reveal biological relationships among genes?
•How do you distinguish real effect from artifact?
Factors to consider in designing
microarray experiments
•Need to do lots of control experiments-validate method
•Do replicate spotting, replicate chips, and reverse labeling
for custom spotted chips
•Do pilot studies before doing “mega chip” experiments
•Don’t design experiment without replication; nothing will
be learned from a single failed experiment
•Design simple (one-two factor) experiments,
i.e. treatment vs. untreatment
•Understand measurement errors
•In designing Databases; they are useful ONLY if quality
of data is assured
•Involve statistical colleagues in the design stages of your studies
Once you have identified an interesting
expression pattern, what comes next?
•With some arrays it is possible to purchase clones of interest for
further experimentation.
•Confirm that the particular clone you now have in your hand shows
the expression pattern so indicated by the array, quantitating
individual mRNA species.
•RT-PCR, Relative, quantitative RT-PCR uses an internal
standard to monitor each reaction and allow comparisons
between different reactions to be made.
• Competitive RT-PCR --a competition between a known amount
of a template and an unknown target.
•Northern analysis