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Microarrays for Gene Expression Analysis

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Title: Microarrays for Gene Expression Analysis


1
Microarrays for Gene Expression Analysis
Questions What genes are expressed in this
tissue under these conditions? What genes are
expressed in my treated cells versus the
control? What genes are expressed during the
phases of the cell cycle? What genes are
expressed in diseased tissue versus normal
tissue?
2
Microarrays other uses
Questions What point mutations exist and what
bases are located at the substitution
positions? What bases are substituted where
there are multiple mutations very close
together? Which allele of this gene do we
have? Is this the mutant or wildtype?
3
Goals
Finding Co-Regulated Genes Understanding Gene
Regulatory Networks
4
Expressed Genes mRNA
DNA
messenger RNA
protein
5
Expressed Genes Currently Transcribed
Extract RNA
Isolate mRNAs
mRNA
mRNA
mRNA
mRNA
mRNA
6
Affymetrix Oriented
  • Fluorescently tagged cRNA
  • One chip per sample
  • One for control
  • One for each experiment
  • Other methods include two dyes/one chip
  • Red dye
  • Green dye
  • Control and experiment on same chip

7
Creating Targets
PCR Amplification of DNA
In Vitro transcription to create cRNA
8
RNA-DNA Hybridization
Targets RNA
probe sets DNA (25 base oligonucleotides of known
sequence)
9
Non-Hybridized Targets are Washed Away
Targets (fluorescently tagged)
probe sets (oligos)
Non-bound ones are washed away
10
Picture of Gene Chip
11
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12
Handling Chip
13
570nm
Argon laser 488nm
Scanner based on epifluorescence confocal
microscopy
14
Custom Chips vs Affy Chips
  • Affy chips contains thousands of gene probes
  • Genes selected from sources such as GenBank
  • Custom chips can be designed for individual
  • investigators
  • Few genes, but more copies of each
  • Done on microscope slide

15
Example Affy Chips
  • Rat Toxicology Chip - gt850 genes
  • CYP450s, Heat Shock proteins
  • Drug transporters
  • Stress-activated kinases
  • Rat Neurobiology chip - gt 1,200 genes
  • Synuclein 1, prion protein, Huntingtons
    disease
  • Syntaxin, Neurexin, neurotransmitters

16
Example Affy Chips
  • Arabidopsis Genome Chip
  • Murine Genome Chip - gt36,000 genes
  • E. coli Genome Chip - gt4,200 ORFs
  • Drosophila Genome Chip - gt13,500 sequences
  • Yeast Genome Chip - gt6,400 ORFs
  • Human Genome Chip - gtgt60,000 human genes

17
Definitions
Probe a single-stranded DNA oligonucleotide
complementary to a specific sequence. Each probe
cell consists of millions of probe
molecules. Probe Array a collection of probes
sets. Probe Set a set of probes designed to
detect one transcript. 16-20 probe pairs. A 20
probe pair set is made up of 20 PM and 20 MM for
a total of 40 probe cells. Probe Pair Two probe
cells, a PM and its corresponding MM. Perfect
Match(PM) probes that are designed to be
complementary to the reference sequence. MisMatch(
PM) probes that are designed to be
complementary to the reference sequence except
for 1 base. Target sequence from your sample.
18
GeneChip Hierarchy
Probe Array Chip Probe Set 16-20 probe
pairs(to detect particular gene) Probe Pair
Probe Cell (MisMatch) 20 Probe Cell (Perfect
Match) 20 Probes lt 25 bases (millions of
copies) Pixels 24 sq. um
19
probe cell
probe pair
Probe Array (chip)
20
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21
Probe a single-stranded DNA oligonucleotide
complementary to a specific sequence. Each probe
cell consists of millions of the same probe
molecules. The intensity of each cell is an
average of each of its scanned pixels.
Pixel 3 24 um
Probe Cell 20 - 50 micrometers
22
Affymetrix Tiling Strategies
  • Standard
  • Alternative
  • Block
  • Expression

23
Affymetrix Standard Tiling
  • Purpose detection of mutations and polymorphisms
    and determination of which base is at a certain
    position.
  • Probes are arranged in sets of 4.
  • Each probe in a set of 4 has one of 4 bases at
    the substitution position.
  • Compares the four target-to-probe hybrid
    intensities in each set to identify the base in
    the substitution position.

24
Affymetrix Standard Tiling
25
Affymetrix AlternativeTiling
  • Purpose determination of base where multiple
    mutations are close together as opposed to a
    single point mutation.
  • Probes are arranged in sets of 5.
  • Includes a single base deletion at substitution
    point.
  • Compares the four target-to-probe hybrid
    intensities in each set to identify the base in
    the substitution position.

26
Affymetrix Alternative Tiling
27
Affymetrix Block Tiling
  • Purpose determination of genotype wildtype or
    mutant. Determines which allele is present.
  • Probes are arranged in sets of 5.
  • Includes a single base deletion at substitution
    point.
  • Compares the four target-to-probe hybrid
    intensities in each set to identify the base in
    the substitution position.

28
Affymetrix Block Tiling
M S
-2
-1
1
2
29
Affymetrix Expression Tiling
  • Purpose measure the relative abundance of
    various mRNAs.
  • A set of probe pairs for each mRNA
  • PM perfect match
  • MM mismatch by one base
  • Software compares the hybridization intensities
    of the PM to those of the MM to determine the
    absolute or difference call for each probe set.

30
Affymetrix Expression Tiling
TARGET ACGGATG
PM ACGGATG
MM ACAGATG
31
Data Analysis for Gene Expression
.cel file (pixel readings)
.dat file (average intensities, etc. are
calculated)
.chp file (parameters are calculated)
data mining, statistical analysis
32
Raw Data to Cooked Data
of pixels
Intensity
Probe cell Avg Intensity
33
Raw Data to Cooked Data
  1. Calculate the Average Intensity of every probe
    cell
  2. Calculate the background
  3. Subtract the background
  4. Calculate the Noise (pixel-to-pixel variation
    within a probe cell)
  5. Determine numbers of Positive and Negative probe
    pairsfor every probe set.
  6. Positive Probe Pair PM intensity gt MM intensity
  7. Negative Probe Pair MM intensity gt PM intensity
  8. Calculate Positive Fraction
  9. Calculate Pos/Neg Ratio
  10. Calculate Log Average Ratio Avg Difference

34
Absolute Analysis Parameters
  • Probe Set Name
  • Positive - number of pairs scored positive
  • Negative number of pairs scored negative
  • Pairs number of probe pairs for a probe set
  • Pairs Used those not masked for some reason
  • PairsInAvg excludes those with extremely
    intense or weak scores

35
Absolute Analysis Parameters
  • PM Excess have exceeded limit for intensity
  • MM Excess have exceeded limit for intensity
  • Avg Diff average difference of fluorescence
    intensity between the PM and MM cells.
  • Log Avg Ratio a measure of the hybridization
    performance
  • Higher better
  • Log Avg 0 indicates random cross
    hybridization
  • Pos/Neg ratio of positive probe pairs to
    negative probe pairs
  • Positive Fraction positive probe pairs/probe
    pairs
  • Abs Call Present, Absent or Marginal. Is this
    gene present in this sample?

36
Raw Data to Cooked Data
Positive Fraction Pos/Neg Ratio Log Avg
Ratio
Decision Matrix
Absolute Call (Present, Absent, Marginal)
37
Data Analysis
Absolute Analysis used to determine whether
transcripts represented on the probe array are
detected or not within one sample(uses data from
one probe array experiment). Comparison Analysis
used to determine the relative change in
abundance for each transcript between a baseline
and an experimental sample(uses data from two
probe array experiments). Intensities for each
experiment are compared to a baseline/control.
38
Approaches
  • What genes are Present/Absent in my tissue?
  • 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 based
    on my knowledge of the biological system under
    investigation?

39
Approaches to Data Analysis
Database Queries
Graphical Analysis Statistical Analysis
Biological Knowledge
40
Set Filter Parameters
Adjust filter parameters
Query
Pivot
Scatter/Fold Graph
Select Points
Add probe sets to filter
Bar Graph
Identify interesting relationships
41
Data Analysis
Absolute Analysis used to determine whether
transcripts represented on the probe array are
detected or not within one sample(uses data from
one probe array experiment). Comparison Analysis
used to determine the relative change in
abundance for each transcript between a baseline
and an experimental sample(uses data from two
probe array experiments). Intensities for each
experiment are compared to a baseline/control.
42
Comparison Analysis Parameters
  • Inc number of probe pairs that increased
  • Dec number of probe pairs that decreased
  • Inc Ratio
  • Dec Ratio
  • Max Inc Dec Ratio
  • Pos Change
  • Neg Change
  • Inc/Dec
  • DPos-DNeg Ratio
  • Log Avg Ratio Change
  • Diff Call did this gene increase or decrease?
  • Increase, Marginal Increase, Decrease,
    Marginal Decrease,
  • No Change

43
Comparison Analysis Parameters(continued)
  • Avg Diff Change how much did the difference
    between PM and MM change from the control to the
    treated?(Avg Dif Exp Avg Dif Control)
  • BA was this gene present in the control?
  • Fold Change how many times more expression did
    the treated have compared to the control?
    (positive or negative)
  • Sort Score a ranking based fold change and avg
    diff change

44
Data Analysis
Filter/Query Select those oligos which have
shown a real,significant change.
45
Filter Sort to Find Real Changes
Avg. Difference Change gt 200
and FoldChange gt 3 and INC gt 70 and
DEC 0
46
Query Results
47
Query Results
Probe1 Probe2 Probe3 Exp1 1 4
9 Exp2 3 6 8
48
Pivot the Query Results
  • Experiments columns
  • Genes Rows
  • Shows how genes change across experiments

49
Pivot Results
Exp1 Exp2 Probe1 1 3 Probe2
4 6 Probe3 9 8
50
Pivoted Data Can be sorted by any parameter.
Sort in descending order to show greatest
differences.
51
Description of gene
Link to NCBI
52
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53
Graphical Analyses
Scatter Plot Graph requires Control vs Experiment
54
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55
Fold Change Graphs
How many times did the expression of this gene
change in the treated tissue versus the control?
56
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Statistical Techniques
59
Statistical Techniques
  • Self-Organizing Maps
  • Correlation Coefficient Clustering
  • Analysis Function
  • Matrix

60
Self-Organizing Maps
  • Clustering
  • Automatically discovering classes

61
Self-Organizing Maps

62
Self-Organizing Maps

Genes whose expression level rise/fall
together under the same conditions, cluster
together Co-regulated ?
63
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65
Statistical Techniques
  • Average
  • Standard Deviation
  • Median
  • T-test parametric comparison of means.
  • assumes a normal distribution
  • Mann-Whitney for the comparison of two samples
  • non-parametric
  • no assumption about underlying distribution

66
Is there any difference in the expression pattern
for Exp1 Versus the expression pattern for
Exp2? A Mann-Whitney (non-parametric comparison)
can help answer such questions.
Exp1 Exp2 Probe1 1 3 Probe2 4
6 Probe3 9 8
67
Uses of Expression Analysis
  • hypothesis generation
  • hypothesis testing
  • need for replication

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Microarray DBs on the Web
http//www.biologie.ens.fr/en/genetiqu/puces/bdden
g.html
70
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Free SOM Software http//rana.lbl.gov/EisenSoftwa
re.htm
74
Contacts
Brad Yoder 934-0994 Li Hong Teng
934-0995 Aubrey Hill 934-4069 www.affymetrix
.com Michael Eisen Lab at Lawrence-Berkley Labs
http//rana.lbl.gov/ Stanford MicroArray
Database http//genome-www4.stanford.edu/MicroArr
ay/SMD/ Review of Currently Available Microarray
Software http//www.the-scientist.com/yr2001/apr/
profile1_010430.html
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