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MICROARRAYS and FUNCTIONAL GENOMICS

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Title: MICROARRAYS and FUNCTIONAL GENOMICS


1
MICROARRAYSand FUNCTIONAL GENOMICS
SAMIR
ELLEN
HSUAN
MIKE
2
Human Genome Project
  • By Dept of Energy and NIH and
  • Celera Genomics
  • Identified 30-40K protein coding
  • genes
  • Thousands of genes and their
  • activation levels -- observed by
  • microarrays

3
Functional Genomics
  • Goal
  • Only 50 of genes have known functions.
  • Interplay between sequence protein
  • environment.
  • Helps identify groups of genes and that
  • characterize a particular class of tumor by
    comparing diff. in gene expression of
  • Normal and Tumor cell.

4
Biological Concepts
  • What is a Gene?
  • What is Gene Expression (GE)?
  • Gene Expression level quantitative
  • description of Gene Expression by
  • measuring intermediary molecules
  • produced during protein synthesis

5
Central Dogma
  • The expression of the genetic information stored
    in the DNA molecule occurs in two stages

6
Biology
  • In simple words,
  • GE involves copying DNA code into
  • mRNA molecule. Thus, a measure of gene
    expression level is the abundance of mRNA
    produced.

7
Techniques to measure GE
  • 1) Northern and Southern Blots
  • Developed in 1977
  • Identify and locate mRNA and DNA
  • sequences that are complementary
  • to a segment of DNA
  • Small number of genes examined at
  • a time.

8
Techniques to measure GE (cont.)
  • 2) SAGE (Serial Analysis of Gene Expression)
  • Velculescu et al. (1995)
  • Short stretches of DNA uniquely identify
  • the genes expressed in a particular cell.
  • These are used to mark transcripts and
  • the no. of transcripts by each gene
  • determines the measure of GE.
  • Slow

9
Techniques to measure GE
  • 3) Microarrays
  • Developed in 1995
  • Simultaneous measurement of relative
  • expression level of a large number of genes.
  • Experimentation in parallel
  • Two important concepts
  • a) Reverse Transcription
  • b) Hybridization

10
How Microarrays Work
  • Reverse Transcription
  • Hybridization
  • Heat.
  • Strands melt at 65 C.
  • Cool down.

11
Hybridization
12
Microarray Terminology
  • Oligonucleotides (oligos)
  • Probes
  • Target
  • Dyes

13
Microarray Types
  • cDNA Technology Microarray (Stanford
  • Schena et al, 1995)
  • Synthetic Oligo-nucleotide Microarray (Affymetrix)

14
cDNA Microarrays
15
A flow chart of the process
16
RGB Overlay of Cy3 and Cy5
17
Q1 Who invented the first cDNA microarray?
  • The Pat Brown Lab did!

18
Who invented the first cDNA microarray?
  • Quantitative monitoring of gene expression
    patterns with a complementary DNA microarray
    (Schena et al., Science, 1995)
  • 45 genes of Arabidopsis were analyzed, and 2
    color fluorescence hybridization was used then.

19
Q2 When should I use cDNA microarrays for my
experiment?
  • http//www.ncbi.nlm.nih.gov/About/primer/microarra
    ys.html

20
When should I use cDNA microarrays for my
experiment?
21
Example 1 search for predictive markers of
papillary thyroid carcinoma
  • Yano et al., Clin Cancer Res. 2004 Mar
    1510(6)2035-43.
  • Gene expression profiles for PTC tissue, normal
    thyroid tissue, and healthy peripheral blood
    cells were compared by use of a human 4000-gene
    cDNA microarray.
  • Protein expressions of the up-regulated genes in
    PTC were examined in thyroid tissues by
    immunohistochemistry.

22
Example 1 (cont.)
  • Basic fibroblast growth factor, which has been
    identified as a biomarker for PTC, was
    overexpressed in 54 of PTC cases, 67 of
    follicular thyroid carcinomas, and 36 of benign
    thyroid neoplasms.
  • Platelet-derived growth factor was overexpressed
    in 81 of PTC cases and 100 of follicular
    carcinomas, but was immunonegative in normal
    thyroid tissues and benign thyroid neoplasms.

23
Example 2 analysis of endothelial cells in
response to green tea
  • Satippour et al., Int J Oncol. 2004
    Jul25(1)193-202.
  • HUVEC (human umbilical vein endothelial cells)
    were exposed in vitro to green tea for either 6
    or 48 h.
  • Result a global down-regulation of multiple
    genes involved in
  • Endothelial cell growth,
  • Signal transduction,
  • Oxidation,
  • Up-regulation of several apoptotic genes.

24
Q3 What probes are available?
  • Actually you can put whatever you want!

25
Probe selection
  • For organisms whose genomes have been completely
    sequenced, it is possible to array genomic DNA
    from every known gene or suspected open reading
    frame (ORF) in the organism.
  • The Pat Brown Lab has arrayed all known or
    suspected genes of S. cerevisciae (roughly 6100)
    on a single microarray.
  • Amplify clone inserts from human cDNA libraries.
  • Available arrays in U. Michigan
  • http//www.umich.edu/caparray/arrays.html
  • Available commercialized cDNA clones
  • http//www.openbiosystems.com/incyte_cdna_and_est_
    clones.php

26
Probe Selection
  • Usually selected from databases such as GenBank,
    dbEST, and UniGene.
  • You can choose either full-length cDNA, or
    partially sequenced cDNAs (or ESTs).
  • To avoid redundancy, UniGene is preferred.
  • UniGene is an experimental system for
    automatically partitioning GenBank sequences into
    a non-redundant set of gene-oriented clusters.
    Each UniGene cluster contains sequences that
    represent a unique gene, as well as related
    information such as the tissue types in which the
    gene has been expressed and map location.

27
Q4 How much will it cost to use cDNA microarrays
in my experiment?
  • Using cDNAs is Relatively cheap!

28
How much do cDNA microarrays cost?
  • About several hundred dollars per slide, but
    cheaper than Affymetrix arrays.
  • Pricing in NINDS NIMH Microarray Consortium
  • http//arrayconsortium.tgen.org/np2/public/service
    sPricing.jsp
  • Pricing in U. Miami microarray core facility
  • http//www.biomed.miami.edu/arrays/services_ma_pri
    cing.html

29
Q5 How small can my samples be?
  • Often the case is you need more sample than you
    think.

30
How small can my samples be?
  • According to a 1999 paper in Nature, 50 to 200
    ug of total RNA is required for one slide.

31
How small can my samples be?
  • mRNA accounts for only about 3 of all RNA in a
    cell. Usually, 10 ug of total RNA is the minimum
    requirement.
  • (Quantities as small as 1ug can be amplified
    first, but its unreasonable to expect perfectly
    uniform amplification.)
  • The requirement in U. Miami
  • Tissue 100 mgCell Culture 5 million
    cellsTotal RNA 100 ug or mRNA 400 ng
  • http//www.biomed.miami.edu/arrays/faq.html3
  • The amount of clinical sample is often very
    small.
  • Tumor tissue may not be homogeneous.
  • (These are my own experiences)

32
Q6 Where does the bias come from?
  • Biological variation
  • Non-biological sources of variation
  • Labeling efficiencies
  • Dye effects (checked by dye swapping)
  • Emission intensity is proportional to RNA
    concentration (by calibration)
  • Hybridization (Cross-hybridization)
  • Within array spot size, global background, local
    background
  • Between arrays spot run, PCR batch
  • The amount of RNA from the 2 samples are assumed
    to be equal. (Difficult to check!)

33
Q7 How are cDNA microarray experiments designed?
  • A three layer experimental design proposed by
    Churchill

34
Churchill, Nature, 2002
35
Conclusion of the features
  • Low specificity, high sensitivity.
  • Inter-experiment comparisons can be difficult,
    unless done on exactly same slide print batch.
  • Can have up to 50,000 cDNA per slide.
  • Highly customizable.
  • Dye swap doubles the cost of each data point.
  • Often some drop out of spots due to printing
    process and not all clones sequence-verified,
    causing tracking issues.

36
Useful web resources
  • Microarray data analysis
  • http//www.statsci.org/micrarra/
  • The Stanford microarray resources
  • http//genome-www5.stanford.edu/resources/
  • A flash animation
  • http//www.bio.davidson.edu/courses/genomics/chip/
    chip.html
  • Comparison of features of different types of
    arrays
  • http//arrayconsortium.tgen.org/np2/public/arrayPl
    atforms.jsp

37
Oligonucleotide Microarrays
38
Oligonucleotide Microarrays
  • Oligo refers to short, synthetic cDNA sequences
  • Sequences are placed on silicon chips using
    photolithographic technology (same as
    microprocessor fabrication)
  • Laser scanner produces image
  • SINGLE fluroescence

39
Manufacturers
  • Patented Affymetrix GeneChip
  • Agilent Printed Microarrays
  • Amersham Codelink System
  • Illumina, Nimblegen

http//www.chem.agilent.com/Scripts/PDS.asp?lPage
3071
40
Affymetrix GeneChip
  • Premanufactured
  • Range in Size
  • Lower 17000 (Murine Genome U74)
  • Higher 33000 (Human Genome U133)
  • Principle using a set of gene fragments
  • uniquely identifies specific gene
  • reduces the chance of random cross-hybridization

41
GeneChip details
  • 25-mers 25 bases per oligonucleotide probe
  • Probe set each gene represented by probe
    pairs (11-20 per gene)
  • Probe pair
  • PM Perfect match probe
  • MM Mismatch probe (13th homomeric base)
  • Non specific binding
  • Background noise
  • Each square probe cell contains millions of
    samples of a PM/MM probe
  • Probes are distributed to prevent systematic bias
  • Approximately 30,000 genes can be represented on
    1 cm2

42
Probe sets
43
Probe Selection
  • Good selection results in reliability,
    sensitivity, specificity
  • Computer models Experiments used
  • Hybridization conditions considered (pH,
    salinity, temperature)
  • Accounts for splicing and polyadenylation
    variants
  • Cross-hybridization potential considered

44
Oligo vs. cDNA technology
  • Pros
  • Spot quality / consistency
  • More information per gene (PM/MM, exon
    specificity)
  • Requires less total RNA (5 µg) due to less cross
    hybridization
  • More dynamic range (detects 1 in 106)
  • Less prone to systematic errors found in cDNA
    printing
  • Cons
  • Probe selection unavailable
  • Expense (400-600 / chip)

45
Pre-Hybridization Procedures
  • Total RNA is extracted
  • mRNA is reverse transcribed to cDNA
  • cDNA is made double stranded
  • Double stranded cDNA is denatured to cRNA and
    fluorescently labeled

46
Post hybridization procedures
  • Chip is washed and scanned
  • Laser scanner generates image
  • Image is gridded to identify probes in cells
  • Analysis extracts the signal intensity of each
    cell
  • Information from each set of probes is combined

47
Resulting Data
48
Resulting Data
  • Image DAT file 107 pixels or 50MB
  • Some groups are working on lossless compression
    (FDA regulations)
  • Quantification CEL file Cell intensities,
    probe level values
  • CDF file Chip Description file contains layout
    of GeneChip

49
Oligonucleotide Analysis
  • Chip contains recognizable features to help
    alignment
  • Important steps
  • Quantifying the results image processing
  • Finding meaning data analysis
  • Most expressions measures are based on PM-MM to
    correct for background and non-specific binding
  • MM can also carry a signal
  • Details on Algorithms and Analysis for will be
    discussed in detail at a later date.

50
Open Challenges Recent News
51
Open Challenges
  • For Analysts
  • Experimental Design and Probe Selection
  • Quality Assessment, Normalization, and Metric
    Selection
  • Validation
  • Differential and Survival Analysis
  • Does clustering provide the right answer?
  • For Lab Scientists and Engineers
  • Minimize Cost of Experiments
  • Minimize Time of Experiments
  • Minimize Cross-Hybridization

52
Experimental Design
  • Considerations
  • Budget
  • Number of Samples
  • Number and kind of replicates
  • Hypothesis Test or Generation
  • Analysis Method

53
Probe Selection
  • cDNA Arrays
  • Which genes to probe (UniGene)
  • Synthesized oligo probes are gaining
    popularity (length, /gene)
  • Oligonucleotide Arrays
  • Probe Selection has been evolving with each
    new array design
  • Goal is to improve specificity and sensitivity
    with the minimal number of probes used
  • This was recently addressed in a paper by L.
    Zhang, M. Miles, and K. Aldape that appeared as a
    letter in Nature Biotechnology

54
Probe Selection
  • Paper Summary . . . In one slide . . .
  • hybridization dependent on steric hindrance,
    probe-probe interaction, RNA secondary structure
    interactions.
  • Zhang et al present a nearest-neighbor based
    simple free energy model for the formation of
    RNA-DNA duplexes that includes the assignment of
    a nucleotide position specific weight (PDNN) and
    takes into account gene specific (GSB) and
    non-gene specific binding (NSB)
  • Conclusions
  • Quantification of NSB is critical for
    interpreting array data
  • Determination of GSB and NSB requires only PM
    probes
  • Probe Selection Criteria
  • i. Maximize GSB, minimize NSB

55
Quality Assessment Normalization
Improved metrics, standardization of quality
metrics and normalization methods by experiment
design
56
Survival Analysis
Analysis methods exist for studies where two
discrete conditions are being tested, how can one
continuous variable be tested using microarrays?
An example would be gene expression correlated to
life expectancy of cancer patients
57
Analysis Methods
Does clustering give the right answers? What
alternatives to clustering exist?
58
Recently in the News
  • Variation Detection, SNP Genotyping, Haplotype
    Blocks and Tagging SNPs
  • Diagnostic Arrays
  • Protein Arrays

59
Detection of DNA Variation By Using DNA Chips
60
Single Nucleotide Polymorphisms (SNPs)
  • Each variable base (SNP) results from a single
    error in DNA replication that occurred once in
    the history of mankind
  • Each SNP is characterized by only two bases
  • The more ancient the error, the more common the
    SNP
  • SNPs result in functional differences by altering
    the quality and/or the quantity of cellular
    proteins
  • DNA sequence comparison of any two copies of the
    human genome reveals only 0.1 sequence
    variability

61
Detection of DNA Variation By Using DNA Chips
DNA sequence of Interest
DNA Synthesized on chip
5
3
5
3
G
A
A
A
A
T
C
C
A
T
G
T
T
C
G
T
T
G
T
C
A
C
G
A
G
A C G T
DNA 1
Labeled DNA Hybridized to Chip
5
3
A
A
A
A
A
T
C
C
A
T
G
T
T
C
G
T
T
G
T
C
A
C
G
A
G
A C G T
DNA 2
62
Genotype Determination of Individual Samples
Polymorphism
Polymorphism
Synthesized Oligonucleotides
Sense
Antisense
5
3
5
3
63
SNP Genotyping Array
CC
GC
G
A
G
A
G
A
G
A
G
A
G
A
G
A
G
A
G
A
G
A
G
A
G
A
G
A
G
A
G
A
G
A
G
A
G
A
G
A
G
A
GG
T
C
T
C
T
C
T
C
T
C
T
C
T
C
T
C
T
C
T
C
T
C
T
C
T
C
T
C
T
C
T
C
T
C
T
C
T
C
T
C
G/C Polymorphism
cgtatcgtagaaGtctatgctaatg
alleleref A
cgtatcgtagaaCtctatgctaatg
allelealt B
-2,-1,0,1,2
SNP base position
64
Pharmacogenomic studies
Drug Response responders vs. non-responders sid
e-effect vs. no side-effect
65
Diagnostic Arrays
AmpliChip CYP450 (Roche Affymetrix) First
chip-based test approved for diagnostic use in
the European Union The test detects genetic
variations in the Cytochrome P450 2D6 and 2C19
genes and provides the associated predictive
phenotype (poor, intermediate, extensive, or
ultra-rapid metabolizer). Results can be used by
physicians as an aid for selecting drugs and
individualizing treatment doses for drugs
primarily metabolized by the enzymes these genes
encode.
66
Diagnostic Arrays
The AmpliChip CYP450 Test distinguishes 29 known
polymorphisms in the CYP2D6 gene, including gene
duplication and gene deletion, as well as two
major polymorphisms in the CYP2C19 gene.
Detection of these CYP2D6 polymorphisms results
in the identification of 33 unique alleles,
including seven CYP2D6 gene duplication alleles
67
Microarrays On Campus?
  • Many Labs on the USC campus use microarrays in
    their experiments, including
  • Aparicio Lab Replication fork firing
  • Arbeitman Lab Drosophila Sex Differentiation
  • Finkel Lab GASP and DNA eating in E. coli

68
Acknowledgements
69
Questions?
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