MICROARRAYS and FUNCTIONAL GENOMICS

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MICROARRAYSand FUNCTIONAL GENOMICS
SAMIR
ELLEN
HSUAN
MIKE
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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

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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.

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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

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Central Dogma

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

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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.

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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.

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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

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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

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How Microarrays Work

• Reverse Transcription
• Hybridization
• Heat.
• Strands melt at 65 C.
• Cool down.

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Hybridization
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Microarray Terminology

• Oligonucleotides (oligos)
• Probes
• Target
• Dyes

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Microarray Types

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

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cDNA Microarrays
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A flow chart of the process
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RGB Overlay of Cy3 and Cy5
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Q1 Who invented the first cDNA microarray?

• The Pat Brown Lab did!

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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.

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Q2 When should I use cDNA microarrays for my
experiment?

• http//www.ncbi.nlm.nih.gov/About/primer/microarra
  ys.html

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When should I use cDNA microarrays for my
experiment?
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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.

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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.

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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.

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Q3 What probes are available?

• Actually you can put whatever you want!

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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

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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.

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Q4 How much will it cost to use cDNA microarrays
in my experiment?

• Using cDNAs is Relatively cheap!

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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

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Q5 How small can my samples be?

• Often the case is you need more sample than you
  think.

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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.

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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)

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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!)

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Q7 How are cDNA microarray experiments designed?

• A three layer experimental design proposed by
  Churchill

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Churchill, Nature, 2002
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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.

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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

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Oligonucleotide Microarrays
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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

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Manufacturers

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

http//www.chem.agilent.com/Scripts/PDS.asp?lPage
3071
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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

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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

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Probe sets
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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

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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)

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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

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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

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Resulting Data
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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

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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.

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Open Challenges Recent News
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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

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Experimental Design

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

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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

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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

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Quality Assessment Normalization
Improved metrics, standardization of quality
metrics and normalization methods by experiment
design
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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
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Analysis Methods
Does clustering give the right answers? What
alternatives to clustering exist?
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Recently in the News

• Variation Detection, SNP Genotyping, Haplotype
  Blocks and Tagging SNPs
• Diagnostic Arrays
• Protein Arrays

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Detection of DNA Variation By Using DNA Chips
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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

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Detection of DNA Variation By Using DNA Chips
DNA sequence of Interest
DNA Synthesized on chip
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A C G T
DNA 1
Labeled DNA Hybridized to Chip
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DNA 2
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Genotype Determination of Individual Samples
Polymorphism
Polymorphism
Synthesized Oligonucleotides
Sense
Antisense
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SNP Genotyping Array
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GC
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G/C Polymorphism
cgtatcgtagaaGtctatgctaatg
alleleref A
cgtatcgtagaaCtctatgctaatg
allelealt B
-2,-1,0,1,2
SNP base position
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Pharmacogenomic studies
Drug Response responders vs. non-responders sid
e-effect vs. no side-effect
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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.
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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
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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

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Acknowledgements
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Questions?