Gene Expression Data Analyses (1)

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Gene Expression Data Analyses (1)
Trupti Joshi Computer Science Department 317
Engineering Building North E-mail
joshitr_at_missouri.edu 573-884-3528(O)
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Lecture Schedule for Gene Expression Analyses

• Concept of microarray and experimental design for
  DNA microarray (9/6/05)
• Data transformation and normalization for DNA
  microarray (9/8/05)
• Statistical analysis for DNA microarray and
  Software comparison (9/13/05)
• Clustering Techniques for DNA microarray (Dr.
  Dong Xu 9/15/05)

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Lecture Outline

• Central Dogma of Molecular Biology
• Introduction to Gene Expression and Microarray
• Experimental Design

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Lecture Outline

• Central Dogma of Molecular Biology
• Introduction to Gene Expression and Microarray
• Experimental Design

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Central Dogma of Molecular Biology
Gene Expression
mRNA level
Protein level
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Lecture Outline

• Central Dogma of Molecular Biology
• Introduction to Gene Expression and Microarray
• Experimental Design

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Introduction Gene Expression

• Same DNA in all cells, but only a few percent
  common
• genes expressed (house-keeping genes).
• A few examples
• (1) Specialized cell over-represented hemoglobin
  in blood cells.
• (2) Different stages of life cycle hemoglobins
  before and after
• birth, caterpillar and butterfly.
• (3) Different environments microbial in nutrient
  poor or rich
• environment.
• (4) Diversity of life.

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Microarray is about gene expression.

• All information about living being is coded in
  DNA as a set of genes.
• Each gene contains structural information about
  protein sequence and regulatory information about
  protein expression.
• Intermediate step between gene and protein is
  mRNA.
• The concentration of mRNA is measured by
  microarray.

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Problem

• RNA levels and protein levels are not always
  directly correlated.
• No mRNA no protein Relation is not simple and
  not universal.
• Functional genomics fill the gap between gene
  expression and organism function.
• The meaning of life is hidden in gene expression
  value but it is not easy to get it out.

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Eucaryote Gene Expression Control
nucleus
cytosol
inactive mRNA
mRNA degradation control
Primary RNA transcript
DNA
mRNA
mRNA
RNA transport control
translation control
transcriptional control
RNA processing control
protein
protein activity control
nucleus membrane
Microarray ? mRNAMass-spec ? protein
inactive protein
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Principle of DNA Microarray

• Complimentary hybridizationis the basis of RNA
  measurement.
• Base-pairing rules
• DNA A-T and G-C
• RNA A-U, G-C, G-U

A--T G--C T--A C--G
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Microarray Technology

• Macroarray sample spot sizes gt 300 microns
• Microarray typically lt 200 microns
• biochip, DNA chip, DNA microarray, gene array,
  genome array, gene chip

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Initial Ideas of DNA Microarray
Immunoassay
Ekins, R. and F. W. Chu. Microarrays their
origins and applications. Trends in Biotech. 17
217-218
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Application of DNA Microarray Technology

• Gene discovery
• Biological mechanisms (gene regulatory network,
  etc.)
• Disease diagnosis (cancer, infectious disease,
  etc.)
• Drug discovery Pharmacogenomics
• Toxicological research Toxicogenomics
• Microbial diversity in the environment

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Increasing Microarray Applications
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Advantages and Disadvantages of Micoarray

• Advantages
• High-throughput
• Analyze gene expressions of different cells or
  from cells under different condition
  simultaneously
• Disadvantages
• High noise
• Relatively high cost

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Categories of DNA Microarray

• Probe based
• cDNA microarray cDNA (5005,000 bases) as probe.
  10,000-20,000 spots/slide.
• Oligo microarray (Affimetrix Microarray)
  oligonucleotide (2080-mer oligos) as probe.
  200,000-500,000 spots/slide.
• Dye based
• Double label. For example, Cy3 and Cy5.
• One sample is labeled with a green dye and the
  other with red.
• Relative fluorescent intensity of red and green
  from the same spot.
• Single label.
• All samples are labeled with one color.
• Absolute fluorescent intensity between different
  slides.
• Does not control for the amount of DNA in each
  spot.

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Chips

• Typically a glass slide with
• cDNA or oligo
• Printed by robot or
• synthesized by photo-lithography.
• Typical arrays are 25x75
• mm. Contains up to 500,000
  probed gene fragments.

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Probe Layout on Chips

• Positive control
• Genome DNA
• House keeping genes
• Negative control
• Spots with cDNA from very different species
• Blank spots
• Spots with buffer
• Samples
• Technical replicates

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Microarray Procedures
Experimental Design
Data interpretation
RNA extraction cDNA prepration
Statistical analysis
Data transformation and Normalization
Image Analysis
cDNA labeling
Sample mixing
Scanning
Hybridization
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Molecular Interaction on microarray

• 1 molecule per square angstroms
• Large molecules are easily to be folded
• by themselves
• Short targets are better than large
• targets to interact with tethered oligos
• Ideally, target and probe should have
• the same length
• Molecules interaction are dynamic
• Competitive hybridization

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Lecture Outline

• Central Dogma of Molecular Biology
• Introduction to Gene Expression and Microarray
• Experimental Design

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Experimental Protocol

• A. Synthesis of cDNA
• 
  
• Synthesis of the second strand DNA
• B. Labeling
• C. Hybridization
• D. Scanning

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Rational for Experimental Design

• Scientific constrains
• Scientific aims and their priorities
• Physical constrains
• Number of slides
• Amount of mRNA
• Goal of an optimal design Minimize costs from
  money, time
• Maximize the useful information

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Issues for Experimental Design

• Scientific
• Specific questions and their priorities.
• Practical (logistic)
• Types of mRNA samples reference, control,
  treatment.
• Amount of material available (mRNA, slides,
  dyes).
• Other factors
• The experimental process before hybridization
  sample isolation, mRNA extraction, amplification,
  and labeling.
• Controls planned positive, negative, ratio, and
  so on.
• Verification method northern blot, reverse
  transcriptase (RT)-PCR, in situ hybridization,
  and so on.

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Variability and Replicates

• Gene expression level for one gene in different
  slides may not be the same
• Replicates
• Technical replicates the target mRNA is from the
  same pool (RNA extraction)
• Reduce variability
• Biological replicates the target mRNA is from
  different individual extraction.
• Obtain averages of independent data
• Validate generalizations of conclusions
• Variation within technical replicates are smaller
  than that within Biological replicates

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Importance of Replicates
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Graphical Representation of Design
Cy5 red
Cy3 green
Cy3Cy5 blue

• Use directed graphs
• Node sample
• Edge hybridization, use Cy3 ?Cy5
• Weight replicates

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Direct Indirect Comparison

• Compared objectives T and C
• Directive design TC are on the same slide
• Indirect design TR and CR are on the same
  slides, respectively. But T and C are on
  different slides

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Variance Std Deviation

• Variance
• The most common statistical measure of
  variability of a random quantity or random sample
  about its mean. Its scale is the square of the
  scale of the random quantity or sample.
• Standard Deviation
• Standard deviation is the square root of the
  variance.  It measures the spread of a set of
  observations. The larger the standard deviation
  is, the more spread out the observations are.

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Variance for Indirect Design

• For sample T and C
• Differential Expression
• Direct design
• Indirect design

a and ß are means of log intensities across
slides for a typical gene.
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Dye-swapped Replication
Dye-swapped replications
Two sets of replications

• Two hybridizations for two mRNA samples are on
  the two slides, but dye swapped. For example, Cy3
  for A and Cy5 for the first hybridization (slide
  1), then C5 for A and Cy3 for the second
  hybridization (slide 2).
• Advantage reduce systematic bias (e.g. dye bias)

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Reference Design
It may not be feasible to perform direct design
when experimental conditions are more than 3.
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Factors in the design

• Single factor
• Two factors
• Multiple factors

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Single Factor Experiments
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Time-course Experiments
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2x2 factorial experiments
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Lecture Outline

• Central Dogma of Molecular Biology
• Introduction to Microarray
• Application
• Advantage vs. Disadvantage
• Chips
• Microarray procedure
• Experimental design
• Rational
• Variability and Replication
• Graphical representation
• Direct comparison and Indirect comparison
• Dye swap
• Reference design
• Single-factor design
• Multifactorial design

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Reading Assignments

• Suggested reading
• Yang, YH and T. Speed. 2002. Design issues for
  cDNA microarray experiments. Nature Reviews, 3
  579-588.
• Statistical analysis of gene expression
  microarray data. Chapter 2. pp. 35-92.
  ChapmanHall/CRC Press, 2003.