Introduction to DNA Microarrays

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Introduction to DNA Microarrays

• Todd Lowe
• BME 88a
• March 11, 2003

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Topics

• Goal study many genes at once
• Major types of DNA microarray
• How to roll your own
• Designing the right experiment
• Many pretty spots Now what?
• Interpreting the data

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The Goal

• Big Picture biology
• What are all the components processes taking
  place in a cell?
• How do these components processes interact to
  sustain life?
• One approach What happens to the entire cell
  when one particular gene/process is perturbed?

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Genome Sequence Flood

• Typical results from initial analysis of a new
  genome by the best computational methods
• For 1/3 of the genes we have a good idea what
  they are doing (high similarity to exp. studied
  genes)
• For 1/3 of the genes, we have a guess at what
  they are doing (some similarity to previously
  seen genes)
• For 1/3 of genes, we have no idea what they are
  doing (no similarity to studied genes)

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Large Scale Approaches

• Geneticists used to study only one (or a few)
  genes at a time
• Now, thousands of identified genes to assign
  biological function to
• Microarrays allow massively parallel measurements
  in one experiment (3 orders of magnitude or
  greater)

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Several types of arrays

• Spotted DNA arrays
• Developed by Pat Browns lab at Stanford
• PCR products of full-length genes (gt100nt)
• Affymetrix gene chips
• Photolithography technology from computer
  industry allows building many 25-mers
• Ink-jet microarrays from Agilent
• 25-60-mers printed directly on glass slides
• Flexible, rapid, but expensive

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Basis The Southern Blot

• Basic DNA detection technique that has been used
  for over 30 years, known as Southern blots
• A known strand of DNA is deposited on a solid
  support (i.e. nitocellulose paper)
• An unknown mixed bag of DNA is labelled
  (radioactive or flourescent)
• Unknown DNA solution allowed to mix with known
  DNA (attached to nitro paper), then excess
  solution washed off
• If a copy of known DNA occurs in unknown
  sample, it will stick (hybridize), and labeled
  DNA will be detected on photographic film

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Spotting Robot Demo
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Massive Increase in Measurements

• Most commonly, 5-50 samples can be tested in each
  traditional Southern experiment
• Affymetrix chips have gt250,000 oligos per chip
  (multiple oligos per gene)
• Microarray spotters are high-precision robots
  with metal pins that dip into DNA solution tap
  down on glass slide (pins work like a fountain
  pen)
• Currently, 48,000 different DNA spots can fit on
  one glass microscope slide

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Pros/Cons of Different Technologies

• Spotted Arrays
• relative cheap to make (10 slide)
• flexible - spot anything you want
• Cheap so can repeat experiments many times
• highly variable spot deposition
• usually have to make your own
• Accuracy at extremes in range may be less

• Affy Gene Chips
• expensive (500 or more)
• limited types avail, no chance of specialized
  chips
• fewer repeated experiments usually
• more uniform DNA feaures
• Can buy off the shelf
• Dynamic range may be slightly better

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Types of Array Exp

• mRNA transcription analysis
• Single experiment (control v. experimental)
• Time course (multiple samples in same exp)
• Genomic DNA -- similarity of genomes
• Genetic Footprinting
• Species cross hybridization (existence of a
  specific pathway in a related species)

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An Array Experiment
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Yeast Genome Expression Array
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Image Analysis Data Visualization
Cy5 Cy3
log2
Cy3
Cy5
Experiments
8 4 2 fold 2 4 8
Underexpressed Overexpressed
Genes
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What do we want to know?

• Genes involved in a specific biological process
  (i.e. heat shock)
• Guilt by association - assumption that genes
  with same pattern of changes in expression are
  involved the same pathway
• Tumor classification - predict outcome /
  prescribe appropriate treatment based on
  clustering with known outcome tumors

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Developing New Methods

• How do you know when your method performs better
  than a previous method?
• A gold standard test set for benchmarking array
  data doesnt exist
• There is too much biology we dont know if a new
  method classifies a gene in the wrong gene
  group, is it recognizing new biology, or just
  getting it wrong??

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Limitations of Arrays

• Do not necessarily reflect true levels of
  proteins - protein levels are regulated by
  translation initiation degradation as well
• Generally, do not prove new biology - simply
  suggest genes involved in a process, a hypothesis
  that will require traditional experimental
  verification
• Expensive! 20-100K to make your own / buy
  enough to get publishable data

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Array Sequence Analysis

• Promoter motif extraction (Church/
• Cluster / classify genes with common response
  pattern
• Align upstream promoter regions (Gibbs sampler)
  or count over-represented X-mers
• Develop profile / motif from set search genome
  for new candidates w/ motif
• Return to array data, look for supporting
  evidence for new members
• Carry out experiment to support hypothesis