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Gene Expression. Christina Azodi, Lexi Bloom, Martine Stewart & Hope Yu Middlebury College : Bioinformatics and Genomics : May 3 rd 2011. POPs Microarrays . Part I: Software Comparisons. Bioconductor BRB Array NIA Array. 1. Bioconductor. Reads Affymetrix data from CEL files

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gene expression
Gene Expression

Christina Azodi, Lexi Bloom, Martine Stewart & Hope Yu

Middlebury College : Bioinformatics and Genomics : May 3rd 2011

POPs Microarrays

part i software comparisons
Part I: Software Comparisons
  • Bioconductor
  • BRB Array
  • NIA Array
1 bioconductor
1. Bioconductor
  • Reads Affymetrix data from CEL files
  • Upload data and normalize the intensity values
  • Very powerful tool- R packages exist to run 100s of different types of analysis
  • Our main difficulty: beginner programmers!
2 brb array
2. BRB Array
  • Uses Excel as the front end
  • The analytic and visualization tools are developed in R, C, Fortran and Java
  • Visual Basic for Applications integrates the components and hides the complexity
  • Normalize and summarize with GC-RMA

3. NIA Array

  • Initial Motivation
    • Trying another approach
    • No programs to download
    • Ability to analyze data stored in .txt files

- The Hochstenbach set

    • Ability to run Principal Component Analysis

3. NIA Array: Basic Use

  • Obtain microarray data from NCBI GEO
    • Save in tab-delimited format
  • Upload the data matrix
  • Upload the probe matrix
  • Choose parameters
  • Fill in known information
  • Run

3. NIA Array: Basic Use

  • Obtain microarray data from NCBI GEO
    • Save in tab-delimited format
  • Upload the data matrix
  • Upload the probe matrix
  • Choose parameters
  • Fill in known information
  • Run

3. NIA Array: Basic Use

  • Obtain microarray data from NCBI GEO
    • Save in tab-delimited format
  • Upload the data matrix
  • Upload the probe matrix
  • Choose parameters
  • Fill in known information
  • Run

3. NIA Array: Challenges

  • Running 2-color arrays
    • Data available from NCBI GEO is already normalized to subtract out control levels
    • NIA Array requires non-normalized data (ie: hybridization values for both control and experimental) to be able to run 2-color arrays
    • Consequence: we were unable to retest the Hochstenbach gene set (which is 2-color)
  • Requires specific manipulation of input data format
    • Including specific knowledge of array type and experimental design—can be difficult to find

3. NIA Array: Perl to manipulate .txt

  • Goal: strip out the word “sample” from the text file (many times—tedious by hand)
  • Used
    • open (INPUT, $file) and open (OUTPUT, $fixedfile) to read the input file and write to the output file
    • $line=~ s/sample 1/ /g to replace “sample 1” with a blank space
  • This program could be manipulated to be useful for relabeling other data sets

3. NIA Array: Capabilities

  • Provides output of significantly up- and down-regulated genes
  • Scatter plots
  • Principal Component Analysis

3. NIA Array: Principal Component Analysis

  • Concept
    • Reduce the dimensionality of the data without compromising variation
      • Makes data easier to visualize graphically
    • Reduces output to a more manageable size
part ii a study of two pops
Part II: A Study of Two POPs
  • PCB & Dioxin
  • Disclaimers
  • Our Expression Results
persistent organic pollutants pops
Persistent Organic Pollutants (POPs)
  • Organic chemical substances
  • Survive in the environment for long periods of time
  • Travel throughout the environment
  • Bioaccumulate
  • Toxic to humans and many ecosystems
  • Specific effects:
    • Cancer
    • Allergies
    • Damage to the nervous systems
    • Reproductive disorders
    • Damage to the immune system

pops of interest
POPs of Interest
  • Polychlorinated biphenyls (PCBs):
  • Dioxin (TCDD):

hochstenbach et al 2010
Hochstenbach et al., 2010
  • Whole-genome gene expression using microarray techniques
    • Human Peripheral Blood Mononuclear Cells (PBMCs)
  • Identified 48 genes that distinguish between immunotoxic and nonimmunotoxic chemicals.

Our criteria:

  • Fold change in gene expression >2 in at least two sample sets
  • Fold change in gene expression >8 in any of the sample sets
  • P<0.005 as determined by class comparison

*venn diagrams made at

Hochstenbach et al.criteria:

  • Fold change in gene expression >1.5 or <0.67
  • Fold change in gene expression >1.5 or <0.67 in three of five donors
  • P<0.001 in a t-test of experimental vs. control
tools used in brb array
Tools used in BRB Array


  • In ArrayTools, generated scatterplots with fold change limits at 2 and again at 8
  • Generated a list of both up- and down-regulated genes
tools used in brb array1
Tools used in BRB Array

Finding significant differences in expression:

  • In ArrayTools, select class comparisons between groups of arrays
  • Generates a table of genes whose expressions are significantly different across sample groups as determined by the p-value limit (we used p<0.005)
  • Generates a table with log-transformed gene expressions for significant genes across all sample groups
  • Generates a heatmap to illustrate the differences between control and experimental conditions for all significant genes
  • Limited to studies available through NCBI GEO
    • Arrays were done by different labs
    • Variation in concentration and exposure time
    • Dioxin (TCDD)
    • PCBs (77, 126, 153 and Arclor)
  • Limited in our knowledge of the system
results brb array
Results: BRB Array
  • FN1 was differentially regulated in 4 of our studies- two PCB & 2 dioxin
  • ATF3 was differentially expressed in Hoch, H Hep w/ PCB and in Martine's study
  • Frequently differentially expressed in our studies, but not included in Hochstenbach's top 38: CYP1A1, CYP1a2, CYP1B1, Aldh3a1, Aldh1a7, Ugt1a6
  • Lots of similarities between the female Rats treated with Arclor and TCDD
results brb array1
Results: BRB Array

Results: BRB Array

  • Fibronectin1 (FN1)
    • High MWT glycoprotein
    • Located in plasma and at the cell surface (ECM)
  • Functions in cell adhesion and migration processes
  • 450 KDa dimer
    • Composed of repeating structural motifs: FN-I,II,III
    • FN-III10 mediates cell adhesion via an integrin-binding motif

immune response role of integrins in nk cells cytotoxicity
Immune Response: Role of integrins in NK cells cytotoxicity
  • NK cells are lymphocytes that destroy infected cells
  • Integrins are adhesion receptors that function in NK cell migration and adhesion of NK to target cells
    • ICAM1, ICAM2, ICAM3, FN1, and VCAM1 are all common ligands for integrins
  • Other genes to highlight:
    • ATF3&5 were upregulated
    • SOS1&2 were upregulated
    • ICAM1&3 were upregulated
    • IL-8 was downregulated
  • Transcription of FN1 may be affected by POPs and is thus downregulated so that the immune system cannot destroy infected cells
  • ICAM1 is most likely upregulated during the natural immune response in preparation to clear the body of cells infected with POPs
  • IL-8 is upregulated naturally during the inflammatory response, but found that it was downregulated in our gene set
  • ATF3 may be involved in the inhibition of some genes in the pathway
  • Microarray analysis software can be incredibly powerful, however can only get out how much you can put in
  • Limited in:
    • Programming knowledge
    • Biological system background
  • Possibilities for analysis are endless