1. Functional Genomics in Evolutionary Research

2. What Is Microarray Technology?
High throughput method for measuring simultaneously, mRNA abundances for thousands of genes.
Thousands of probes or features
adhered to a solid substrate at
known x,y coordinates.
Probes:
Spotted cDNA ~ 200 bp
Oligo = 25 to 60 bp

3. Why Is Microarray Technology Important?
From NSF Program Announcement: Environmental Genomics

4. How Do Microarrays Work?
Hybridization Technique
- RNA targets isolated from a cell line or tissue of interest are labeled and hybridized to the probes.
- Label intensity at a given location on the substrate correlates with the amount of target for a given mRNA (gene) present in the sample.
Differentially expressed Genes:
Identified statistically (e.g. t-test)
by comparing control vs experimental.

5. The Burden of Multiple Testing
A given microarray may have over 40,000 probes!!!
This means that you may run as many as 40,000 statistical tests.
If you reject a null hypothesis when P < 0.05, then 5% of the time you are rejecting true null hypotheses.
If you run 40,000 tests, then by chance alone you will reject ~ 40,000 x 0.05 = 2000 true null hypotheses (i.e., you will have ~ 2000 false positives)

6. Sources of Variation in Microarray Experiments
Biological
(1) Experimental Treatments
(2) Individual variance... may or may not be good
(3) Nonspecific hybridization
Paralogs of gene families
Technical (Bad)
(1) RNA quality
(2) Dye biases
(3) Stochasticity during scanning, image processing
(5) Errors during probe synthesis or deposition
(6) Stochasticity in labeling targets

7. What gene expression changes are associated with the evolution of paedomorphosis?
Example Design
Larval
Adult
Metamorphosis
R x x x x
x x x x
x x x x x x
(1) Sample tissue from 15 time
points (x), including an early
reference (R) time point.
(2) Compare expression for
each time point and the reference
on a DNA chip.
Metamorphosis?
Metamorphic Life Cycle
Paedomorphic Life Cycle
(3) Quantify relative expression
of each gene across all DNA chips.
(2 life cycles x 3 tissues x 14 timepoints)
(4) Model gene expression to determine
how genes are expressed temporally within life cycle cycles for each tissue.
(6) Compare gene expression
profiles among life cycles and
tissues to identify differentially
expressed genes.
(7)Verify results by rt-PCR and
analyze candidates in thyroid
hormone-induced paedomorphs.

8. Visualization & Categorization
Can be done for genes and/or arrays... Options Include a variety of multivariate and pattern matching techniques including the methodologies listed below
Quadratic Regression
Principal Component Analysis
ClusteringHeat maps
Liu et al From the Stromberg Group
here at UK

9. Gene Ontology & Biological Relevance
Microarray datasets can be overwhelming because they contain A LOT of information
Even experts on a system can be overwhelmed by the number of genes that are differentially regulated in some experiments
Having a standardized nomenclature that places a gene into one or more biological contexts can be invaluable for functional grouping (previous grouping techniques were irrespective of biological information)
Gene Ontology is a standardized hierarchical nomenclature that classifies genes under three broad categories