Download Microarray Analysis & Functional Genomics

yes no Was this document useful for you?
   Thank you for your participation!

* Your assessment is very important for improving the work of artificial intelligence, which forms the content of this project

Document related concepts

Quantitative trait locus wikipedia, lookup

Genomics wikipedia, lookup

Transposable element wikipedia, lookup

Copy-number variation wikipedia, lookup

Oncogenomics wikipedia, lookup

Cancer epigenetics wikipedia, lookup

NEDD9 wikipedia, lookup

Pathogenomics wikipedia, lookup

Non-coding RNA wikipedia, lookup

Non-coding DNA wikipedia, lookup

RNA interference wikipedia, lookup

Primary transcript wikipedia, lookup

Epitranscriptome wikipedia, lookup

Epigenetics in learning and memory wikipedia, lookup

X-inactivation wikipedia, lookup

Genetic engineering wikipedia, lookup

Gene therapy of the human retina wikipedia, lookup

RNA silencing wikipedia, lookup

Polycomb Group Proteins and Cancer wikipedia, lookup

Gene therapy wikipedia, lookup

Epigenetics of neurodegenerative diseases wikipedia, lookup

Minimal genome wikipedia, lookup

Vectors in gene therapy wikipedia, lookup

Public health genomics wikipedia, lookup

Long non-coding RNA wikipedia, lookup

Gene desert wikipedia, lookup

Gene nomenclature wikipedia, lookup

Mir-92 microRNA precursor family wikipedia, lookup

Epigenetics of diabetes Type 2 wikipedia, lookup

Ridge (biology) wikipedia, lookup

Biology and consumer behaviour wikipedia, lookup

Helitron (biology) wikipedia, lookup

Genome evolution wikipedia, lookup

History of genetic engineering wikipedia, lookup

Genomic imprinting wikipedia, lookup

Genome (book) wikipedia, lookup

Site-specific recombinase technology wikipedia, lookup

Gene wikipedia, lookup

Nutriepigenomics wikipedia, lookup

Therapeutic gene modulation wikipedia, lookup

Epigenetics of human development wikipedia, lookup

Gene expression programming wikipedia, lookup

Microevolution wikipedia, lookup

Designer baby wikipedia, lookup

Artificial gene synthesis wikipedia, lookup

RNA-Seq wikipedia, lookup

Gene expression profiling wikipedia, lookup

Functional Genomics in
Evolutionary Research
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.
Spotted cDNA ~ 200 bp
Oligo = 25 to 60 bp
Why Is Microarray Technology Important?
From NSF Program Announcement: Environmental Genomics
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.
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)
Sources of Variation in Microarray Experiments
Technical (Bad)
(1) Experimental Treatments
(1) RNA quality
(2) Individual variance... may or
may not be good
(2) Dye biases
(3) Nonspecific hybridization
Paralogs of gene families
(3) Stochasticity during scanning,
image processing
(5) Errors during probe synthesis or
(6) Stochasticity in labeling targets
What gene expression changes are
associated with the evolution of
Example Design
(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.
Metamorphic Life Cycle
R x x x x
x x x x
R x x x x
x x x x
Paedomorphic Life Cycle
(3) Quantify relative expression
of each gene across all DNA chips.
(2 life cycles x 3 tissues x 14
(7)Verify results by rt-PCR and
analyze candidates in thyroid
hormone-induced paedomorphs.
(6) Compare gene expression
profiles among life cycles and
tissues to identify differentially
expressed genes.
(4) Model gene expression to determine
how genes are expressed temporally
within life cycle cycles for each tissue.
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
Liu et al. 2005... From the Stromberg Group
here at UK
Principal Component
Heat maps
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