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Student Research
Symposium Oct 2006 |
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Validation of Mixed-Genome Microarrays as a Method for Genetic Discrimination Yan Wan1, Shira L. Broschat1,2, and Douglas R. Call2
1School of Electrical Engineering and Computer Science,2
Department of Veterinary Microbiology and Pathology, Washington State
University, Pullman,WA 99164Comparative genomic hybridizations have been
used to examine genetic relationships between bacteria. The microarrays used in
these experiments may have open reading frames from one or more reference
strains, or they may be composed of random DNA fragments from a large number of
strains (mixed-genome microarrays; MGM). Herein both experimental and virtual
arrays are analyzed to assess the validity of genetic inferences from these
experiments with a focus on MGMs. Empirical data is analyzed from an
Enterococcus
MGM while a virtual MGM is constructed
in silico
using sequenced genomes (Streptococcus).
On average a small MGM is capable of correctly deriving phylogenetic
relationships between seven species of
Enterococcus
with 100% (n=100 probes) and 95% (n=46 probes)
accuracy; more probes are required for intra-specific differentiation. Compared
to multilocus sequence methods and whole-genome microarrays, MGM provides
additional discrimination between closely related strains and offers the
possibility of identifying unique strain or lineage markers. Representational
bias can have mixed effects. Microarrays composed of probes from a single genome
can be used to derive phylogenetic relationships, although branch length can be
exaggerated for the reference strain. We describe a case where disproportional
representation of different strains used to construct an MGM can result in
inaccurate phylogenetic inferences and we illustrate an algorithm that is
capable of correcting for this type of bias. This bias-correction algorithm
automatically provides bootstrap confidence values, and can provide multiple
bias-corrected trees with a high confidence values.
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