SNP Genotyping
A large portion of the research in our lab focuses on understanding
how sequence variation in the human genome predisposes to disease.
Single nucleotide polymorphisms (SNPs), the most common form of
sequence variation, occur frequently throughout the human genome,
and the DNA sequence of any two humans differs in more than 3 million
positions. While a large number of these variants may have no discernible
function, we are exploring whether some of these SNPs are associated
with increased risk for disorders in humans. Furthermore, research
focuses on the evolution of these SNPs, and their relationship to
each other.
All of this work depends on the availability of robust, dependable,
and affordable method to interrogate these SNPs in large numbers
of DNA samples. Most currently available SNP genotyping methods
provide reliability, and, to some extent, the ability for high-throughput
operation. However, most of them are still relatively expensive
since they require initial PCR amplification of the sample DNA prior
to genotyping, and thus not suitable in their current format for
large-scale or even genome-wide SNP association studies.
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Figure 1:
Schematic of the Invader Assay
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In our lab, we have used extensively the Invader® Assay for
analyzing genetic variation. The method has been developed by Third
Wave Technologies (TWT), a biotech firm based in Madison, WI. In
collaboration with researchers at the company, we have used the
technology in our ongoing research projects, and are in the process
of testing modifications to the commercially available platform
to reduce cost and improve throughput and usefulness for large-scale
studies. While the assay can be used on genomic DNA, it requires
relative large amounts (~30ng per genotype) which is not feasible
for most studies using valuable patient DNA.
As part of our technology development efforts, we are working on
a microarray-based SNP genotyping platform that would permit the
efficient and rapid analysis of large numbers of DNA samples directly
from small amounts of genomic DNA without prior PCR amplification.
The platform uses novel surface chemistry in conjunction with existing
Invader® technology. Miniaturization and the elimination of
PCR would significantly reduce the overall cost of SNP genotyping.
Collaborators: |
Martin Hessner (MCW) |
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Bruce Neri (TWT, Madison, WI) |
Expression Analysis
A large number of tools are available for the analysis of individual
or global gene expression levels. Chip- or microarray-based approaches
allow the interrogation of large numbers of genes in parallel. Alternatively,
real-time PCR-based methods allow the accurate quantification of
expression levels of individual genes.
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Figure 2:
Real-time Invader Assay. Fluorescent signal intensity is plotted
against time for different concentrations of PCR amplicons.
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While all methods work reliably at detecting two-fold or larger
differences in mRNA levels between samples, it is difficult to reliably
detect small concentration differences (<10%) with any of the
existing technologies. However, polygenic disorders may develop
due to small changes in gene expression levels for a number of genes,
resulting in a disorder that develops later in life. Testing this
hypothesis would depend on technology that would permit the reliable
and accurate quantification of transcript levels from different
samples.
In our lab, we are applying both real-time PCR technology (Taqman,
CyberGreen assays) and novel real-time Invader® technology to
samples to assess the limitation and variability of these approaches.
In collaboration with Third Wave Technologies, we have applied their
technology to the quantification of cDNA, and are currently testing
the minimally detectable quantity differences.
Collaborators: |
Marilyn Olsson (TWT, Madison, WI) |
Proteomics
As part of the MCW Proteomics Center (http://proteomics.mcw.edu),
we are focusing on aspects in our laboratory:
1.) development of improved methods for isolation of proteins from
cells
2.) novel approaches for protein separation and fractionation in
preparation for analysis by mass spectrometry
3.) development of protocols for use of new mass spectrometry and
microfluidics technologies
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Figure 3:
Schematic of New (Hypothetical) Mass Spectrometry Instrument.
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Technology development is closely linked to our collaborators at
UW Madison (Dr. L. Smith, Dr. M. Westphall), at Oak Ridge National
Laboratory (Dr. M Ramsey), and at Perbio Sciences AB (Dr. W. Qoronfleh).
Protocols and methods as well as results of our analysis will be
distributed through the center website. Currently, efforts are focusing
on the development of traditional protein quantification approaches
(ELISA) for a number of proteins known to affect angiogenesis. These
assays will be used to generate quantitative data against which
we will test any new mass spectrometry technology.
Collaborators: |
Walid Qoronfleh (Pierce Milwaukee) |
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Mike Ramsey (Oak Ridge National Laboratory) |
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Lloyd Smith (UW Madison) |
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Mike Westphall (UW Madison) |
Analysis Software Tools
a) Sequence Management Pipeline
In collaboration with the Bioinformatics Research Center and other
faculty members at the HMGC, we have developed a web-based tool
that allows the efficient management of sequence data for SNP discovery.
The tool allows the design of PCR primers for re-sequencing of large
genomic regions and handles the data management and archiving of
the resulting sequence data. A public link can be found at http://xeres.brc.mcw.edu/smp-bin/smp_interface.cgi.
Collaborators: |
Uli Broeckel (MCW) |
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Anne Kwitek (MCW) |
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Jeff Nie (MCW) |
b) Clustering Algorithm
Most SNP genotyping methods record fluorescent signal intensities
for two separate colors for the two alleles of a SNP. The resulting
data can be represented in a scatter plot, and the data points fall
into four distinct groups:
1. samples with little fluorescence for either color (negative controls
and failed reactions)
2. samples with signal for only dye 1
3. samples with signal for only dye 2
4. samples with intense signal for both dyes (heterozygous samples)
Traditionally, most researchers have assigned the genotypes visually
by identifying the data points belonging clearly to each of the
four groups. Data points that do not fall clearly into one group
usually are discarded.
We have developed a statistical tool that assigns cluster memberships
(i.e. genotypes) automatically, and calculates relative probabilities
(i.e. confidence scores) for each genotype assignment. The algorithm
is based on mathematical clustering approaches, and is superior
to traditional k-means clustering. The algorithm has been successfully
tested with Taqman data and Invader assay results, but can be used
for any method that generates distinguishable signals of varying
intensity for the two alleles.
The algorithm will be available as a web-based tool soon.
Collaborators: Jason von Bergen (MCW) Henk Neefs (Palo Alto, CA)
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Figure 4:
Cluster Algorithm User Interface.
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c) Linkage Disequilibrium and Haplotype Analysis
Research in human genetics over the past few years has focused
on understanding the linkage disequilibrium and haplotype patterns
across large regions of the human genome. Several parameters have
been proposed to calculate pairwise linkage disequilibrium, and
numerous approaches have been proposed to determine resulting haplotype
“blocks”.
We are trying to develop tools that not only automate the analysis
of linkage disequilibrium and haplotype patterns, but also visualize
the results in a meaningful way for biomedical researchers. Efforts
are under way to link these tools directly with haplotype inference
algorithms and tools for association analysis as an advanced tools
for studies of complex human disorders.
Collaborators: |
Simon Twigger (MCW) |
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Tao Wang (MCW) |
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Xujing Wang (MCW) |
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