Publication:
Andolfatto,P.;
Davison,D.; Erezyilmaz,D.; Hu,T.T.; Mast,J.; Sunayama-Morita,T.; Stern,D.L.
¿Multiplexed Shotgun Genotyping for Rapid and Efficient Genetic Mapping¿, Genome
Research, 2011, 21, 610-617.
Initial Markets
Discovery Research - Identification of new genes involved in
biological processes
Scientists and companies routinely perform forward genetic screens
to identify new genes involved in biological processes. This has historically
proven to be the most powerful method to identify genes in biological pathways
in all of the genetic model systems, including viruses, bacteria, yeast,
nematodes, fruit flies, fish, and mice. In recent years, scientists and
companies have moved away from these experiments, because identification of the
causal mutations can be extremely time consuming and expensive. We have
demonstrated that MSG can be used to rapidly map a genetic mutation to high
resolution. This information on the genomic location of the mutation can be
combined with whole genome resequencing, which is now available at reasonable
cost for essentially all model systems, to directly identify the mutation
isolated in a genetic screen. Applying MSG together with whole-genome
re-sequencing would save researchers months (at least) of work and considerable
expense. There is a large existing market of researchers who would be willing
and able to pay for this service to accelerate their discovery research. In
addition, we believe that many researchers would return to these screens if they
had an easy means of identifying the mutations. A service to identify these
mutations would therefore create a larger market than already
exists.
Selective Breeding Programs - Identification of introgressed
regions
The second market includes plant and animal breeders (including
major agriculture companies) and
researchers who are developing new breeds of animals and plants through
selective breeding. Selective breeding is a politically palatable alternative to
the creation of genetically modified organisms (GMO), and is therefore likely to
become an increasingly important source of the world¿s agricultural animal and
plant breeds. Selective breeding involves the introduction of favorable traits
from one strain into a second strain through an extensive series of genetic
crosses, called introgression. One major hurdle to introgression experiments is
to identify which individuals have inherited the targeted genome regions. A
second major difficulty, which rarely is addressed directly in these projects,
is to identify unwanted regions that have been accidentally introgressed, which
might lead to the introduction of unwanted traits along with the desired traits.
MSG provides an efficient method to solve both problems in a single experiment,
because MSG identifies all introgressed regions.
Commercialization Strategy
To serve the immediate needs of the two near term market
opportunities in Selective Breeding and Discovery Research we envision a start
up that could initially be run with minimal personnel (as few as three people),
to process approximately 2-3 samples per week. As demand increased, greater
throughput could be gained by purchasing liquid handling robots and in the
hiring of qualified technicians.
The entire service contemplated lends itself to automation. Many of these
steps are currently performed in our laboratory with liquid handling robots.
Estimated start up needs are estimated to be between $500,000 and $1.1M
depending on the use of alternative computing facilities and access to HTS
sequencing machines. Lower estimates of the start-up costs are based on the use
of cloud computing for data storage and the outsourcing of sequencing needs.
Patent protection is pending.
The
Inventors
David Stern,
PhD
Professor Stern is
an HHMI Investigator and Professor of Ecology and Evolutionary Biology at
Princeton University. His current
research is focused on the genetic causes of natural variation in appearance and
behavior. His laboratory is developing new genotyping and phenotyping assays,
and new genetic tools to accelerate discovery of the genes that have led to the
evolution of new species.
Peter Andolfatto, PhD
Professor
Andolfatto is Assistant
Professor of Ecology and Evolutionary Biology and the Lewis-Sigler Institute for
Integrative Genomics. His current research is focused on a broad range of topics
in Evolutionary Genetics and combines genomics, experimental manipulations and
computational population genetics approaches, primarily using Drosophila as a
model system.
Contact:
Laurie
Tzodikov
Princeton
University Office of Technology Licensing
¿ (609) 258-7256¿ tzodikov@princeton.edu
PU
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