We have used a machine learning approach to identify 100 novel genes in Arabidopsis, which our analysis suggests are involved in seed development. This set of genes is being evaluated for addition to our patent portfolio by the NYU Office of Industrial Liaison. The current NYU patent portfolio on plant genes from the lab of the PI is the basis for a set of commercial licensing agreements with two major US agricultural companies working on trees, corn, alfalfa and other crop species.
We have received continuous funding from the Biotechnology Research and Development Corporation (BRDC), a consortium of industries, to develop new plant promoters, and methodologies to improve plant transformation. We have obtained 8 patents, and applied for several others that are pending.
Identified a soybean cyst nematode inducible promoter (patent 7,223,901)
A co-dominant marker was developed for pungency that has been licensed to industry breeding programs.
A segregating population has been developed for mapping that has also been licensed for private use.
Licensed genetic stocks to Syngenta and DuPont/Pioneer
My program has provided marker assisted selection services to the following private wheat breeding companies: WestBred, Resource Seed, Inc., and Arizona Plant Breeders. Two of these companies are releasing cultivars in 2007 developed with the help of our marker assisted selection services.
The computational tools and resources are documented at gene.genetics.uga.edu and www.fgsc.net. These websites are used to keep track of requests for software, data, and laboratory resources. Requests from companies include Pfizer, Bristol-Myers-Squib, Millenium Pharmaceuticals, MycoPharmaceuticals, Novozyme, Paradigm Genetics. Additionally, many academic labs have requested our tools.
The funding resulted in material transfer agreements between the Regents of the University of California and Mendel Biotech
Commercial versions of our spliced alignment software are distributed by NewLink Genetics (http://www.linkp.com/) and licensed to several big agro companies.
Released open source software (TASSEL) that implements association mapping algorithms have helped companies get these to run in environments. It has been used by researcher’s at all major seed companies.
An experimental line that carries the two G. soja resistance QTL was released.