Purdue team develops fast-track process for genetic improvement of plant traits
Web-based tool for plant biologists to discover regulators for their trait-of-interest
Kranthi Varala, and 9 co-authors from HLA, published the details of the new web-based regulatory gene discovery tool in the Proceedings of the National Academy of Sciences. Varala has a patent pending on the results that relate to economically important seed oil biosynthesis. The research team, which includes two post-docs, three graduate students, and three undergraduate researchers from HLA, built a resource that learns from large amounts of publicly available data to quickly identify what transcription factors regulate a given trait-of-interest. The team used a computational method called the inference approach to predict what transcription factors were going to regulate the seed oil biosynthesis process in Arabidopsis. The approach found eight previously known and five new transcription factors that regulate seed oil, an unprecedented success rate for a prediction tool. The resource is now available to the broader plant community for gene discovery and validation, thanks to an intuitive web interface built by our very own data science expert, Kirby Kalbaugh.
Authors: Rajeev Ranjan, Sonali Srijan, Somaiah Balekuttira, Tina Agarwal, Melissa Ramey, Madison Dobbins, Rachel Kuhn, Xiaojin Wang, Karen Hudson, Ying Li and Kranthi Varala
This research was supported by the U.S. Department of Energy Office of Science.