Dr. Li has been developing an integrated experimental/biocomputational approach to identify the factors that regulate plant metabolism, with an emphasis on soybean seed composition and starch metabolism. Her research has focused on expanding the fundamental understanding of biological networks, in particular those that shift metabolism and thus alter composition. Her research strategy integrates systems-based experimental data (such as transcriptomic, metabolomic and proteomic data, protein-protein interaction, genomic sequences, and 3D structural information etc), to reveal the entirety of processes that makeup a biological network. The integration of such comprehensive datasets with genetic manipulations and bioinformatic analysis is revealing the structure and regulation of complex molecular interaction networks, which impact metabolic and signaling processes. This integrated strategy is identifying new gene functions and identifying innovative strategies on how to improve the performance of biological systems and solve problems in agriculture. One example of her research on the characterization of the Arabidopsis-specific QQS orphan gene and its interactor in regulation of carbon and nitrogen allocation illustrates this strategy, and provides a prototype of how to improve biological traits (developing a molecular tool to increase protein content in agronomic species), and how fundamental biotechnological research could bridge basic and applied research.
Regulation of Seed Composition