In this collaborative project with the Rhee lab (MSU) and the Maeda lab (UWM), we integrate bioinformatics, biochemistry, and plant genomics to advance plant metabolism annotations for thousands of plant species and transform long-standing enzyme function prediction challenges by combining targeted, high-throughput experimental characterization of unidentified enzymes with an established computational inference pipeline.
Advances in omics technologies have created a vast gap between observational data and insights about how organisms work in nature. Gene function annotations and biological pathway frameworks such as genome-scale metabolic network reconstructions are essential components in bridging this gap. Our research will employ state-of-the-art computational techniques to annotate metabolic enzymes and pathways for all sequenced plant genomes. Additionally, we plan to initiate an experimentation-based enzyme function consortium with two leading scientists in plant enzyme family characterizations. This proof-of-concept, if successful, could be expanded to accelerate gene function discovery and transform the genomics field.
If you would like to read more:
- Hawkins C, Xue B, Yasmin F, Wyatt G, Zerbe P, Rhee SY (2025) Plant Metabolic Network 16: expansion of underrepresented plant groups and experimentally supported enzyme data. Nucleic Acids Res. 53:D1606-D1613. [Link]
This research has been generously supported by:
