This action funds an NSF National Plant Genome Initiative Postdoctoral Research Fellowship in Biology for FY 2013. The fellowship supports a research and training plan in a host laboratory for the Fellow who also presents a plan to broaden participation in biology. The title of the research and training plan for this fellowship to James C Schnable is "A Comparative Genomics Approach to Studying C4 Photosynthesis" The host institution for the fellowship is the Donald Danforth Plant Science Center and the sponsoring scientist is Dr. Thomas Brutnell.
Plants create chemical energy in the form of sugars using sunlight, carbon dioxide, and water. While this process (photosynthesis) is responsible for supplying the vast majority of energy used by life on earth, it is also remarkably inefficient. C4 photosynthesis brings together a number of structural and biochemical innovations to allow plants to more efficiently capture carbon dioxide, making plants more productive while at the same time increasing the efficiency with which they use water and nitrogen. C4 photosynthesis has arisen independently in different families of plants including multiple independent origins in the grass family. This project will identify genes and regulatory sequences co-opted into the regulation of C4 photosynthesis. Data on sequence conservation, gene expression patterns, and epigenetic modifications will be generated from multiple grass species representing independent origins of C4 photosynthesis as well as a closely related non-C4 grass species. Candidate genes and regulatory approaches identified using in silico approaches will be experimentally validated in the model C4 grass species Setaria virdis.
Training objectives include plant genetics, comparative genomics, epigenomics, and analysis of novel next generation sequencing datasets. Broader impacts include capacity-building and advanced training for students from the United States to engage in interdisciplinary research in plant improvement and associated sciences such as physiology, quantitative genetics, and computational biology. In addition, comparative genomics/transcriptomics visualization tools will be developed that may be employed in studying other novel traits emerging in multiple species, as well as interspecies datasets which will aid in the study of other divergent traits among grass crop species.
