CoPIs: Dong Wang, Aaron Lorenz, Ashok Samal(University of Nebraska), Argelia Lorence (Arkansas State University)
Collaborators: Mark Tester (Australian Centre for Plant Functional Genomics), Abdelbagi Ismail (International Rice Research Institute, The Philippines), Susan McCouch (Cornell University)
Salinity is one of the major environmental limitations for irrigated agriculture with yield losses estimated to exceed $12 billion dollars annually. Only 17% of agriculture is under irrigation, yet it provides a third of the global food supply. Rice is arguably the most important crop for global food security, but is also the most salt-sensitive among staple cereals. The extent of genetic variation for salt tolerance in rice is largely unknown and under-utilized. This project aims to fill this knowledge gap by utilizing newly developed genomic resources in combination with recent advances in high-throughput image-based phenotyping to elucidate the underlying genetic basis of adaptive responses to salinity stress. This project will provide genome-level information that will link genes and pathways associated with physiological responses associated with salinity tolerance in rice. Knowledge derived from this work will ultimately inform breeders as to which alleles present in the vast genetic diversity of germplasm banks can be introduced into elite cultivars for salt tolerance. This comprehensive study of physiological impact of salt stress in rice will be broadly useful for other cereals such as wheat and maize. Both the biological knowledge and the methodologies used and refined during the course of data analysis will be valuable for large-scale biology projects that have significant phenomics and genomics components.
Sequence data will be deposited at the NCBI and Gramene. Phenotypic, sequence, and GWAS data will be available via the project website. Image analysis software and scripts will be available upon request. Investigators will develop multidisciplinary active learning modules for undergraduate students in Plant Physiology and Image Analysis courses at the University of Nebraska and at summer workshops for graduate students and predominantly minority undergraduates at Arkansas State University. Development of instructional material based on the research in this project will be broadly useful in both traditional and online learning environments. Six students and postdoctoral scientists will be trained in multidisciplinary research at the intersection of plant physiology, quantitative genetics, bioinformatics and image informatics. Training students in phenomics will fill a void as high-throughput phenotyping is increasingly deployed in industry but not yet available at most public institutions for research and training.
