Project proposal

Project NSF documents

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Project summary

Medicago truncatula is a close relative of the world's most important forage legume, alfalfa (Medicago sativa), and is the subject of several major US genomics initiatives funded both federally through NSF, and privately through the Samuel Roberts Noble Foundation (SRNF). It is a rich source of natural products, such as flavonoids, isoflavonoids and triterpenes, which impact its properties as a forage legume. The main experimental approach of this project is to perturb the expression of these natural products, and other areas of metabolism, by exposing cell cultures to biotic and abiotic elicitors. Use of cell suspension cultures will allow sufficient material to be collected and analyzed in parallel. Three experimental conditions have been chosen that mimic natural environmental challenges: exposure to purified yeast elicitor, methyl jasmonate and UV light. The ultimate goal of this project is to generate a truly functional genomics data set for control and elicited cell cultures. Such data will encompass expressed sequence information and the associated mRNA, protein and metabolite identities and concentrations. Replicate induced and control cell samples will therefore be analyzed for: i) gene expression using DNA microarrays (linked to extensive M. truncatula EST databases at SRNF and from the NSF-funded Medicago genomics program); ii) protein expression patterns using two-dimensional gel electrophoresis and mass spectrometry (MALDI-TOF and Q-TOF); iii) changes in a range of primary and secondary metabolites by HPLC/MS and GC/MS analyses. The ability to compare information from all functional levels of gene expression in a homogeneous, inducible system, will lead to a synergistic leap in our understanding of the genetic programming of cellular metabolism.

Because this project will produce data from three hierarchical levels of functional gene expression, it becomes imperative to establish integrative models and software to facilitate relational analysis of the data to each other and to previous knowledge on sequences and pathways. Software is a facilitator of the discovery process when it enables the user to "navigate" the biological data in a dynamic and transparent way, requiring only the most basic computational skills. The bioinformatics component of this project will: i) construct a relational database to store all data; ii) construct an expandable analysis server that will facilitate processing the data with several statistical and numerical algorithms; and iii) integrate the above components through a web interface. The data as well as the software will be made available publicly.

The data generated by this project will be used to construct a quantitative predictive model of the time courses after elicitation, which is required to interpret the regulation of the underlying complex biological processes. The data will provide information about the extent and nature of gene expression reprogramming in response to biotic and abiotic signals at the transcription, translation and metabolic levels. These studies will allow the expansion of the scope of our understanding of induced plant defense responses to a global cellular level. There will also be practical applications in directed gene discovery for important agronomic traits involving plant natural products. Finally, this project will make available to the scientific community a bioinformatics system capable of supporting functional genomics ranging from the transcriptome to the metabolome. This system will include an extensible set of statistical and numerical analyses.