Objective
Plants continually monitor the environment to modify physiology and development at the molecular level to ensure maximal fitness. Central in the signaling network is the SnRK1 kinases (homologous to AMPK and SNF1 in mammals and yeast respectively). These kinases are vital to the energy balance of the organism and regulate primary metabolism by controlling transcription factors, which control the expression of genes encoding key enzymes. SnRK1 signaling and reprogrammed metabolism have turned out to be crucial for establishments of tolerance and sustained growth during stress.
This proposal suggests a multilevel approach to signaling in which all levels of the signal transduction pathway are addressed. The proposal is truly interdisciplinary and a wide range of methodology will be deployed ranging from classical physiology to state-of-the-art mass spectrometry based protein and metabolite profiling, massive sequencing of immuno-precipitated chromatin and whole genome expression profiling. This will be further supported by bioinformatic approaches, phylogenetical as well as network based. The aim is to understand the mechanisms regulating energy balance in plants and their impact on plant performance under stress. Improved stress tolerance of plants is of strategic importance in a world with rising population and changing climate. This strategic importance as well as future recruitment possibilities motivates the high involvement of industrial partners in the proposed activities.
The proposed training activities will coach future top-performers for professional career in the biotech industry as well as in the academia. The training program includes network-wide workshops (methodology, industry relevant skills and more) as well as structured local training in the host institutions. Important is a rich schedule of secondments in witch the young researchers will learn new technologies, widen their scientific horizons and establish their academic networks.
Fields of science (EuroSciVoc)
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques.
- medical and health sciencesbasic medicinephysiology
- natural sciencesbiological scienceszoologymammalogy
- natural scienceschemical sciencesanalytical chemistrymass spectrometry
- natural sciencesbiological sciencesgeneticsgenomes
- natural sciencesbiological sciencesbiochemistrybiomoleculesproteinsenzymes
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Call for proposal
FP7-PEOPLE-2010-ITN
See other projects for this call
Funding Scheme
MC-ITN - Networks for Initial Training (ITN)Coordinator
3584 CS Utrecht
Netherlands