ATSYSTM-BIOL
System biology of nitrogen-carbon-signal integration in the overall Arabidopsis signaling network
| Coordinatore | CENTRE NATIONAL DE LA RECHERCHE SCIENTIFIQUE
Organization address
address: Rue Michel -Ange 3 contact info |
| Nazionalità Coordinatore | France [FR] |
| Totale costo | 193˙036 € |
| EC contributo | 193˙036 € |
| Programma | FP7-PEOPLE
Specific programme "People" implementing the Seventh Framework Programme of the European Community for research, technological development and demonstration activities (2007 to 2013) |
| Code Call | FP7-PEOPLE-2007-4-1-IOF |
| Funding Scheme | MC-IOF |
| Anno di inizio | 2008 |
| Periodo (anno-mese-giorno) | 2008-10-01 - 2011-06-30 |
Partecipanti
| # | ||||
|---|---|---|---|---|
| 1 |
CENTRE NATIONAL DE LA RECHERCHE SCIENTIFIQUE
Organization address
address: Rue Michel -Ange 3 contact info |
FR (PARIS) | coordinator | 0.00 |
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Obiettivo del progetto (Objective)
'Plant development is under the control of abiotic environment. Nitrogen (N) and Carbon (C) signaling are well known to interact together, but also with a set of diverse signaling pathways including light and the plant hormones, auxin or cytokinin. Relationships of C/N “balance” with these “growth factors” are hypothesized to trigger the regulation of broad developmental processes such as root/shoot development or flowering. The overall aim of this proposal is to use a genomics and systems biology approach to design and explore an experimental space to test how the intersection of light, carbon, nitrogen and hormone signaling pathways acts to coordinate responses of gene networks in Arabidopsis. Combinatorial Design will be used to select a set of treatments designed to broadly cover the experimental space of interactions using a minimal number of treatments, as described in Lejay et al 2005, and whole genome responses will be assayed using Affymetrix Gene Chips. The work flow includes: Aim 1. Design and test the entire experimental space of treatments using reporter gene constructs, to aid in selection of an optimal CD set for transcriptome analysis. Aim 2. Integrate & analyze transcriptomic data in the context of Arabidopsis multinetworks to identify regulatory gene networks whose expression is controlled by the interaction of these different signals on gene regulation. This analysis will allow us to identify “hub”-genes involved in coordinating gene network responses to N/C/Light/Hormones signals. Aim 3. Validate the gene regulatory networks by classical reverse-genetics concerning “hub”-gene and to place these molecular actors into previously identified gene networks. This project will mark a significant and useful turn in my scientific experience to genomics, biocomputing and systems biology.'