EMERGENCE
Building a regulatory network for lateral root emergence
| Coordinatore | THE UNIVERSITY OF NOTTINGHAM
Organization address
address: University Park contact info |
| Nazionalità Coordinatore | United Kingdom [UK] |
| Totale costo | 178˙307 € |
| EC contributo | 178˙307 € |
| 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-2007-2-1-IEF |
| Funding Scheme | MC-IEF |
| Anno di inizio | 2008 |
| Periodo (anno-mese-giorno) | 2008-08-01 - 2010-07-31 |
Partecipanti
| # | ||||
|---|---|---|---|---|
| 1 |
THE UNIVERSITY OF NOTTINGHAM
Organization address
address: University Park contact info |
UK (NOTTINGHAM) | coordinator | 0.00 |
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Obiettivo del progetto (Objective)
'Cell separation is a critical process for plants. Germinating seedlings emerge from their seed coats, anthers dehisce, fruit ripen, and organs are shed as a result of plant cell separation. To date, several cell wall remodeling enzymes associated with cell separation have been identified, however very little is known about the signals and mechanisms controlling their expression. The host laboratory has recently made major advances in the identification of the signals and molecular mechanisms regulating cell separation during lateral root emergence. The auxin influx transporter LAX3 allows the auxin inducible expression of a set of cell wall remodeling genes in front of the lateral root primordium to promote cell separation. The expression of these genes is dependant on the AUX/IAA proteins SLR1 and SHY2. The main aim of the present project is to study the signals and regulatory network that coordinates plant cell separation employing lateral root emergence as a model. I propose to adopt a Multidisciplinary Integrative Biology based approach which takes advantage of the facilities and expertise available in the host laboratory. Functional genomic, chemical genetic and mathematical modeling approaches will allow to identify new regulatory components and target genes then to build a regulatory network that will be modeled and tested.'