Network modelling of drought responses

Water availability is the biggest single limitation on plant productivity worldwide. In Arabidopsis, changes in metabolism and gene expression drive increased drought tolerance and initiate diverse drought avoidance and escape responses. To investigate regulatory processes that integrate early and late stress responses, a high-resolution time series transcriptomics dataset coupled with Bayesian network modelling is used to identify key regulatory genes.

HSF3

Two typical 5-month-old T1 transgenic oilseed rape (#1, #3) and a control azygous sibling over-expressing AtHSFA1b (Bechtold et al 2013).

This project has produced a number of gene regulatory networks that have led to the isolation of novel candidate genes. We essentially analyse the functions of these novel candidate genes to understand the molecular mechanisms of drought stress as well as the impact these genes have on plant physiology and performance.

In addition these genes will be evaluated for the improvement of drought tolerance and productivity by gene manipulation in Brassicacea and other crop species.

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