Professor Katherine Denby, York
Elucidating and re-designing regulatory networks underlying plant defence
Plant responses to biotic stress involve large-scale transcriptional reprogramming. We are elucidating the gene regulatory networks underlying these transcriptional responses to pathogen infection using a combination of experimental and computational/mathematical tools. We generated high-resolution time series expression data from Arabidopsis leaves following infection with bacterial and fungal pathogens. These time series data sets have enabled us to identify transient changes in gene expression and resolve the chronology of plant defence responses. We have generated transcriptional network models predicting regulatory relationships between differentially expressed transcription factors and identified key regulators of the Arabidopsis defence response from our networks. Crucially many of these key regulators were not previously known to affect susceptibility to plant pathogens. We have extended the network models by identifying groups of genes co-regulated across multiple environmental stress responses and validated by experimentally testing regulatory predictions from model simulations. We are using simulations of the network models to predict how to re-wire the defence transcriptional network to enhance expression of positive regulators of defence (and reduce expression of negative regulators) and hence increase the disease resistance of Arabidopsis. We are also testing whether such network-based approaches work in crop plants and can speed up breeding for resistance.