Using systems biology approaches to elucidate gene regulatory networks controlling the plant defence response

Abstract

Transcriptional regulation controlling pathogen-responsive gene expression in Arabidopsis is believed to underlie the plant defence response, which confers partial immunity of Arabidopsis to infection by Botrytis cinerea. In this thesis networks of transcriptional regulation mediating the defence response are studied in various ways. First transcriptional regulation was predicted for all genes differentially expressed during B. cinerea infection by development of a novel clustering approach, Temporal Clustering by Affinity Propagation (TCAP). This approach finds groups of genes whose expression profile time series have strong time-delayed correlation, a measure that is demonstrated to be more predictive of transcriptional regulation than conventionally used similarity measures. TCAP predicts the known regulation of GI by LHY, and co-clusters ORA59 and some of its downstream targets. Predicted novel regulators of pathogen-responsive gene expression were then studied in a reverse genetics screen, which discovered several novel but weakly altered susceptibility phenotypes. Comparison of predicted targets to known targets was complicated by the sparsity of mutant versus wildtype gene expression experiments performed during B. cinerea infections in the literature. To explore the context-dependence of transcriptional regulation, evidence of transcriptional regulation in different contexts was collected. This was compiled to generate a qualitative model of transcriptional regulation during the defence response. This model was validated and extended by experimental analysis of transcription factor-promoter binding in Yeast and transcriptional activation in planta. Comparative transcriptomics showed that downstream genes of some of these regulators | TGA3, ARF2, ERF1 and ANAC072 | are over-represented in the list of genes differentially expressed during B. cinerea infection, which is consistent with these targets being regulated by them during B. cinerea infection. Finally this qualitative model was used as prior information and was used along with gene expression time series to infer quantitative models of the gene regulatory network mediating the defence response. Some known regulation was predicted, and additionally ANAC055 was predicted to be a central regulator of pathogenresponsive gene expression