Transcriptional regulatory codes underlying Arabidopsis stress responses

Plant adaptation to stress is dependent upon the initialisation of molecular signalling networks that regulate the expression of stress-related genes. By examining high-resolution microarray datasets it has been possible to track gene expression changes over time during senescence and in response to infection by fungal pathogen Botrytis cineria in the model organism Arabidopsis thaliana. Dramatic variations in gene expression are observed at the onset of stress with different groups of genes showing different expression time-courses. This observation must, for a large part, be down to the action of different transcription factors (TFs) binding to the cis-regulatory DNA in the promoters of genes in each group and it is this regulatory code that underpins the gene regulatory networks that regulate stress responses. This thesis presents an interdisciplinary investigation of the regulatory codes that are responsible for controlling plant stress responses. Computational analysis of non-coding sequences provides a powerful approach to identify patterns within DNA that may function to regulate gene expression. This thesis covers the development of Analysis of Plant Promoter-Linked Elements (APPLES), an object-orientated software framework for the analysis of non-coding DNA. Within this environment, methods were developed to probe the regulatory codes that exist within these non-coding sequences and identify regulatory motifs that may function to regulate stress responses in Arabidopsis. APPLES methods were used to identify a novel motif that is likely to play a role in regulating drought responses in Arabidopsis, with experimental approaches providing support for this view. Using known motifs that describe previously characterised TF binding sites, it was possible to identify motifs that are associated with clusters of co-regulated genes identified from the senescence and Botrytis microarray time-course datasets. This analysis revealed cis-regulatory elements that may contribute to generating the observed expression patterns. In a contrasting approach to in silico identification of regulatory elements, the Yeast-1-Hybrid (Y1H) assay was used to experimentally identify interactions between TFs and non-coding DNA. The use of a TF library allowed the ability of approximately 1400 Arabidopsis TFs to interact with a given DNA sequence in a single assay. Using the stress-associated ANAC092 promoter as a test case, it was possible to use this highthroughput procedure to identify TFs that can bind to the promoter of this gene. This high-throughput Y1H system was then used to perform a detailed mapping of protein- DNA interactions that can occur across the core promoters of three highly related stress inducible TF-encoding genes, ANAC019, ANAC055 and ANAC072. Microarrays were used to assess the regulatory consequence of a subset of these interactions by perturbing the expression of interacting TFs and observing the effect on target gene expression during multiple stresses. This approach confirmed predicted regulatory relationships and therefore enhanced the current understanding of the transcriptional regulatory networks that operate during stress responses in Arabidopsis.