Identifying gene regulatory networks common to multiple plant stress responses
mesheuropmc: food and beverages | fungi
Stress responses in plants can be defined as a change that affects the homeostasis of pathways,\ud resulting in a phenotype that may or may not be visible to the human eye, affecting the fitness\ud of the plant. Crosstalk is believed to be the shared components of pathways of networks, and\ud is widespread in plants, as shown by examples of crosstalk between transcriptional regulation\ud pathways, and hormone signalling.\ud Crosstalk between stress responses is believed to exist, particularly crosstalk within the responses\ud to biotic stress, and within the responses to abiotic stress. Certain hormone pathways are known\ud to be involved in the crosstalk between the responses to both biotic and abiotic stresses, and can\ud confer immunity or tolerance of Arabidopsis thaliana to these stresses. Transcriptional regulation\ud has also been identified as an important factor in controlling tolerance and resistance to stresses.\ud In this thesis, networks of regulation mediating the response tomultiple stresses are studied. Firstly,\ud co-regulation was predicted for genes differentially expressed in two or more stresses by development\ud of a novel multi-clustering approach, Wigwams Identifies Genes Working Across Multiple\ud Stresses (Wigwams). This approach finds groups of genes whose expression is correlated within\ud stresses, but also identifies a strong statistical link between subsets of stresses. Wigwams identifies\ud the known co-expression of genes encoding enzymes of metabolic and flavonoid biosynthesis\ud pathways, and predicts novels clusters of co-expressed genes. By hypothesising that by being coexpressed\ud could also infer that the genes are co-regulated, promoter motif analysis and modelling\ud provides information for potential upstream regulators.\ud The context-free regulation of groups of co-expressed genes, or potential regulons, was explored\ud using models generated by modelling techniques, in order to generate a quantitative model of\ud transcriptional regulation during the response to B. cinerea, P. syringae pv. tomato DC3000 and\ud senescence. This model was subsequently validated and extended by experimental techniques,\ud using Yeast 1-Hybrid to investigate the protein-DNA interactions, and also microarrays. Analysis\ud of mutants and plants overexpressing a predicted regulator, Rap2.6L, by gene expression analysis\ud identified a number of potential regulon members as downstream targets.\ud Rap2.6L was identified as an indirect regulator of the transcription factor members of three potential\ud regulons co-expressed in the stresses B. cinerea, P. syringae pv. tomato DC3000 and long\ud day senescence, allowing the confirmation of a predicted gene regulatory network operating in\ud multiple stress responses.
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