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Title: Engineering stress resilient plants using gene regulatory network rewiring
Author: Gherman, Julia
ISNI:       0000 0004 8498 0420
Awarding Body: University of Warwick
Current Institution: University of Warwick
Date of Award: 2019
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In spite of advances in food production brought on by the Green Revolution, the challenge of providing access to nutritious, safe food that has been grown sustainably is considerable. One such barrier to food security is biotic stress - infection with pathogens such as bacteria, fungi and oomycetes impact negatively on plant growth and survival. Synthetic biology, an interdisciplinary field combining biology, engineering and mathematics, is a promising tool for understanding and developing stress tolerant plants. The response of the model plant Arabidopsis thaliana to biotic and abiotic stresses involves the transcriptional reprogramming of thousands of genes. Among these differentially expressed genes are transcription factors, which form complex causal networks specific to the stress in question. This thesis focuses on network rewiring as a tool for enhancing the Arabidopsis response to stress, in particular to Botrytis cinerea infection. This is a model system for studying plant-necrotrophic pathogen interactions and as such, a large amount of data are available, including a high-resolution transcriptomic time series of Arabidopsis during B. cinerea infection. This was used to construct gene regulatory networks with hundreds of transcription factors that are differentially expressed, in order to obtain a systems view of the effects of infection and the relationships between these regulators. Rewiring was applied to subnetworks of the original network using two different methodologies: control engineering, and Gaussian process dynamical systems. The former focuses on eliminating the effects of perturbation on a single node in a small 9-gene network, and requires detailed parameterisation of biological processes such as mRNA degradation and transcription rates. The latter provides a general modelling framework for optimising the overall expression of genes in a larger 70 gene subnetwork that eschews parameterisation or definition of a precise function for modelling relationships between genes. The process of generating stably transformed and rewired Arabidopsis is long and requires growing hundreds of plants for each construct. In order to test the hypotheses generated by such computational tools quickly and on a large scale, Arabidopsis protoplasts treated with chitin were trialled as a model system for studying plant defence responses to B. cinerea. RNAseq analysis of protoplasts was used to determine the similarities and differences between the defence responses triggered in protoplasts and in Arabidopsis plants. Both protoplasts and plants were also rewired, and gene expression measurements used to understand the effects of this genetic engineering on the defence response of each.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available
Keywords: QK Botany