Patron Group: Engineering gene regulatory networks for crop disease-resistance
Supervisor:
Dr Nicola Patron
Overview:
Quantitative traits are phenotypes that are determined by many genes and impacted by the environment. In plants, these include many agricultural traits such as biomass, seed yield, resistance to abiotic stress and resistance against generalist pathogens, such as the fungal pathogen Botrytis cinerea. These traits result from the actions of suites of genes working combinatorially within gene regulatory networks (GRNs). The complexity of GRNs has made them challenging to investigate using traditional genetic approaches. Similarly, predicting the effects of perturbations has been a significant barrier to applying genetic engineering to the improvement of quantitative traits. Crude interventions such as over-expression or loss-of-function can have undesirable pleiotropic effects on growth, development, and responses to other stresses. This project will use synthetic biology approaches to rewire a regulatory network that coordinates pathogen resistance in lettuce
Importance of Research:
Lettuce is the most valuable leafy vegetable grown in the UK with production valued at >£180 million in 2021 (DEFRA). Lettuce is susceptible to a wide range of plant pathogens including the fungal pathogens Botrytis cinerea and Sclerotinia sclerotiorum, causal agents of grey mould and lettuce drop, respectively. Chemical control is routinely used but there is an urgent need to develop varieties with enhanced resistance given the economic and environmental costs of preventative pesticide sprays, the prevalence of fungicide-resistant isolates of both pathogens in the field, and the increasing withdrawal of approved fungicides through legislation.
What will the successful applicant do?
In recent work, we have modelled and validated a causal regulatory network mediating resistance to broad host-range fungal pathogens in lettuce. This work has identified several strategies for engineering resistance in lettuce. This project will design, build and test synthetic genetic circuits to implement engineering strategies that our models predict will increase disease resistance. This will include disrupting network edges using gene editing to introduce mutations into the regulatory regions of network genes and building synthetic genetic controllers to tune expression of network genes in response to specific signals. Work will be carried out in collaboration with the Denby laboratory at the University of York.
This project will provide training in a range of technical skills including the design, build, and test of synthetic constructs, gene editing, plant biology and working with plant pathogens. We also mentor students to acquire the skills, independence, and confidence they need to reach their career goals, with a focus on the development of writing, critical thinking, time management, collaboration, and presentation skills.
References:
Tansley C, Patron NJ, and Guiziou S (2024) Engineering plant cell fates and functions for agriculture and industry. ACS Synthetic Biology. DOI:10.1021/acssynbio.4c00047
Pink H, Talbot A, Carter R Hickman R, Cooper O, Law R, Higgins G, Yao C, Gawthrop F, Hand P, Pink D. Clarkson J, Denby K (2023) Identification of Lactuca sativa transcription factors impacting resistance to Botrytis cinerea through predictive network inference. DOI:10.1101/2023.07.19.549542