Postgraduate Research Opportunity

Mathematical approaches in inferring gene regulatory networks mediating the transition between early and late stages of plants' response to drought

Details

Title: SCH39: Mathematical approaches in inferring gene regulatory networks mediating the transition between early and late stages of plants' response to drought

Funding: A full Home/EU fee waiver or equivalent fee discount for overseas students  (£5,103 in 2020-21) (further fee details - international students will need to pay the balance of their fees) plus a doctoral stipend equivalent to the RCUK Minimum Doctoral Stipend (£15,285 in 2020-21).

Application deadline: Tuesday 31 March 2020

Start date: October 2020

Duration: 3 years (full time)

Location: Colchester Campus

Based in: Department of Mathematical Sciences (in collaboration with the School of Life Sciences)

Overview 

Water limitation in agriculture is increasing due to urbanisation, industrialisation, depletion of aquifers and climate change.

Reduced water availability leads to drought stress, a major constraint on the productivity of crop plants. Understanding the mechanisms of drought response is essential for the improvement of plant performance.

In 2016, the co-supervisors of the project, Dr Ulrike Bechtold and Prof. Phil Mullineaux of the School of Life Sciences, published high-resolution transcriptomics data sets, coupled with detailed physiological and metabolic analyses in Arabidopsis plants that were subjected to a slow transition from well-watered to drought conditions. 1815 drought-responsive differentially expressed genes (DEGs) responded to the transition between early and late stages of drought.

The co-supervisors used Bayesian network modelling of DEGs coding for transcription factors to construct gene regulatory networks (GRNs). This led to the identification of a novel drought responsive signalling network (Bechtold et al. (2016), Plant Cell, 28, 345).

This complex dataset is a comprehensive resource that remains mathematically under-exploited.

The project

In this project, to be supervised primarily by Dr Chris Antonopoulos of the Department of Mathematical Sciences, a leading expert in network inference (see for example Bianco-Martinez et al. (2016), Chaos, 26 (4), 043102), you will develop new mathematical approaches that will find better ways to infer GRNs and model their structure.

The project is expected to lead to improved accuracy of inferring water deficit-associated GRNs that will improve the success rate of identifying novel drought-responsive genes, which will be validated experimentally in Arabidopsis and crop plant species.

Funding

The award consists of a full Home/EU fee waiver or equivalent fee discount for overseas students (further fee details), a doctoral stipend equivalent to the Research Councils UK National Minimum Doctoral Stipend (£15,285 in 2020-21), plus £2,500 training bursary via Proficio funding, which may be used to cover the cost of advanced skills training including conference attendance and travel.

Supervisors

Dr Ulrike Bechtold

Co-supervisor

School of Life Sciences, University of Essex

Dr Ulrike Bechtold is a Senior Lecturer in Life Sciences with 15 years’ experience working on plant abiotic stress responses. In the past 3 years, she has published 2 papers on gene- and metabolite-regulatory networks utilising time series datasets, which are the basis for this PhD. She is an expert in the molecular analysis of plant stress responses integrating large datasets (genomics, phenomics) and targeted gene manipulation to investigate novel signalling pathways.

Professor Philip Mullineaux

Co-supervisor

School of Life Sciences, University of Essex

Prof Mullineaux has 36 years’ research experience in plant molecular responses to environmental stress. His most advanced work is on defining redox-active cell signalling networks that govern plant responses to stress. With Dr Ulrike Bechtold, he developed the comprehensive time series datasets for responses to drought and other stresses. His long experience ensures that the advanced mathematics to be done in this project will find immediate application in improving plant productivity under adverse environmental conditions.

Criteria

We are looking for candidates with a BSc in Maths or related subjects, and an MSc in Biology or related subjects.

How to apply

You can apply for this postgraduate research opportunity online.

Please include your CV, covering letter, personal statement, and transcripts of UG and Masters degrees in your application.

The University has moved to requiring only one reference for PhD applications and these can be received after a conditional offer has been made so the absence of these will not hold up the recruitment process.

Instruction to applicants

When you apply online you will be prompted to fill out several boxes in the form:

  • For "Course title" please put "PhD Applied Mathematics"
  • For "Proposed research topic or area of research" please put the title of this studentship (SCH39: Mathematical approaches in inferring gene regulatory networks mediating the transition between early and late stages of plants' response to drought)
  • For "If you have contacted a potential supervisor..." please put the name of the lead supervisor (Dr Chris Antonopoulos)

If you have any informal queries about this opportunity please email the lead supervisor, Dr Chris Antonopoulos (canton@essex.ac.uk).

You can find the terms and conditions of this studentship here (PDF).

Student and academic working at a board together
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