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The impact of gene expression noise on plant fitness under stress conditions linked to climate change


Project Description

Start date: October 2020
Duration: 3 years (full time)
Location: Colchester Campus
Based in: School of Life Sciences (in collaboration with Department of Mathematical Sciences)

Plants are constantly exposed to a wide range of environmental changes. Stress-related gene expression patterns are characterised by distinct transcriptional mechanisms, but may also enhance gene expression noise.

Intrinsic gene expression noise refers to variation that arises from molecular-level fluctuations, and it has been hypothesised that gene expression noise has undergone significant evolutionary drifts.

Genome-scale studies on unicellular organisms such as yeast have shown that dose-sensitive genes and proteins forming multicomponent complexes have low gene expression noise, genes responding to changes in the environment display high noise levels.

High levels of gene expression noise need to be balanced with growth-related gene expression programmes, and emerging data suggest that organisms exploit this noise to fuel phenotypic variation.

The project

We hypothesise that in plants, intrinsic gene expression noise may lead to selective advantage under stress and that the overall stochastic features of noise may provide beneficial diversity and survival under stress responses.

This PhD aims to investigate whether evolution has fine-tuned noise-generating mechanisms and genetic network architectures leading to plant diversity enhancing stress responses and survival.

We will use existing timeseries gene expression datasets to investigate the patterns of noise in Arabidopsis exposed to short term (high-light, pathogen infections) and long-term (drought, senescence) stress conditions.

Furthermore, we will identify groups of genes with high levels of inherent noise under control and stress conditions and validate whether high level of noise in specific genes is essential for survival under stress.

Criteria

The ideal candidate will hold a BSc/MSc in Biology or Bioinformatics (preferably MSc).

How to apply

You can apply for this postgraduate research opportunity online (https://www1.essex.ac.uk/pgapply/login.aspx).

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.

Find out more about this studentship and information on how to apply on our website (https://www.essex.ac.uk/postgraduate-research-degrees/opportunities/the-impact-of-gene-expression-noise-on-plant-fitness).

Funding Notes

A full Home/EU fee waiver or equivalent fee discount for overseas students (£5,103 in 2019-20) (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 (£15,009 in 2019-20, stipend for 2020-21 tbc).

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