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Epigenetic temperature sensing in plants


Project Description

The changing climate is already having a dramatic effect on the growth and development of the plants that support our entire civilisation. This is likely to be amplified as we await concerted action on climate change. It is therefore essential that we attempt to understand the mechanisms that enable factors such as increased temperature to affect plant performance. Understanding these mechanisms will allow us to engineer altered responses and thereby mitigate the negative effects. We have used a genetic screen to identify novel components of the mechanism that allows plants to decide when to flower in response to temperature. One of the novel genes that we identified directly links the epigenetic control of gene expression to temperature perception. In this project you will discover the underlying mechanism, identify more components and use our new understanding to engineer plants that respond differently to temperature. In addition, you will explore the biotechnological applications of the mechanism. You will join a collaborative team including plant developmental biologists, virologists and RNA biologists to apply advanced molecular genetic and genomic approaches to study this highly topical global challenge.

Funding Notes

White Rose BBSRC Doctoral Training Partnership in Mechanistic Biology
4 year fully-funded programme of integrated research and skills training, starting Oct 2020:
• Research Council Stipend
• UK/EU Tuition Fees
• Conference and research funding

Requirements:
At least a 2:1 honours degree or equivalent. We welcome students with backgrounds in biological, chemical or physical sciences, or mathematical backgrounds with an interest in biological questions.

EU candidates require 3 years of UK residency to receive full studentship

Not all projects will be funded; the DTP will appoint a limited number of candidates via a competitive process.

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How good is research at University of Leeds in Biological Sciences?

FTE Category A staff submitted: 60.90

Research output data provided by the Research Excellence Framework (REF)

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