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Computational Analysis of RNA modifications using Nanopore direct RNA sequencing

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  • Full or part time
    Dr Anton James Enright
  • Application Deadline
    No more applications being accepted
  • Funded PhD Project (European/UK Students Only)
    Funded PhD Project (European/UK Students Only)

Project Description

The rapid advance of high-throughput sequencing technologies has lead to the identification of specific post-transcriptional modifications in thousands of transcripts. These are derived for both protein-coding RNAs and other less abundant RNA classes. Biological functions for the vast majority of these modifications remain uncharacterised. However, many are expected to have significant structural impact. For instance, the well characterized N6-methyladenosine (m6A) modification has been shown to flag mRNAs for fast-track processing via m6A induced structural switches. Our laboratory is using novel technologies and methods to develop the next generation of approaches to the detection and understanding of RNA methylation. This project will involve the analysis of Oxford Nanopore RNA sequencing data with a view to developing novel basecalling algorithms which can delineate between methylated and unmethylated bases. Additionally, we will use this technology to explore the extent of RNA methylation across tissue types and disease states including cancer.

Funding Notes

Funding* will cover the student's stipend at the current Research Council rate and University Fees. The studentships will be funded for three years in the first instance subject to eligibility**, with the possibility of additional funding in the fourth year depending on circumstances. **The studentships are available to UK nationals and EU students who meet the UK residency requirements. Further information about your fee status can be found at the following website: . Applications from ineligible candidates will not be considered.

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

FTE Category A staff submitted: 189.63

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