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PhD Studentship: Functional interpretation of human NF1 genetic variation using precision genome editing and in vivo phenotyping

University of Exeter - Clinical and Biomedical Sciences

Qualification Type: PhD
Location: Exeter
Funding for: UK Students, International Students
Funding amount: £21,805 The studentship will provide funding of fees and a stipend of £21,805 per annum for 2026/7.
Hours: Full Time
Placed On: 28th October 2026
Closes: 8th December 2026
Reference: 6025

Neurofibromatosis type 1 (NF1) is a genetic disorder that causes a range of symptoms and affects approximately 1 in 3,000 people. These include abnormalities in skin pigmentation, problems with the heart and circulatory system, and nerve tumours that cause chronic pain and movement problems. This multisystem genetic disorder is caused by mutations in the NF1 gene, which encodes the neurofibromin protein. Neurofibromin contains seven functional domains and each domain interacts with different signalling pathways. Although mutations throughout the entire NF1 gene can cause disease, it remains unclear how genetic variants in different domains are associated with distinct clinical phenotypes.

This PhD project addresses the gap between genetic variants in humans, molecular functions, and organismal phenotypes in NF1. The project will be delivered by combining data science and in vitro and in vivo analyses to address three objectives; 1) Identification and prioritisation of human NF1 variants, 2) Assessment of their effects on NF1-dependent signalling, and 3) Validation of the genetic variants in zebrafish model. The student will screen and prioritise NF1 pathogenic variants using population data focusing on genotype–phenotype association. In addition, AI-based approaches such as biological foundation models will be used to predict their functional effects and select variants representing different NF1 domains. Next, effects of selected variants on the signalling pathways downstream of neurofibromin will be investigated using human cell culture systems.

The student will quantitatively measure cellular phenotypes and investigate the rescue by drug treatment with the existing chemical compounds such as MEK inhibitors targeting the oncogenic Ras pathway regulated by neurofibromin. To connect molecular function to organismal phenotype, the student will establish a novel humanised zebrafish platform during the project. Zebrafish possess two paralogs of the human NF1 gene, referred to as nf1a and nf1b, both of which show comparable levels of conservation across DNA sequences and protein domain structures. Interestingly, nf1a/b mutant zebrafish reproduce many of the common NF1 phenotypes, such as the loss of pigmentation and abnormal patterning of the central nervous system.

To generate a precise disease model, the protein-coding sequence of the zebrafish nf1 is excised and replaced with the human NF1 sequence using CRISPR/Cas9-based genome editing technologies. By using the humanised zebrafish, the student will create a multidimensional functional map of NF1 which links the genetic variants, signalling activities, and organismal phenotypes. The selected variants will be introduced into the replaced human NF1 gene using precise genome editing technologies such as prime editing and donor DNA-based knock-in. Functional effects of the variants on tissue patterning and pharmacological responses will be assessed by imaging transgenic reporter zebrafish lines that label oligodendrocytes, Schwann cells, or endothelial cells in blood vessels.

This integrated functional genomics project which combines data science and cell and developmental biology will lead to a deeper mechanistic understanding of neurofibromin function and the contributions of individual genetic variants to organismal phenotypes relevant to symptoms observed in NF1 patients. By connecting individual variants to quantitative in vivo phenotypes and signalling outputs, this platform will provide a scalable strategy for variant interpretation, understanding of disease mechanisms, and improved therapies.

Funded by: EPSRC Engineering and Physical Sciences Research Council 

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