PhD Studentship: Investigating the oligogenic model of Amyotrophic Lateral Sclerosis (ALS; motor neuron disease, MND)

Funding amount: Home tuition fees & stipend (Year 1 - £19,000; Year 2 - £20,000; Year 3 - £21,000). Applicants with overseas fee status will need to fund the difference between Home and International tuition fees.

A PhD studentship (3 years) is available from October 2023 under the supervision of Professor Majid Hafezparast, Department of Neuroscience, School of Life Sciences, University of Sussex & Dr Johnathan Cooper-Knock, Department of Neuroscience, University of Sheffield.

Project Title: Investigating the oligogenic model of Amyotrophic Lateral Sclerosis (ALS; motor neuron disease, MND)

The Project:

Applications are invited for a multidisciplinary PhD studentship funded by the Motor Neurone Disease Association to study the cumulative contribution of coinherited subthreshold amyotrophic lateral sclerosis (ALS) risk gene variants in the development of cellular hallmarks of ALS pathology. Successful candidate will be trained in cutting-edge bioinformatics and neurobiology techniques.

ALS is a fatal neurodegenerative disease affecting motor neurons in the central nervous system. Despite the discovery of some ALS-associated genes, ~85% of cases are not caused by mutations in a single gene making ALS typically a complex disease. ALS-associated genetic variants can exhibit variable penetrance (the frequency with which a genotype manifests itself in a given phenotype) with some carriers never developing the disease. Penetrance increases with age in ALS and the variability in penetrance can be caused by the presence of other genotypes, epigenetic factors, & lifestyle. It is therefore thought that the cause of non-familial cases of ALS has a significant genetic component, perhaps multiple uncommon variants with moderate effect size (oligogenic) or a large number of common variants (polygenic).

This project will test the oligogenic hypothesis of ALS onset by identifying subthreshold variants of ALS-associated proteins, focusing on those involved in autophagy, ubiquitin-proteasome system (UPS), & axonal transport to model & analyse their co-inheritance in motor neurons derived from CRISPR-Cas9 edited human induced pluripotent stem cells (iPSCs). By focusing on the autophagy/UPS/axonal transport proteostasis regulation axis, this project promises to potentially provide experimental evidence for the oligogenic model of ALS onset and a platform for the development of high throughput screening strategies to identify disease modifying drugs for treating ALS.

This multidisciplinary project will utilise methods at the forefront of human genome sequence analysis (bioinformatics) combined with CRISPR-Cas9 genome editing technology to create human iPSCs harbouring combinations of the subthreshold ALS-associated variants. These iPSC lines will then be differentiated into motor neurons & analysed for ALS pathology using a range of cellular & molecular neurobiology and advanced fluorescence microscopy techniques.

Applications are particularly welcomed from candidates with protected characteristics – e.g. from Black & other ethnic minorities – who are under-represented in postgraduate research at our institutions.

How to apply:

Please submit a formal application using the online admissions portal attaching a CV, degree transcripts & certificates, personal statement & two academic references.

On the application system select Programme of Study – PhD Neuroscience. Please state the project title under funding & the supervisor’s name where required.

Ideal candidates will have a strong background in cellular &  molecular biology with additional experience of bioinformatics.

Eligible candidates will have recently received an MSc and/or a First or 2:1 BSc in a relevant subject.

Candidates for whom English is not their first language will require an IELTS score of 6.5 overall, with not less than 6.0 in any section.

For enquiries about the application process, contact Emma Chorley: lifesci-rec@sussex.ac.uk

For enquiries about the project, contact supervisors: Professor Majid Hafezparast (m.hafezparast@sussex.ac.uk) or Dr Johnathan Cooper-Knock (j.cooper-knock@sheffield.ac.uk).  

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