Improving our understanding of key immune system genes that influence multiple sclerosis

About the research project

Multiple sclerosis (MS) is a progressive autoimmune and neurodegenerative disease, and genetic factors account for around half the risk of developing the disease. MS prevalence shows a heterogeneous geographical pattern, being higher in populations of European ancestry and increasing with distance from the equator within those populations. This pattern has been shaped by population genetic processes including genetic drift, admixture, and natural selection. Our research focuses on understanding how these processes have shaped MS and using this knowledge to identify functional genetic variation underlying disease.

The major histocompatibility complex (MHC) region on chromosome 6 is central to genetic risk of multiple sclerosis and other autoimmune diseases. It encompasses many genes critical to immune system function, most notably the human leukocyte antigen (HLA) complex. The MHC is the most polymorphic region of the human genome and has the greatest number of trait and disease association signals. Because of its extreme diversity and structural variation, it is notoriously difficult to analyse using short-read sequencing data. Standard analysis approaches relying on linear reference genomes introduce strong biases in variant detection. This project will improve the resolution of variant calling in the MHC by characterising global genetic diversity and developing new alignment and variant calling pipelines.

First, you will carry out de novo assembly of newly-available long-read data from the 1000 Genomes Project. You will use these assemblies to build a set of population-specific and global pangenome reference graphs for the MHC. This will allow us to characterise sequence and structural variation across diverse populations. Second, you will develop a pipeline for aligning long- or short-read sequencing data to these pangenome graphs to accurately call HLA haplotypes with minimal reference bias. You will test a range of different approaches for alignment and variant calling of sequencing data from MS families and other cohorts.

This is a computational project and would best suit someone with a background in population genetics or molecular evolution and experience in bioinformatics.

Primary supervisor

Meet Doctor Bennet McComish

Funding

Applicants will be considered for a Research Training Program (RTP) scholarship or Tasmania Graduate Research Scholarship (TGRS) which, if successful, provides:

• a living allowance stipend funded by University of Tasmania of $34,315 per annum for 3.5 years
• a relocation allowance of up to $2,000
• a tuition fees offset covering the cost of tuition fees for up to four years (domestic applicants only)

A tuition fee offset may be offered to eligible international applicants following competitive assessment 

As part of the application process you may indicate if you do not wish to be considered for scholarship funding.

Other funding opportunities and fees

For further information regarding other scholarships on offer, and the various fees for undertaking a research degree, please visit our Scholarships and fees on research degrees page.

Eligibility

Applicants should review the Higher Degree by Research minimum entry requirements.

Ensure your eligibility for the scholarship round by referring to our Key Dates.

Selection criteria

The project is competitively assessed and awarded. Selection is based on academic merit and suitability to the project as determined by the College.

Additional desirable selection criteria specific to this project:

• Experience in bioinformatics or computational biology, including coding/scripting skills
• Experience in analysing long-read sequencing data

Application process

1. Select your project, and check that you meet the eligibility and selection criteria, including citizenship;
2. Contact Doctor Bennet McComish to discuss your suitability and the project's requirements; and
3. In your application:
   • Copy and paste the title of the project from this advertisement into your application. If you don’t correctly do this your application may be rejected.
   • Submit a signed supervisory support form, a CV including contact details of 2 referees and your project research proposal.
4. Apply prior to 1 October 2026.

Full details of the application process can be found under the ' How to apply ' section of the Research Degrees website.

Following the closing date applications will be assessed within the College. Applicants should expect to receive notification of the outcome by email by the advertised outcome date.

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