Kennedy Trust Prize Studentships
Investigating the causes of inflammatory arthritis with computational and single-cell genomics
Ankylosing spondylitis (AS) is a common and highly heritable1form of arthritis which characteristically involves inflammation of the sacroiliac joints and spine. Current therapeutics do not work in all patients and cannot induce disease remission. Inflammation in AS is known to involve the IL-23/IL-17 immune pathway2but the molecular origins of the disease remain unknown. The strong genetic association of AS with the human leukocyte antigen (HLA) class I molecule HLA-B*27 suggests that inflammation is triggered by an ‘arthritogenic’ peptide, but there is also evidence for several other models of disease pathogenesis. Historically the extraordinary heterogeneity of the immune system has posed a major roadblock to the identification of the cellular mechanisms that underlie AS. To overcome this challenge, we are now applying ultra-high-throughput single-cell RNA-sequencing3to study biopsy samples from the inflamed joints of AS patients. In this mainly computational project, you will learn and develop single-cell genomics analysis methods in order to discover the cell states, biological pathways and genes associated with the development of AS. Working closely with experimental colleagues you will design follow-up experiments and test hypotheses using the latest functional genomics approaches such as CRISPR-based gene editing. Ultimately, the results of this research will provide a rational basis for the development of more effective therapeutics that target the causes, rather than the symptoms, of AS.
The Kennedy Institute is a world-renowned research centre, housed in a brand new, state-of-the-art facility at the University of Oxford. The Botnar Research Centre plays host to the University of Oxford's Institute of Musculoskeletal Sciences, which enables and encourages research and education into the causes of musculoskeletal disease and their treatment. Students will become fluent in computational genomics and acquire an expert understanding of chronic inflammatory disease. Training will be provided in techniques including the writing of computational pipelines (see e.g. https://github.com/sansomlab/tenx) with Python, the use of Linux high-performance compute clusters, and statistical data analysis and visualisation with R. Students will have the opportunity to utilise machine learning approaches, to work closely with world-leading statistical geneticists, and will perform integrated analyses with “big data” from sources such as the Human Cell Atlas (https://www.humancellatlas.org/) and ImmGen projects. You will be expected to develop a close understanding of experimental research through regular attendance of wet-lab group meetings. You will have the opportunity to be closely involved in the generation of functional genomics data and to learn the various immunological techniques that are up and running in the Bowness lab.
A core curriculum of lectures will be taken in the first term to provide a solid foundation in a broad range of subjects including musculoskeletal biology, inflammation, epigenetics, translational immunology, data analysis and the microbiome. Students will attend regular seminars within the department and those relevant in the wider University. Students will be expected to present data regularly in the departmental PGR seminars, Sansom and Bowness group meetings and to attend external conferences to present their research globally.
Students will have access to various courses run by the Medical Sciences Division Skills Training Team and other departments. All students are required to attend a 2 - day Statistical and Experimental Design course at NDORMS.
- HLA-B27. Bowness P. Annual Review Immunology, 2015
- The interleukin (IL)-23/IL-17 axis in ankylosing spondylitis: new advances and potentials for treatment. Jethwa H, Bowness P. Clin Exp Immunology, 2016
- Pathologically distinct fibroblast subsets drive inflammation and tissue damage in arthritis. Adam Croft, Joana Campos, Kathrin Jansen, Jason Turner, Jennifer Marshall, Mustafa Attar, Loriane Savary, Harris Perlman, Francesca Barone, Helen McGettrick, Douglas Fearon, Kevin Wei, Soumya Raychaudhuri, Ilya Lorsunsky, Michael Brenner, Mark Coles, Stephen Sansom, Andrew Filer, Christopher D Buckley. BioRxiv: https://doi.org/10.1101/374330
Bioinformatics, Statistics and Computational Biology; Genes, Genetics, Epigenetics and Genomics; Immunology; Musculoskeletal Science; Translational Medicine and Medical Technology