Cookies on this website

We use cookies to ensure that we give you the best experience on our website. If you click 'Accept all cookies' we'll assume that you are happy to receive all cookies and you won't see this message again. If you click 'Reject all non-essential cookies' only necessary cookies providing core functionality such as security, network management, and accessibility will be enabled. Click 'Find out more' for information on how to change your cookie settings.

Project Overview

The pathogenesis of chronic inflammatory diseases such as irritable bowel disease (IBD), ankylosing spondylitis and vasculitis involves a complex interplay between the host immune system, genetic and environmental factors. As an example, in IBD's such as Crohn's Disease and Ulcerative Colitis, circulating immune cell populations migrate into the intestine where they can differentiate and adopt pro- or anti-inflammatory states. In a recent breakthrough, we uncovered a role for the pro-inflammatory transcription factor IRF51 in a mouse model of intestinal inflammation using a reverse-genetics approach. Following such observations, we are generating population and single-cell genomics data to dissect the functions of immune cell populations and candidate factors during chronic inflammation.

In this project, you will apply the latest computational methods to data from cutting-edge functional genomics techniques2 in order to study the cell types, states, pathways and genes responsible for sustaining inflammation. Working closely with experimental colleagues you will design follow-up experiments and test hypotheses using the latest massively-parallel droplet-based single-cell RNA-seq approaches. The translational relevance of significant findings will be assessed using samples from human patients - ultimately this research aims to inform the identification of context-specific pathways and factors as targets for selective therapies in inflammatory disease

Training Opportunities

Housed in a brand-new research facility, which includes a state-of-the-art high performance compute cluster, the Kennedy Institute is world famous for its discovery of anti-TNF therapy for the treatment of rheumatoid arthritis. Students will become fluent in computational genomics and acquire an expert understanding of the immune system. Trainees will become proficient in programming in languages such as Python and R, learn to design and write pipelines for genomics analysis and to apply the latest analysis algorithms. They will gain skills in statistical data analysis and visualisation, have the opportunity to utilise machine learning approaches and will perform integrated analyses with "big data" from sources such as the ENCODE and ImmGen projects. Students will be encouraged to develop a close understanding of experimental research - for example by regular attendance of wet-lab group meetings - and will have the opportunity to be closely involved in the generation of functional genomics data. In addition to hands on training, students will attend courses at the neighbouring Wellcome Trust Centre for Human Genetics, more broadly across the University and externally and online as appropriate. They will be expected to present their research at internal group meetings and seminars and to disseminate their findings at national and international scientific conferences. 

Relevant Publications

  1. IRF5 promotes inflammatory macrophage polarization and TH1-TH17 responses. Krausgruber T, Blazek K, Smallie T, Alzabin S, Lockstone H, Sahgal N, Hussell T, Feldmann M, Udalova IA. Nat Immunol. 2011.
  2. Population and single cell genomics reveal the Aire-dependency, relief from Polycomb silencing and distribution of self-antigen expression in thymic epithelia. Stephen N. Sansom, Noriko Shikama-Dorn, Saule Zhanybekova2, Gretel Nusspaumer, Iain C. Macaulay, Mary E. Deadman, Andreas Heger, Chris P. Ponting, Georg A. Holländer. Genome Research, 2014

Scientific Themes

Bioinformatics, Statistics and Computational Biology; Genes, Genetics, Epigenetics and Genomics; Immunology; Musculoskeletal Science; Translational Medicine and Medical Technology.

Further information

Dr Stephen Sansom, Kennedy Institute, University of Oxford

Professor Irina Udalova,  Kennedy Institute, University of Oxford

Project reference number #201712


study with us