Baillie lab, Roslin Institute, University of Edinburgh
If you like what we do, and you think you could contribute, please get in touch. Jobs and PhD studentships become available from time to time and we'll post them here, but if there are good candidates out there then it helps to know about them. We're always looking for talented people - we can help you write fellowship applications or try to find support from other sources.
Supervisors: Dr JK Baillie (Roslin Institute/Royal Infirmary), Prof. C Haley (Institute for Genetics and Molecular Medicine/Roslin Institute)
The unprecedented access to genome-wide association (GWAS) signals for a wide variety of human diseases opens up new opportunities to improve understanding of the underlying mechanisms of disease and identify new therapies. We have developed statistical and bioinformatic approaches to collate this information and draw robust inferences about disease mechanisms from public data.1
In our previous work, we demonstrated that many biological pathways can be detected from expression patterns in high-resolution transcriptomic data2, we interrogated shared activity patterns (i.e. coexpression) arising from regulatory regions containing variants associated with inflammatory bowel disease. Our re-analysis of two large GWAS studies reveals two distinct groups of variants associated with both Crohn’s disease and ulcerative colitis. This discovery may indicate two distinct mechanisms underlying each disease. Alternatively, it may indicate the existence of two distinct endotypes3 of each condition. It is at least plausible, and in our opinion probable, that patients with a preponderance of ‘immune’ or ‘epithelial’ genetic variants will respond differently to immunomodulatory therapies.
The student will develop the computational and statistical tools to detect and validate mechanistic relationships between diseases for which GWAS data are available (340 diseases at the time of writing).
This will form several distinct stages which will overlap in time during the course of the PhD:
Optimisation of coexpression methodology for high-performance computing and incorporation of data from different sources including GTEx, Roadmap Epigenetics and ENCODE.
Training outcomes: process optimisation, parallelisation, SQL database construction and usage, handling large files
for evaluation of disease-disease interactions, including linkage disequilibrium score regression, genomic correlation and coexpression analysis.
Training outcomes: statistics, quantitative genetics, regression modelling
Re-analyses of published and ongoing GWAS studies, including UK biobank, will be performed to detect distinct biological pathways underlying clinical phenotypes. Candidates will be chosen for further validation, in large population studies or clinical trials where genotyping data are available. Biological validation of specific mechanistic hypotheses will be performed in genome-editing experiments collaboration with wet-lab scientists in the Baillie lab (myeloid cells, endothelial cells) and others (hepatocytes, epithelial cells, iPSC-derived primary cells).
Training outcomes: collaboration, hypothesis testing, academic writing
Applications should be made through the University of Edinburgh application system.
Application deadline is Monday, January 07, 2019.
We are very grateful to recieve funding from the following sources: Wellcome Trust, BBSRC, Intensive Care Society, MRC, NIH.