Finding pathways central to the pathogenesis of T2D through the integration of genetic and genomic data

Novel therapeutic strategies need to be informed by a more complete understanding of the molecular and physiological basis of type 2 diabetes, designed to deliver validated interventional targets and biomarkers that can be used to define disease risk, progression, and subtype. We are using human genetics to deliver this understanding, and, working as part of large global consortia have interrogated several large genetic resources (~800,000 samples with GWAS and exome array data; ~40,000 with exome sequence data; several thousand whole genome sequences), and have contributed to identification of >100 T2D-associated regions. We are currently leading efforts to perform a massive transethnic analysis of T2D association, involving GWAS data from >1M individuals, which will define additional regions associated with T2D and further refine the location of the variants driving disease risk. Most of these will map to regulatory sequence, and most seem to act through perturbation of pancreatic islet function.

To define the molecular and cellular processes through which these risk variants act, we have been establishing a detailed genomic map of islet regulatory features incorporating RNA-Seq, ChiP-Seq, ATAC-Seq, Methylation-Seq and Capture-C conformational capture. By intersecting these data with the genetic maps, we are now in a position to highlight the processes which underlying T2D predisposition. The acquisition of richer genetic and genomic information continues, and this DPhil project will involve analysis of these growing genetic and genomic data sets and the systematic identification of key processes involved in the development of T2D. This work is funded by the Wellcome Trust and the US National Institutes of Health.

The DPhil project will involve several components:

Analysis of the transethnic GWAS data sets described above, to identify new signals, and to fine-map others;
Analysis and interpretation of additional islet genomic data (e.g. from conformational capture studies) and integration with the genetic data
The identification of regulatory elements that are globally enriched for T2D association signals, as well as those that are likely to be perturbed at individual loci
Design and implementation of follow-up studies.

The DPhil would be based primarily at the Wellcome Trust Centre for Human Genetics but with strong interactions with colleagues at the Oxford Centre for Diabetes Endocrinology and Metabolism (Anna Gloyn, Fredrik Karpe) and the Weatherall Institute of Molecular Medicine (Doug Higgs, Jim Hughes). The student will receive training in diverse aspects of complex trait genetics, and will benefit from the strong computational and statistical focus of the WTCHG, and the expertise in molecular and cellular work at the WIMM and OCDEM. They will also have the opportunity, through existing collaborations to interact with other leading groups in human genetics. Through the strong network of diabetes collaborators in Oxford and beyond the student will be well-placed to further develop their understanding of related biology.

The core of the project is computational and statistical and the student will deploy and develop their skills in the management of complex large biomedical and genomic data sets. Depending on interest and aptitude, the student will have the possibility to pursue follow-up of the findings that emerge in a variety of alternative directions, through a focus on the application of in silico methods (bioinformatics), the generation of additional genomic data, and/or empirical functional studies.

This project provides an opportunity for a highly-motivated student with good computational and analytical skills, and an interest in human biology, to train in one of the internationally-leading centres at a uniquely-exciting time in the development of human genetics.