Rare and low frequency DNA variants and their contribution to developing type 2 diabetes

The recent wave of genome wide association studies has been hugely successful in defining common variants influencing many complex traits. The McCarthy group, with colleagues in Oxford and elsewhere, has played a leading role in such studies, with a particular emphasis on the characterisation of variants influencing risk of type 2 diabetes and obesity (see publications below). These studies have provided many novel insights into the biology of these traits, though the proportion of the genetic variance attributable to variants so far identified remains modest (10 percent at most). The task is now to extend these efforts to reach variants of lower frequency that are likely to have escaped detection by the approaches so far advocated. This project will make use of proprietary, collaborative and public data emerging from a variety of sources including deep resequencing and high-throughput genotyping, functional studies and novel genetic approaches to evaluate the role of such variants in complex trait susceptibility. In particular, the project will benefit from the data being generated through the GoT2D and T2D-GENES projects with which the supervisor is closely involved. These studies have so far accumulated ~4000 whole genome, and ~26000 (55,000 by late 2016) exome sequences, along with exome array data from 450,000 T2D case-control subjects.

The project will have a strong computational and statistical genetics focus, though involvement in experimental design and implementation is encouraged. The student will benefit from a rich network of collaborators and local capacity for large-scale data generation. The student will develop, refine and implement approaches for the integrated analysis of such data, and for the targeted followup of selected variants and genes of interest from a statistical, functional and physiological perspective. For example, as part of the recently awarded MRC Experimental Challenges award to the supervisor and colleagues, we will be in a position to interrogate selected variants using detailed human physiological analysis of subjects recalled on the basis of genotypes of interest, and to integrate these findings with data generated in cellular and animal model systems.