Type II Diabetes Study

As our lifestyle and diets change, the prevalence of Type 2 Diabetes (T2D) around the world is increasing. An improved understanding of the genetic basis of the disease is vital if we are to uncover the mechanisms involved in diabetes development and to improve the approaches for prevention and treatment.

Working as part of an international consortium of leaders in the field of T2D research, the Oxford Genomics Centre has supported the efforts of the GoT2D (Genetics of Type 2 diabetes) consortium. This project, funded by the NIH and the Wellcome Trust, is led by Professor Mark McCarthy in Oxford and colleagues in the US and Europe (including David Altshuler at the Broad Institute and Mike Boehnke at the University of Michigan) and has completed low-pass whole genome sequencing, deep exome sequencing and dense array genotyping of ~2800 T2D cases and controls of Northern European origin. As well as enumerating the contribution of low frequency and rare variants to the pathogenesis of type 2 diabetes, this project seeks to explore the relative merits of these different approaches to risk variant discovery and to develop novel statistical and analytical tools for the analyses of such data.

Finding the Causative Mutation in a 4-Year Old Patient With Craniosynostosis

The Oxford Genomics Centre have been involved in a collaboration to sequence 500 whole genomes.

The first example of just how powerful this project will be was when one of Professor Andrew Wilkie's patients and her parents were sequenced to help to find the mutation causing her craniosynostosis. The patient was found to have a likely pathogenic single nucleotide change in the X-linked gene HUWE1 that was not present in either of her parents. Knowing the causative mutation will guide the genetic counselling that the family receives.

UKCRC Modernising Medical Microbiology Consortium- Using the MiSeq

Whilst participating in the MiSeq early access program, there was a suspected outbreak in a local hospital. We had an urgent need to obtain genomic data on the bacteria very quickly so we used the MiSeq; generating data in less than five days. This enabled the hospital to rapidly determine if there was a common source of bacteria. The power of this machine and the ability to help in a situation like this was pretty exciting. You can get to results very, very quickly.

Annie Cavanagh, Wellcome Images^®