Identifying low frequency and rare genetic variation involved in type 2 diabetes using next generation sequencing data. (360G-Wellcome-092447_Z_10_Z)

To answer my research question, I will utilize the following datasets: Dataset 1: Whole genome sequence from 1500 Type 2 diabetes patients and 1500 characterised controls at 4 fold coverage. Dataset 2: Targeted sequencing of 50-200 selected genes from 480 young onset diabetes patients and 480 normo-glycaemic controls, at 50 fold coverage. Dataset 3: Variant data from the publicly available 1000 genomes project My project will then proceed in four stages. In Stage 1 I will use NGS data fr om datasets 1-3 to identify low frequency and rare variants in the coding regions of selected candidate genes. In Stage 2 I will annotate these variants including their likely functional effect and genomic context. In Stage 3 I will prioritise variants for follow up using a combination of criteria including nominal association (p < 0.05). In Stage 4 I will follow up prioritised rare variants by genotyping in additional samples of up to 50,000 cases and equivalent numbers of controls. I will also t est the impact these variants have on beta-cell function and insulin resistance in well phenotyped non-diabetic cohorts. My fellowship will improve understanding of biological mechanisms involved in diabetes and may lead to stratification of individuals for treatment or preventative measures.