Understanding the impact of ‘near-coding’ variation in human disease (360G-Wellcome-220134_Z_20_Z)

Rare diseases (prevalence <1/2000) collectively affect >250 million people globally. Current approaches for identifying the genetic cause of a disease focus on regions of the genome that code directly for protein, finding a disease-causing variant in only ~50% of cases. My aim is to identify novel genetic variants outside of these protein-coding regions that lead to disease, and the mechanisms through which they do so. I will do this by applying computational and statistical methods to pioneering large-scale genomic datasets, totalling ~700,000 individuals. My approach will focus on ‘near- coding’ regions, defined as those directly adjacent to protein-coding sequence that have important functions regulating protein expression. I will use complementary approaches that (a) look for near-coding variants in rare disease patients without a causative coding variant and (b) assess the strength of negative selection acting on categories of near-coding variants to predict which are deleterious and cause disease. The findings from my work will be translated into clinical care to enable more patients to receive a valuable genetic diagnosis. In addition, increasing our understanding of the near-coding variant types that are deleterious will inform on genetic mechanisms underlying disease and suggest novel therapeutic strategies.