Understanding the impact of 'near-coding' variation in human disease

Over 250 million people globally have a rare disease. For these individuals, and their families, identifying the exact genetic variant that causes the disease has enormous value for diagnosis, screening and personalised treatment. This knowledge can also reveal the biology behind why the disease developed, suggesting new therapeutic strategies. Current clinical screening approaches are limited in the regions of DNA they assess, only looking at those that directly encode proteins. These methods identify disease-causing variants in only ~50% of patients. I aim to improve our understanding of genetic variants outside of these protein-coding regions to identify those that cause rare disease. I will do this by applying state-of-the-art statistical and computational approaches to large datasets of individuals with and without rare disease. This work will inform clinical genetic testing guidelines, enable more patients to receive a valuable genetic diagnosis, and improve our understanding of the genetic mechanisms leading to disease.