We use computational approaches and large genomic datasets to uncover novel genetic variants that cause rare disease, and understand the mechanisms through which they do so.
Clinical genetic testing has become common place for rare disease patients. Identifying the genetic cause of disease is of huge benefit to both patients and their families; allowing us to screen additional family members to identify those also at risk, return an accurate diagnosis to the patient, and dictate personalised treatment approaches. Through current approaches, however, we only find a genetic diagnosis in around half of all rare disease patients. These approaches almost exclusively focus on the regions of the genome that code directly for proteins.
We believe that a subset of the undiagnosed patients will have genetic variants in regions outside of this protein-coding sequence, that have crucial roles in regulating the amount of proteins that are produced. Our aim is to identify these disease-causing regulatory variants and determine how they lead to disease. By identifying these variants, we hope to influence clinical genetic testing guidelines and allow a valuable genetic diagnosis to be returned to more rare disease patients.
Using population cohorts to identify specific variants in functional non-coding elements that show signals of being under strong negative selection, indicating that they are likely deleterious
Identifying disease-causing non-coding variants in rare disease cases
Assessing the contribution of non-coding variants in enhancer regions linked to known cardiomyopathy (heart muscle disease) genes
Creating tools and resources to improve annotation of functional non-coding variants