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RNA-seq in patient derived ex-vivo models: genetic diagnostics beyond whole exomes


Generating solutions




2015 Disruptive Innovation in Genomics Competition

Genome Centre(s)



Project Leader(s)

Fiscal Year Project Launched


Project Description

Phase 1 Project

There are more than 6,000 rare (or orphan) diseases that are caused by mutations in a single gene; together they affect more than 500,000 Canadian children. Exactly what gene is causing a disease is unknown in more than half the cases. Without diagnosis, patients do not have access to optimal clinical care, resulting in tremendous healthcare costs and emotional burden for patients and families. There is a need to develop new strategies for clinical diagnostics, both to identify genetic mutations responsible for undiagnosed diseases and to uncover new causes of genetic disease.

Drs. James Dowling and Michael Brudno, of The Hospital for Sick Children believe that RNAseq, a technology that provides the code, composition and quantity of the RNA material in cells, is the ideal strategy for discovering novel genetic mutations that cause rare disease. RNA differs in all cells of the body (while the genome is the same). The key problem in using RNAseq for clinical diagnostics is the necessity of obtaining the appropriate tissues (e.g., heart, kidney, muscle, brain) that contain the RNAs of interest.  This presents an obvious challenge, particularly in settings where appropriate source material is difficult or impossible to obtain.  To overcome this problem, Dr. Dowling’s lab will build on the recent success at SickKids of creating ex vivo disease models, and use these models in the place of tissue biopsies in order to perform RNAseq for gene mutation discovery. The lab will define the disease contexts (and tissue types) in which RNAseq may be utilized and, as proof of principle, test RNAseq on samples from a cohort of patients with unsolved pediatric genetic disease. Dr. Brudno’s Centre for Computational Medicine will perform the computational analysis of the resulting datasets, and develop new algorithms to identify disease-causing mutations.

The project will determine the ability to use RNAseq as a novel diagnostic tool and as an analytic platform for the genetic diseases for which the technology will be suitable. By combining recent advances in cell biology, genomics and bioinformatics, the lab will develop a new diagnostic methodology, fundamentally transforming the clinical diagnostics process.