Hank Cheng, E-21, IsoRanker Connects RNA Data to Rare Disease Discovery

MSTP student, E-21, Hank Cheng, and colleagues developed IsoRanker, a long read RNA sequencing framework that prioritizes transcript abnormalities most likely to cause rare genetic disease.

Using IsoRanker, the Stergachis lab was able to identify disease causing noncoding variants in HARS1 in a previously undiagnosed patient, leading to a diagnosis and the discovery of additional patients with the same condition. Hopefully, this tool will continue to improve the outcomes of patients going forward.

In addition, the study also showed that direct RNA analysis can detect complex molecular effects missed by some DNA based AI prediction models. Overall, Cheng’s findings demonstrate how long read transcriptomics can improve rare disease diagnosis and uncover potential therapeutic targets.

Read the full article here: IsoRanker: Finding the signal in long-read RNA sequencing | Brotman Baty Institute