Methods for improving clinical diagnostic by detection, prediction, interpretation and prioritization of aberrant transcriptome variations

University Of Pennsylvania, Philadelphia PA

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Abstract

The goal of this research program project is to develop methods to improve clinical diagnosis of children with rare Mendelian disorders. Even with the most advanced standard-of-care genetic test of exome sequencing (ES) diagnostic rate is still below 50%. One reason for this rate is that mutations in non-protein coding regions or those that are synonymous (code for the same protein) are generally discarded even though these could be deleterious due to their effect on the processing of RNA transcribed from the underlying gene. We propose 2 complementary methods to help improve clinical diagnosis: The first is ?RNA-first?, where our algorithms suggest which clinically accessible tissue (CAT) to use for RNA sequencing, then compare the results to a larger pool of donors to detect which RNA processing variations may be deleterious. The second is a ?DNA-first? approach where we develop ?RNA splicing code? models that predict the effect of genetic variations on RNA processing in a given tissue of interest. The two approaches, ?RNA-first? and ?DNA-first?, will be combined into a clinical diagnostic pipeline at the Children Hospital of Philadelphia (CHOP) and applied to solve undiagnosed cases at CHOP and other centers, including the NIH?s Undiagnosed Disease Network (UDN).