RNA sequencing uplifts diagnostic rate in undiagnosed rare disease patients

Abstract RNA-sequencing is increasingly being used as a complementary tool to DNA sequencing in diagnostics where DNA analysis has been uninformative as it enables the identification of alternative splicing (AS), aberrant gene expression and allele specific expression. Using RNA from patient blood, we have used both RNA-sequencing and RT-PCR to detect splicing and gene expression outliers in a heterogenous cohort of 87 patients with suspected Mendelian disorders, 38% of which did not have a candidate sequence variant. Expression outliers were detected using OUTRIDER, and we compared the performance of multiple open-source alternative splicing tools (MAJIQ, rMATS-turbo, and LeafCutterMD) in identifying alternative splicing events. As well as clarifying the impact of variants of uncertain significance (VUSs), we trialled two novel approaches to identify new potential diagnoses in patients with no candidate variants. We were able to assess 85% of VUSs and validate splicing abnormalities in 18/48 patients with a VUS. Furthermore, we identified four new diagnoses by detecting novel AS events in patients with no candidate sequence variants from prior genomic DNA testing (n=33) or those in which the candidate VUS did not affect splicing (n=23) and identified one additional diagnosis through detection of skewed X-inactivation. These results gave an overall uplift in diagnostic yield of 26%. In this work we demonstrate the utility of blood-based RNA analysis in improving diagnostic yields and highlight optimal approaches for such analysis.