RAPID: A Targeted Long-Read RNA Workflow for Functional Resolution of Splicing Variants in Rare Disease
Montgomery, K.-a.; Macpherson, H.; Anderson, C.; Wade, C.; Gustavsson, E. K.; Lynch, D. S.; Wilson, L. C.; Davison, J.; Wakeling, E.; Tuschl, K.; Houlden, H.; Clement, E.; Mills, P.; Ryten, M.
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BackgroundMolecular diagnosis of rare disease plateaus at [~]50%, partly due to technical limitations of short-read sequencing and the persistent challenge of interpreting variants of uncertain significance (VUS). Splice-altering variation represents a major source of unresolved cases, yet functional assessment remains difficult in routine practice. MethodsWe developed a fully modular, sample-to-answer workflow for targeted long-read RNA sequencing (lrRNA-seq) using Oxford Nanopore Technologies and applied it to six unsolved cases with suspected monogenic neurometabolic disease. Candidates were selected after WES/WGS and multidisciplinary team review (MDT) indicating [≤]5 genes of interest. The workflow was designed to be diagnostically deployable, enabling near-full-length transcript assessment from accessible tissues without reliance on large control cohorts. ResultslrRNA-seq yielded actionable findings for all six probands. It confirmed pathogenic splice disruption in two cases, prompted gene exclusion in one case, and generated RNA-level evidence prioritising further DNA investigation in three cases. Across these scenarios, lrRNA-seq provided direct, mechanism-level insight that either resolved diagnosis or refined variant interpretation. The workflow provided near-full-length isoform structures with reproducible single-sample interpretation and produced informative results within two working days at <{pound}500 per sample reagent cost. ConclusionTargeted lrRNA-seq offers rapid, cost-effective functional evidence to resolve VUS, direct DNA follow-up, and support timely diagnosis in rare disease. The RAPID workflow demonstrates that long-read RNA sequencing can be implemented within existing diagnostic infrastructure and provides a scalable route to routine transcript-level assessment in clinical genomics.
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