RAPID: a targeted long-read RNA workflow for functional resolution of splicing variants in rare disease | LC26
- shared.published_on: May 19 2026
Abstract
Molecular diagnosis of rare disease plateaus at approximately 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. We 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 whole-exome sequencing/whole-genome sequencing (WES/WGS) and multidisciplinary team review 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. Long-read RNA sequencing yielded actionable findings for all six probands. We 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 <£500 per sample reagent cost. In conclusion, targeted 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.
Biography
Kylie Montgomery is a PhD candidate working at the interface of genomics, rare disease, and functional variant interpretation. Her work focuses on developing diagnostically deployable long-read sequencing workflows, with particular emphasis on transcriptome sequencing and splice-altering variation. Kylie is interested in translating advanced sequencing technologies into routine clinical practice, improving resolution of variants of uncertain significance, and bridging wet-lab, computational, and clinical genomics to increase diagnostic yield in unsolved genetic disease.
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