Exome and whole-genome sequencing are becoming increasingly routine approaches in Mendelian disease diagnosis. Despite their success, the current diagnostic rate for genomic analyses across a variety of rare diseases is approximately 25 to 50%. We explore the utility of transcriptome sequencing [RNA sequencing (RNA-seq)] as a complementary diagnostic tool in a cohort of 50 patients with genetically undiagnosed rare muscle disorders. We describe an integrated approach to analyze patient muscle RNA-seq, leveraging an analysis framework focused on the detection of transcript-level changes that are unique to the patient compared to more than 180 control skeletal muscle samples. We demonstrate the power of RNA-seq to validate candidate splice-disrupting mutations and to identify splice-altering variants in both exonic and deep intronic regions, yielding an overall diagnosis rate of 35%. We also report the discovery of a highly recurrent de novo intronic mutation in COL6A1 that results in a dominantly acting splice-gain event, disrupting the critical glycine repeat motif of the triple helical domain. We identify this pathogenic variant in a total of 27 genetically unsolved patients in an external collagen VI–like dystrophy cohort, thus explaining approximately 25% of patients clinically suggestive of having collagen VI dystrophy in whom prior genetic analysis is negative. Overall, this study represents a large systematic application of transcriptome sequencing to rare disease diagnosis and highlights its utility for the detection and interpretation of variants missed by current standard diagnostic approaches.

Gene-panel and whole-exome analyses are now standard methodologies for mutation detection in Mendelian disease. However, the diagnostic yield achieved is at best 50%, leaving the genetic basis for disease unsolved in many individuals. New approaches are thus needed to narrow the diagnostic gap. Whole-genome sequencing is one potential strategy, but it currently has variant-interpretation challenges, particularly for non-coding changes. In this study we focus on transcriptome analysis, specifically total RNA sequencing (RNA-seq), by using monogenetic neuromuscular disorders as proof of principle. We examined a cohort of 25 exome and/or panel “negative” cases and provided genetic resolution in 36% (9/25). Causative mutations were identified in coding and non-coding exons, as well as in intronic regions, and the mutational pathomechanisms included transcriptional repression, exon skipping, and intron inclusion. We address a key barrier of transcriptome-based diagnostics: the need for source material with disease-representative expression patterns. We establish that blood-based RNA-seq is not adequate for neuromuscular diagnostics, whereas myotubes generated by transdifferentiation from an individual’s fibroblasts accurately reflect the muscle transcriptome and faithfully reveal disease-causing mutations. Our work confirms that RNA-seq can greatly improve diagnostic yield in genetically unresolved cases of Mendelian disease, defines strengths and challenges of the technology, and demonstrates the suitability of cell models for RNA-based diagnostics. Our data set the stage for development of RNA-seq as a powerful clinical diagnostic tool that can be applied to the large population of individuals with undiagnosed, rare diseases and provide a framework for establishing minimally invasive strategies for doing so.

One Sentence Summary: Transcriptome sequencing improves the diagnostic rate for Mendelian disease in patients for whom genetic analysis has not returned a diagnosis. AbstractExome and whole-genome sequencing are becoming increasingly routine approaches in Mendelian disease diagnosis. Despite their success, the current diagnostic rate for genomic analyses across a variety of rare diseases is approximately 25-50%. Here, we explore the utility of transcriptome sequencing (RNA-seq) as a complementary diagnostic tool in a cohort of 50 patients with genetically undiagnosed rare muscle disorders. We describe an integrated approach to analyze patient muscle RNA-seq, leveraging an analysis framework focused on the detection of transcript-level changes that are unique to the patient compared to over 180 control skeletal muscle samples. We demonstrate the power of RNA-seq to validate candidate splice-disrupting mutations and to identify splice-altering variants in both exonic and deep intronic regions, yielding an overall diagnosis rate of 35%. We also report the discovery of a highly recurrent de novo intronic mutation in COL6A1 that results in a dominantly acting splice-gain event, disrupting the critical glycine repeat motif of the triple helical domain. We identify this pathogenic variant in a total of 27 genetically unsolved patients in an external collagen VI-like dystrophy cohort, thus explaining approximately 25% of patients clinically suggestive of collagen VI dystrophy in whom prior genetic analysis is negative. Overall, this study represents a large systematic application of transcriptome sequencing to rare disease diagnosis and highlights its utility for the detection and interpretation of variants missed by current standard diagnostic approaches. IntroductionThe advent of exome (WES) and whole genome (WGS) sequencing has greatly accelerated our capacity to identify variants that explain many Mendelian diseases in both known and new disease genes. While these technologies are mainstays in Mendelian disease diagnosis, their success rate for detecting causal variants is far from complete, ranging from 25-50% (1-4). The primary challenge of these genome-based diagnostics is that the capacity of WES and WGS to discover genetic variants substantially exceeds our ability to interpret their functional and clinical impact (5-7).

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