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.

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).

IMPORTANCETo our knowledge, the efficacy of transferring next-generation sequencing from a research setting to neuromuscular clinics has never been evaluated.OBJECTIVE To translate whole-exome sequencing (WES) to clinical practice for the genetic diagnosis of a large cohort of patients with limb-girdle muscular dystrophy (LGMD) for whom protein-based analyses and targeted Sanger sequencing failed to identify the genetic cause of their disorder. DESIGN, SETTING, AND PARTICIPANTSWe performed WES on 60 families with LGMDs (100 exomes). Data analysis was performed between January 6 and December 19, 2014, using the xBrowse bioinformatics interface (Broad Institute). Patients with LGMD were ascertained retrospectively through the Institute for Neuroscience and Muscle Research Biospecimen Bank between 2006 and 2014. Enrolled patients had been extensively investigated via protein studies and candidate gene sequencing and remained undiagnosed. Patients presented with more than 2 years of muscle weakness and with dystrophic or myopathic changes present in muscle biopsy specimens. MAIN OUTCOMES AND MEASURESThe diagnostic rate of LGMD in Australia and the relative frequencies of the different LGMD subtypes. Our central goals were to improve the genetic diagnosis of LGMD, investigate whether the WES platform provides adequate coverage of known LGMD-related genes, and identify new LGMD-related genes.RESULTS With WES, we identified likely pathogenic mutations in known myopathy genes for 27 of 60 families. Twelve families had mutations in known LGMD-related genes. However, 15 families had variants in disease-related genes not typically associated with LGMD, highlighting the clinical overlap between LGMD and other myopathies. Common causes of phenotypic overlap were due to mutations in congenital muscular dystrophy-related genes (4 families) and collagen myopathy-related genes (4 families). Less common myopathies included metabolic myopathy (2 families), congenital myasthenic syndrome (DOK7), congenital myopathy (ACTA1), tubular aggregate myopathy (STIM1), myofibrillar myopathy (FLNC), and mutation of CHD7, usually associated with the CHARGE syndrome. Inclusion of family members increased the diagnostic efficacy of WES, with a diagnostic rate of 60% for "trios" (an affected proband with both parents) vs 40% for single probands. A follow-up screening of patients whose conditions were undiagnosed on a targeted neuromuscular disease-related gene panel did not improve our diagnostic yield. CONCLUSIONS AND RELEVANCEWith WES, we achieved a diagnostic success rate of 45.0% in our difficult-to-diagnose cohort of patients with LGMD. We expand the clinical phenotypes associated with known myopathy genes, and we stress the importance of accurate clinical examination and histopathological results for interpretation of WES, with many diagnoses requiring follow-up review and ancillary investigations of biopsy specimens or serum samples.