Improving genetic diagnosis in Mendelian disease with transcriptome sequencing

Other members of the AWG, Genotype-Tissue Expression Consortium, National Institutes of Health (NIH) Common Fund, iospecimen Collection Source Site-National Disease Research Interchange, Biospecimen Collection Source Site-Roswell Park Cancer Institute, Biospecimen Core Resource-Van Andel Research Institute, Brain Bank Repository-University of Miami, Leidos Biomedical Project Management, Ethical, Legal, and Social Implications Study, Genome Browser Data Integration, and Visualization-European Bioinformatics Institute, Genome Browser Data Integration and Visualization-Genomics Institute, University of California, Santa Cruz:, LDACC-Analysis Working Group (AWG), Funded Statistical Methods groups-AWG, Enhancing GTEx funded Group, NIH/NHGRI, NIH/NCI, NIH/NIMH, NIH/NIDA

Research output: Contribution to journalArticle

Abstract

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. 2017

Original languageEnglish (US)
Article numbereaal5209
JournalScience translational medicine
Volume9
Issue number386
DOIs
StatePublished - Apr 19 2017

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ASJC Scopus subject areas

  • Medicine(all)

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Other members of the AWG, Genotype-Tissue Expression Consortium, National Institutes of Health (NIH) Common Fund, iospecimen Collection Source Site-National Disease Research Interchange, Biospecimen Collection Source Site-Roswell Park Cancer Institute, Biospecimen Core Resource-Van Andel Research Institute, Brain Bank Repository-University of Miami, Leidos Biomedical Project Management, Ethical, Legal, and Social Implications Study, Genome Browser Data Integration, and Visualization-European Bioinformatics Institute, Genome Browser Data Integration and Visualization-Genomics Institute, University of California, Santa Cruz:, LDACC-Analysis Working Group (AWG), Funded Statistical Methods groups-AWG, Enhancing GTEx funded Group, NIH/NHGRI, NIH/NCI, NIH/NIMH, & NIH/NIDA (2017). Improving genetic diagnosis in Mendelian disease with transcriptome sequencing. Science translational medicine, 9(386), [eaal5209]. https://doi.org/10.1126/scitranslmed.aal5209