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Gonorazky HD, Naumenko S, Ramani AK, Nelakuditi V, Mashouri P, Wang P, Kao D, Ohri K, Viththiyapaskaran S, Tarnopolsky MA, Mathews KD, Moore SA, Osorio AN, Villanova D, Kemaladewi DU, Cohn RD, Brudno M, Dowling JJ. Expanding the Boundaries of RNA Sequencing as a Diagnostic Tool for Rare Mendelian Disease. Am J Hum Genet 2019; 104:1007. [PMID: 31051109 DOI: 10.1016/j.ajhg.2019.04.004] [Citation(s) in RCA: 41] [Impact Index Per Article: 8.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/26/2022] Open
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Gonorazky HD, Naumenko S, Ramani AK, Nelakuditi V, Mashouri P, Wang P, Kao D, Ohri K, Viththiyapaskaran S, Tarnopolsky MA, Mathews KD, Moore SA, Osorio AN, Villanova D, Kemaladewi DU, Cohn RD, Brudno M, Dowling JJ. Expanding the Boundaries of RNA Sequencing as a Diagnostic Tool for Rare Mendelian Disease. Am J Hum Genet 2019; 104:466-483. [PMID: 30827497 PMCID: PMC6407525 DOI: 10.1016/j.ajhg.2019.01.012] [Citation(s) in RCA: 138] [Impact Index Per Article: 27.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2018] [Accepted: 01/22/2019] [Indexed: 02/06/2023] Open
Abstract
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.
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Affiliation(s)
- Hernan D Gonorazky
- Division of Neurology, the Hospital for Sick Children, Toronto, ON M5G 1X8, Canada; Program in Genetics and Genome Biology, Research Institute, the Hospital for Sick Children, Toronto, ON M5G 0A4, Canada
| | - Sergey Naumenko
- Centre for Computational Medicine, the Hospital for Sick Children, Toronto, ON M5G 1X8, Canada
| | - Arun K Ramani
- Centre for Computational Medicine, the Hospital for Sick Children, Toronto, ON M5G 1X8, Canada
| | - Viswateja Nelakuditi
- Centre for Computational Medicine, the Hospital for Sick Children, Toronto, ON M5G 1X8, Canada
| | - Pouria Mashouri
- Centre for Computational Medicine, the Hospital for Sick Children, Toronto, ON M5G 1X8, Canada
| | - Peiqui Wang
- Centre for Computational Medicine, the Hospital for Sick Children, Toronto, ON M5G 1X8, Canada
| | - Dennis Kao
- Centre for Computational Medicine, the Hospital for Sick Children, Toronto, ON M5G 1X8, Canada
| | - Krish Ohri
- Department of Molecular Genetics, University of Toronto, Toronto, ON M5G 1X8, Canada
| | | | - Mark A Tarnopolsky
- Department of Pediatrics, McMaster University, Hamilton, ON L8S 4L8, Canada
| | - Katherine D Mathews
- Departments of Pediatrics and Neurology, University of Iowa Carver College of Medicine, Iowa City, IA 52242, USA
| | - Steven A Moore
- Department of Pathology, University of Iowa Carver College of Medicine, Iowa City, IA 52242, USA
| | - Andres N Osorio
- Neuromuscular Unit, Neuropaediatrics Department, Institut de Recerca Hospital Universitari Sant Joan de Deu, Barcelona 08950, Spain; Center for the Biomedical Research on Rare Diseases (CIBERER), Instituto de Salud Carlos III (ISCIII), Barcelona 08950, Spain
| | - David Villanova
- GenomicTales Parc de la Mola, 10, AD700 Escaldes-Engordany, Andorra
| | - Dwi U Kemaladewi
- Program in Genetics and Genome Biology, Research Institute, the Hospital for Sick Children, Toronto, ON M5G 0A4, Canada
| | - Ronald D Cohn
- Department of Molecular Genetics, University of Toronto, Toronto, ON M5G 1X8, Canada; Program in Genetics and Genome Biology, Research Institute, the Hospital for Sick Children, Toronto, ON M5G 0A4, Canada
| | - Michael Brudno
- Centre for Computational Medicine, the Hospital for Sick Children, Toronto, ON M5G 1X8, Canada; Program in Genetics and Genome Biology, Research Institute, the Hospital for Sick Children, Toronto, ON M5G 0A4, Canada; Department of Computer Science, University of Toronto, Toronto, ON M5G 0A4, Canada.
| | - James J Dowling
- Division of Neurology, the Hospital for Sick Children, Toronto, ON M5G 1X8, Canada; Department of Molecular Genetics, University of Toronto, Toronto, ON M5G 1X8, Canada; Program in Genetics and Genome Biology, Research Institute, the Hospital for Sick Children, Toronto, ON M5G 0A4, Canada.
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