Format

Send to

Choose Destination
Sci Transl Med. 2017 Apr 19;9(386). pii: eaal5209. doi: 10.1126/scitranslmed.aal5209.

Improving genetic diagnosis in Mendelian disease with transcriptome sequencing.

Author information

1
Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA 02114, USA.
2
Medical and Population Genetics, Broad Institute of Massachusetts Institute of Technology and Harvard, Cambridge, MA 02142, USA.
3
Program in Biological and Biomedical Sciences, Harvard Medical School, Boston, MA 02115, USA.
4
School of Paediatrics and Child Health, University of Sydney, Sydney, New South Wales 2006, Australia.
5
Institute for Neuroscience and Muscle Research, Kids Research Institute, The Children's Hospital at Westmead, Sydney, New South Wales 2145, Australia.
6
Neuromuscular and Neurogenetic Disorders of Childhood Section, Neurogenetics Branch, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD 20892, USA.
7
Division of Genetics and Genomics, Manton Center for Orphan Disease Research, Boston Children's Hospital, Harvard Medical School, Boston, MA 02115, USA.
8
Division of Pediatric Neurology, Department of Pediatrics, University of Florida College of Medicine, Gainesville, FL 32610, USA.
9
Dubowitz Neuromuscular Centre, University College London Institute of Child Health, London WC1N 1EH, U.K.
10
Division of Neurology, Hospital for Sick Children, Toronto, Ontario M5G 1X8, Canada.
11
Department of Neurology, University Hospitals Leuven and University of Leuven (Katholieke Universiteit Leuven), Leuven 3000, Belgium.
12
Department of Diagnostic Genomics, PathWest Laboratory Medicine, Perth, Western Australia 6009, Australia.
13
Harry Perkins Institute of Medical Research, University of Western Australia, Perth, Western Australia 6009, Australia.
14
John Walton Muscular Dystrophy Research Centre, MRC (Medical Research Council) Centre for Neuromuscular Diseases, Institute of Genetic Medicine, Newcastle University, Newcastle upon Tyne NE1 3BZ, U.K.
15
Murdoch Childrens Research Institute, Royal Children's Hospital, Parkville, Melbourne, Victoria 3052, Australia.
16
Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA 02114, USA. danmac@broadinstitute.org.

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.

PMID:
28424332
PMCID:
PMC5548421
DOI:
10.1126/scitranslmed.aal5209
[Indexed for MEDLINE]
Free PMC Article

Supplemental Content

Full text links

Icon for HighWire Icon for PubMed Central
Loading ...
Support Center