Transcriptome-based variant calling and aberrant mRNA discovery enhance diagnostic efficiency for neuromuscular diseases

Sung Eun Hong(Seoul National University), Jana Kneissl(Seoul National University), Anna Cho(Seoul National University Bundang Hospital), Man Jin Kim(Seoul National University), Soojin Park(Seoul National University Children's Hospital), J. Lee(Seoul National University), Sijae Woo(Korea Advanced Institute of Science and Technology), Sora Kim(Gachon University), Jun‐Soon Kim(Seoul National University), Soo Yeon Kim(Gachon University), Sungwon Jung(Gachon University), Jin‐Kuk Kim(Seoul National University), Je-Young Shin(Seoul National University), Jong‐Hee Chae(Seoul National University), Murim Choi(Seoul National University)
Journal of Medical Genetics
April 6, 2022
Cited by 19Open Access
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Abstract

Background Whole-exome sequencing-based diagnosis of rare diseases typically yields 40%–50% of success rate. Precise diagnosis of the patients with neuromuscular disorders (NMDs) has been hampered by locus heterogeneity or phenotypic heterogeneity. We evaluated the utility of transcriptome sequencing as an independent approach in diagnosing NMDs. Methods The RNA sequencing (RNA-Seq) of muscle tissues from 117 Korean patients with suspected Mendelian NMD was performed to evaluate the ability to detect pathogenic variants. Aberrant splicing and CNVs were inspected to identify additional causal genetic factors for NMD. Aberrant splicing events in Dystrophin (DMD) were investigated by using antisense oligonucleotides (ASOs). A non-negative matrix factorisation analysis of the transcriptome data followed by cell type deconvolution was performed to cluster samples by expression-based signatures and identify cluster-specific gene ontologies. Results Our pipeline called 38.1% of pathogenic variants exclusively from the muscle transcriptomes, demonstrating a higher diagnostic rate than that achieved via exome analysis (34.9%). The discovery of variants causing aberrant splicing allowed the application of ASOs to the patient-derived cells, providing a therapeutic approach tailored to individual patients. RNA-Seq data further enabled sample clustering by distinct gene expression profiles that corresponded to clinical parameters, conferring additional advantages over exome sequencing. Conclusion The RNA-Seq-based diagnosis of NMDs achieves an increased diagnostic rate and provided pathogenic status information, which is not easily accessible through exome analysis.


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