Key result
A combined approach of RNA-seq, targeted long-read sequencing, and in silico prediction successfully identified pathogenic intronic variants and complex splicing abnormalities in all 20 (100%) genetically undiagnosed dystrophinopathy patients.
Why the study?
Approximately 1% of patients with dystrophinopathy remain genetically undiagnosed because standard methods do not detect intronic variations in DMD.
Cross-Sectional (n=20)
Yes
A combined approach of RNA-seq, targeted long-read sequencing, and in silico prediction successfully identified pathogenic intronic variants in 100% of previously genetically undiagnosed dystrophinopathy patients.
This is the authors' abstract. We don't add key points for this paper.
Dystrophinopathy is caused by alterations in DMD. Approximately 1% of patients remain genetically undiagnosed because intronic variations are not detected by standard methods. Here, we combined laboratory and in silico analyses to identify disease-causing genomic variants in genetically undiagnosed patients and determine the regulatory mechanisms underlying abnormal DMD transcript generation. DMD transcripts from 20 genetically undiagnosed dystrophinopathy patients in whom no exon variants were identified, despite dystrophin deficiency on muscle biopsy, were analyzed by transcriptome sequencing. Genome sequencing captured intronic variants and their effects were interpreted using in silico tools. Targeted long-read sequencing was applied in cases with suspected structural genomic abnormalities. Abnormal DMD transcripts were detected in all cases analyzed. Exonization of intronic sequences was observed in 15 cases and exon skipping in one case; 13 single nucleotide variants and three structural rearrangements were identified as causal genomic variations. DMD transcripts were aberrantly spliced and polyadenylated in two cases in which chromosome rearrangements were detected. In one case, DMD transcripts were terminated due to nucleotide repeat expansion. Our combined analysis approach successfully identified pathogenic events. Detection of diseasing-causing mechanisms in DMD transcripts could inform the therapeutic options for patients with dystrophinopathy.
May aid molecular diagnosis in select undiagnosed dystrophinopathy cases; leaves open validation and broader applicability.
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Okubo et al. (2022) conducted a cross-sectional in Genetically undiagnosed dystrophinopathy (n=20). Combined RNA-seq, targeted long-read sequencing, and in silico prediction was evaluated on Detection of abnormal DMD transcripts and pathogenic genomic variants. A combined approach of RNA-seq, targeted long-read sequencing, and in silico prediction successfully identified pathogenic intronic variants and complex splicing abnormalities in all 20 (100%) genetically undiagnosed dystrophinopathy patients.
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