ArticleScientific reports2024
Biallelic structural variants in three patients with ERCC8-related Cockayne syndrome and a potential pitfall of copy number variation analysis.
Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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4 citing papers in PubMed.
- Whole-genome discovery of pathogenic snRNA variants and efficient extended-exome screening.iScience · 2026Article
- Augmenting cost-effectiveness in clinical diagnosis using extended whole-exome sequencing: SNVs, SVs, and beyond.Journal of human genetics · 2026Article
- The Converging Roles of Nucleases and Helicases in Genome Maintenance and the Aging Process.Life (Basel, Switzerland) · 2025Review
- A rare variation of ERCC8 gene cause Cockayne syndrome in a Chinese family.Frontiers in genetics · 2025Article
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14 authors.
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Abstract
Cockayne syndrome (CS) is a rare autosomal recessive disorder caused by mutations in ERCC8 or ERCC6. Most pathogenic variants in ERCC8 are single nucleotide substitutions. Structural variants (SVs) have been reported in patients with ERCC8-related CS. However, comprehensive molecular detection, including SVs of ERCC8, in CS patients remains problematic. Herein, we present three Japanese patients with ERCC8-related CS in whom causative SVs were identified using whole-exome-based copy number variation (CNV) detection tools. One patient showed compound heterozygosity for a 259-kb deletion and a deletion of exon 4 which has previously been reported as an Asia-specific variant. The other two patients were homozygous for the same exon 4 deletion. The exon 4 deletion was detected only by the ExomeDepth software. Intrigued by the discrepancy in the detection capability of various tools for the SVs, we evaluated the analytic performance of four whole-exome-based CNV detection tools using an exome data set from 337 healthy individuals. A total of 1,278,141 exons were predicted as being affected by the 4 CNV tools. Interestingly 95.1% of these affected exons were detected by one tool alone. Thus, we expect that the use of multiple tools may improve the detection rate of SVs from aligned exome data.
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