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Unraveling missing variants through target capture-based long-read sequencing in autosomal recessive disorders.

Jul 2026 · European Journal of Human Genetics · 0 citations · 25 references
Medicine

TL;DR

It is demonstrated that target capture-based LRS effectively detects diverse types of variants missed by SRS, and integrating this assay into stepwise diagnostic workflows offers a practical and cost-effective strategy to enhance diagnostic yield in autosomal recessive diseases.

Abstract

Short-read sequencing (SRS)-based disease-targeted NGS gene panels have revolutionized rare disease diagnostics but often leave autosomal recessive cases unsolved when only one pathogenic allele is detected. Missing variants may reside in deep intronic regions or involve structural variants (SVs) undetectable by SRS. To improve diagnostic yield, we implemented a cost-effective target capture-based long-read sequencing (LRS) assay covering 56 genes and retrospectively analyzed 78 patients suspected of autosomal recessive disorders who remained undiagnosed after SRS. Functional validation using reverse transcription PCR (RT-PCR) and minigene assays was performed to further determine pathogenicity. Target capture-based LRS solved 25.6% (20/78) of cases by identifying 10 SVs, 3 deep intronic variants experimentally confirmed to cause aberrant splicing, and 7 cases in which haplotype phasing confirmed that variants were in trans with the known pathogenic variant, leading to reclassification of the VUS as likely pathogenic. This study demonstrates that target capture-based LRS effectively detects diverse types of variants missed by SRS. Integrating this assay into stepwise diagnostic workflows offers a practical and cost-effective strategy to enhance diagnostic yield in autosomal recessive diseases. However, because this cohort was retrospectively defined based on a prior single-allele detection by SRS, this 25.6% (20/78) diagnostic yield reflects performance within a highly enriched population and should not be directly extrapolated to unselected rare disease cohorts.

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