Detection of structural variation using target captured next-generation sequencing data for genetic diagnostic testing

Abstract

PurposeStructural variation (SV) is associated with inherited diseases. Next-generation sequencing (NGS) is an efficient method for SV detection because of its high-throughput, low cost, and base-pair resolution. However, due to lack of standard NGS protocols and a limited number of clinical samples with pathogenic SVs, comprehensive standards for SV detection, interpretation, and reporting are to be established.MethodsWe performed SV assessment on 60,000 clinical samples tested with hereditary cancer NGS panels spanning 48 genes. To evaluate NGS results, NGS and orthogonal methods were used separately in a blinded fashion for SV detection in all samples.ResultsA total of 1,037 SVs in coding sequence (CDS) or untranslated regions (UTRs) and 30,847 SVs in introns were detected and validated. Across all variant types, NGS shows 100% sensitivity and 99.9% specificity. Overall, 64% of CDS/UTR SVs were classified as pathogenic/likely pathogenic, and five deletions/duplications were reclassified as pathogenic using breakpoint information from NGS.ConclusionThe SVs presented here can be used as a valuable resource for clinical research and diagnostics. The data illustrate NGS as a powerful tool for SV detection. Application of NGS and confirmation technologies in genetic testing ensures delivering accurate and reliable results for diagnosis and patient care.

Splicing profile by capture RNA-seq identifies pathogenic germline variants in tumor suppressor genes

“…Sequencing raw data processing was described previously. 43 RNA samples that failed the coverage or QC cutoffs were re-prepared and re-sequenced. Data from samples that again failed the covarage and/or QC cutoffs are not included in the study.…”

RNA Analysis Identifies Pathogenic Duplications in MSH2 in Patients With Lynch Syndrome

“…RNA data were used as evidence toward the assessment of these germline SV based on the ACMG/AMP guidelines, 6 which resulted in the reclassification of all tested MSH2 VUS into clinically actionable PV. Exonic duplications account for approximately 33% of all SV in cancer predisposition genes, 2 indicating that this workflow could also be used to reduce VUS in other genes. DNA-based assays may be able to show whether a duplication is in tandem, but they cannot provide any direct functional evidence that the alteration is disrupting gene expression.…”

Computational Methods for Detecting Large-Scale Structural Rearrangements in Chromosomes

“…A vast number of short reads (typically 50-150 bp) are sequenced in a single stroke. The sequence information is compared to a human genome reference sequence to identify any structural variations or mutations in the targeted sequences (10,11). Many NGS methods use pairedend reading, where two paired reads are generated at an approximately known distance in the tested genomes (usually around 500 bp).…”