Abstract
Clinical Whole Exome Sequencing (WES) offers a high diagnostic yield test by detecting pathogenic variants in all coding genes of the human genome. WES is poised to consolidate multiple genetic tests by accurately identifying Copy Number Variation (CNV) events, typically necessitating microarray analysis. However, standard commercial exome kits are typically limited to targeting exon coding regions, leaving significant gaps in coverage between genes, which could hinder comprehensive CNV detection. To convert microarray CNV calling with NGS, advances in both assay design and computational methods are needed.
Addressing the need for comprehensive coverage, Twist Bioscience has developed an enhanced Exome 2.0 Plus Comprehensive Exome Spike-in panel with added CNV “backbone” probes. These probes target common SNPs polymorphic in multiple populations and are evenly distributed in the intergenic and intronic regions, with three varying densities at 25 kb, 50 kb, and 100 kb intervals from highest to lowest resolution respectively. Concurrently, Golden Helix has developed a multi-modal CNV caller designed specifically for target-capture NGS data to detect single-exon to whole-chromosome aneuploidy CNV events. This study evaluates the combined efficacy of the backbone-probe enhanced exome capture kit and VS-CNV 2.6 in identifying known CNVs using the Coriell CNVPANEL01 reference set.
The integration of the enhanced capture kit with VS-CNV 2.6 achieved a 100% sensitivity rate for the detection of known CNV events at all three probe densities. The application of best-practice quality metrics, annotations, and filters was shown to have a minimal impact on this high sensitivity. These findings underscore the potential of the augmented Twist Exome in tandem with the VS-CNV caller and VarSeq’s annotation and filtering capabilities. This combination presents a promising alternative to conventional microarray assays, potentially consolidating WES and CNV into a single assay obviating the need for additional testing in clinical CNV detection. The study’s results advocate for the implementation of this integrated approach as a more efficient and equally sensitive method for CNV analysis in a clinical setting.
Competing Interest Statement
Three of the authors of this study are employed by Golden Helix Inc. and two authors are employed by Twist Bioscience. Golden Helix is the developer of the VS-CNV 2.6 multi-modal CNV caller used in this study, while Twist Bioscience developed the Exome 2.0 Plus Comprehensive Exome Spike-in panel. The employment relationships and the use of these proprietary tools in the study may be considered potential conflicts of interest. However, the study design, data analysis, and interpretation of the results were conducted with the objective of ensuring scientific integrity and minimizing bias.
