CNV Detection from Exome Sequencing Data in Routine Diagnostics of Rare Genetic Disorders: Opportunities and Limitations

Abstract

To assess the potential of detecting copy number variations (CNVs) directly from exome sequencing (ES) data in diagnostic settings, we developed a CNV-detection pipeline based on ExomeDepth software and applied it to ES data of 450 individuals. Initially, only CNVs affecting genes in the requested diagnostic gene panels were scored and tested against arrayCGH results. Pathogenic CNVs were detected in 18 individuals. Most detected CNVs were larger than 400 kb (11/18), but three individuals had small CNVs impacting one or a few exons only and were thus not detectable by arrayCGH. Conversely, two pathogenic CNVs were initially missed, as they impacted genes not included in the original gene panel analysed, and a third one was missed as it was in a poorly covered region. The overall combined diagnostic rate (SNVs + CNVs) in our cohort was 36%, with wide differences between clinical domains. We conclude that (1) the ES-based CNV pipeline detects efficiently large and small pathogenic CNVs, (2) the detection of CNV relies on uniformity of sequencing and good coverage, and (3) in patients who remain unsolved by the gene panel analysis, CNV analysis should be extended to all captured genes, as diagnostically relevant CNVs may occur everywhere in the genome.

Atypical, Composite, or Blended Phenotypes: How Different Molecular Mechanisms Could Associate in Double-Diagnosed Patients

“…Concerning this, it seems evident that wide analyses, such as whole-exome and whole-genome sequencing, are the most powerful tools to bring to light multiple conditions in one single patient. This could be even more appropriate thanks to the ongoing incorporation of technologies for copy-number variants (CNVs) detection in the WES pipeline, uncovering at the same time monogenic and genomic disorders [ 22 ], as in Case 6. For example, copy number variants and single-nucleotide variants as a part of multiple diagnoses were reported in 11.9% of double-diagnosed patients by Posey et al [ 1 ], whereas Chen et al recently applied simultaneous CNV-seq and WES analysis on a large cohort of malformed fetuses and detected coincidental pathogenic CNVs and single gene variants in about 1% of them.…”

Whole Genome Sequencing, Focused Assays and Functional Studies Increasing Understanding in Cryptic Inherited Retinal Dystrophies

“…Targeted capture, genomic PCR-based approaches have limited ability to detect SV/CNVs, and rely on coverage and an average read depth of exons or regions of interest which are sensitive to lack of uniformity and reproducibility in read depth and quality [ 38 ]. WGS is a superior technology in this regard due to the ability to obtain more informative split reads which span the SV/CNV breakpoint, allowing for the precise mapping of breakpoints.…”

Case Report: Whole-Exome Sequencing-Based Copy Number Variation Analysis Identified a Novel DRC1 Homozygous Exon Deletion in a Patient With Primary Ciliary Dyskinesia

“…Firstly, it permits concurrently detection of large and small CNVs (as previously detected by array CGH and MLPA, respectively) ( Roca et al, 2019 ). Secondly, it is practical as it allows to determine SNVs, INDELs, and CNVs simultaneously, thus eliminating the necessity of using multiple different techniques in one patient and helping speed up the diagnostic process ( Royer-Bertrand et al, 2021 ). Among WES-based CNV approaches, the “Exomedepth” package has been corroborated to have higher sensitivity and efficiency in detecting rare CNVs ( Roca et al, 2019 ; Rajagopalan et al, 2020 ), and it is most used to identify CNVs in neurological diseases and mental disorders ( Szatkiewicz et al, 2020 ; Cheng et al, 2021 ; Yu et al, 2021 ).…”

“…CNVs were called from the read depth of WES data using the ExomeDepth package according to the developers’ guidelines. ExomeDepth is a validated method for exome read-depth analysis, generating normalized read counts of the test sample by using an optimized set of reference samples as a comparison to determine the presence of a CNV at the exon level ( Royer-Bertrand et al, 2021 ). Each exome was compared with a set of matched, aggregate reference samples for these analyses.…”