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

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 d...

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Bibliographic Details
Published in:Genes 2021-09, Vol.12 (9), p.1427
Main Authors: Royer-Bertrand, Beryl, Cisarova, Katarina, Niel-Butschi, Florence, Mittaz-Crettol, Laureane, Fodstad, Heidi, Superti-Furga, Andrea
Format: Article
Language:English
Subjects:
Adolescent
Adult
Aged
Aged, 80 and over
Annotations
Bioinformatics
Child
Child, Preschool
Chromosomes
Cohort Studies
Copy number
Diagnostic Tests, Routine
DNA Copy Number Variations
Exons
Female
Genes
Genetic disorders
Genetic Testing - methods
Genomes
Genomics
High-Throughput Nucleotide Sequencing - methods
Humans
Infant
Informed consent
Laboratories
Male
Middle Aged
Patients
Rare Diseases - diagnosis
Rare Diseases - epidemiology
Rare Diseases - genetics
Sequence Analysis, DNA - methods
Software
Switzerland - epidemiology
Whole Exome Sequencing - methods
Young Adult
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Summary: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.
ISSN:2073-4425
2073-4425
DOI:10.3390/genes12091427