Analysis of Copy Number Variants Is an Important Consideration in Exome Sequencing

Abstract

Copy number variants (CNVs) contribute significantly to the pathogenicity of rare genetic diseases and tend to have a more severe effect on phenotype compared to single nucleotide variants (SNVs). In the past decades, exome sequencing (ES) has proven valuable input in the characterization of underlying genetic defects. Our aim was to investigate the impact of integrating CNV analysis tools into standard ES analysis on its diagnostic yield. We worked on ES data from an original cohort of 840 patients, in whom the first analysis was able to detect causative SNVs and indels in 383 (45.6%). Using the ExomeDepth algorithm, clinically relevant CNVs were identified in 55 patients out of the 457 unsolved cases, thus enhancing the diagnostic yield to 52.1%. Among the enrolled subjects, neurodevelopmental delay was the most prevalent phenotype. The detected CNVs comprised 43 deletions (74.1%) and 15 duplications (25.9%), ranging in size from 94 bp to 94.3 Mb, and were classified as 56 pathogenic/likely pathogenic and 2 uncertain with high interest. The study presents further evidence that incorporating CNV analysis tools into ES pipelines improves the diagnostic yield and emphasizes the involvement of CNVs in the etiology of genetic disorders.