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

Katarina Cisarova,Laureane Mittaz-Crettol,Florence Niel-Butschi,Andrea Superti-Furga,Heidi Fodstad,Beryl Royer-Bertrand

doi:10.3390/genes12091427

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.

Highlights

In clinical practice, the process of finding a molecular genetic diagnosis for rare genetic disorders is challenging
Human genetic disorders may arise from genetic variations that range in size from a whole chromosome down to a single-nucleotide variant (SNV)
Of the 450 patients processed with the next-generation sequencing (NGS)-based copy number variations (CNVs) pipeline, approximately half had a neurodevelopmental condition (n = 227), 63 had neurodegeneration disorder, 40 suffered from renal disease, 35 from cardiac problems, 20 had connective tissues disease, 19 had vision problems, 17 suffered from hearing loss, 20 patients had a diverse set of diseases, and the remaining categories had fewer number of patients (Figure 1b)

Summary

Introduction

The process of finding a molecular genetic diagnosis for rare genetic disorders is challenging. In spite of advances in laboratory technology in the last 10 years, approximately one-half to two-thirds of patients remain without a clear diagnosis, depending on their clinical manifestation [1,2,3]. Human genetic disorders may arise from genetic variations that range in size from a whole chromosome down to a single-nucleotide variant (SNV). To detect CNVs, specific techniques such as genome-wide CNV detection (arrayCGH (aCGH)) or locus CNV detection (multiplex ligation-dependent probe amplification (MLPA)) are needed. They can detect CNVs either at a large scale (50 kb) or at the level of a single exon [5]. Optical genome mapping is a novel method allowing the detection with high accuracy of structural variants, CNVs [6,7]

Methods

Results

Discussion

Conclusion