Identification of Pathogenic Copy Number Variants in Mexican Patients With Inherited Retinal Dystrophies Applying an Exome Sequencing Data-Based Read-Depth Approach.

Abstract

Background: Retinal dystrophies (RDs) are the most common cause of inherited blindness worldwide and are caused by genetic defects in about 300 different genes. While targeted next-generation sequencing (NGS) has been demonstrated to be a reliable and efficient method to identify RD disease-causing variants, it doesn't routinely identify pathogenic structural variant as copy number variations (CNVs). Targeted NGS-based CNV detection has become a crucial step for RDs molecular diagnosis, particularly in cases without identified causative single nucleotide or Indels variants. Herein, we report the exome sequencing (ES) data-based read-depth bioinformatic analysis in a group of 30 unrelated Mexican RD patients with a negative or inconclusive genetic result after ES.

Methods: CNV detection was performed using ExomeDepth software, an R package designed to detect CNVs using exome data. Bioinformatic validation of identified CNVs was conducted through a commercially available CNV caller. All identified candidate pathogenic CNVs were orthogonally verified through quantitative PCR assays.

Results: Pathogenic or likely pathogenic CNVs were identified in 6 out of 30 cases (20%), and of them, a definitive molecular diagnosis was reached in 5 cases, for a final diagnostic rate of ~17%. CNV-carrying genes included CLN3 (2 cases), ABCA4 (novel deletion), EYS, and RPGRIP1.

Conclusions: Our results indicate that bioinformatic analysis of ES data is a reliable method for pathogenic CNV detection and that it should be incorporated in cases with a negative or inconclusive molecular result after ES.