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

• Published in: Molecular genetics & genomic medicine 2024-10, Vol.12 (10), p.e70019-n/a
• Main Authors: Fabian‐Morales, Gerardo E., Ordoñez‐Labastida, Vianey, Garcia‐Martínez, Froylan, Montes‐Almanza, Luis, Zenteno, Juan C.
• Format: Article
• Language: English
• Subjects: Adolescent; Adult; Child; Computational Biology; Congenital diseases; Copy number; copy number variation; Data analysis; deletion; Diagnosis; Disease; DNA Copy Number Variations - genetics; Exome Sequencing; Female; Gene sequencing; Genes; Genetic analysis; Genetic testing; Genomes; Genomics; Humans; Identification methods; Male; Mexico; Middle Aged; Nucleotides; Original; Patients; Retina; Retinal Dystrophies - diagnosis; Retinal Dystrophies - genetics; Retinal Dystrophies - pathology; retinal dystrophy; Sequence Deletion - genetics; Whole genome sequencing; Young Adult
• ISSN: 2324-9269; 2324-9269
• DOI: 10.1002/mgg3.70019

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. Exome sequencing (ES) data‐based read‐depth bioinformatic analysis was performed in 30 patients with retinal dystrophy who had a negative ES result. Five cases were solved by the identification of pathogenic copy number variations (CNVs). Bioinformatic analysis focused on CNV detection should be incorporated in samples with an inconclusive molecular result.