AI Article Synopsis

  • Retinal dystrophies (RDs) are a leading cause of inherited blindness, linked to genetic defects in around 300 genes, and targeted next-generation sequencing (NGS) struggles to detect copy number variations (CNVs) vital for accurate diagnosis.
  • * In a study of 30 unrelated Mexican RD patients with inconclusive results from exome sequencing (ES), CNV detection was performed using ExomeDepth software and verified through quantitative PCR assays.
  • * Pathogenic CNVs were identified in 20% of cases, leading to definitive molecular diagnoses in 5 patients, emphasizing the importance of integrating bioinformatic CNV detection in RD diagnostics after ES.*

Article 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.

Download full-text PDF

Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11472028PMC
http://dx.doi.org/10.1002/mgg3.70019DOI Listing

Publication Analysis

Top Keywords

cnv detection
12
copy number
8
mexican patients
8
retinal dystrophies
8
exome sequencing
8
sequencing data-based
8
data-based read-depth
8
molecular diagnosis
8
bioinformatic analysis
8
negative inconclusive
8

Similar Publications

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!