Whole Exome Sequencing Unveils Novel Pathogenic Variants in an Iranian Cohort with Retinal Dystrophies: Implications for Genetic Diagnosis and Counseling.
Abstract
Background
Retinal dystrophies (RD) are a heterogeneous group of genetic disorders leading to progressive vision loss. The notable gap in the genetics of RD is primarily due to unidentified disease genes and variants. Advanced genotyping technologies present significant opportunities for the identification of causative variants, thereby contributing to improved disease management.
Methods
This study investigates the genetic basis of RD in 12 families from Iran. Comprehensive ophthalmic evaluations were conducted for each participant, including visual acuity testing, slit-lamp examinations, and optical coherence tomography (OCT). Whole exome sequencing (WES) and computer-assisted data analysis were utilized for genotyping and identifying DNA variants. Exome enrichment was achieved using the Illumina TruSeq kit, and sequencing was performed on the Illumina NextSeq500 platform. Bioinformatic analysis involved variant calling and annotation, with stringent filtering based on established criteria. Variants were prioritized according to the American College of Medical Genetics and Genomics (ACMG) guidelines, and pathogenic variants were validated through Sanger sequencing, achieving a 100% concordance rate.
Results
We identified variants in all the families, including significant pathogenic variants in genes such as EYS. Several novel variants were also discovered, contributing to the expanding genetic landscape of RD. Additionally, variants in syndromic RD genes were identified, emphasizing the need for comprehensive genetic screening.
Conclusions
Our findings demonstrate the utility of WES in the molecular diagnosis of retinal dystrophies, highlighting the importance of functional validation of newly identified variants. This study contributes valuable insights into the genetic basis of RD. Our findings have the potential to enhance genetic counseling and improve the classification of subtypes in RD.