تجاوز إلى المحتوى الرئيسي

Identification and Functional Characterization of Mutation in FYCO1 in Families with Congenital Cataract

Author name : Muhammad Atif Mushtaq Ahmed
Publication Date : 2023-09-06
Journal Name : Life

Abstract

Congenital cataract (CC) causes a third of the cases of treatable childhood blindness worldwide. CC is a disorder of the crystalline lens which is established as clinically divergent and has complex heterogeneity. This study aimed to determine the genetic basis of CC. Whole blood was obtained from four consanguineous families with CC. Genomic DNA was extracted from the blood, and the combination of targeted and Sanger sequencing was used to identify the causative gene. The mutations detected were analyzed in silico for structural and protein-protein interactions to predict their impact on protein activities. The sequencing found a known FYCO1 mutation (c.2206C>T; p.Gln736Term) in autosomal recessive mode in families with CC. Co-segregation analysis showed affected individuals as homozygous and carriers as heterozygous for the mutation and the unaffected as wild-type. Bioinformatics tools uncovered the loss of the Znf domain and structural compactness of the mutant protein. In conclusion, a previously reported nonsense mutation was identified in four consanguineous families with CC. Structural analysis predicted the protein as disordered and coordinated with other structural proteins. The autophagy process was found to be significant for the development of the lens and maintenance of its transparency. The identification of these markers expands the scientific knowledge of CC; the future goal should be to understand the mechanism of disease severity. Ascertaining the genetic etiology of CC in a family member facilitates establishing a molecular diagnosis, unlocks the prospect of prenatal diagnosis in pregnancies, and guides the successive generations by genetic counseling.

Keywords

congenital cataractFYCO1mutationsconsanguineous familiesin silico analysis

Publication Link

https://doi.org/10.3390/ life13081788

Block_researches_list_suggestions

Suggestions to read

HIDS-IoMT: A Deep Learning-Based Intelligent Intrusion Detection System for the Internet of Medical Things
Ahlem . Harchy Ep Berguiga
“Synthesis and Characterization study of SnO2/α-Fe2O3, In2O3/α-Fe2O3 and ZnO/α-Fe2O3 thin films and its application as transparent conducting electrode in silicon heterojunction solar cell”
Asma Arfaoui
Frequency and voltage dependent of electrical and dielectric properties of 14 nm Fully Depleted Silicon-On-Insulator (FD-SOI)
MOHAMMED OMAR MOHAMMEDAHMED IBRAHIM
Biosynthesis of Zn-nano complex using Olive seeds for Antimicrobial Regulation of Nanostructured Materials
MERVAT RAGAB ATTA MOHAMED
تواصل معنا