Identification and Classification of Novel Genetic Variants: En Route to the Diagnosis of Primary Ciliary Dyskinesia

Autor: Anita Skakic, Predrag Minic, Maja Stojiljkovic, Aleksandar Sovtic, Sonja Pavlovic, Nina Stevanovic, Marina Andjelkovic
Jazyk: angličtina
Rok vydání: 2021
Předmět:
Genetic Markers
Candidate gene
QH301-705.5
In silico
DNAI1
SPAG16
Computational biology
Biology
Article
Catalysis
functional analysis
Inorganic Chemistry
03 medical and health sciences
0302 clinical medicine
medicine
otorhinolaryngologic diseases
Humans
Biology (General)
Physical and Theoretical Chemistry
QD1-999
Molecular Biology
Gene
Spectroscopy
030304 developmental biology
Primary ciliary dyskinesia
0303 health sciences
Organic Chemistry
Inheritance (genetic algorithm)
High-Throughput Nucleotide Sequencing
Axonemal Dyneins
General Medicine
medicine.disease
PCD
in silico structural analysis
3. Good health
Computer Science Applications
Chemistry
030228 respiratory system
Case-Control Studies
NGS
Mutation
Motile cilium
Identification (biology)
Microtubule-Associated Proteins
Function (biology)
Ciliary Motility Disorders
Zdroj: International Journal of Molecular Sciences
Volume 22
Issue 16
International Journal of Molecular Sciences, Vol 22, Iss 8821, p 8821 (2021)
ISSN: 1422-0067
DOI: 10.3390/ijms22168821
Popis: Primary ciliary dyskinesia (PCD) is a disease caused by impaired function of motile cilia. PCD mainly affects the lungs and reproductive organs. Inheritance is autosomal recessive and X-linked. PCD patients have diverse clinical manifestations, thus making the establishment of proper diagnosis challenging. The utility of next-generation sequencing (NGS) technology for diagnostic purposes allows for better understanding of the PCD genetic background. However, identification of specific disease-causing variants is difficult. The main aim of this study was to create a unique guideline that will enable the standardization of the assessment of novel genetic variants within PCD-associated genes. The designed pipeline consists of three main steps: (1) sequencing, detection, and identification of genes/variants
(2) classification of variants according to their effect
and (3) variant characterization using in silico structural and functional analysis. The pipeline was validated through the analysis of the variants detected in a well-known PCD disease-causing gene (DNAI1) and the novel candidate gene (SPAG16). The application of this pipeline resulted in identification of potential disease-causing variants, as well as validation of the variants pathogenicity, through their analysis on transcriptional, translational, and posttranslational levels. The application of this pipeline leads to the confirmation of PCD diagnosis and enables a shift from candidate to PCD disease-causing gene.
Databáze: OpenAIRE
Externí odkaz: