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.
Keywords: DNAI1; NGS; PCD; SPAG16; functional analysis; in silico structural analysis.