Next-generation sequencing represents an important step in diagnostics of monogenic conditions, as it allows the analysis of the majority of the human genome, including non-coding regions. However, characterization of the pathogenic effect of variants identified by these approaches and their functional assessment remain a challenge. The aim of this research is analysis of cases with undiagnosed genetic conditions that harbor genetic variants of uncertain clinical significance, and cases in which conventional genetic approaches identified no causal variants. Using next-generation sequencing based RNA analysis, we explained the pathogenic and functional effects and mechanisms in cases with known suspect variants. Additionally, we were able to identify disease-causing variants in samples with unknown variants. Based on the functional data, we reassessed the pathogenicity of variants according to American College of Medical Genetics and Association for Clinical Genomic Science standards and we found that the clinical classification of pathogenicity has improved in every case. In four cases we confirmed exon skipping, in three cases a frameshift mutation, and one case of each intron retention and novel splice site introduction. In conclusion, using the RNA transcript analysis we improved the functional characterization and classification of pathogenicity as well as identified the mechanism of their development. We demonstrate that next-generation sequencing-based RNA analysis can improve the assessment of the pathogenic effect of variants in coding and non-coding regions of the genome.
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