Investigation of the Frequency and Characteristic Features of De Novo Mutations in Clinical Exome Sequence Trio Samples

Abstract

Advanced genome sequencing technologies have provided us with the opportunity to deeply understand the mechanisms underlying conditions associated with the genome. There has been significant interest recently in understanding the characteristics of de novo mutations, which are genetic changes that arise in reproductive cells and are not present in parents, as well as the mechanisms involved in their occurrence. These mutations can be transmitted to subsequent generations and have the potential to influence genetic diversity and susceptibility to diseases, making this topic important. Due to limited studies in this area, the formation mechanisms and characteristic features of such mutations have not yet been fully understood. Background/Aims: In this study, we aimed to conduct a comprehensive analysis of de novo mutations in families undergoing trio clinical exome sequencing analysis. The objectives of the study were to investigate the relationship between parental ages and the frequency of de novo mutations, the distribution, prevalence, relationships, and molecular characteristics of de novo mutations. Methods: A total of 69 families who underwent Trio Clinical Exome Sequencing (CES) analysis at the Department of Medical Genetics, Faculty of Medicine, Selçuk University, between January 1, 2017, and December 31, 2023, were included in the study. DNA samples extracted from peripheral venous blood of individuals were sequenced using the Roche CES kit and DNBSEQ-G400™ sequencing device, and a total of 3892 genes were analyzed using the Seq Platform. Results: After analysis, 407 de novo variants were identified, with the majority being variants of unknown significance (55.28%). When examining the base change profile, the most common changes were found to be C -> G, G -> A, A -> G. The most commonly mutated genes were found to be DSPP, HPS4, VCL, and BMP4 genes. Conclusions: Correlation analysis revealed no significant relationship between parental age and the number of de novo mutations, and regression analysis showed that age was not a significant parameter in determining the number of de novo mutations