Exome sequencing in individuals with cardiovascular laterality defects identifies potential candidate genes

Investigation of the genetic and clinical features of laterality disorders in prenatal diagnosis: discovery of a novel compound heterozygous mutation in the DNAH11 gene

BACKGROUND

Left-right laterality disorders are a heterogeneous group of disorders caused by an altered position or orientation of the thoracic and intra-abdominal organs and vasculature across the left-right axis. They mainly include situs inversus and heterotaxy. Those disorders are complicated by cardiovascular abnormalities significantly more frequently than situs solitus.

METHODS

In this study, 16 patients with a fetal diagnosis of laterality disorder with congenital heart defects (CHD) were evaluated with a single nucleotide polymorphism array (SNP-arry) combined with whole-exome sequencing (WES).

RESULTS

Although the diagnostic rate of copy number variations was 0 and the diagnostic rate of WES was 6.3% (1/16), the likely pathogenic gene DNAH11 and the candidate gene OFD1 were ultimately identified. In addition, novel compound heterozygous mutations in the DNAH11 gene and novel hemizygous variants in the OFD1 gene were found. Among the combined CHD, a single atrium/single ventricle had the highest incidence (50%, 8/16), followed by atrioventricular septal defects (37.5%, 6/16). Notably, two rare cases of common pulmonary vein atresia (CPVA) were also found on autopsy.

CONCLUSION

This study identified the types of CHD with a high incidence in patients with laterality disorders. It is clear that WES is an effective tool for diagnosing laterality disorders and can play an important role in future research.

Identification of high-risk non-synonymous SNPs (nsSNPs) in DNAH1 and DNAH17 genes associated with male infertility: a bioinformatics analysis

Male infertility is a significant reproductive issue affecting a considerable number of couples worldwide. While there are various causes of male infertility, genetic factors play a crucial role in its development. We focused on identifying and analyzing the high-risk nsSNPs in DNAH1 and DNAH17 genes, which encode proteins involved in sperm motility. A total of 20 nsSNPs for DNAH1 and 10 nsSNPs for DNAH17 were analyzed using various bioinformatics tools including SIFT, PolyPhen-2, CADD, PhD-SNPg, VEST-4, and MutPred2. As a result, V1287G, L2071R, R2356W, R3169C, R3229C, E3284K, R4096L, R4133C, and A4174T in DNAH1 gene and C1803Y, C1829Y, R1903C, and L3595P in DNAH17 gene were identified as high-risk nsSNPs. These nsSNPs were predicted to decrease protein stability, and almost all were found in highly conserved amino acid positions. Additionally, 4 nsSNPs were observed to alter post-translational modification status. Furthermore, the interaction network analysis revealed that DNAH1 and DNAH17 interact with DNAH2, DNAH3, DNAH5, DNAH7, DNAH8, DNAI2, DNAL1, CFAP70, DNAI3, DNAI4, ODAD1, and DNAI7, demonstrating the importance of DNAH1 and DNAH17 proteins in the overall functioning of the sperm motility machinery. Taken together, these findings revealed the detrimental effects of identified high-risk nsSNPs on protein structure and function and highlighted their potential relevance to male infertility. Further studies are warranted to validate these findings and to elucidate the underlying mechanisms.