Single-cell RNA sequencing analysis to characterize cells and gene expression landscapes in atrial septal defect

Transcriptome studies of congenital heart diseases: identifying current gaps and therapeutic frontiers

Congenital heart disease (CHD) are genetically complex and comprise a wide range of structural defects that often predispose to - early heart failure, a common cause of neonatal morbidity and mortality. Transcriptome studies of CHD in human pediatric patients indicated a broad spectrum of diverse molecular signatures across various types of CHD. In order to advance research on congenital heart diseases (CHDs), we conducted a detailed review of transcriptome studies on this topic. Our analysis identified gaps in the literature, with a particular focus on the cardiac transcriptome signatures found in various biological specimens across different types of CHDs. In addition to translational studies involving human subjects, we also examined transcriptomic analyses of CHDs in a range of model systems, including iPSCs and animal models. We concluded that RNA-seq technology has revolutionized medical research and many of the discoveries from CHD transcriptome studies draw attention to biological pathways that concurrently open the door to a better understanding of cardiac development and related therapeutic avenue. While some crucial impediments to perfectly studying CHDs in this context remain obtaining pediatric cardiac tissue samples, phenotypic variation, and the lack of anatomical/spatial context with model systems. Combining model systems, RNA-seq technology, and integrating algorithms for analyzing transcriptomic data at both single-cell and high throughput spatial resolution is expected to continue uncovering unique biological pathways that are perturbed in CHDs, thus facilitating the development of novel therapy for congenital heart disease.

Single-cell RNA sequencing analysis to characterize cells and gene expression landscapes in atrial septal defect

This study aimed to characterize the cells and gene expression landscape in atrial septal defect (ASD). We performed single-cell RNA sequencing of cells derived from cardiac tissue of an ASD patient. Unsupervised clustering analysis was performed to identify different cell populations, followed by the investigation of the cellular crosstalk by analysing ligand-receptor interactions across cell types. Finally, differences between ASD and normal samples for all cell types were further investigated. An expression matrix of 18,411 genes in 6487 cells was obtained and used in this analysis. Five cell types, including cardiomyocytes, endothelial cells, smooth muscle cells, fibroblasts and macrophages were identified. ASD showed a decreased proportion of cardiomyocytes and an increased proportion of fibroblasts. There was more cellular crosstalk among cardiomyocytes, fibroblasts and macrophages, especially between fibroblast and macrophage. For all cell types, the majority of the DEGs were downregulated in ASD samples. For cardiomyocytes, there were 199 DEGs (42 upregulated and 157 downregulated) between ASD and normal samples. PPI analysis showed that cardiomyocyte marker gene FABP4 interacted with FOS, while FOS showed interaction with NPPA. Cell trajectory analysis showed that FABP4, FOS, and NPPA showed different expression changes along the pseudotime trajectory. Our results showed that single-cell RNA sequencing provides a powerful tool to study DEG profiles in the cell subpopulations of interest at the single-cell level. These findings enhance the understanding of the underlying mechanisms of ASD at both the cellular and molecular level and highlight potential targets for the treatment of ASD.