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.