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Vascular integrity is essential for organ homeostasis to prevent edema formation and infiltration of inflammatory cells. Long non-coding RNAs (lncRNAs) are important regulators of gene expression and often expressed in a cell type-specific manner. By screening for endothelial-enriched lncRNAs, we identified the undescribed lncRNA NTRAS to control endothelial cell functions. Silencing of NTRAS induces endothelial cell dysfunction in vitro and increases vascular permeability and lethality in mice. Biochemical analysis revealed that NTRAS, through its CA-dinucleotide repeat motif, sequesters the splicing regulator hnRNPL to control alternative splicing of tight junction protein 1 (TJP1; also named zona occludens 1, ZO-1) pre-mRNA. Deletion of the hnRNPL binding motif in mice (Ntras∆CA/∆CA) significantly repressed TJP1 exon 20 usage, favoring expression of the TJP1α- isoform, which augments permeability of the endothelial monolayer. Ntras∆CA/∆CA mice further showed reduced retinal vessel growth and increased vascular permeability and myocarditis. In summary, this study demonstrates that NTRAS is an essential gatekeeper of vascular integrity.
Background: With the rise of single-cell RNA sequencing new bioinformatic tools have been developed to handle specific demands, such as quantifying unique molecular identifiers and correcting cell barcodes. Here, we benchmarked several datasets with the most common alignment tools for single-cell RNA sequencing data. We evaluated differences in the whitelisting, gene quantification, overall performance, and potential variations in clustering or detection of differentially expressed genes. We compared the tools Cell Ranger version 6, STARsolo, Kallisto, Alevin, and Alevin-fry on 3 published datasets for human and mouse, sequenced with different versions of the 10X sequencing protocol.
Results: Striking differences were observed in the overall runtime of the mappers. Besides that, Kallisto and Alevin showed variances in the number of valid cells and detected genes per cell. Kallisto reported the highest number of cells; however, we observed an overrepresentation of cells with low gene content and unknown cell type. Conversely, Alevin rarely reported such low-content cells. Further variations were detected in the set of expressed genes. While STARsolo, Cell Ranger 6, Alevin-fry, and Alevin produced similar gene sets, Kallisto detected additional genes from the Vmn and Olfr gene family, which are likely mapping artefacts. We also observed differences in the mitochondrial content of the resulting cells when comparing a prefiltered annotation set to the full annotation set that includes pseudogenes and other biotypes.
Conclusion: Overall, this study provides a detailed comparison of common single-cell RNA sequencing mappers and shows their specific properties on 10X Genomics data.