Uncovering functional lncRNAs by unconventional scRNA-seq analysis
Long non-coding RNAs (lncRNAs) play fundamental roles in cellular processes and pathologies, regulating gene expression at multiple levels. Despite being highly cell-type specific, their study at single-cell level has been challenging due to their less accurate annotation and low expression. Here, we show that single-cell RNA-seq (scRNA-seq) preprocessing workflows using the pseudoaligner Kallisto enhance the detection and quantification of lncRNAs. Further, using single-cell multiome data, we demonstrate that the ATAC-seq profiles exhibit higher concordance when the scRNA-seq is processed by Kallisto. We then experimentally confirmed the expression patterns of cell-type specific lncRNAs exclusively detected by Kallisto and unveiled biologically relevant lncRNAs, such as AL121895.1, a previously undocumented cis-repressor lncRNA, whose role in proliferation of breast cancer cells was detected by Kallisto and overlooked by other pipelines. Our results emphasize the necessity for an alternative scRNA-seq preprocessing workflow tailored to lncRNAs that sheds light on the multifaceted roles of lncRNAs. Overall design: 5 scRNA-Seq samples **Raw data were removed Jun 30, 2024 due to privacy concerns, and added back on Oct 10, 2024 with revised ethical requirements**