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Long non-coding RNAs (lncRNAs) are important regulators to modulate geneexpression and cell proliferation in the developing human brain. Previousmethods mainly use bulk lncRNA and mRNA expression data to study lncRNAregulation. However, to analyze lncRNA regulation regarding individual cells,we focus on single-cell RNA-sequencing (scRNA-seq) data instead of bulk data.Recent advance in scRNA-seq has provided a way to investigate lncRNA regulationat single-cell level. We will propose a novel computational method, CSlncR(cell-specific lncRNA regulation), which combines putative lncRNA-mRNA bindinginformation with scRNA-seq data including lncRNAs and mRNAs to identifycell-specific lncRNA-mRNA regulation networks at individual cells. Tounderstand lncRNA regulation at different development stages, we apply CSlncRto the scRNA-seq data of human neocortex. Network analysis shows that thelncRNA regulation is unique in each cell from the different human neocortexdevelopment stages. The comparison results indicate that CSlncR is also aneffective tool for predicting cell-specific lncRNA targets and clusteringsingle cells, which helps understand cell-cell communication.

Inferring cell-specific lncRNA regulation with single-cell RNA-sequencing data in the developing human neocortex