Small RNA transcriptome analysis using parallel single-cell small RNA sequencing

Abstract

AbstractmiRNA and other forms of small RNAs are known to regulate many biological processes. Single-cell small RNA sequencing can be used to profile small RNAs of individual cells; however, limitations of efficiency and scale prevent its widespread application. Here, we developed parallel single-cell small RNA sequencing (PSCSR-seq), which can overcome the limitations of existing methods and enable high-throughput small RNA expression profiling of individual cells. Analysis of PSCSR-seq data indicated that diverse cell types could be identified based on patterns of miRNA expression, and showed that miRNA content in nuclei is informative (for example, cell type marker miRNAs can be detected in isolated nuclei). PSCSR-seq is very sensitive: analysis of only 732 peripheral blood mononuclear cells (PBMCs) detected 774 miRNAs, whereas bulk small RNA analysis would require input RNA from approximately 106 cells to detect as many miRNAs. We identified 42 miRNAs as markers for PBMC subpopulations. Moreover, we analyzed the miRNA profiles of 9,533 cells from lung cancer biopsies, and by dissecting cell subpopulations, we identified potentially diagnostic and therapeutic miRNAs for lung cancers. Our study demonstrates that PSCSR-seq is highly sensitive and reproducible, thus making it an advanced tool for miRNA analysis in cancer and life science research.