Single-cell isoform RNA sequencing characterizes isoforms in thousands of cerebellar cells

Abstract

Full-length RNA sequencing (RNA-Seq) has been applied to bulk tissue, cell lines and sorted cells to characterize transcriptomes 1–11 , but applying this technology to single cells has proven to be difficult, with less than ten single-cell transcriptomes having been analyzed thus far 12,13 . Although single splicing events have been described for ≤200 single cells with statistical confidence 14,15 , full-length mRNA analyses for hundreds of cells have not been reported. Single-cell short-read 3′ sequencing enables the identification of cellular subtypes 16–21 , but full-length mRNA isoforms for these cell types cannot be profiled. We developed a method that starts with bulk tissue and identifies single-cell types and their full-length RNA isoforms without fluorescence-activated cell sorting. Using single-cell isoform RNA-Seq (ScISOr-Seq), we identified RNA isoforms in neurons, astrocytes, microglia, and cell subtypes such as Purkinje and Granule cells, and cell-type-specific combination patterns of distant splice sites 6–9,22,23 . We used ScISOr-Seq to improve genome annotation in mouse Gencode version 10 by determining the cell-type-specific expression of 18,173 known and 16,872 novel isoforms.

Publication
Nature Biotechnology