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

Ishaan Gupta, Paul G. Collier, Bettina Haase, Ahmed Mahfouz, Anoushka Joglekar, Taylor Floyd, Frank Koopmans, Ben Barres, August B. Smit, Steven A. Sloan, Wenjie Luo, Olivier Fedrigo, M. Elizabeth Ross, Hagen U. Tilgner

Research output: Contribution to journalArticlepeer-review

134 Scopus citations


Full-length RNA sequencing (RNA-Seq) has been applied to bulk tissue, cell lines and sorted cells to characterize transcriptomes1–11, but applying this technology to single cells has proven to be difficult, with less than ten single-cell transcriptomes having been analyzed thus far12,13. Although single splicing events have been described for ≤200 single cells with statistical confidence14,15, full-length mRNA analyses for hundreds of cells have not been reported. Single-cell short-read 3′ sequencing enables the identification of cellular subtypes16–21, 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 sites6–9,22,23. 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.

Original languageEnglish
Pages (from-to)1197-1202
Number of pages6
JournalNature Biotechnology
Issue number12
StatePublished - 1 Dec 2018
Externally publishedYes


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