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, but applying this technology to single cells has proven to be difficult, with less than ten single-cell transcriptomes having been analyzed thus far. Although single splicing events have been described for ≤200 single cells with statistical confidence, full-length mRNA analyses for hundreds of cells have not been reported. Single-cell short-read 3′ sequencing enables the identification of cellular subtypes, 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. 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.

Ishaan Gupta, Paul G Collier, Bettina Haase, Ahmed Mahfouz, Anoushka Joglekar, et al. Single-cell isoform RNA sequencing characterizes isoforms in thousands of cerebellar cells. Nature Biotechnology, 2018.
@article { bib:2018_natbiotech_scisorseq,
author = { Ishaan Gupta and Paul G Collier and Bettina Haase and Ahmed Mahfouz and Anoushka Joglekar and Taylor Floyd and Frank Koopmans and Ben Barres and August B Smit and Steven A Sloan and Wenjie Luo and Olivier Fedrigo and M Elizabeth Ross and Hagen U Tilgner },
title = { Single-cell isoform RNA sequencing characterizes isoforms in thousands of cerebellar cells },
journal = { Nature Biotechnology },
year = { 2018 },
doi = { 10.1038/nbt.4259 },
}
scISOr-seq screenshot

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