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

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

Journal Article (2018)

Author(s)

Ishaan Gupta (Brain and Mind Research Institute and Center for Neurogenetics, New York)

Paul G. Collier (Brain and Mind Research Institute and Center for Neurogenetics, New York)

Bettina Haase (The Rockefeller University)

Ahmed Mahfouz (Leiden University Medical Center, TU Delft - Electrical Engineering, Mathematics and Computer Science, Brain and Mind Research Institute and Center for Neurogenetics, New York)

Anoushka Joglekar (Brain and Mind Research Institute and Center for Neurogenetics, New York)

Taylor Floyd (Brain and Mind Research Institute and Center for Neurogenetics, New York)

Frank Koopmans (Vrije Universiteit Amsterdam)

Ben Barres (Stanford University)

Wenjie Luo (Weill Cornell Medicine, New York)

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Research Group

Pattern Recognition and Bioinformatics

DOI related publication

https://doi.org/10.1038/nbt.4259 Final published version

To reference this document use

https://resolver.tudelft.nl/uuid:e2685e4c-d484-4752-8e33-5a14f5ceb248

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Publication Year

2018

Language

English

Research Group

Pattern Recognition and Bioinformatics

Journal title

Nature Biotechnology

Issue number

12

Volume number

36

Pages (from-to)

1197-1202

Downloads counter

136

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.