SMARTer single cell total RNA sequencing

Author:

Verboom Karen12ORCID,Everaert Celine12,Bolduc Nathalie3,Livak Kenneth J4,Yigit Nurten12,Rombaut Dries12,Anckaert Jasper12,Lee Simon3,Venø Morten T5,Kjems Jørgen5,Speleman Frank12,Mestdagh Pieter12,Vandesompele Jo12ORCID

Affiliation:

1. Center for Medical Genetics, Ghent University, Ghent, Belgium

2. Cancer Research Institute Ghent, Ghent, Belgium

3. Takara Bio USA, Mountain View, CA 94043, USA

4. Fluidigm Corporation, South San Francisco, CA 94080, USA

5. Department of Molecular Biology and Genetics and Interdisciplinary Nanoscience Center, Aarhus University, Aarhus DK-8000, Denmark

Abstract

Abstract Single cell RNA sequencing methods have been increasingly used to understand cellular heterogeneity. Nevertheless, most of these methods suffer from one or more limitations, such as focusing only on polyadenylated RNA, sequencing of only the 3′ end of the transcript, an exuberant fraction of reads mapping to ribosomal RNA, and the unstranded nature of the sequencing data. Here, we developed a novel single cell strand-specific total RNA library preparation method addressing all the aforementioned shortcomings. Our method was validated on a microfluidics system using three different cancer cell lines undergoing a chemical or genetic perturbation and on two other cancer cell lines sorted in microplates. We demonstrate that our total RNA-seq method detects an equal or higher number of genes compared to classic polyA[+] RNA-seq, including novel and non-polyadenylated genes. The obtained RNA expression patterns also recapitulate the expected biological signal. Inherent to total RNA-seq, our method is also able to detect circular RNAs. Taken together, SMARTer single cell total RNA sequencing is very well suited for any single cell sequencing experiment in which transcript level information is needed beyond polyadenylated genes.

Funder

Ghent University

Scientific Research Flanders

Hercules Foundation

Publisher

Oxford University Press (OUP)

Subject

Genetics

Reference48 articles.

1. mRNA-Seq whole-transcriptome analysis of a single cell;Tang;Nat. Methods,2009

2. Every cell is special: genome-wide studies add a new dimension to single-cell biology;Junker;Cell,2014

3. Characterization of the single-cell transcriptional landscape by highly multiplex RNA-seq;Islam;Genome Res.,2011

4. Characterization of directed differentiation by high-throughput single-cell RNA-Seq - SI;Soumillon,2014

5. Full-length RNA-seq from single cells using Smart-seq2;Picelli;Nat. Protoc.,2014

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