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SMARTer single cell total RNA sequencing

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 m...

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Autores principales: Verboom, Karen, Everaert, Celine, Bolduc, Nathalie, Livak, Kenneth J, Yigit, Nurten, Rombaut, Dries, Anckaert, Jasper, Lee, Simon, Venø, Morten T, Kjems, Jørgen, Speleman, Frank, Mestdagh, Pieter, Vandesompele, Jo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6895261/
https://www.ncbi.nlm.nih.gov/pubmed/31216024
http://dx.doi.org/10.1093/nar/gkz535
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author Verboom, Karen
Everaert, Celine
Bolduc, Nathalie
Livak, Kenneth J
Yigit, Nurten
Rombaut, Dries
Anckaert, Jasper
Lee, Simon
Venø, Morten T
Kjems, Jørgen
Speleman, Frank
Mestdagh, Pieter
Vandesompele, Jo
author_facet Verboom, Karen
Everaert, Celine
Bolduc, Nathalie
Livak, Kenneth J
Yigit, Nurten
Rombaut, Dries
Anckaert, Jasper
Lee, Simon
Venø, Morten T
Kjems, Jørgen
Speleman, Frank
Mestdagh, Pieter
Vandesompele, Jo
author_sort Verboom, Karen
collection PubMed
description 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.
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spelling pubmed-68952612019-12-11 SMARTer single cell total RNA sequencing Verboom, Karen Everaert, Celine Bolduc, Nathalie Livak, Kenneth J Yigit, Nurten Rombaut, Dries Anckaert, Jasper Lee, Simon Venø, Morten T Kjems, Jørgen Speleman, Frank Mestdagh, Pieter Vandesompele, Jo Nucleic Acids Res Methods Online 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. Oxford University Press 2019-09-19 2019-06-19 /pmc/articles/PMC6895261/ /pubmed/31216024 http://dx.doi.org/10.1093/nar/gkz535 Text en © The Author(s) 2019. Published by Oxford University Press on behalf of Nucleic Acids Research. http://creativecommons.org/licenses/by/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Methods Online
Verboom, Karen
Everaert, Celine
Bolduc, Nathalie
Livak, Kenneth J
Yigit, Nurten
Rombaut, Dries
Anckaert, Jasper
Lee, Simon
Venø, Morten T
Kjems, Jørgen
Speleman, Frank
Mestdagh, Pieter
Vandesompele, Jo
SMARTer single cell total RNA sequencing
title SMARTer single cell total RNA sequencing
title_full SMARTer single cell total RNA sequencing
title_fullStr SMARTer single cell total RNA sequencing
title_full_unstemmed SMARTer single cell total RNA sequencing
title_short SMARTer single cell total RNA sequencing
title_sort smarter single cell total rna sequencing
topic Methods Online
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6895261/
https://www.ncbi.nlm.nih.gov/pubmed/31216024
http://dx.doi.org/10.1093/nar/gkz535
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