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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...
Autores principales: | , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2019
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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. |
format | Online Article Text |
id | pubmed-6895261 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
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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