High-throughput total RNA sequencing in single cells using VASA-seq

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  • dc.contributor.author Salmen, Fredrik
  • dc.contributor.author De Jonghe, Joachim
  • dc.contributor.author Kaminski, Tomasz S.
  • dc.contributor.author Alemany, Anna
  • dc.contributor.author Parada, Guillermo E.
  • dc.contributor.author Verity-Legg, Joe
  • dc.contributor.author Yanagida, Ayaka
  • dc.contributor.author Kohler, Timo N.
  • dc.contributor.author Battich, Nicholas
  • dc.contributor.author van den Brekel, Floris
  • dc.contributor.author Ellermann, Anna L.
  • dc.contributor.author Martínez Arias, Alfonso
  • dc.contributor.author Nichols, Jennifer
  • dc.contributor.author Hemberg, Martin
  • dc.contributor.author Hollfelder, Florian
  • dc.contributor.author van Oudenaarden, Alexander
  • dc.date.accessioned 2022-09-08T06:04:41Z
  • dc.date.available 2022-09-08T06:04:41Z
  • dc.date.issued 2022
  • dc.description Data de publicació electrònica: 27-06-2022
  • dc.description.abstract Most methods for single-cell transcriptome sequencing amplify the termini of polyadenylated transcripts, capturing only a small fraction of the total cellular transcriptome. This precludes the detection of many long non-coding, short non-coding and non-polyadenylated protein-coding transcripts and hinders alternative splicing analysis. We, therefore, developed VASA-seq to detect the total transcriptome in single cells, which is enabled by fragmenting and tailing all RNA molecules subsequent to cell lysis. The method is compatible with both plate-based formats and droplet microfluidics. We applied VASA-seq to more than 30,000 single cells in the developing mouse embryo during gastrulation and early organogenesis. Analyzing the dynamics of the total single-cell transcriptome, we discovered cell type markers, many based on non-coding RNA, and performed in vivo cell cycle analysis via detection of non-polyadenylated histone genes. RNA velocity characterization was improved, accurately retracing blood maturation trajectories. Moreover, our VASA-seq data provide a comprehensive analysis of alternative splicing during mammalian development, which highlighted substantial rearrangements during blood development and heart morphogenesis.
  • dc.description.sponsorship This work was supported by a European Research Council (ERC) Advanced Grant (ERC-AdG 742225-IntScOmics), a Nederlandse Organisatie voor Wetenschappelijk Onderzoek (NWO) TOP award (NWO-CW 714.016.001) and the Wellcome Trust (WT108438/C/15/Z). This work is part of the Oncode Institute, which is partly financed by the Dutch Cancer Society. J.D.J. received scholarship support from the Biotechnology and Biological Sciences Research Council (BBSRC), T.N.K. from AstraZeneca, A.L.E. from the Cambridge Trusts and the EU H2020 Marie Curie ITN MMBio and T.S.K. from an EU H2020 Marie Skłodowska-Curie Actions Individual Fellowship (MSCA-IF 750772). F.H. is an H2020 ERC Advanced Investigator (69566). M.H. was supported by a core grant from the Wellcome Trust and by funding from the Evergrande Center for Immunologic Diseases. J.N. was funded by the Wellcome Trust (03151/Z/16/Z). For the purpose of open access, the author has applied a CC BY public copyright license to any Author Accepted Manuscript version arising from this submission. A.Y. was funded by the BBSRC (RG83885), and the mice used in the study are associated with the Wellcome Trust Strategic Grant (105031). Parts of the illustrations were designed using BioRender.
  • dc.format.mimetype application/pdf
  • dc.identifier.citation Salmen F, De Jonghe J, Kaminski TS, Alemany A, Parada GE, Verity-Legg J, Yanagida A, Kohler TN, Battich N, van den Brekel F, Ellermann AL, Arias AM, Nichols J, Hemberg M, Hollfelder F, van Oudenaarden A. High-throughput total RNA sequencing in single cells using VASA-seq. Nat Biotechnol. 2022 Jun 27. DOI: 10.1038/s41587-022-01361-8
  • dc.identifier.doi http://dx.doi.org/10.1038/s41587-022-01361-8
  • dc.identifier.issn 1087-0156
  • dc.identifier.uri http://hdl.handle.net/10230/54019
  • dc.language.iso eng
  • dc.publisher Nature Research
  • dc.relation.ispartof Nat Biotechnol. 2022 Jun 27
  • dc.relation.projectID info:eu-repo/grantAgreement/EC/H2020/742225
  • dc.relation.projectID info:eu-repo/grantAgreement/EC/H2020/750772
  • dc.rights © The Author(s) 2022. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.
  • dc.rights.accessRights info:eu-repo/semantics/openAccess
  • dc.rights.uri http://creativecommons.org/licenses/by/4.0/
  • dc.subject.keyword Databases
  • dc.subject.keyword Gastrulation
  • dc.subject.keyword Non-coding RNAs
  • dc.subject.keyword RNA splicing
  • dc.subject.keyword Transcriptomics
  • dc.title High-throughput total RNA sequencing in single cells using VASA-seq
  • dc.type info:eu-repo/semantics/article
  • dc.type.version info:eu-repo/semantics/publishedVersion

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