2026-04-13T13:41:00Zhttps://recercat.cat/oai/request

oai:recercat.cat:10230/540192026-03-07T08:42:46Zcom_2072_6col_2072_452952

00925njm 22002777a 4500 dc Salmen, Fredrik author De Jonghe, Joachim author Kaminski, Tomasz S. author Alemany, Anna author Parada, Guillermo E. author Verity-Legg, Joe author Yanagida, Ayaka author Kohler, Timo N. author Battich, Nicholas author van den Brekel, Floris author Ellermann, Anna L. author Martinez Arias, Alfonso author Nichols, Jennifer author Hemberg, Martin author Hollfelder, Florian author van Oudenaarden, Alexander author 2022-09-08T06:04:41Z 2022-09-08T06:04:41Z 2022 Data de publicació electrònica: 27-06-2022 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. 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. Databases Gastrulation Non-coding RNAs RNA splicing Transcriptomics High-throughput total RNA sequencing in single cells using VASA-seq