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NASC-seq monitors RNA synthesis in single cells

Author

Listed:
  • Gert-Jan Hendriks

    (Biomedicum)

  • Lisa A. Jung

    (NEO)

  • Anton J. M. Larsson

    (Biomedicum)

  • Michael Lidschreiber

    (NEO
    Max Planck Institute for Biophysical Chemistry)

  • Oscar Andersson Forsman

    (Biomedicum)

  • Katja Lidschreiber

    (Max Planck Institute for Biophysical Chemistry)

  • Patrick Cramer

    (NEO
    Max Planck Institute for Biophysical Chemistry)

  • Rickard Sandberg

    (Biomedicum)

Abstract

Sequencing of newly synthesised RNA can monitor transcriptional dynamics with great sensitivity and high temporal resolution, but is currently restricted to populations of cells. Here, we develop new transcriptome alkylation-dependent single-cell RNA sequencing (NASC-seq), to monitor newly synthesised and pre-existing RNA simultaneously in single cells. We validate the method on pre-labelled RNA, and by demonstrating that more newly synthesised RNA was detected for genes with known high mRNA turnover. Monitoring RNA synthesis during Jurkat T-cell activation with NASC-seq reveals both rapidly up- and down-regulated genes, and that induced genes are almost exclusively detected as newly transcribed. Moreover, the newly synthesised and pre-existing transcriptomes after T-cell activation are distinct, confirming that NASC-seq simultaneously measures gene expression corresponding to two time points in single cells. Altogether, NASC-seq enables precise temporal monitoring of RNA synthesis at single-cell resolution during homoeostasis, perturbation responses and cellular differentiation.

Suggested Citation

  • Gert-Jan Hendriks & Lisa A. Jung & Anton J. M. Larsson & Michael Lidschreiber & Oscar Andersson Forsman & Katja Lidschreiber & Patrick Cramer & Rickard Sandberg, 2019. "NASC-seq monitors RNA synthesis in single cells," Nature Communications, Nature, vol. 10(1), pages 1-9, December.
    • Handle: RePEc:nat:natcom:v:10:y:2019:i:1:d:10.1038_s41467-019-11028-9
    DOI: 10.1038/s41467-019-11028-9
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    Cited by:

    1. Shichao Lin & Kun Yin & Yingkun Zhang & Fanghe Lin & Xiaoyong Chen & Xi Zeng & Xiaoxu Guo & Huimin Zhang & Jia Song & Chaoyong Yang, 2023. "Well-TEMP-seq as a microwell-based strategy for massively parallel profiling of single-cell temporal RNA dynamics," Nature Communications, Nature, vol. 14(1), pages 1-11, December.
    2. Teresa Rummel & Lygeri Sakellaridi & Florian Erhard, 2023. "grandR: a comprehensive package for nucleotide conversion RNA-seq data analysis," Nature Communications, Nature, vol. 14(1), pages 1-17, December.
    3. Lior Fishman & Avani Modak & Gal Nechooshtan & Talya Razin & Florian Erhard & Aviv Regev & Jeffrey A. Farrell & Michal Rabani, 2024. "Cell-type-specific mRNA transcription and degradation kinetics in zebrafish embryogenesis from metabolically labeled single-cell RNA-seq," Nature Communications, Nature, vol. 15(1), pages 1-20, December.
    4. Stevens, Nicolas & Papavasiliou, Anthony, 2022. "Application of the Level Method for Computing Locational Convex Hull Prices," LIDAM Discussion Papers CORE 2022002, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

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