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PreprintCited by 78Single-cell and spatial transcriptomicsRNA Research and SplicingRNA and protein synthesis mechanisms

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Spatiotemporally resolved transcriptomics reveals subcellular RNA kinetic landscape

Open access
Ren, Jingyi, Zhou, Haowen, Zeng, Hu, Wang, Connie Kangni, Huang, Jiahao, Qiu, Xiaojie, Maher, Kamal, Lin, Zuwan, He, Yichun, Tang, Xin, Li, Brian, Liu, Jia, Wang, Xiao·2022·Nature Methods
DOI 10.1101/2022.09.27.509606PMC PMC10172111

Preprint — published as 10.1038/s41592-023-01829-8 · Paper page

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Abstract

Summary: Spatiotemporal regulation of the cellular transcriptome is crucial for proper protein expression and cellular function 1 . However, the intricate subcellular dynamics of RNA synthesis, decay, export, and translocation remain obscured due to the limitations of existing transcriptomics methods 2–8 . Here, we report a spatiotemporally resolved RNA mapping method (TEMPOmap) to uncover subcellular RNA profiles across time and space at the single-cell level in heterogeneous cell populations. TEMPOmap integrates pulse-chase metabolic labeling of the transcriptome with highly multiplexed three-dimensional (3D) in situ sequencing to simultaneously profile the age and location of individual RNA molecules. Using TEMPOmap, we constructed the subcellular RNA kinetic landscape of 991 genes in human HeLa cells from upstream transcription to downstream subcellular translocation. Clustering analysis of critical RNA kinetic parameters across single cells revealed kinetic gene clusters whose expression patterns were shaped by multi-step kinetic sculpting. Importantly, these kinetic gene clusters are functionally segregated, suggesting that subcellular RNA kinetics are differentially regulated to serve molecular and cellular functions in cell-cycle dependent manner. Together, these single-cell spatiotemporally resolved transcriptomics measurements provide us the gateway to uncover new gene regulation principles and understand how kinetic strategies enable precise RNA expression in time and space.

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Metadata

Authors
Ren, J., Zhou, H., Zeng, H., Wang, C. K., Huang, J., Qiu, X., Maher, K., Lin, Z., He, Y., Tang, X., Li, B., Liu, J., & Wang, X.
Affiliations
  • Broad Institute (US)
  • Whitehead Institute for Biomedical Research (US)
Corresponding author
Wang, Xiao
ORCID
Venue
Nature Methods
Publisher
openRxiv
Published
2022-09-27
Volume
20
Issue
5
Pages
695-705
ISSN
1548-7091 (ISSN-L)
DOI
10.1101/2022.09.27.509606
PMC
PMC10172111
OpenAlex
W4362737502
Cited by
78
References
1
Citations by year
2026: 21 · 2025: 26 · 2024: 23 · 2023: 8
FWCI
6.89
Type
journal article
Language
en
Open access
Licence
cc-by
Locations
  • Nature Methods (publishedVersion, cc-by)
  • bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion, cc-by-nc-nd)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • Digital Access to Scholarship at Harvard (DASH) (Harvard University) (submittedVersion, cc-by)
Funders
  • National Institutes of Health
  • National Institute of General Medical Sciences (T32GM087237, DP2GM146245)
  • National Institute of Arthritis and Musculoskeletal and Skin Diseases (T32AR007098)
Topics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Single-cell and spatial transcriptomics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › RNA Research and Splicing
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › RNA and protein synthesis mechanisms
Keywords
spatiotemporal transcriptomics, RNA localization, RNA degradation, spatiotemporal gene regulation
MeSH terms
Gene Expression Regulation, Humans, Kinetics, RNA, Gene Expression Profiling, Single-Cell Analysis, Transcriptome

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