Abstract
Controlled gene expression programs have a crucial role in shaping cellular functions and activities. At the core of this process lies the RNA life cycle, ensuring protein products are synthesized in the right place at the right time. Here we detail an integrated protocol for imaging-based highly multiplexed in situ profiling of spatial transcriptome using antibody-based protein comapping (STARmap PLUS), spatial translatome mapping (RIBOmap) and spatiotemporal transcriptome mapping (TEMPOmap). These methods selectively convert targeted RNAs, ribosome-bound mRNAs or metabolically labeled RNAs to DNA amplicons with gene-unique barcodes, which are read out through in situ sequencing under a confocal microscope. Compared with other methods, they provide the analytical capacity to track the spatial and temporal dynamics of thousands of RNA species in intact cells and tissues. Our protocol can be readily performed in laboratories experienced in working with RNA and equipped with confocal microscopy instruments. The wet lab experiments in preparing the amplicon library take 2–3 d, followed by variable sequencing times depending on the sample size and target gene number. The spatially resolved single-cell profiles enable downstream analysis, including cell type classification, cell cycle identification and determination of RNA life cycle kinetic parameters through computational analysis guided by the established tutorials. This spatial omics toolkit will help users to better understand spatial and temporal RNA dynamics in heterogeneous cells and tissues.
Key points
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This protocol for highly multiplexed in situ profiling of spatial transcriptome uses STARmap PLUS, RIBOmap or TEMPOmap to selectively convert targeted RNAs, ribosome-bound mRNAs or metabolically labeled RNAs to DNA amplicons with gene-unique barcodes, which are read out through imaging-based in situ sequencing.
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These new methodologies provide the analytical capacity to track the spatial and temporal dynamics of thousands of RNA species and their translational status in intact cells and tissues.
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Data availability
The datasets mentioned and discussed in this protocol are available in the supporting primary research articles15,16,17. All of the processed sequencing data are available in the Single Cell Portal (STARmap PLUS: https://singlecell.broadinstitute.org/single_cell/study/SCP1375, https://singlecell.broadinstitute.org/single_cell/study/SCP1830; RIBOmap: https://singlecell.broadinstitute.org/single_cell/study/SCP1835; TEMPOmap: https://singlecell.broadinstitute.org/single_cell/study/SCP1792) and Zenodo (STARmap PLUS: https://doi.org/10.5281/zenodo.7332091, https://doi.org/10.5281/zenodo.8327576; RIBOmap: https://doi.org/10.5281/zenodo.8041114; TEMPOmap: https://doi.org/10.5281/zenodo.7803716). The demo dataset for tutorial purposes is available via Single Cell Portal at https://singlecell.broadinstitute.org/single_cell/study/SCP2637 and via Zenodo at https://doi.org/10.5281/zenodo.11176779 (ref. 54). Additional information is available at the Wang Lab website (https://www.wangxiaolab.org). Additional raw images or data are available for research purposes upon request from the corresponding author.
Code availability
All codes and analyses are available via GitHub (STARmap PLUS: https://github.com/wanglab-broad/mAD-analysis, https://github.com/wanglab-broad/mCNS-atlas; RIBOmap: https://github.com/wanglab-broad/RIBOmap-analysis; TEMPOmap: https://github.com/wanglab-broad/TEMPOmap) and Zenodo (STARmap PLUS: https://doi.org/10.5281/zenodo.7332091; RIBOmap: https://doi.org/10.5281/zenodo.8041114; TEMPOmap: https://doi.org/10.5281/zenodo.7803716). Probe design is available via GitHub at https://github.com/wanglab-broad/probe-design. Starfinder analysis tool will be maintained and updated at https://github.com/wanglab-broad/starfinder. ClusterMap segmentation method is available at https://github.com/wanglab-broad/ClusterMap. Additional requests can be made by contacting the corresponding author.
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Acknowledgements
H.S. is supported by Helen Hay Whitney Foundation postdoctoral fellowship. X.W. gratefully acknowledges support from the Searle Scholars Program, Thomas D. and Virginia W. Cabot Professorship, Edward Scolnick Professorship, Ono Pharma Breakthrough Science Initiative Award, Packard Fellowship for Science and Engineering, Merkin Institute Fellowship, NIH DP2 New Innovator Award, and Stanley Center gift from the Broad Institute. We thank Y. Zhou, W. X. Wang, M. Wu, Q. Zhang and Y. He for their helpful suggestions to the manuscript.
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Contributions
J.R. and H. Zeng. designed the protocols and performed the experiments. J.H., X.S., C.K.W., H. Zhou, M.W., Z.T. and S.L. performed the computational analysis. J.H. and M.W. cleaned up the starfinder package. J.R., H. Zeng and J.H. wrote the manuscript. H.S., J.T. and X.S. provided critical comments for the manuscript. X.W. supervised the study. All authors critically reviewed and revised the manuscript.
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X.W. is a scientific cofounder of Stellaromics. X.W., J.R. and H. Zeng are inventors on patent applications (International Application No. PCT/US2022/031275, No. PCT/US2022/035271 and No. PCT/US2022/028012) related to STARmap PLUS, RIBOmap and TEMPOmap. The other authors declare no competing interests.
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Nature Protocols thanks Junyue Cao and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.
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Supplementary information
Supplementary Table 1
Complete list of primer and padlock probe hybridization regions for human transcriptome.
Supplementary Table 2
Complete list of primer and padlock probe hybridization regions for mouse transcriptome.
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Ren, J., Zeng, H., Huang, J. et al. Spatially resolved in situ profiling of mRNA life cycle at transcriptome scale in intact cells and tissues using STARmap PLUS, RIBOmap and TEMPOmap. Nat Protoc (2025). https://doi.org/10.1038/s41596-025-01248-3
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DOI: https://doi.org/10.1038/s41596-025-01248-3