Evidence map›Paper›PMID 41286200›Full record

ArticleNature methods2025

Scalable spatial single-cell transcriptomics and translatomics in 3D thick tissue blocks.

Xin Sui, Jennifer A Lo, Shuchen Luo, Yichun He, Zefang Tang, Zuwan Lin, Dániel L Barabási, Yiming Zhou, Wendy Xueyi Wang, Jia Liu and 1 more

Abstract read
PubMed Publisher
In one paragraph

Article in Nature methods, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers.

0numbers the graph read from it
0cells of the map it votes in
26citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

26 citing papers in PubMed.

  1. Review
  2. Article
  3. Article
  4. Article
  5. Subcellularly Resolved 3D Translatome in Mouse Oocytes and Early Embryos.bioRxiv : the preprint server for biology · 2026
    Article
  6. Article
  7. Article
  8. Review
  9. Review
  10. Article
  11. A Guide for Spatial Omics Technologies: Innovation, Evaluation, and Application.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026
    Review
  12. Review
  13. Review
  14. Review
  15. Article
  16. Year in review 2025.Nature methods · 2026
    Article
  17. Review
  18. Review
  19. Review
  20. Review
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

11 authors.

Xin Sui *Department of Chemistry, Massachusetts Institute of Technology, Cambridge, MA, USA.ORCID http://orcid.org/0000-0002-7286-9448
Jennifer A Lo *Broad Institute of MIT and Harvard, Cambridge, MA, USA.ORCID http://orcid.org/0000-0002-9520-6874
Shuchen LuoDepartment of Chemistry, Massachusetts Institute of Technology, Cambridge, MA, USA.ORCID http://orcid.org/0000-0001-8754-1413
Yichun HeBroad Institute of MIT and Harvard, Cambridge, MA, USA.ORCID http://orcid.org/0000-0001-9573-2682
Zefang TangDepartment of Chemistry, Massachusetts Institute of Technology, Cambridge, MA, USA.ORCID http://orcid.org/0000-0002-5264-9560
Zuwan LinBroad Institute of MIT and Harvard, Cambridge, MA, USA.
Dániel L BarabásiBroad Institute of MIT and Harvard, Cambridge, MA, USA.ORCID http://orcid.org/0000-0001-6015-7534
Yiming ZhouDepartment of Chemistry, Massachusetts Institute of Technology, Cambridge, MA, USA.
Wendy Xueyi WangDepartment of Chemistry, Massachusetts Institute of Technology, Cambridge, MA, USA.ORCID http://orcid.org/0000-0001-6472-1075
Jia LiuJohn A. Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, MA, USA.ORCID http://orcid.org/0000-0003-2217-6982
Xiao WangDepartment of Chemistry, Massachusetts Institute of Technology, Cambridge, MA, USA. xwangx@mit.edu.ORCID http://orcid.org/0000-0002-3090-9894

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Characterizing the transcriptional and translational gene expression patterns at the single-cell level within their three-dimensional (3D) tissue context is essential for revealing how genes shape tissue structure and function in health and disease. However, most existing spatial profiling techniques are limited to 5-20 µm thin tissue sections. Here, we developed Deep-STARmap and Deep-RIBOmap, which enable 3D in situ quantification of thousands of gene transcripts and their corresponding translation activities, respectively, within 60-200-µm thick tissue blocks. This is achieved through scalable probe synthesis, hydrogel embedding with efficient probe anchoring and robust cDNA crosslinking. We first utilized Deep-STARmap in combination with multicolor fluorescent protein imaging for simultaneous molecular cell typing and 3D neuron morphology tracing in the mouse brain. We also demonstrate that 3D spatial profiling facilitates comprehensive and quantitative analysis of tumor-immune interactions in human skin cancer.

Indexed as

Gene Expression ProfilingImaging, Three-DimensionalSingle-Cell AnalysisTranscriptomeAnimalsBrainHumansMiceNeuronsSkin Neoplasms

Identifiers

PMID41286200

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.