ArticleCell2025
Sequencing-free whole-genome spatial transcriptomics at single-molecule resolution.
Article in Cell, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 27 papers.
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.
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.
Who cites it
27 citing papers in PubMed.
- Interpretable AI model reveals spatial codes of cell recruitment in tissues.Nature biomedical engineering · 2026Article
- Decoding epithelial-mesenchymal transitions with multi-omics.Nature reviews. Genetics · 2026Review
- Article
- Artificial intelligence in spatial transcriptomics: a review of methods, datasets, and directions.Briefings in bioinformatics · 2026Review
- Spatial omics illuminates tumor heterogeneity.Cell reports methods · 2026Review
- Review
- Three-dimensional multimodal fractal dynamics integrating spatial metabolism, cytoarchitecture, and perfusion for preoperative prediction of microvascular invasion in colorectal liver metastases.Journal of translational medicine · 2026Article
- Data-intensive immune network modelling for One Health.Briefings in bioinformatics · 2026Review
- Causal effect estimation from trans-regulatory single-cell CRISPR screens.Cell genomics · 2026Review
- Imaging-Based Spatial Transcriptomics: Data Interpretation Methods and Biomedical Applications.Biology · 2026Review
- Metabolic and redox adaptations of the corneal endothelium: From metabolic plasticity to therapeutic opportunities.Redox biology · 2026Review
- Review
- A Guide for Spatial Omics Technologies: Innovation, Evaluation, and Application.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Review
- Beyond the Cell Atlas: Functional Communities as the Essential Pathologic Units Driving Kidney Disease.Journal of the American Society of Nephrology : JASN · 2026Review
- Whole-genome spatial transcriptomic imaging with RAEFISH.Nature reviews. Genetics · 2026Article
- A transcriptomic axis aligns with in vivo functional dynamics in hippocampal inhibitory circuits.bioRxiv : the preprint server for biology · 2026Article
- Single-Cell and Spatial Omics: Methods and Applications.MedComm · 2026Review
- Decoding neurodegeneration one cell at a time.The Journal of clinical investigation · 2026Review
- Probing neuropsychiatric disorders through in vivo CRISPR screening.Current opinion in genetics & development · 2026Review
- Mapping multipathology via spatial omic integration.Current opinion in biotechnology · 2026Review
Corrections and comments
- Erratum issued
- Update of
Authors and funding
10 authors.
Funding
Abstract
Recent breakthroughs in spatial transcriptomics technologies have enhanced our understanding of diverse cellular identities, spatial organizations, and functions. Yet existing spatial transcriptomics tools are still limited in either transcriptomic coverage or spatial resolution, hindering unbiased, hypothesis-free transcriptomic analyses at high spatial resolution. Here, we develop reverse-padlock amplicon-encoding fluorescence in situ hybridization (RAEFISH), an image-based spatial transcriptomics method with whole-genome coverage and single-molecule resolution in intact tissues. We demonstrate the spatial profiling of transcripts from 23,000 human or 22,000 mouse genes in single cells and tissue sections. Our analyses reveal transcript-specific subcellular localization, cell-type-specific and cell-type-invariant zonation-dependent transcriptomes, and gene programs underlying preferential cell-cell interactions. Finally, we further develop our technology for the direct spatial readout of guide RNAs (gRNAs) in an image-based, high-content CRISPR screen. Overall, these developments offer a broadly applicable technology that enables high-coverage, high-resolution spatial profiling of both long and short, native and engineered RNAs in many biomedical contexts.
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Registered trials
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.