ArticleNature genetics2023
Spatiotemporal transcriptomic maps of whole mouse embryos at the onset of organogenesis.
Article in Nature genetics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 53 papers.
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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.
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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.
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Who cites it
53 citing papers in PubMed, 81 citations in OpenAlex.
- 3D multi-omics tumour atlases: from technology to biology and clinical translation.Nature reviews. Cancer · 2026Review
- Towards predictive virtual embryos with genomics and AI.Nature methods · 2026Article
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- Reassessing forebrain organization: recent evidence challenges the prosomere model.Current opinion in genetics & development · 2026Review
- STAID: A Self-Refining Deep Learning Framework for Spatial Cell-Type Deconvolution with Biologically Informed Modeling.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Article
- Article
- Decoding Cardiac Development and Maturation at Single-Cell and Spatial Transcriptomic Resolution.Circulation research · 2026Review
- Review
- Spatial transcriptomic profiling of developing mouse hearts reveals a spatially patterned signaling environment.Communications biology · 2026Article
- SpatialESD: Spatial Ensemble Domain Detection in Spatial Transcriptomics.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Article
- Research progress in single‑cell omics technologies for kidney disease (Review).International journal of molecular medicine · 2026Review
- Celcomen: spatial causal disentanglement for single-cell and tissue perturbation modeling.Nature communications · 2026Article
- stSCI: A multi-task learning framework for integrative analysis of single-cell and spatial transcriptomics data.Innovation (Cambridge (Mass.)) · 2026Article
- SpatialDG: a novel spatial domain identification method for spatially resolved transcriptomics data based on dual-graph neural network.Briefings in bioinformatics · 2026Article
- sc3D: A Comprehensive Tool for 3D Spatial Transcriptomic Analysis.Bio-protocol · 2026Article
- PreTSA: computationally efficient modeling of temporal and spatial gene expression patterns.Genome biology · 2026Article
- ASTRO: Automated Spatial-Transcriptome whole RNA Output.Bioinformatics (Oxford, England) · 2026Article
- jsPCA: fast, scalable, and interpretable identification of spatial domains and variable genes across multi-slice and multi-sample spatial transcriptomics data.Bioinformatics advances · 2026Article
- When imaging technology meets single-cell omics: new paradigm in developmental biology.Cell regeneration (London, England) · 2025Review
- Spatial transcriptomic alignment, integration, and 3D reconstruction by STAIR.Genome biology · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
16 authors at 3 institutions in 3 countries.
Funding
Abstract
Spatiotemporal orchestration of gene expression is required for proper embryonic development. The use of single-cell technologies has begun to provide improved resolution of early regulatory dynamics, including detailed molecular definitions of most cell states during mouse embryogenesis. Here we used Slide-seq to build spatial transcriptomic maps of complete embryonic day (E) 8.5 and E9.0, and partial E9.5 embryos. To support their utility, we developed sc3D, a tool for reconstructing and exploring three-dimensional 'virtual embryos', which enables the quantitative investigation of regionalized gene expression patterns. Our measurements along the main embryonic axes of the developing neural tube revealed several previously unannotated genes with distinct spatial patterns. We also characterized the conflicting transcriptional identity of 'ectopic' neural tubes that emerge in Tbx6 mutant embryos. Taken together, we present an experimental and computational framework for the spatiotemporal investigation of whole embryonic structures and mutant phenotypes.
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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.