ArticleScience (New York, N.Y.)2021
Embryo-scale, single-cell spatial transcriptomics.
Article in Science (New York, N.Y.), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 164 papers.
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Who cites it
164 citing papers in PubMed.
- Integrative single-cell and spatial transcriptomic approaches to decipher the tumor microenvironment and therapeutic resistance in pancreatic cancer.Cancer biology & therapy · 2026Review
- Resolving cell-cell interaction networks and their molecular logic in complex tissues.Nature methods · 2026Article
- Insights Into Spatial Transcriptomics: Exploring Recent Technical Developments and Their Diverse Applications.FASEB journal : official publication of the Federation of American Societies for Experimental Biology · 2026Review
- Specificity-driven graph learning for the identification of rare cell states.Advanced biotechnology · 2026Article
- Mesolens imaging in microbiology.Essays in biochemistry · 2026Review
- Single-Cell Annotation and Localization via Integrating Spatial Transcriptomics Maps the Mouse Ocular Atlas and RAO Dynamics.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Article
- STAID: A Self-Refining Deep Learning Framework for Spatial Cell-Type Deconvolution with Biologically Informed Modeling.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Article
- Sequencing-free spatial profiling of post-transcriptional regulation in fresh tissues using nanoneedle arrays.Nature biomedical engineering · 2026Article
- Specificity-driven cell-gene graph learning identifies rare cell states in single-cell and spatial transcriptomic data.Advanced biotechnology · 2026Article
- Advances in the Comprehensive Tree Shrew Brain Atlas.Biomolecules · 2026Review
- Dissecting human organ development using spatial technologies.Developmental cell · 2026Review
- Variational sparse Gaussian-process method for detecting spatially variable genes and cellular interactions in spatial transcriptomics.Briefings in bioinformatics · 2026Article
- The applications of single-cell and spatial transcriptomics in neuroscience and brain disorders.Neuroscience and biobehavioral reviews · 2026Review
- Optics-free spatial genomics for mapping mammalian brain aging by IRISeq.Nature neuroscience · 2026Article
- Embryo-scale Visual Cell Sorting reveals a conserved transcriptomic signature of nucleolar size linked to proteostasis.bioRxiv : the preprint server for biology · 2026Article
- A Guide for Spatial Omics Technologies: Innovation, Evaluation, and Application.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Review
- Advances in the application of spatial transcriptomics in understanding development and disease.Molecular and cellular biochemistry · 2026Review
- An expanded role for single-cell chemical genomics profiling in drug discovery.The Biochemical journal · 2026Review
- Spatial omics at the forefront: emerging technologies, analytical innovations, and clinical applications.Cancer cell · 2026Review
- Spatial information matters: are traditional imputation methods effective for spatial transcriptomics data?Briefings in bioinformatics · 2026Article
104 more citing papers are in PubMed but not listed here.
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Authors and funding
15 authors.
Funding
Abstract
Spatial patterns of gene expression manifest at scales ranging from local (e.g., cell-cell interactions) to global (e.g., body axis patterning). However, current spatial transcriptomics methods either average local contexts or are restricted to limited fields of view. Here, we introduce sci-Space, which retains single-cell resolution while resolving spatial heterogeneity at larger scales. Applying sci-Space to developing mouse embryos, we captured approximate spatial coordinates and whole transcriptomes of about 120,000 nuclei. We identify thousands of genes exhibiting anatomically patterned expression, leverage spatial information to annotate cellular subtypes, show that cell types vary substantially in their extent of spatial patterning, and reveal correlations between pseudotime and the migratory patterns of differentiating neurons. Looking forward, we anticipate that sci-Space will facilitate the construction of spatially resolved single-cell atlases of mammalian development.
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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.