ArticleNature biotechnology2022
Integration of spatial and single-cell transcriptomic data elucidates mouse organogenesis.
Article in Nature biotechnology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 224 papers.
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Who cites it
224 citing papers in PubMed, 336 citations in OpenAlex.
- Immunophenotyping by Spatial Biology.Methods in molecular biology (Clifton, N.J.) · 2027Article
- 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
- FlowMap: Geometry-Dynamics Consistent Embedding of RNA Velocity for Interpretable Cellular Trajectories.bioRxiv : the preprint server for biology · 2026Article
- Weighted sliced inverse regression for scalable supervised dimensionality reduction of spatial transcriptomics data.Nature communications · 2026Article
- Single-cell and single-nucleus transcriptomics of the dorsal root ganglion in neuropathic pain: cell-state remodeling and translational prospects.Journal of translational medicine · 2026Review
- OT-knn: A neighborhood-aware optimal transport framework for aligning spatial transcriptomics data.PLoS computational biology · 2026Article
- Reassessing forebrain organization: recent evidence challenges the prosomere model.Current opinion in genetics & development · 2026Review
- CTMAP: an adversarial cross-modal learning framework for accurate and robust cell-type annotation in single-cell resolution spatial transcriptomics.Briefings in bioinformatics · 2026Article
- Scalable multi-group nonnegative spatial factorization for spatial genomics data with cell-type heterogeneity.bioRxiv : the preprint server for biology · 2026Article
- Dissecting and steering cell dynamics using spatially-informed RNA velocity with veloAgent.Molecular systems biology · 2026Article
- A masked generative graph representation learning framework empowering precise spatial domain identification.Bioinformatics (Oxford, England) · 2026Article
- Spatially tunable multiomic sequencing using light-driven combinatorial barcoding of molecules in tissues.Proceedings of the National Academy of Sciences of the United States of America · 2026Article
- Interpretable, flexible and spatially aware integration of multiple spatial transcriptomics datasets from diverse sources.Nature genetics · 2026Article
- SpatialQuery: scalable discovery and molecular characterization of multicellular motifs from spatial omics data.bioRxiv : the preprint server for biology · 2026Article
- Spatial Mapping of Single Cells via Correlation and Importance Between Cells and Spots.Interdisciplinary sciences, computational life sciences · 2026Article
- Topography-aware optimal transport for alignment of spatial omics data.Cell reports methods · 2026Article
- spRefine denoises and imputes spatial transcriptomic data with a reference-free framework powered by genomic language model.Genome research · 2026Article
- autoFISH: a modular toolbox for sequential single-molecule RNA FISH experiments.Communications biology · 2026Article
- Alignment of spatial transcriptomics slices across diseases, platforms and conditions.Genome medicine · 2026Article
- Single-Cell Multi-Omics Reveal Gene Regulatory Mechanisms Underlying Cardiac Embryonic Development.Genes · 2026Review
164 more citing papers are in PubMed but not listed here.
Corrections and comments
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Authors and funding
20 authors at 8 institutions in 4 countries.
Funding
Abstract
Molecular profiling of single cells has advanced our knowledge of the molecular basis of development. However, current approaches mostly rely on dissociating cells from tissues, thereby losing the crucial spatial context of regulatory processes. Here, we apply an image-based single-cell transcriptomics method, sequential fluorescence in situ hybridization (seqFISH), to detect mRNAs for 387 target genes in tissue sections of mouse embryos at the 8-12 somite stage. By integrating spatial context and multiplexed transcriptional measurements with two single-cell transcriptome atlases, we characterize cell types across the embryo and demonstrate that spatially resolved expression of genes not profiled by seqFISH can be imputed. We use this high-resolution spatial map to characterize fundamental steps in the patterning of the midbrain-hindbrain boundary (MHB) and the developing gut tube. We uncover axes of cell differentiation that are not apparent from single-cell RNA-sequencing (scRNA-seq) data, such as early dorsal-ventral separation of esophageal and tracheal progenitor populations in the gut tube. Our method provides an approach for studying cell fate decisions in complex tissues and 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.