ArticleProceedings of the National Academy of Sciences of the United States of America2023
Neighbor-specific gene expression revealed from physically interacting cells during mouse embryonic development.
Article in Proceedings of the National Academy of Sciences of the United States of America, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
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Who cites it
14 citing papers in PubMed, 18 citations in OpenAlex.
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- SC2Spa: a deep learning based approach to map transcriptome to spatial origins at cellular resolution.BMC bioinformatics · 2025Article
- SCIG: Machine learning uncovers cell identity genes in single cells by genetic sequence codes.Nucleic acids research · 2025Article
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- A novel method for characterizing cell-cell interactions at single-cell resolution reveals unique signatures in blood T cell-monocyte complexes during infection.bioRxiv : the preprint server for biology · 2024Article
- CellContrast: Reconstructing spatial relationships in single-cell RNA sequencing data via deep contrastive learning.Patterns (New York, N.Y.) · 2024Article
- Simultaneous CRISPR screening and spatial transcriptomics reveals intracellular, intercellular, and functional transcriptional circuits.bioRxiv : the preprint server for biology · 2023Article
- CellNeighborEX: deciphering neighbor-dependent gene expression from spatial transcriptomics data.Molecular systems biology · 2023Article
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- Spatial transcriptomics in glioblastoma: is knowing the right zip code the key to the next therapeutic breakthrough?Frontiers in oncology · 2023Review
- Adult tissue-specific stem cell interaction: novel technologies and research advances.Frontiers in cell and developmental biology · 2023Review
- CCPLS reveals cell-type-specific spatial dependence of transcriptomes in single cells.Bioinformatics (Oxford, England) · 2022Article
Corrections and comments
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Authors and funding
19 authors at 5 institutions in 5 countries.
Funding
Abstract
Development of multicellular organisms is orchestrated by persistent cell-cell communication between neighboring partners. Direct interaction between different cell types can induce molecular signals that dictate lineage specification and cell fate decisions. Current single-cell RNA-seq technology cannot adequately analyze cell-cell contact-dependent gene expression, mainly due to the loss of spatial information. To overcome this obstacle and resolve cell-cell contact-specific gene expression during embryogenesis, we performed RNA sequencing of physically interacting cells (PIC-seq) and assessed them alongside similar single-cell transcriptomes derived from developing mouse embryos between embryonic day (E) 7.5 and E9.5. Analysis of the PIC-seq data identified gene expression signatures that were dependent on the presence of specific neighboring cell types. Our computational predictions, validated experimentally, demonstrated that neural progenitor (NP) cells upregulate
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Registered trials
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