The DOI matches its Crossref record; 122 of the 122 references it cites were found in a registry or an index.
Cells of the human intestinal tract mapped across space and time
Open accessAbstract
The cellular landscape of the human intestinal tract is dynamic throughout life, developing in utero and changing in response to functional requirements and environmental exposures. Here, to comprehensively map cell lineages, we use single-cell RNA sequencing and antigen receptor analysis of almost half a million cells from up to 5 anatomical regions in the developing and up to 11 distinct anatomical regions in the healthy paediatric and adult human gut. This reveals the existence of transcriptionally distinct BEST4 epithelial cells throughout the human intestinal tract. Furthermore, we implicate IgG sensing as a function of intestinal tuft cells. We describe neural cell populations in the developing enteric nervous system, and predict cell-type-specific expression of genes associated with Hirschsprung’s disease. Finally, using a systems approach, we identify key cell players that drive the formation of secondary lymphoid tissue in early human development. We show that these programs are adopted in inflammatory bowel disease to recruit and retain immune cells at the site of inflammation. This catalogue of intestinal cells will provide new insights into cellular programs in development, homeostasis and disease.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
limma powers differential expression analyses for RNA-sequencing and microarray studies
Ritchie, M. E., Phipson, B., Wu, D., Hu, Y., Law, C. W., Shi, W., & Smyth, G. K. (2015) · Nucleic Acids Research · doi:10.1093/nar/gkv007 · Cited by 40,458
Tissue-based map of the human proteome
Uhlén, M., Fagerberg, L., Hallström, B. M., Lindskog, C., Oksvold, P., Mardinoglu, A., Sivertsson, Å., Kampf, C., Sjöstedt, E., Asplund, A., et al. (2015) · Science · doi:10.1126/science.1260419 · Cited by 15,286
UMAP: Uniform Manifold Approximation and Projection
McInnes, L., Healy, J., Saul, N., & Großberger, L. (2018) · Journal of Open Source Software · doi:10.21105/joss.00861 · Cited by 9,826
Trapnell, C., Cacchiarelli, D., Grimsby, J., Pokharel, P., Li, S., Morse, M., Lennon, N. J., Livak, K. J., Mikkelsen, T. S., & Rinn, J. L. (2014) · Nature Biotechnology · doi:10.1038/nbt.2859 · Cited by 7,314
Reversed graph embedding resolves complex single-cell trajectories
Qiu, X., Mao, Q., Tang, Y., Wang, L., Chawla, R., Pliner, H. A., & Trapnell, C. (2017) · Nature Methods · doi:10.1038/nmeth.4402 · Cited by 5,070
Dissecting the multicellular ecosystem of metastatic melanoma by single-cell RNA-seq
Tirosh, I., Izar, B., Prakadan, S. M., Wadsworth, M. H., Treacy, D., Trombetta, J. J., Rotem, A., Rodman, C., Lian, C., Murphy, G., et al. (2016) · Science · doi:10.1126/science.aad0501 · Cited by 4,944
The single-cell transcriptional landscape of mammalian organogenesis
Cao, J., Spielmann, M., Qiu, X., Huang, X., Ibrahim, D. M., Hill, A. J., Zhang, F., Mundlos, S., Christiansen, L., Steemers, F. J., et al. (2019) · Nature · doi:10.1038/s41586-019-0969-x · Cited by 4,490
Efremova, M., Vento-Tormo, M., Teichmann, S. A., & Vento-Tormo, R. (2020) · Nature Protocols · doi:10.1038/s41596-020-0292-x · Cited by 3,449
Self-citationGeneralizing RNA velocity to transient cell states through dynamical modeling
Bergen, V., Lange, M., Peidli, S., Wolf, F. A., & Theis, F. J. (2020) · Nature Biotechnology · doi:10.1038/s41587-020-0591-3 · Cited by 2,951
Single-cell reconstruction of the early maternal–fetal interface in humans
Vento-Tormo, R., Efremova, M., Botting, R. A., Turco, M. Y., Vento-Tormo, M., Meyer, K. B., Park, J.-E., Stephenson, E., Polański, K., Goncalves, A., et al. (2018) · Nature · doi:10.1038/s41586-018-0698-6 · Cited by 2,358
Self-citation
Cited by
Cell2location maps fine-grained cell types in spatial transcriptomics
Kleshchevnikov, V., Shmatko, A., Dann, E., Aivazidis, A., King, H. W., Li, T., Elmentaite, R., Lomakin, A., Kedlian, V., Gayoso, A., et al. (2022) · Nature Biotechnology · doi:10.1038/s41587-021-01139-4 · Cited by 1,279
Self-citationSpatially resolved multiomics of human cardiac niches
Kanemaru, K., Cranley, J., Muraro, D., Miranda, A. M. A., Ho, S. Y., Wilbrey-Clark, A., Patrick Pett, J., Polanski, K., Richardson, L., Litvinukova, M., et al. (2023) · Nature · doi:10.1038/s41586-023-06311-1 · Cited by 425
Self-citationThe emerging landscape of spatial profiling technologies
Moffitt, J. R., Lundberg, E., & Heyn, H. (2022) · Nature Reviews Genetics · doi:10.1038/s41576-022-00515-3 · Cited by 419
Mapping the developing human immune system across organs
Suo, C., Dann, E., Goh, I., Jardine, L., Kleshchevnikov, V., Park, J.-E., Botting, R. A., Stephenson, E., Engelbert, J., Tuong, Z. K., et al. (2022) · Science · doi:10.1126/science.abo0510 · Cited by 340
Self-citationBANKSY unifies cell typing and tissue domain segmentation for scalable spatial omics data analysis
Singhal, V., Chou, N., Lee, J., Yue, Y., Liu, J., Chock, W. K., Lin, L., Chang, Y.-C., Teo, E. M. L., Aow, J., et al. (2024) · Nature Genetics · doi:10.1038/s41588-024-01664-3 · Cited by 282
Metadata
- Authors
- Elmentaite, R., Kumasaka, N., Roberts, K., Fleming, A., Dann, E., King, H. W., Kleshchevnikov, V., Dabrowska, M., Pritchard, S., Bolt, L., Vieira, S. F., Mamanova, L., Huang, N., Perrone, F., Goh Kai’En, I., Lisgo, S. N., Katan, M., Leonard, S., Oliver, T. R. W., Hook, C. E., Nayak, K., Campos, L. S., Domínguez Conde, C., Stephenson, E., Engelbert, J., Botting, R. A., Polanski, K., van Dongen, S., Patel, M., Morgan, M. D., Marioni, J. C., Bayraktar, O. A., Meyer, K. B., He, X., Barker, R. A., Uhlig, H. H., Mahbubani, K. T., Saeb-Parsy, K., Zilbauer, M., Clatworthy, M. R., Haniffa, M., James, K. R., & Teichmann, S. A.
- Venue
- Nature
- Published
- 2021-09-08
- Volume
- 597
- Issue
- 7875
- Pages
- 250-255
- ISSN
- 0028-0836 (ISSN-L)
- 1476-4687
- OpenAlex
- W3149417142
- Cited by
- 699
- References
- 122
- FWCI
- 25.83
- Type
- journal article
- Language
- en
- Open access
- hybrid
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Cells of the human intestinal tract mapped across space and time. https://app.cochat.ai/papers/10.1038/s41586-021-03852-1
- The paper
- Elmentaite, R., Kumasaka, N., Roberts, K., Fleming, A., Dann, E., King, H. W., Kleshchevnikov, V., Dabrowska, M., Pritchard, S., Bolt, L., Vieira, S. F., Mamanova, L., Huang, N., Perrone, F., Goh Kai’En, I., Lisgo, S. N., Katan, M., Leonard, S., Oliver, T. R. W., . . . Teichmann, S. A. (2021). Cells of the human intestinal tract mapped across space and time. Nature. https://doi.org/10.1038/s41586-021-03852-1
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
