The DOI matches its Crossref record; 52 of the 52 references it cites were found in a registry or an index.
Epithelial-Mesenchymal Micro-niches Govern Stem Cell Lineage Choices
Open accessAbstract
Summary Adult tissue stem cells (SCs) reside in niches, which through intercellular contacts and signaling, influence SC behavior. Once activated, SCs typically give rise to short-lived transit-amplifying cells (TACs), which then progress to differentiate into their lineages. Here, using single cell RNA-sequencing, we unearth unexpected heterogeneity among SCs and TACs of hair follicles. We trace the roots of this heterogeneity to micro-niches along epithelial-mesenchymal interfaces, where progenitors display molecular signatures reflective of spatially distinct local signals and intercellular interactions. Using lineage-tracing, temporal single cell analyses and chromatin landscaping, we show that SC plasticity becomes restricted in a sequentially and spatially choreographed program, culminating in seven spatially arranged uni-lineage progenitors within TACs of mature follicles. By compartmentalizing SCs into micro-niches, tissues gain precise control over morphogenesis and regeneration: Some progenitors specify lineages immediately; others retain potency, preserving self-renewing features established early while progressively restricting lineages as they experience dynamic changes in microenvironment.
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
Scikit-learn: Machine Learning in Python
Pedregosa, F., Varoquaux, G., Gramfort, A., Michel, V., Thirion, B., Grisel, O., Blondel, M., Müller, A., Nothman, J., Louppe, G., et al. (2012) · arXiv · doi:10.48550/arxiv.1201.0490 · Cited by 71,016
Fast gapped-read alignment with Bowtie 2
Langmead, B., & Salzberg, S. L. (2012) · Nature Methods · doi:10.1038/nmeth.1923 · Cited by 56,400
Subramanian, A., Tamayo, P., Mootha, V. K., Mukherjee, S., Ebert, B. L., Gillette, M. A., Paulovich, A., Pomeroy, S. L., Golub, T. R., Lander, E. S., et al. (2005) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0506580102 · Cited by 53,625
Systematic and integrative analysis of large gene lists using DAVID bioinformatics resources
Huang, D. W., Sherman, B. T., & Lempicki, R. A. (2009) · Nature Protocols · doi:10.1038/nprot.2008.211 · Cited by 35,890
(2008) · Journal of Machine Learning Research · Cited by 33,051
RSEM: accurate transcript quantification from RNA-Seq data with or without a reference genome
Li, B., & Dewey, C. N. (2011) · BMC Bioinformatics · doi:10.1186/1471-2105-12-323 · Cited by 22,179
Differential expression analysis for sequence count data
Anders, S., & Huber, W. (2010) · Genome Biology · doi:10.1186/gb-2010-11-10-r106 · Cited by 15,581
Robinson, J. T., Thorvaldsdóttir, H., Winckler, W., Guttman, M., Lander, E. S., Getz, G., & Mesirov, J. P. (2011) · Nature Biotechnology · doi:10.1038/nbt.1754 · Cited by 15,390
Buenrostro, J. D., Giresi, P. G., Zaba, L. C., Chang, H. Y., & Greenleaf, W. J. (2013) · Nature Methods · doi:10.1038/nmeth.2688 · Cited by 6,422
Model-Based Clustering, Discriminant Analysis, and Density Estimation
Fraley, C., & Raftery, A. E. (2002) · Journal of the American Statistical Association · doi:10.1198/016214502760047131 · Cited by 4,257
Cited by
Chromatin Potential Identified by Shared Single-Cell Profiling of RNA and Chromatin
Ma, S., Zhang, B., LaFave, L. M., Earl, A. S., Chiang, Z., Hu, Y., Ding, J., Brack, A., Kartha, V. K., Tay, T., et al. (2020) · Cell · doi:10.1016/j.cell.2020.09.056 · Cited by 1,146
Guerrero-Juarez, C. F., Dedhia, P. H., Jin, S., Ruiz-Vega, R., Ma, D., Liu, Y., Yamaga, K., Shestova, O., Gay, D. L., Yang, Z., et al. (2019) · Nature Communications · doi:10.1038/s41467-018-08247-x · Cited by 521
Skin and Its Regenerative Powers: An Alliance between Stem Cells and Their Niche
Gonzales, K. A. U., & Fuchs, E. (2017) · Developmental Cell · doi:10.1016/j.devcel.2017.10.001 · Cited by 414
Self-citationTissue Stem Cells: Architects of Their Niches
Fuchs, E., & Blau, H. M. (2020) · Cell Stem Cell · doi:10.1016/j.stem.2020.09.011 · Cited by 332
Self-citationThe Molecular Anatomy of Mouse Skin during Hair Growth and Rest
Joost, S., Annusver, K., Jacob, T., Sun, X., Dalessandri, T., Sivan, U., Sequeira, I., Sandberg, R., & Kasper, M. (2020) · Cell Stem Cell · doi:10.1016/j.stem.2020.01.012 · Cited by 328
Metadata
- Authors
- Yang, H., Adam, R. C., Ge, Y., Hua, Z. L., & Fuchs, E.
- Venue
- Cell
- Publisher
- Elsevier BV
- Published
- 2017-04
- Volume
- 169
- Issue
- 3
- Pages
- 483-496.e13
- ISSN
- 0092-8674 (ISSN-L)
- OpenAlex
- W2607067924
- Cited by
- 257
- References
- 52
- FWCI
- 37.04
- Type
- journal article
- Language
- en
- Open access
- bronze
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: Epithelial-Mesenchymal Micro-niches Govern Stem Cell Lineage Choices. https://app.cochat.ai/papers/10.1016/j.cell.2017.03.038
- The paper
- Yang, H., Adam, R. C., Ge, Y., Hua, Z. L., & Fuchs, E. (2017). Epithelial-Mesenchymal Micro-niches Govern Stem Cell Lineage Choices. Cell. https://doi.org/10.1016/j.cell.2017.03.038
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.