Single-Cell Transcriptomics Reveals that Differentiation and Spatial Signatures Shape Epidermal and Hair Follicle Heterogeneity
Open accessAbstract
The murine epidermis with its hair follicles represents an invaluable model system for tissue regeneration and stem cell research. Here we used single-cell RNA-sequencing to reveal how cellular heterogeneity of murine telogen epidermis is tuned at the transcriptional level. Unbiased clustering of 1,422 single-cell transcriptomes revealed 25 distinct populations of interfollicular and follicular epidermal cells. Our data allowed the reconstruction of gene expression programs during epidermal differentiation and along the proximal-distal axis of the hair follicle at unprecedented resolution. Moreover, transcriptional heterogeneity of the epidermis can essentially be explained along these two axes, and we show that heterogeneity in stem cell compartments generally reflects this model: stem cell populations are segregated by spatial signatures but share a common basal-epidermal gene module. This study provides an unbiased and systematic view of transcriptional organization of adult epidermis and highlights how cellular heterogeneity can be orchestrated in vivo to assure tissue homeostasis.
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Putative pilosebaceous clusters were identified based on expression of KRT15, LHX2, and SOX9.
“We identified putative pilosebaceous clusters based on expression of known hair follicle markers or transcription factors (KRT15, LHX2, SOX9) and prior mouse and human studies in addition to manual cross-referencing of the Human Protein Atlas (Joost et al., 2016, Purba et al., 2015, Uhlén et al., 2015) and removed these from further analysis.”
From Multimodal Analysis of Composition and Spatial Architecture in Human Squamous Cell Carcinoma (2020) · cites this paper as Joost et al., 2016
The epithelial group contained three epidermal sub-clusters: CXCL14+ basal, KRT1+ intermediate, and KRT4+ peridermal keratinocytes.
“The epithelial group contained three epidermal sub-clusters: CXCL14+ basal, KRT1+ intermediate, and KRT4+ peridermal keratinocytes (Fig. 2e, Extended Data Fig. 5)22.”
From Hair-bearing human skin generated entirely from pluripotent stem cells (2020) · cites this paper as [22]
The Results sections on unbiased clustering and subclustering describe murine epidermal and hair-follicle populations, including basal cells marked by Krt14 and Krt5. The searched passages do not describe an epithelial group divided into CXCL14+ basal, KRT1+ intermediate, and KRT4+ peridermal sub-clusters. (LLM, conf=0.76)
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Watanabe, K., Mirkov, M. U., de Leeuw, C., van den Heuvel, M. P., & Posthuma, D. (2019) · Nature Communications · doi:10.1038/s41467-019-11181-1 · Cited by 323 · see citing works
The 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 314 · see citing works
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“We tested the accuracy of imputation on four publicly available scRNA-seq datasets (Additional file 3: Table S1): two cell lines, Jurkat and 293T (10X Genomic); one mouse neuron cells dataset (10X Genomics); and one mouse interfollicular epidermis dataset deposited in GSE67602.”
MethodInfluentialSkin Cell Heterogeneity in Development, Wound Healing, and Cancer
Rognoni, E., & Watt, F. M. (2018) · Trends in Cell Biology · doi:10.1016/j.tcb.2018.05.002 · Cited by 301 · see citing works
“Single cell transcriptomic analysis of mouse dorsal epidermis and cultured human epidermis has identifiedat least twodistinct IFESC transcriptional signatures, even though there appears tobea single terminal differentiation programme [18,19].”
BackgroundTranscriptional Programming of Normal and Inflamed Human Epidermis at Single-Cell Resolution
Cheng, J. B., Sedgewick, A. J., Finnegan, A. I., Harirchian, P., Lee, J., Kwon, S., Fassett, M. S., Golovato, J., Gray, M., Ghadially, R., et al. (2018) · Cell Reports · doi:10.1016/j.celrep.2018.09.006 · Cited by 284 · see citing works
“, 1989), and mouse sebaceous glands (MGST1; Joost et al., 2016; APOC1; Jong et al., 1998).”
InfluentialHughes, T. K., Wadsworth, M. H., Gierahn, T. M., Do, T. H., Weiss, D. I., Andrade, P. R., Ma, F., Silva, B. J. D. A., Shao, S., Tsoi, L. C., et al. (2020) · Immunity · doi:10.1016/j.immuni.2020.09.015 · Cited by 282 · see citing works
“We further identified distinct lineages for basal KCs (COL17A1) and cells of the hair follicle, where we detected enrichment of published hair follicle signatures (Figure 6E) (Joost et al., 2016).”
BackgroundZhu, Q., Shah, S., Dries, R., Cai, L., & Yuan, G. (2018) · Nature Biotechnology · doi:10.1038/nbt.4260 · Cited by 248 · see citing works
Epithelial-Mesenchymal Micro-niches Govern Stem Cell Lineage Choices
Yang, H., Adam, R. C., Ge, Y., Hua, Z. L., & Fuchs, E. V. (2017) · Cell · doi:10.1016/j.cell.2017.03.038 · Cited by 249 · see citing works
“Bulge HFSCs (Telo-HFSC) were homogeneous and distinguished by Cd34+Krt24+ (Figures 6B–6D), consistent with a recent study on unfractionated telogen skin cells (Joost et al., 2016).”
Identifying cell populations with scRNASeq
Andrews, T. S., & Hemberg, M. (2017) · Molecular Aspects of Medicine · doi:10.1016/j.mam.2017.07.002 · Cited by 240 · see citing works
“Another way to assess the reliability of cell clusters is to subsample cells and/or genes and re-analyze the result (Joost et al., 2016; Tasic et al., 2016; Zeisel et al., 2015).”
BackgroundMethodRegulation of adult stem cell quiescence and its functions in the maintenance of tissue integrity
de Morrée, A., & Rando, T. A. (2023) · Nature Reviews Molecular Cell Biology · doi:10.1038/s41580-022-00568-6 · Cited by 243 · see citing works
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Defining Adult Stem Cells by Function, not by Phenotype
Clevers, H. C., & Watt, F. M. (2018) · Annual Review of Biochemistry · doi:10.1146/annurev-biochem-062917-012341 · Cited by 226 · see citing works
A radical switch in clonality reveals a stem cell niche in the epiphyseal growth plate
Newton, P. T., Li, L., Zhou, B., Schweingruber, C., Hovořáková, M., Xie, M., Sun, X., Sandhow, L., Artemov, A. V., Ivashkin, E. G., et al. (2019) · Nature · doi:10.1038/s41586-019-0989-6 · Cited by 224 · see citing works
Tutorial: guidelines for the experimental design of single-cell RNA sequencing studies
Lafzi, A., Moutinho, C., Picelli, S., & Heyn, H. (2018) · Nature Protocols · doi:10.1038/s41596-018-0073-y · Cited by 218 · see citing works
Single cell transcriptomics of human epidermis identifies basal stem cell transition states
Wang, S., Drummond, M. L., Guerrero-Juarez, C. F., Tarapore, E., MacLean, A. L., Stabell, A. R., Wu, S. C., Gutierrez, G., That, B. T., Benavente, C. A., et al. (2020) · Nature Communications · doi:10.1038/s41467-020-18075-7 · Cited by 218 · see citing works
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Signaling in the stem cell niche: regulating cell fate, function and plasticity
Chacón‐Martínez, C. A., Koester, J., & Wickström, S. A. (2018) · Development · doi:10.1242/dev.165399 · Cited by 193 · see citing works
“In addition, a degree of transcriptional heterogeneity and the existence of an LGR6 subpopulation within the mouse back skin IFE has been observed (Füllgrabe et al., 2015; Joost et al., 2016; Snippert et al., 2010a), but the functional significance of this heterogeneity is unclear.”
BackgroundEndogenous retroviruses promote homeostatic and inflammatory responses to the microbiota
Lima-Junior, D. S., Krishnamurthy, S. R., Bouladoux, N. J., Collins, N., Han, S., Chen, Y. E., Constantinides, M. G., Link, V. M., Lim, A. I., Enamorado, M., et al. (2021) · Cell · doi:10.1016/j.cell.2021.05.020 · Cited by 198 · see citing works
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Mechanisms of stretch-mediated skin expansion at single-cell resolution
Aragona, M., Sifrim, A., Malfait, M., Song, Y., Herck, J. V., Dekoninck, S., Gargouri, S., Lapouge, G., Swedlund, B., Dubois, C., et al. (2020) · Nature · doi:10.1038/s41586-020-2555-7 · Cited by 188 · see citing works
Kernfeld, E. M., Genga, R. M. J., Neherin, K., Magaletta, M. E., Xu, P., & Maehr, R. (2018) · Immunity · doi:10.1016/j.immuni.2018.04.015 · Cited by 186 · see citing works
“, 2016), epidermis and hair follicle (Joost et al., 2016), and heart tissue (DeLaughter et al.”
Statistical and machine learning methods for spatially resolved transcriptomics data analysis
Zeng, Z., Li, Y., Li, Y., & Luo, Y. (2022) · Genome Biology · doi:10.1186/s13059-022-02653-7 · Cited by 186 · see citing works
“…spatial location reconstruction for scRNA-seq data is often performed in two steps—the feature engineering step to extract reference information from spatial transcriptomics data [50, 52, 54, 81, 82] and the model building step to infer spatial location probabilities of the cells in scRNA-seq data.”
MethodWounding induces dedifferentiation of epidermal Gata6+ cells and acquisition of stem cell properties
Donati, G., Rognoni, E., Hiratsuka, T., Liakath‐Ali, K., Hoste, E., Kar, G., Kayikci, M., Russell, R., Kretzschmar, K., Mulder, K. W., et al. (2017) · Nature Cell Biology · doi:10.1038/ncb3532 · Cited by 175 · see citing works
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The benefits and pitfalls of machine learning for biomarker discovery
Ng, S. L.-K., Masarone, S., Watson, D., & Barnes, M. R. (2023) · Cell and Tissue Research · doi:10.1007/s00441-023-03816-z · Cited by 181 · see citing works
“For example, in a single-cell RNAseq (scRNAseq) study of human skin, t-SNE was used to identify clusters of cells with similar gene expression patterns, leading to the discovery of new epidermal cell types and sub-populations (Joost et al. 2016).”
MethodLef1 expression in fibroblasts maintains developmental potential in adult skin to regenerate wounds
Phan, Q. M., Fine, G. M., Salz, L., Herrera, G. G., Wildman, B., Driskell, I. M., & Driskell, R. R. (2020) · eLife · doi:10.7554/elife.60066 · Cited by 170 · see citing works
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Insulin mutations impair beta-cell development in a patient-derived iPSC model of neonatal diabetes
Balboa, D., Saarimäki‐Vire, J., Borshagovski, D., Survila, M., Lindholm, P., Galli, E., Eurola, S., Ustinov, J., Grym, H., Huopio, H., et al. (2018) · eLife · doi:10.7554/elife.38519 · Cited by 151 · see citing works
“…which carries a proinsulin cysteine disruption mutation (C96Y) that leads to mutant proinsulin accumulation in the ER, enlarged ER, reduction of secretory granules and mitochondrial swelling (Izumi et al., 2003; Kayo and Koizumi, 1998; Wang et al., 1999; Yoshioka et al., 1997; Zuber et al., 2004).”
BackgroundCell lineage and communication network inference via optimization for single-cell transcriptomics
Wang, S., Karikomi, M. K., MacLean, A. L., & Nie, Q. H. (2019) · Nucleic Acids Research · doi:10.1093/nar/gkz204 · Cited by 153 · see citing works
“We go on to apply SoptSC to skin regeneration (32) to investigate lineage relationships, cell communication networks and crosstalk between cells.”
BackgroundMethodInfluentialVu, R., Jin, S., Sun, P., Haensel, D., Nguyen, Q., Dragan, M., Kessenbrock, K., Nie, Q. H., & Dai, X. (2022) · Cell Reports · doi:10.1016/j.celrep.2022.111155 · Cited by 149 · see citing works
“…skin, we observed 13 clusters assigned the following identities based on each cluster’s top markers and known marker genes (Haensel et al., 2020; Joost et al., 2016) (Figures 2B and 2C; Table S2): (1) two epithelial, a basal cluster with both IFE (Krt14 + ) and HF (Krt14 + Krt17 + ) cells, and…”
InfluentialMathur, A. N., Zirak, B., Boothby, I. C., Tan, M., Cohen, J. N., Mauro, T., Mehta, P., Lowe, M. M., Abbas, A. K., Ali, N., et al. (2019) · Immunity · doi:10.1016/j.immuni.2019.02.013 · Cited by 149 · see citing works
“Recently, the heterogeneity of murine epidermal transcriptomes has been dissected into distinct follicular and interfollicular subsets at the single-cell level (Joost et al., 2016).”
Gellatly, K. J., Strassner, J. P., Essien, K. I., Refat, M. A., Murphy, R. L., Coffin-Schmitt, A., Pandya, A. G., Tovar‐Garza, A., Frisoli, M. L., Fan, X., et al. (2021) · Science Translational Medicine · doi:10.1126/scitranslmed.abd8995 · Cited by 143 · see citing works
“We identified epidermal cell types and immune cells identified in previous studies performed on skin biopsies (16, 18, 19) but were unable to detect fibroblasts and other cells found deeper in the dermis of the skin.”
BackgroundResultBMAL1-Driven Tissue Clocks Respond Independently to Light to Maintain Homeostasis
Welz, P.-S., Zinna, V. M., Symeonidi, A., Koronowski, K. B., Kinouchi, K., Smith, J. G., Guillén, I. M., Castellanos‐Martín, A., Furrow, S., Aragón, F., et al. (2019) · Cell · doi:10.1016/j.cell.2019.05.009 · Cited by 139 · see citing works
“We used single-cell RNA sequencing (RNA-seq) data to compare these gene expression changes to the transcriptome signatures that occur as keratinocytes progressively differentiate during epidermal stratification (Joost et al., 2016).”
Liu, X., Chen, W., Zeng, Q., Ma, B., Li, Z., Meng, T., Chen, J., Yu, N., Zhou, Z., & Long, X. (2021) · Journal of Investigative Dermatology · doi:10.1016/j.jid.2021.06.010 · Cited by 137 · see citing works
A cell identity switch allows residual BCC to survive Hedgehog pathway inhibition
Biehs, B., Dijkgraaf, G. J. P., Piskol, R., Alicke, B., Boumahdi, S., Peale, F., Gould, S. E., & de Sauvage, F. J. (2018) · Nature · doi:10.1038/s41586-018-0596-y · Cited by 137 · see citing works
Stem cells expand potency and alter tissue fitness by accumulating diverse epigenetic memories
Gonzales, K. A. U., Polak, L., Matos, I., Tierney, M. T., Gola, A., Wong, E., Infarinato, N. R., Nikolova, M., Luo, S., Liu, S., et al. (2021) · Science · doi:10.1126/science.abh2444 · Cited by 136 · see citing works
“S4B), Leiden clustering of all epithelial cells at day 0 revealed six distinct subsets, readily identified by established markers (16, 17) and underscoring the marked differences between bulge HFSCs and EpdSCs (Fig.”
BackgroundLou, F., Sun, Y., Xu, Z., Niu, L., Wang, Z., Deng, S., Liu, Z., Zhou, H., Bai, J., Yin, Q., et al. (2020) · Immunity · doi:10.1016/j.immuni.2020.06.004 · Cited by 135 · see citing works
Law, N. C., Oatley, M. J., & Oatley, J. M. (2019) · Nature Communications · doi:10.1038/s41467-019-10596-0 · Cited by 130 · see citing works
Comparison of Computational Methods for Imputing Single-Cell RNA-Sequencing Data
Zhang, L., & Zhang, S. (2018) · IEEE Transactions on Computational Biology and Bioinformatics · doi:10.1109/tcbb.2018.2848633 · Cited by 125 · see citing works
Manifold learning-based methods for analyzing single-cell RNA-sequencing data
Moon, K. R., Stanley, J. S., Burkhardt, D. B., van Dijk, D., Wolf, G., & Krishnaswamy, S. (2017) · Current Opinion in Systems Biology · doi:10.1016/j.coisb.2017.12.008 · Cited by 127 · see citing works
Tracing the origin of hair follicle stem cells
Morita, R., Sanzen, N., Sasaki, H., Hayashi, T., Umeda, M., Yoshimura, M., Yamamoto, T., Shibata, T., Abe, T., Kiyonari, H., et al. (2021) · Nature · doi:10.1038/s41586-021-03638-5 · Cited by 124 · see citing works
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Gao, Y., Yao, X.-Y., Zhai, Y., Li, L., Li, H., Sun, X., Yu, P., Xue, T., Li, Y.-Z., & Hu, Y.-Z. (2021) · Cell Death and Disease · doi:10.1038/s41419-021-03724-6 · Cited by 97 · see citing works
Single-Cell RNA Sequencing with Spatial Transcriptomics of Cancer Tissues
Ahmed, R., Zaman, T., Chowdhury, F., Mraiche, F., Tariq, M., Ahmad, I. S., & Hasan, A. (2022) · International Journal of Molecular Sciences · doi:10.3390/ijms23063042 · Cited by 101 · see citing works
“Furthermore, further advancement took place when single-cell RNA-seq was carried out on clustered cell populations in the murine epidermis, which resulted in the identification of 25 different types of cells from the tissue samples [17].”
BackgroundLong-term expansion and differentiation of adult murine epidermal stem cells in 3D organoid cultures
Boonekamp, K. E., Kretzschmar, K., Wiener, D. J., Asra, P., Derakhshan, S., Puschhof, J., López-Iglesias, C., Peters, P. J., Basak, O., & Clevers, H. (2019) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1715272116 · Cited by 96 · see citing works
“Using single-cell transcriptome analysis of murine epidermis, Kasper and colleagues (54) recently showed that the various epidermal stem cell populations share a set of common genes.”
BackgroundThe Roles of YAP/TAZ and the Hippo Pathway in Healthy and Diseased Skin
Rognoni, E., & Walko, G. (2019) · Cells · doi:10.3390/cells8050411 · Cited by 99 · see citing works
Dynamic regulation of tissue fluidity controls skin repair during wound healing
Sarate, R. M., Hochstetter, J., Valet, M., Hallou, A., Song, Y., Bansaccal, N., Ligare, M., Aragona, M., Engelman, D., Bauduin, A., et al. (2024) · Cell · doi:10.1016/j.cell.2024.07.031 · Cited by 103 · see citing works
Generative adversarial networks simulate gene expression and predict perturbations in single cellsPreprint
Ghahramani, A., Watt, F. M., & Luscombe, N. M. (2018) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/262501 · Cited by 98 · see citing works
Sexual dimorphism in skin immunity is mediated by an androgen-ILC2-dendritic cell axis
Chi, L., Liu, C., Gribonika, I., Gschwend, J., Corral, D., Han, S., Lim, A. I., Rivera, C. A., Link, V. M., Wells, A. C., et al. (2024) · Science · doi:10.1126/science.adk6200 · Cited by 103 · see citing works
The extracellular matrix dictates regional competence for tumour initiation
Bansaccal, N., Vieugué, P., Sarate, R. M., Song, Y., Minguijón, E., Miroshnikova, Y. A., Zeuschner, D., Collin, A. M., Allard, J., Engelman, D., et al. (2023) · Nature · doi:10.1038/s41586-023-06740-y · Cited by 93 · see citing works
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“For gene set 3, they enriched canonical IFE markers such as Krt10, Krt15 and the GO terms “cell junction organization, keratinocyte differentiation, and response to wounding” [41].”
BackgroundExtracellular Matrix as a Regulator of Epidermal Stem Cell Fate
Chermnykh, E., Kalabusheva, E., & Vorotelyak, E. (2018) · International Journal of Molecular Sciences · doi:10.3390/ijms19041003 · Cited by 95 · see citing works
Defining the Design Principles of Skin Epidermis Postnatal Growth
Dekoninck, S., Hannezo, É., Sifrim, A., Miroshnikova, Y. A., Aragona, M., Malfait, M., Gargouri, S., de Neunheuser, C., Dubois, C., Voet, T., et al. (2020) · Cell · doi:10.1016/j.cell.2020.03.015 · Cited by 85 · see citing works
“We performed unsupervised clustering and excluded the cell clusters of the infundibulum (Sox9, Krt17, and Krt79), sebaceous gland cells (Scd1, Mgst1, and Elovl6), as well as cells containing a high content of mitochondrial genes, such as mt-Co1 (dying cells) and performed further bioinformatics analysis on IFE cells (…”
BackgroundMethodCockburn, K., Annusver, K., Gonzalez, D. G., Ganesan, S., May, D. P., Mesa, K. R., Kawaguchi, K., Kasper, M., & Greco, V. (2022) · Nature Cell Biology · doi:10.1038/s41556-022-01021-8 · Cited by 84 · see citing works
Single-Cell Multi-omics: An Engine for New Quantitative Models of Gene Regulation
Packer, J. S., & Trapnell, C. (2018) · Trends in Genetics · doi:10.1016/j.tig.2018.06.001 · Cited by 84 · see citing works
Skin organoids: a new human model for developmental and translational research
Lee, J., & Koehler, K. R. (2021) · Experimental Dermatology · doi:10.1111/exd.14292 · Cited by 85 · see citing works
MIRA: joint regulatory modeling of multimodal expression and chromatin accessibility in single cells
Lynch, A. W., Theodoris, C. V., Long, H. W., Brown, M., Liu, X. S., & Meyer, C. A. (2022) · Nature Methods · doi:10.1038/s41592-022-01595-z · Cited by 80 · see citing works
Defining Transcriptional Signatures of Human Hair Follicle Cell States
Takahashi, R., Grzenda, A. L., Allison, T. F., Rawnsley, J. D., Balin, S. J., Sabri, S., Plath, K., & Lowry, W. E. (2019) · Journal of Investigative Dermatology · doi:10.1016/j.jid.2019.07.726 · Cited by 81 · see citing works
“The first single-cell mapping of murine epidermal and hair follicle cells yielded 1,422 unique transcriptome profiles, clustering into 25 unique subpopulations (Acosta et al., 2017; Joost et al., 2016).”
BackgroundKeratinocyte-intrinsic MHCII expression controls microbiota-induced Th1 cell responses
Tamoutounour, S., Han, S., Deckers, J., Constantinides, M. G., Hurabielle, C., Harrison, O. J., Bouladoux, N. J., Linehan, J. L., Link, V. M., Vujkovic-Cvijin, I., et al. (2019) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1912432116 · Cited by 79 · see citing works
“epidermidis-associated MHCII and MHCII keratinocytes to different subsets of keratinocytes, lists of signature genes (versus baseline) from published single-cell RNA-seq data were downloaded (21) and overlaid with gene expression (normalized to tran-”
MethodDNA Methylation in Epidermal Differentiation, Aging, and Cancer
Köhler, F., & Rodríguez‐Paredes, M. (2019) · Journal of Investigative Dermatology · doi:10.1016/j.jid.2019.05.011 · Cited by 79 · see citing works
“In this regard, single-cell RNA sequencing has recently allowed the unbiased reconstruction of mouse epidermal differentiation, enabling the visualization of individual cells along a trajectory through the application of network-based approaches (Joost et al., 2016; Trapnell et al., 2014).”
BackgroundHair follicle stem cells as a skin‐organizing signaling center during adult homeostasis
Li, K. N., & Tumbar, T. (2021) · The EMBO Journal · doi:10.15252/embj.2020107135 · Cited by 75 · see citing works
“This information provides a platform for the more precise dissection of molecular interaction between the epithelium and the surrounding environment (Joost et al, 2016).”
Deep learning tackles single-cell analysis—a survey of deep learning for scRNA-seq analysis
Flores, M. A., Liu, Z., Zhang, T., Hasib, M. M., Chiu, Y., Ye, Z., Paniagua, K., Jo, S., Zhang, J., Gao, S., et al. (2021) · Briefings in Bioinformatics · doi:10.1093/bib/bbab531 · Cited by 72 · see citing works
Wang, G., Sweren, E., Andrews, W., Li, Y., Chen, J., Xue, Y., Wier, E. M., Alphonse, M. P., Luo, L., Miao, Y., et al. (2023) · Science Advances · doi:10.1126/sciadv.abo7555 · Cited by 74 · see citing works
Valid Post-clustering Differential Analysis for Single-Cell RNA-Seq
Zhang, J. M., Kamath, G. M., & Tse, D. N. (2019) · Cell Systems · doi:10.1016/j.cels.2019.07.012 · Cited by 72 · see citing works
Acosta, J. R., Joost, S., Karlsson, K., Ehrlund, A., Li, X., Aouadi, M., Kasper, M., Arner, P., Rydén, M., & Laurencikiene, J. (2017) · Stem Cell Research & Therapy · doi:10.1186/s13287-017-0701-4 · Cited by 71 · see citing works
“The data analysis workflow was as described in detail previously [15].”
MethodTsutsui, K., Machida, H., Nakagawa, A., Ahn, K., Morita, R., Sekiguchi, K., Miner, J. H., & Fujiwara, H. (2021) · Nature Communications · doi:10.1038/s41467-021-22881-y · Cited by 73 · see citing works
Hair Follicle Terminal Differentiation Is Orchestrated by Distinct Early and Late Matrix Progenitors
Mesler, A. L., Veniaminova, N. A., Lull, M. V., & Wong, S. Y. (2017) · Cell Reports · doi:10.1016/j.celrep.2017.03.077 · Cited by 69 · see citing works
“During catagen, the CL is eliminated, while cells immediately proximal to the CL persist in the upper reaches of the inner bulge, a region that has recently been reported to harbor at least 3 molecularly distinct subpopulations (Joost et al., 2016).”
BackgroundUSH2A is a Meissner’s corpuscle protein necessary for normal vibration sensing in mice and humans
Schwaller, F., Bégay, V., García‐García, G., Taberner, F. J., Moshourab, R. A., McDonald, B., Docter, T. A., Kühnemund, J., Ojeda‐Alonso, J., Paricio-Montesinos, R., et al. (2020) · Nature Neuroscience · doi:10.1038/s41593-020-00751-y · Cited by 72 · see citing works
NIX initiates mitochondrial fragmentation via DRP1 to drive epidermal differentiation
Simpson, C. L., Tokito, M. K., Uppala, R., Sarkar, M. K., Gudjonsson, J. E., & Holzbaur, E. L. F. (2021) · Cell Reports · doi:10.1016/j.celrep.2021.108689 · Cited by 72 · see citing works
“Using a public single-cell RNA sequence database of murine epidermis (Joost et al., 2016), we queried expression levels of known mitophagy receptors and Parkin (Figure S3A; see graphs generated from http://linnarssonlab.”
MethodConcise Review: Mechanisms of Quiescent Hair Follicle Stem Cell Regulation
Yi, R. (2017) · Stem Cells · doi:10.1002/stem.2696 · Cited by 70 · see citing works
Differential Evolution of the Epidermal Keratin Cytoskeleton in Terrestrial and Aquatic Mammals
Ehrlich, F., Fischer, H., Langbein, L., Praetzel‐Wunder, S., Ebner, B., Figlak, K., Weissenbacher, A., Sipos, W., Tschachler, E., & Eckhart, L. (2018) · Molecular Biology and Evolution · doi:10.1093/molbev/msy214 · Cited by 68 · see citing works
“K10 proteins of different sizes have been reported to arise from an indel polymorphism within exon 7 of Krt10 alleles (Korge et al. 1992) and one of these alleles was even considered to represent a distinct keratin, then named K11 (Moll et al. 1982) but later removed from the list of keratins…”
BackgroundA biomechanical switch regulates the transition towards homeostasis in oesophageal epithelium
McGinn, J., Hallou, A., Han, S., Krizic, K., Ulyanchenko, S., Iglesias‐Bartolomé, R., England, F. J., Verstreken, C. M., Chalut, K. J., Jensen, K. B., et al. (2021) · Nature Cell Biology · doi:10.1038/s41556-021-00679-w · Cited by 63 · see citing works
A Single-Cell Transcriptome Atlas of Cashmere Goat Hair Follicle Morphogenesis
Ge, W., Zhang, W., Zhang, Y., Zheng, Y., Li, F., Wang, S., Liu, J., Tan, S., Yan, Z., Wang, L., et al. (2021) · Genomics Proteomics & Bioinformatics · doi:10.1016/j.gpb.2021.07.003 · Cited by 67 · see citing works
“For clusters 0, 3, 8, 9, and 11, they expressed high levels of the epithelial lineage markers KRT14, KRT17 and KRT85 [25,26], and they were termed as epidermal, keratinocyte, epithelial, keratinocyte, and keratinocyte, respectively.”
BackgroundCircadian control of interferon-sensitive gene expression in murine skin
Greenberg, E. N., Marshall, M. E., Jin, S., Venkatesh, S., Dragan, M., Tsoi, L. C., Gudjonsson, J. E., Nie, Q. H., Takahashi, J. S., & D, B. A. M. (2020) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1915773117 · Cited by 65 · see citing works
“We used Seurat (29) to cluster cells based on their gene expression profiles and t-distributed stochastic neighbor embedding (t-SNE) to display the cell clusters, which were annotated manually based on markers from previous studies (30).”
S100A6: molecular function and biomarker role
Wang, Y., Kang, X., Kang, X., & Yang, F. (2023) · Biomarker Research · doi:10.1186/s40364-023-00515-3 · Cited by 63 · see citing works
“With the development of single-cell sequencing technology, evidence of S100A6 expression in mouse hair follicle bulge cells and the basal layer of the hair follicle inner epidermis is more abundant [110, 111].”
BackgroundVeniaminova, N. A., Jia, Y. Y., Hartigan, A. M., Huyge, T. J., Tsai, S.-Y., Grachtchouk, M. A., Nakagawa, S., Dlugosz, A. A., Atwood, S. X., & Wong, S. Y. (2023) · Cell Reports · doi:10.1016/j.celrep.2023.113121 · Cited by 65 · see citing works
“…reverse transcription was performed, and the resulting Post GEM-RT product was cleaned up and the cDNA was amplified. cDNA was subjected to enzymatic fragmentation and size selection to optimize the cDNA size prior to final library construction following the manufacturer’s protocol (10x Genomics).”
Sakamoto, K., Jin, S., Goel, S., Jo, J., Voisin, B., Kim, D. Y., Nadella, V., Liang, H., Kobayashi, T., Huang, X., et al. (2021) · Immunity · doi:10.1016/j.immuni.2021.09.001 · Cited by 61 · see citing works
Verstappe, J., & Berx, G. (2023) · Seminars in Cancer Biology · doi:10.1016/j.semcancer.2023.02.001 · Cited by 63 · see citing works
Recent Highlights in Psoriasis Research
Hwang, S. T., Nijsten, T. E. C., & Elder, J. T. (2017) · Journal of Investigative Dermatology · doi:10.1016/j.jid.2016.11.007 · Cited by 63 · see citing works
Finnegan, A., Cho, R. J., Luu, A., Harirchian, P., Lee, J. S. H., Cheng, J. B., & Song, J. S. (2019) · Frontiers in Genetics · doi:10.3389/fgene.2019.00775 · Cited by 63 · see citing works
“[3] advanced this approach to the single-cell level in murine epidermis, identifying TFs varying with differentiation pseudotime and constructing gene modules using correlation-based expression similarity.”
BackgroundIdentification of cell types from single cell data using stable clustering
Peyvandipour, A., Shafi, A., Saberian, N., & Drăghici, S. (2020) · Scientific Reports · doi:10.1038/s41598-020-66848-3 · Cited by 60 · see citing works
Transit-Amplifying Cells in the Fast Lane from Stem Cells towards Differentiation
Rangel‐Huerta, E., & Maldonado, E. (2017) · Stem Cells International · doi:10.1155/2017/7602951 · Cited by 62 · see citing works
“Single-cell sequencing (S-CS) [81-83] is a powerful new tool for investigating cellular diversity in several fields of biology, including cancer research.”
InfluentialOptimized design of single-cell RNA sequencing experiments for cell-type-specific eQTL analysis
Mandric, I., Schwarz, T., Majumdar, A., Hou, K., Briscoe, L., Perez, R., Subramaniam, M., Hafemeister, C., Satija, R., Ye, C. J., et al. (2020) · Nature Communications · doi:10.1038/s41467-020-19365-w · Cited by 62 · see citing works
- Authors
- Joost, S., Zeisel, A., Jacob, T., Sun, X., La Manno, G., Lönnerberg, P., Linnarsson, S., & Kasper, M.
- Affiliations
- Karolinska Institutet (SE)
- Corresponding author
- Linnarsson, Sten
- Kasper, Maria
- Venue
- Cell Systems
- Publisher
- Elsevier BV
- Published
- 2016-09
- Volume
- 3
- Issue
- 3
- Pages
- 221-237.e9
- ISSN
- 2405-4712 (ISSN-L)
- PMC
- PMC5052454
- OpenAlex
- W2489812534
- Cited by
- 429
- References
- 73
- Citations by year
- 2026: 42 · 2025: 35 · 2024: 45 · 2023: 40 · 2022: 55 · 2021: 45 · 2020: 68 · 2019: 39 · 2018: 40 · 2017: 18 · 2016: 1 · 2014: 1
- FWCI
- 16.98
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- Locations
- Cell Systems (publishedVersion, cc-by-nc-nd)
- PubMed Central (publishedVersion, cc-by-nc-nd)
- PubMed (publishedVersion)
- Infoscience (Ecole Polytechnique Fédérale de Lausanne) (submittedVersion, cc-by-nc-nd)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Single-cell and spatial transcriptomics
- Health Sciences › Medicine › Urology › Hair Growth and Disorders
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Cell Biology › Skin and Cellular Biology Research
- Keywords
- epidermis, hair follicle, cellular heterogeneity, epidermal differentiation, telogen, interfollicular epidermis, proximal-distal axis, stem cell compartment, transcriptional organization, tissue homeostasis, spatial signatures, mouse skin
- MeSH terms
- Animals, Cell Differentiation, Epidermis, Female, Homeostasis, Mice, Inbred C57BL, Stem Cells, Hair Follicle, Mice, Transcriptome
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