Single-cell Stereo-seq reveals induced progenitor cells involved in axolotl brain regeneration
Abstract
The molecular mechanism underlying brain regeneration in vertebrates remains elusive. We performed spatial enhanced resolution omics sequencing (Stereo-seq) to capture spatially resolved single-cell transcriptomes of axolotl telencephalon sections during development and regeneration. Annotated cell types exhibited distinct spatial distribution, molecular features, and functions. We identified an injury-induced ependymoglial cell cluster at the wound site as a progenitor cell population for the potential replenishment of lost neurons, through a cell state transition process resembling neurogenesis during development. Transcriptome comparisons indicated that these induced cells may originate from local resident ependymoglial cells. We further uncovered spatially defined neurons at the lesion site that may regress to an immature neuron–like state. Our work establishes spatial transcriptome profiles of an anamniote tetrapod brain and decodes potential neurogenesis from ependymoglial cells for development and regeneration, thus providing mechanistic insights into vertebrate brain regeneration.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
Previously, spatial transcriptomics technology has been utilized to create spatiotemporal maps of various life stages, including mouse brain, regenerating axolotl telencephalons, aging ovary, and brain.
“Previously, this technology has been utilized to create spatiotemporal maps of various life stages, including mouse brain, regenerating axolotl telencephalons, aging ovary, and brain.21”
From Spatial transcriptomic landscape unveils immunoglobin-associated senescence as a hallmark of aging (2024) · cites this paper as [37]
Cites
STAR: ultrafast universal RNA-seq aligner
Dobin, A., Davis, C. A., Schlesinger, F., Drenkow, J., Zaleski, C., Jha, S., Batut, P., Chaisson, M., & Gingeras, T. R. (2013) · Bioinformatics · doi:10.1093/bioinformatics/bts635 · Cited by 51,709 · see citing works
Integrated analysis of multimodal single-cell data
Hao, Y., Hao, S., Andersen-Nissen, E., Mauck, W. M., Zheng, S., Butler, A., Lee, M. J., Wilk, A. J., Darby, C., Zagar, M., et al. (2020) · doi:10.1101/2020.10.12.335331 · Cited by 15,508 · see citing works
The Human Transcription Factors
Lambert, S. A., Jolma, A., Campitelli, L. F., Das, P. K., Yin, Y., Albu, M., Chen, X., Taipale, J., Hughes, T. R., & Weirauch, M. T. (2018) · Cell · doi:10.1016/j.cell.2018.01.029 · Cited by 3,399 · see citing works
Spatiotemporal transcriptomic atlas of mouse organogenesis using DNA nanoball-patterned arrays
Chen, A., Liao, S., Cheng, M., Ma, K., Wu, L., Lai, Y., Qiu, X., Yang, J., Xu, J., Hao, S., et al. (2022) · Cell · doi:10.1016/j.cell.2022.04.003 · Cited by 1,784 · see citing works
Self-citationHuman Genome Sequencing Using Unchained Base Reads on Self-Assembling DNA Nanoarrays
Drmanac, R., Sparks, A. B., Callow, M. J., Halpern, A. L., Burns, N. L., Kermani, B. G., Carnevali, P., Nazarenko, I., Nilsen, G. B., Yeung, G., et al. (2010) · Science · doi:10.1126/science.1181498 · Cited by 1,212 · see citing works
Self-citationMethod of the Year: spatially resolved transcriptomics
Marx, V. (2021) · Nature Methods · doi:10.1038/s41592-020-01033-y · Cited by 1,132 · see citing works
Calegari, F., Haubensak, W., Haffner, C., & Huttner, W. B. (2005) · The Journal of Neuroscience · doi:10.1523/jneurosci.0778-05.2005 · Cited by 396 · see citing works
Gaidatzis, D., Burger, L., Florescu, M., & Stadler, M. B. (2015) · Nature Biotechnology · doi:10.1038/nbt.3269 · Cited by 313 · see citing works
Injured adult neurons regress to an embryonic transcriptional growth state
Poplawski, G. H. D., Kawaguchi, R., Van Niekerk, E., Lu, P., Mehta, N., Canete, P., Lie, R., Dragatsis, I., Meves, J. M., Zheng, B., et al. (2020) · Nature · doi:10.1038/s41586-020-2200-5 · Cited by 247 · see citing works
Flagged first, then by citations
Cited by
Sorted by citations
Cell-cell communication: New insights and clinical implications
Su, J., Song, Y., Zhu, Z., Huang, X., Fan, J., Qiao, J., & Mao, F. (2024) · Signal Transduction and Targeted Therapy · doi:10.1038/s41392-024-01888-z · Cited by 433 · see citing works
Spatial transcriptomic landscape unveils immunoglobin-associated senescence as a hallmark of aging
Ma, S., Ji, Z., Zhang, B., Geng, L., Cai, Y., Nie, C., Li, J., Zuo, Y., Sun, Y., Xu, G., et al. (2024) · Cell · doi:10.1016/j.cell.2024.10.019 · Cited by 162 · see citing works
Self-citationMallach, A., Zielonka, M., van Lieshout, V., An, Y., Khoo, J. H., Vanheusden, M., Chen, W.-T., Moechars, D., Arancibia-Carcamo, I. L., Fiers, M., et al. (2024) · Cell Reports · doi:10.1016/j.celrep.2024.114216 · Cited by 135 · see citing works
Cholangiokines: undervalued modulators in the hepatic microenvironment
Cai, X., Tacke, F., Guillot, A., & Liu, H. (2023) · Frontiers in Immunology · doi:10.3389/fimmu.2023.1192840 · Cited by 40 · see citing works
Liu, X., Tang, G., Chen, Y., Li, Y., Li, H., & Wang, X. (2025) · Cancer Research · doi:10.1158/0008-5472.can-24-1472 · Cited by 8 · see citing works
Self-citation
- Authors
- Wei, X., Fu, S., Li, H., Liu, Y., Wang, S., Feng, W., Yang, Y., Liu, X., Zeng, Y.-Y., Cheng, M., Lai, Y., Qiu, X., Wu, L., Zhang, N., Jiang, Y., Xu, J., Su, X., Peng, C., Han, L., Lou, W. P.-K., Liu, C., Yuan, Y., Ma, K., Yang, T., Pan, X., Gao, S., Chen, A., Esteban, M. A., Yang, H., Wang, J., Fan, G., Liu, L., Chen, L., Xu, X., Fei, J.-F., & Gu, Y.
- Affiliations
- BGI Group (China) (CN)
- South China Normal University (CN)
- Zhengzhou University (CN)
- BGI-Qingdao, Qingdao 266555, China.
- Chinese Academy of Sciences (CN)
- Howard Hughes Medical Institute (US)
- Guangdong Academy of Medical Sciences (CN)
- Wuhan University (CN)
- Corresponding author
- Wei, Xiaoyu
- Fu, Sulei
- Li, Hanbo
- Liu, Yang
- Wang, Shuai
- Feng, Weimin
- Yang, Yunzhi
- Chen, Liang
- Xu, Xun
- Fei, Ji-Feng
- Gu, Ying
- ORCID
- Wei, Xiaoyu
- Fu, Sulei
- Li, Hanbo
- Liu, Yang
- Wang, Shuai
- Feng, Weimin
- Yang, Yunzhi
- Lai, Yiwei
- Qiu, Xiaojie
- Wu, Liang
- Zhang, Nannan
- Jiang, Yujia
- Xu, Jiangshan
- Su, Xiaoshan
- Peng, Cheng
- Han, Lei
- Lou, Wilson Pak-Kin
- Liu, Chuanyu
- Yuan, Yue
- Ma, Kailong
- Yang, Tao
- Pan, Xiangyu
- Gao, Shang
- Chen, Ao
- Esteban, Miguel A.
- Yang, Huanming
- Wang, Jian
- Fan, Guangyi
- Liu, Longqi
- Chen, Liang
- Xu, Xun
- Fei, Ji-Feng
- Gu, Ying
- Venue
- Science
- Published
- 2022-09-02
- Volume
- 377
- Issue
- 6610
- Pages
- eabp9444-eabp9444
- ISSN
- 0036-8075 (ISSN-L)
- 1095-9203
- OpenAlex
- W4294042823
- Cited by
- 311
- References
- 9
- Citations by year
- 2026: 69 · 2025: 93 · 2024: 80 · 2023: 58 · 2022: 11
- FWCI
- 23.01
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Science (publishedVersion)
- PubMed (publishedVersion)
- Research at the University of Copenhagen (University of Copenhagen) (submittedVersion)
- Topics
- Life Sciences › Neuroscience › Developmental Neuroscience › Neurogenesis and neuroplasticity mechanisms
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Single-cell and spatial transcriptomics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Developmental Biology and Gene Regulation
- Keywords
- axolotl, brain regeneration, telencephalon, spatial transcriptomics, cell state transitions, neurogenesis
- MeSH terms
- Brain Regeneration, Ambystoma mexicanum, Animals, Telencephalon, Neural Stem Cells, Single-Cell Analysis, Transcriptome
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