IDEAS home Printed from https://ideas.repec.org/a/nat/natcom/v14y2023i1d10.1038_s41467-023-39016-0.html
   My bibliography  Save this article

Spatiotemporal transcriptomic atlas reveals the dynamic characteristics and key regulators of planarian regeneration

Author

Listed:
  • Guanshen Cui

    (Chinese Academy of Sciences
    China National Center for Bioinformation)

  • Kangning Dong

    (Chinese Academy of Sciences
    University of Chinese Academy of Sciences)

  • Jia-Yi Zhou

    (Chinese Academy of Sciences
    China National Center for Bioinformation)

  • Shang Li

    (Chinese Academy of Sciences
    University of Chinese Academy of Sciences)

  • Ying Wu

    (Chinese Academy of Sciences
    China National Center for Bioinformation)

  • Qinghua Han

    (Chinese Academy of Sciences
    University of Chinese Academy of Sciences)

  • Bofei Yao

    (Chinese Academy of Sciences
    China National Center for Bioinformation)

  • Qunlun Shen

    (Chinese Academy of Sciences
    University of Chinese Academy of Sciences)

  • Yong-Liang Zhao

    (Chinese Academy of Sciences
    China National Center for Bioinformation
    University of Chinese Academy of Sciences)

  • Ying Yang

    (Chinese Academy of Sciences
    China National Center for Bioinformation
    University of Chinese Academy of Sciences
    Chinese Academy of Sciences)

  • Jun Cai

    (Chinese Academy of Sciences
    China National Center for Bioinformation
    University of Chinese Academy of Sciences)

  • Shihua Zhang

    (Chinese Academy of Sciences
    University of Chinese Academy of Sciences
    Chinese Academy of Sciences
    University of Chinese Academy of Sciences)

  • Yun-Gui Yang

    (Chinese Academy of Sciences
    China National Center for Bioinformation
    University of Chinese Academy of Sciences
    Chinese Academy of Sciences)

Abstract

Whole-body regeneration of planarians is a natural wonder but how it occurs remains elusive. It requires coordinated responses from each cell in the remaining tissue with spatial awareness to regenerate new cells and missing body parts. While previous studies identified new genes essential to regeneration, a more efficient screening approach that can identify regeneration-associated genes in the spatial context is needed. Here, we present a comprehensive three-dimensional spatiotemporal transcriptomic landscape of planarian regeneration. We describe a pluripotent neoblast subtype, and show that depletion of its marker gene makes planarians more susceptible to sub-lethal radiation. Furthermore, we identified spatial gene expression modules essential for tissue development. Functional analysis of hub genes in spatial modules, such as plk1, shows their important roles in regeneration. Our three-dimensional transcriptomic atlas provides a powerful tool for deciphering regeneration and identifying homeostasis-related genes, and provides a publicly available online spatiotemporal analysis resource for planarian regeneration research.

Suggested Citation

  • Guanshen Cui & Kangning Dong & Jia-Yi Zhou & Shang Li & Ying Wu & Qinghua Han & Bofei Yao & Qunlun Shen & Yong-Liang Zhao & Ying Yang & Jun Cai & Shihua Zhang & Yun-Gui Yang, 2023. "Spatiotemporal transcriptomic atlas reveals the dynamic characteristics and key regulators of planarian regeneration," Nature Communications, Nature, vol. 14(1), pages 1-16, December.
    • Handle: RePEc:nat:natcom:v:14:y:2023:i:1:d:10.1038_s41467-023-39016-0
    DOI: 10.1038/s41467-023-39016-0
    as

    Download full text from publisher

    File URL: https://www.nature.com/articles/s41467-023-39016-0
    File Function: Abstract
    Download Restriction: no
    File URL: https://libkey.io/10.1038/s41467-023-39016-0?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. M. Lucila Scimone & Lauren E. Cote & Peter W. Reddien, 2017. "Orthogonal muscle fibres have different instructive roles in planarian regeneration," Nature, Nature, vol. 551(7682), pages 623-628, November.
    2. Kangning Dong & Shihua Zhang, 2022. "Deciphering spatial domains from spatially resolved transcriptomics with an adaptive graph attention auto-encoder," Nature Communications, Nature, vol. 13(1), pages 1-12, December.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Kaichen Xu & Yan Lu & Suyang Hou & Kainan Liu & Yihang Du & Mengqian Huang & Hao Feng & Hao Wu & Xiaobo Sun, 2024. "Detecting anomalous anatomic regions in spatial transcriptomics with STANDS," Nature Communications, Nature, vol. 15(1), pages 1-23, December.
    2. Yuchen Liang & Guowei Shi & Runlin Cai & Yuchen Yuan & Ziying Xie & Long Yu & Yingjian Huang & Qian Shi & Lizhe Wang & Jun Li & Zhonghui Tang, 2024. "PROST: quantitative identification of spatially variable genes and domain detection in spatial transcriptomics," Nature Communications, Nature, vol. 15(1), pages 1-17, December.
    3. Ryan E. Hulett & Julian O. Kimura & D. Marcela Bolaños & Yi-Jyun Luo & Carlos Rivera-López & Lorenzo Ricci & Mansi Srivastava, 2023. "Acoel single-cell atlas reveals expression dynamics and heterogeneity of adult pluripotent stem cells," Nature Communications, Nature, vol. 14(1), pages 1-15, December.
    4. Benjamin L. Walker & Qing Nie, 2023. "NeST: nested hierarchical structure identification in spatial transcriptomic data," Nature Communications, Nature, vol. 14(1), pages 1-17, December.
    5. Xiaomeng Wan & Jiashun Xiao & Sindy Sing Ting Tam & Mingxuan Cai & Ryohichi Sugimura & Yang Wang & Xiang Wan & Zhixiang Lin & Angela Ruohao Wu & Can Yang, 2023. "Integrating spatial and single-cell transcriptomics data using deep generative models with SpatialScope," Nature Communications, Nature, vol. 14(1), pages 1-22, December.
    6. Chunman Zuo & Yijian Zhang & Chen Cao & Jinwang Feng & Mingqi Jiao & Luonan Chen, 2022. "Elucidating tumor heterogeneity from spatially resolved transcriptomics data by multi-view graph collaborative learning," Nature Communications, Nature, vol. 13(1), pages 1-14, December.
    7. Tianci Song & Charles Broadbent & Rui Kuang, 2023. "GNTD: reconstructing spatial transcriptomes with graph-guided neural tensor decomposition informed by spatial and functional relations," Nature Communications, Nature, vol. 14(1), pages 1-17, December.
    8. Linhua Wang & Mirjana Maletic-Savatic & Zhandong Liu, 2022. "Region-specific denoising identifies spatial co-expression patterns and intra-tissue heterogeneity in spatially resolved transcriptomics data," Nature Communications, Nature, vol. 13(1), pages 1-12, December.
    9. Rongbo Shen & Lin Liu & Zihan Wu & Ying Zhang & Zhiyuan Yuan & Junfu Guo & Fan Yang & Chao Zhang & Bichao Chen & Wanwan Feng & Chao Liu & Jing Guo & Guozhen Fan & Yong Zhang & Yuxiang Li & Xun Xu & Ji, 2022. "Spatial-ID: a cell typing method for spatially resolved transcriptomics via transfer learning and spatial embedding," Nature Communications, Nature, vol. 13(1), pages 1-17, December.
    10. Zhiyuan Yuan & Yisi Li & Minglei Shi & Fan Yang & Juntao Gao & Jianhua Yao & Michael Q. Zhang, 2022. "SOTIP is a versatile method for microenvironment modeling with spatial omics data," Nature Communications, Nature, vol. 13(1), pages 1-19, December.
    11. Biao Zhang & Shuqin Zhang & Shihua Zhang, 2024. "Whole brain alignment of spatial transcriptomics between humans and mice with BrainAlign," Nature Communications, Nature, vol. 15(1), pages 1-15, December.
    12. M. Lucila Scimone & Jennifer K. Cloutier & Chloe L. Maybrun & Peter W. Reddien, 2022. "The planarian wound epidermis gene equinox is required for blastema formation in regeneration," Nature Communications, Nature, vol. 13(1), pages 1-13, December.
    13. Zhiyuan Yuan, 2024. "MENDER: fast and scalable tissue structure identification in spatial omics data," Nature Communications, Nature, vol. 15(1), pages 1-17, December.
    14. Quentin Blampey & Kevin Mulder & Margaux Gardet & Stergios Christodoulidis & Charles-Antoine Dutertre & Fabrice André & Florent Ginhoux & Paul-Henry Cournède, 2024. "Sopa: a technology-invariant pipeline for analyses of image-based spatial omics," Nature Communications, Nature, vol. 15(1), pages 1-12, December.
    15. Hao Xu & Shuyan Wang & Minghao Fang & Songwen Luo & Chunpeng Chen & Siyuan Wan & Rirui Wang & Meifang Tang & Tian Xue & Bin Li & Jun Lin & Kun Qu, 2023. "SPACEL: deep learning-based characterization of spatial transcriptome architectures," Nature Communications, Nature, vol. 14(1), pages 1-18, December.
    16. Jingyang Qian & Jie Liao & Ziqi Liu & Ying Chi & Yin Fang & Yanrong Zheng & Xin Shao & Bingqi Liu & Yongjin Cui & Wenbo Guo & Yining Hu & Hudong Bao & Penghui Yang & Qian Chen & Mingxiao Li & Bing Zha, 2023. "Reconstruction of the cell pseudo-space from single-cell RNA sequencing data with scSpace," Nature Communications, Nature, vol. 14(1), pages 1-18, December.
    17. Eudald Pascual-Carreras & Marta Marín-Barba & Sergio Castillo-Lara & Pablo Coronel-Córdoba & Marta Silvia Magri & Grant N. Wheeler & Jose Luis Gómez-Skarmeta & Josep F. Abril & Emili Saló & Teresa Ade, 2023. "Wnt/β-catenin signalling is required for pole-specific chromatin remodeling during planarian regeneration," Nature Communications, Nature, vol. 14(1), pages 1-16, December.
    18. Zhiyuan Liu & Dafei Wu & Weiwei Zhai & Liang Ma, 2023. "SONAR enables cell type deconvolution with spatially weighted Poisson-Gamma model for spatial transcriptomics," Nature Communications, Nature, vol. 14(1), pages 1-14, December.
    19. Chen-Rui Xia & Zhi-Jie Cao & Xin-Ming Tu & Ge Gao, 2023. "Spatial-linked alignment tool (SLAT) for aligning heterogenous slices," Nature Communications, Nature, vol. 14(1), pages 1-12, December.
    20. Jingyang Qian & Hudong Bao & Xin Shao & Yin Fang & Jie Liao & Zhuo Chen & Chengyu Li & Wenbo Guo & Yining Hu & Anyao Li & Yue Yao & Xiaohui Fan & Yiyu Cheng, 2024. "Simulating multiple variability in spatially resolved transcriptomics with scCube," Nature Communications, Nature, vol. 15(1), pages 1-21, December.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:nat:natcom:v:14:y:2023:i:1:d:10.1038_s41467-023-39016-0. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.nature.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.