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A harmonized atlas of mouse spinal cord cell types and their spatial organization

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  • Daniel E. Russ

    (Division of Cancer Epidemiology and Genetics, Data Science Research Group, National Cancer Institute, NIH)

  • Ryan B. Patterson Cross

    (Spinal Circuits and Plasticity Unit, National Institute of Neurological Disorders and Stroke, NIH)

  • Li Li

    (Spinal Circuits and Plasticity Unit, National Institute of Neurological Disorders and Stroke, NIH)

  • Stephanie C. Koch

    (Department of Neuroscience, Physiology and Pharmacology, Division of Biosciences, University College London)

  • Kaya J. E. Matson

    (Spinal Circuits and Plasticity Unit, National Institute of Neurological Disorders and Stroke, NIH)

  • Archana Yadav

    (Department of Neurology, Center for Translational and Computational Neuroimmunology, Columbia University)

  • Mor R. Alkaslasi

    (Eunice Kennedy Shriver National Institute of Child Health and Human Development, NIH
    Brown University)

  • Dylan I. Lee

    (Department of Neurology, Center for Translational and Computational Neuroimmunology, Columbia University)

  • Claire E. Le Pichon

    (Eunice Kennedy Shriver National Institute of Child Health and Human Development, NIH)

  • Vilas Menon

    (Department of Neurology, Center for Translational and Computational Neuroimmunology, Columbia University)

  • Ariel J. Levine

    (Spinal Circuits and Plasticity Unit, National Institute of Neurological Disorders and Stroke, NIH)

Abstract

Single-cell RNA sequencing data can unveil the molecular diversity of cell types. Cell type atlases of the mouse spinal cord have been published in recent years but have not been integrated together. Here, we generate an atlas of spinal cell types based on single-cell transcriptomic data, unifying the available datasets into a common reference framework. We report a hierarchical structure of postnatal cell type relationships, with location providing the highest level of organization, then neurotransmitter status, family, and finally, dozens of refined populations. We validate a combinatorial marker code for each neuronal cell type and map their spatial distributions in the adult spinal cord. We also show complex lineage relationships among postnatal cell types. Additionally, we develop an open-source cell type classifier, SeqSeek, to facilitate the standardization of cell type identification. This work provides an integrated view of spinal cell types, their gene expression signatures, and their molecular organization.

Suggested Citation

  • Daniel E. Russ & Ryan B. Patterson Cross & Li Li & Stephanie C. Koch & Kaya J. E. Matson & Archana Yadav & Mor R. Alkaslasi & Dylan I. Lee & Claire E. Le Pichon & Vilas Menon & Ariel J. Levine, 2021. "A harmonized atlas of mouse spinal cord cell types and their spatial organization," Nature Communications, Nature, vol. 12(1), pages 1-20, December.
  • Handle: RePEc:nat:natcom:v:12:y:2021:i:1:d:10.1038_s41467-021-25125-1
    DOI: 10.1038/s41467-021-25125-1
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    Citations

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    Cited by:

    1. Yongheng Fan & Xianming Wu & Sufang Han & Qi Zhang & Zheng Sun & Bing Chen & Xiaoyu Xue & Haipeng Zhang & Zhenni Chen & Man Yin & Zhifeng Xiao & Yannan Zhao & Jianwu Dai, 2023. "Single-cell analysis reveals region-heterogeneous responses in rhesus monkey spinal cord with complete injury," Nature Communications, Nature, vol. 14(1), pages 1-20, December.
    2. Charles Warwick & Joseph Salsovic & Junichi Hachisuka & Kelly M. Smith & Tayler D. Sheahan & Haichao Chen & James Ibinson & H. Richard Koerber & Sarah E. Ross, 2022. "Cell type-specific calcium imaging of central sensitization in mouse dorsal horn," Nature Communications, Nature, vol. 13(1), pages 1-17, December.
    3. Kaya J. E. Matson & Daniel E. Russ & Claudia Kathe & Isabelle Hua & Dragan Maric & Yi Ding & Jonathan Krynitsky & Randall Pursley & Anupama Sathyamurthy & Jordan W. Squair & Boaz P. Levi & Gregoire Co, 2022. "Single cell atlas of spinal cord injury in mice reveals a pro-regenerative signature in spinocerebellar neurons," Nature Communications, Nature, vol. 13(1), pages 1-16, December.
    4. Ee Shan Liau & Suoqin Jin & Yen-Chung Chen & Wei-Szu Liu & Maëliss Calon & Stéphane Nedelec & Qing Nie & Jun-An Chen, 2023. "Single-cell transcriptomic analysis reveals diversity within mammalian spinal motor neurons," Nature Communications, Nature, vol. 14(1), pages 1-21, December.

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