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Spatial atlas of the mouse central nervous system at molecular resolution

Author

Listed:
  • Hailing Shi

    (Broad Institute of MIT and Harvard
    Massachusetts Institute of Technology)

  • Yichun He

    (Broad Institute of MIT and Harvard
    Harvard University)

  • Yiming Zhou

    (Broad Institute of MIT and Harvard
    Massachusetts Institute of Technology)

  • Jiahao Huang

    (Broad Institute of MIT and Harvard
    Massachusetts Institute of Technology)

  • Kamal Maher

    (Broad Institute of MIT and Harvard
    Massachusetts Institute of Technology)

  • Brandon Wang

    (Broad Institute of MIT and Harvard
    Massachusetts Institute of Technology
    Massachusetts Institute of Technology)

  • Zefang Tang

    (Broad Institute of MIT and Harvard
    Massachusetts Institute of Technology)

  • Shuchen Luo

    (Broad Institute of MIT and Harvard
    Massachusetts Institute of Technology)

  • Peng Tan

    (Broad Institute of MIT and Harvard
    Broad Institute of MIT and Harvard)

  • Morgan Wu

    (Broad Institute of MIT and Harvard)

  • Zuwan Lin

    (Broad Institute of MIT and Harvard
    Harvard University
    Harvard University)

  • Jingyi Ren

    (Broad Institute of MIT and Harvard
    Massachusetts Institute of Technology)

  • Yaman Thapa

    (Broad Institute of MIT and Harvard)

  • Xin Tang

    (Broad Institute of MIT and Harvard
    Harvard University)

  • Ken Y. Chan

    (Broad Institute of MIT and Harvard
    Broad Institute of MIT and Harvard)

  • Benjamin E. Deverman

    (Broad Institute of MIT and Harvard
    Broad Institute of MIT and Harvard)

  • Hao Shen

    (Harvard University)

  • Albert Liu

    (Broad Institute of MIT and Harvard
    Massachusetts Institute of Technology)

  • Jia Liu

    (Harvard University)

  • Xiao Wang

    (Broad Institute of MIT and Harvard
    Massachusetts Institute of Technology
    Broad Institute of MIT and Harvard)

Abstract

Spatially charting molecular cell types at single-cell resolution across the 3D volume is critical for illustrating the molecular basis of brain anatomy and functions. Single-cell RNA sequencing has profiled molecular cell types in the mouse brain1,2, but cannot capture their spatial organization. Here we used an in situ sequencing method, STARmap PLUS3,4, to profile 1,022 genes in 3D at a voxel size of 194 × 194 × 345 nm3, mapping 1.09 million high-quality cells across the adult mouse brain and spinal cord. We developed computational pipelines to segment, cluster and annotate 230 molecular cell types by single-cell gene expression and 106 molecular tissue regions by spatial niche gene expression. Joint analysis of molecular cell types and molecular tissue regions enabled a systematic molecular spatial cell-type nomenclature and identification of tissue architectures that were undefined in established brain anatomy. To create a transcriptome-wide spatial atlas, we integrated STARmap PLUS measurements with a published single-cell RNA-sequencing atlas1, imputing single-cell expression profiles of 11,844 genes. Finally, we delineated viral tropisms of a brain-wide transgene delivery tool, AAV-PHP.eB5,6. Together, this annotated dataset provides a single-cell resource that integrates the molecular spatial atlas, brain anatomy and the accessibility to genetic manipulation of the mammalian central nervous system.

Suggested Citation

  • Hailing Shi & Yichun He & Yiming Zhou & Jiahao Huang & Kamal Maher & Brandon Wang & Zefang Tang & Shuchen Luo & Peng Tan & Morgan Wu & Zuwan Lin & Jingyi Ren & Yaman Thapa & Xin Tang & Ken Y. Chan & B, 2023. "Spatial atlas of the mouse central nervous system at molecular resolution," Nature, Nature, vol. 622(7983), pages 552-561, October.
  • Handle: RePEc:nat:nature:v:622:y:2023:i:7983:d:10.1038_s41586-023-06569-5
    DOI: 10.1038/s41586-023-06569-5
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    Cited by:

    1. Kalen Clifton & Manjari Anant & Gohta Aihara & Lyla Atta & Osagie K. Aimiuwu & Justus M. Kebschull & Michael I. Miller & Daniel Tward & Jean Fan, 2023. "STalign: Alignment of spatial transcriptomics data using diffeomorphic metric mapping," Nature Communications, Nature, vol. 14(1), pages 1-14, December.

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