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Molecular architecture of the developing mouse brain

Author

Listed:
  • Gioele La Manno

    (Karolinska Institute
    École Polytechnique Fédérale de Lausanne)

  • Kimberly Siletti

    (Karolinska Institute)

  • Alessandro Furlan

    (Karolinska Institute
    Cold Spring Harbor Laboratory)

  • Daniel Gyllborg

    (Stockholm University)

  • Elin Vinsland

    (Karolinska Institute)

  • Alejandro Mossi Albiach

    (Karolinska Institute)

  • Christoffer Mattsson Langseth

    (Stockholm University)

  • Irina Khven

    (École Polytechnique Fédérale de Lausanne)

  • Alex R. Lederer

    (École Polytechnique Fédérale de Lausanne)

  • Lisa M. Dratva

    (École Polytechnique Fédérale de Lausanne)

  • Anna Johnsson

    (Karolinska Institute)

  • Mats Nilsson

    (Stockholm University)

  • Peter Lönnerberg

    (Karolinska Institute)

  • Sten Linnarsson

    (Karolinska Institute)

Abstract

The mammalian brain develops through a complex interplay of spatial cues generated by diffusible morphogens, cell–cell interactions and intrinsic genetic programs that result in probably more than a thousand distinct cell types. A complete understanding of this process requires a systematic characterization of cell states over the entire spatiotemporal range of brain development. The ability of single-cell RNA sequencing and spatial transcriptomics to reveal the molecular heterogeneity of complex tissues has therefore been particularly powerful in the nervous system. Previous studies have explored development in specific brain regions1–8, the whole adult brain9 and even entire embryos10. Here we report a comprehensive single-cell transcriptomic atlas of the embryonic mouse brain between gastrulation and birth. We identified almost eight hundred cellular states that describe a developmental program for the functional elements of the brain and its enclosing membranes, including the early neuroepithelium, region-specific secondary organizers, and both neurogenic and gliogenic progenitors. We also used in situ mRNA sequencing to map the spatial expression patterns of key developmental genes. Integrating the in situ data with our single-cell clusters revealed the precise spatial organization of neural progenitors during the patterning of the nervous system.

Suggested Citation

  • Gioele La Manno & Kimberly Siletti & Alessandro Furlan & Daniel Gyllborg & Elin Vinsland & Alejandro Mossi Albiach & Christoffer Mattsson Langseth & Irina Khven & Alex R. Lederer & Lisa M. Dratva & An, 2021. "Molecular architecture of the developing mouse brain," Nature, Nature, vol. 596(7870), pages 92-96, August.
  • Handle: RePEc:nat:nature:v:596:y:2021:i:7870:d:10.1038_s41586-021-03775-x
    DOI: 10.1038/s41586-021-03775-x
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    Citations

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    Cited by:

    1. Akram A. Hamed & Daniel J. Kunz & Ibrahim El-Hamamy & Quang M. Trinh & Omar D. Subedar & Laura M. Richards & Warren Foltz & Garrett Bullivant & Matthaeus Ware & Maria C. Vladoiu & Jiao Zhang & Antony , 2022. "A brain precursor atlas reveals the acquisition of developmental-like states in adult cerebral tumours," Nature Communications, Nature, vol. 13(1), pages 1-15, December.
    2. Joachim Jonghe & Tomasz S. Kaminski & David B. Morse & Marcin Tabaka & Anna L. Ellermann & Timo N. Kohler & Gianluca Amadei & Charlotte E. Handford & Gregory M. Findlay & Magdalena Zernicka-Goetz & Sa, 2023. "spinDrop: a droplet microfluidic platform to maximise single-cell sequencing information content," Nature Communications, Nature, vol. 14(1), pages 1-18, December.
    3. Yingfeng Tao & Xiaoliu Zhou & Leqiang Sun & Da Lin & Huaiyuan Cai & Xi Chen & Wei Zhou & Bing Yang & Zhe Hu & Jing Yu & Jing Zhang & Xiaoqing Yang & Fang Yang & Bang Shen & Wenbao Qi & Zhenfang Fu & J, 2023. "Highly efficient and robust π-FISH rainbow for multiplexed in situ detection of diverse biomolecules," Nature Communications, Nature, vol. 14(1), pages 1-15, December.
    4. Jia-Ru Wei & Zhao-Zhe Hao & Chuan Xu & Mengyao Huang & Lei Tang & Nana Xu & Ruifeng Liu & Yuhui Shen & Sarah A. Teichmann & Zhichao Miao & Sheng Liu, 2022. "Identification of visual cortex cell types and species differences using single-cell RNA sequencing," Nature Communications, Nature, vol. 13(1), pages 1-21, December.
    5. 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.
    6. Abhijit Chakraborty & Jeffrey G. Wang & Ferhat Ay, 2022. "dcHiC detects differential compartments across multiple Hi-C datasets," Nature Communications, Nature, vol. 13(1), pages 1-21, December.

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