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A transcriptomic atlas of mouse cerebellar cortex comprehensively defines cell types

Author

Listed:
  • Velina Kozareva

    (Stanley Center for Psychiatric Research)

  • Caroline Martin

    (Stanley Center for Psychiatric Research)

  • Tomas Osorno

    (Harvard Medical School)

  • Stephanie Rudolph

    (Harvard Medical School)

  • Chong Guo

    (Harvard Medical School)

  • Charles Vanderburg

    (Stanley Center for Psychiatric Research)

  • Naeem Nadaf

    (Stanley Center for Psychiatric Research)

  • Aviv Regev

    (Stanley Center for Psychiatric Research)

  • Wade G. Regehr

    (Harvard Medical School)

  • Evan Macosko

    (Stanley Center for Psychiatric Research
    Massachusetts General Hospital)

Abstract

The cerebellar cortex is a well-studied brain structure with diverse roles in motor learning, coordination, cognition and autonomic regulation. However, a complete inventory of cerebellar cell types is currently lacking. Here, using recent advances in high-throughput transcriptional profiling1–3, we molecularly define cell types across individual lobules of the adult mouse cerebellum. Purkinje neurons showed considerable regional specialization, with the greatest diversity occurring in the posterior lobules. For several types of cerebellar interneuron, the molecular variation within each type was more continuous, rather than discrete. In particular, for the unipolar brush cells—an interneuron population previously subdivided into discrete populations—the continuous variation in gene expression was associated with a graded continuum of electrophysiological properties. Notably, we found that molecular layer interneurons were composed of two molecularly and functionally distinct types. Both types show a continuum of morphological variation through the thickness of the molecular layer, but electrophysiological recordings revealed marked differences between the two types in spontaneous firing, excitability and electrical coupling. Together, these findings provide a comprehensive cellular atlas of the cerebellar cortex, and outline a methodological and conceptual framework for the integration of molecular, morphological and physiological ontologies for defining brain cell types.

Suggested Citation

  • Velina Kozareva & Caroline Martin & Tomas Osorno & Stephanie Rudolph & Chong Guo & Charles Vanderburg & Naeem Nadaf & Aviv Regev & Wade G. Regehr & Evan Macosko, 2021. "A transcriptomic atlas of mouse cerebellar cortex comprehensively defines cell types," Nature, Nature, vol. 598(7879), pages 214-219, October.
  • Handle: RePEc:nat:nature:v:598:y:2021:i:7879:d:10.1038_s41586-021-03220-z
    DOI: 10.1038/s41586-021-03220-z
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    Citations

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    Cited by:

    1. Md Tauhidul Islam & Lei Xing, 2023. "Cartography of Genomic Interactions Enables Deep Analysis of Single-Cell Expression Data," Nature Communications, Nature, vol. 14(1), pages 1-17, December.
    2. 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.
    3. Jingkuan Wei & Shaoxing Dai & Yaping Yan & Shulin Li & Pengpeng Yang & Ran Zhu & Tianzhuang Huang & Xi Li & Yanchao Duan & Zhengbo Wang & Weizhi Ji & Wei Si, 2023. "Spatiotemporal proteomic atlas of multiple brain regions across early fetal to neonatal stages in cynomolgus monkey," 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. Suijuan Zhong & Mengdi Wang & Luwei Huang & Youqiao Chen & Yuxin Ge & Jiyao Zhang & Yingchao Shi & Hao Dong & Xin Zhou & Bosong Wang & Tian Lu & Xiaoxi Jing & Yufeng Lu & Junjing Zhang & Xiaoqun Wang , 2023. "Single-cell epigenomics and spatiotemporal transcriptomics reveal human cerebellar development," Nature Communications, Nature, vol. 14(1), pages 1-17, December.
    6. Chris. I. De Zeeuw & Julius Koppen & George. G. Bregman & Marit Runge & Devika Narain, 2023. "Heterogeneous encoding of temporal stimuli in the cerebellar cortex," Nature Communications, Nature, vol. 14(1), pages 1-10, December.
    7. Wendy Xueyi Wang & Julie L. Lefebvre, 2022. "Morphological pseudotime ordering and fate mapping reveal diversification of cerebellar inhibitory interneurons," Nature Communications, Nature, vol. 13(1), pages 1-21, December.

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