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Phenotypic variation of transcriptomic cell types in mouse motor cortex

机译：小鼠电机皮层中转录组细胞类型的表型变异

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摘要

Cortical neurons exhibit extreme diversity in gene expression as well as in morphological and electrophysiological properties~(1,2). Most existing neural taxonomies are based on either transcriptomic~(3,4)or morpho-electric~(5,6)criteria, as it has been technically challenging to study both aspects of neuronal diversity in the same set of cells~(7). Here we used Patch-seq~(8)to combine patch-clamp recording, biocytin staining, and single-cell RNA sequencing of more than 1,300 neurons in adult mouse primary motor cortex, providing a morpho-electric annotation of almost all transcriptomically defined neural cell types. We found that, although broad families of transcriptomic types (those expressing Vip, Pvalb, Sst and so on) had distinct and essentially non-overlapping morpho-electric phenotypes, individual transcriptomic types within the same family were not well separated in the morpho-electric space. Instead, there was a continuum of variability in morphology and electrophysiology, with neighbouring transcriptomic cell types showing similar morpho-electric features, often without clear boundaries between them. Our results suggest that neuronal types in the neocortex do not always form discrete entities. Instead, neurons form a hierarchy that consists of distinct non-overlapping branches at the level of families, but can form continuous and correlated transcriptomic and morpho-electrical landscapes within families.
机译：皮质神经元在基因表达中表现出极端的多样性以及形态学和电生理学特性〜（1,2）。大多数现有的神经分类学基于转录组〜（3,4）或Morpho-Electric〜（5,6）标准，因为它在技术上挑战了在同一组细胞中研究神经元多样性的两个方面〜（7） 。在这里，我们使用Patch-Seq〜（8）将蛋白钳记录，生物霉素染色和单细胞RNA测序组合在成人小鼠初级电机皮层中超过1,300个神经元，提供了几乎所有转录组定义神经网络的Morpho-Elector细胞类型。我们发现，虽然过度的转录组织类型（表达VIP，PVALB，SST等）具有明显且基本上不重叠的语气电力表型，但同一家族内的个体转录组织在Morpho-Electry中没有很好地分开空间。相反，在形态和电生理学中存在恒定的变化，相邻的转录组细胞类型显示出类似的主电动特征，通常没有明确的边界。我们的结果表明，Neocortex中的神经元类型并不总是形成离散实体。相反，神经元形成一个层次结构，该层级包括在家庭的水平上的不同的非重叠分支组成，但可以在家庭内形成连续和相关的转录组和态度景观。

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  • 来源
    《Nature》 |2021年第7879期|144-150|共7页
  • 作者

    Federico Scala; Dmitry Kobak; Matteo Bernabucci; Yves Bernaerts; Cathryn René Cadwell; Jesus Ramon Castro; Leonard Hartmanis; Xiaolong Jiang; Sophie Laturnus; Elanine Miranda; Shalaka Mulherkar; Zheng Huan Tan; Zizhen Yao; Hongkui Zeng; Rickard Sandberg; Philipp Berens; Andreas S Tolias;

  • 作者单位

    Center for Neuroscience and Artificial Intelligence Baylor College of Medicine|Department of Neuroscience Baylor College of Medicine;

    Institute for Ophthalmic Research University of Tübingen;

    Center for Neuroscience and Artificial Intelligence Baylor College of Medicine|Department of Neuroscience Baylor College of Medicine;

    Institute for Ophthalmic Research University of Tübingen|International Max Planck Research School for Intelligent Systems;

    Department of Pathology University of California San Francisco;

    Center for Neuroscience and Artificial Intelligence Baylor College of Medicine|Department of Neuroscience Baylor College of Medicine;

    Department of Cell and Molecular Biology Karolinska Institutet;

    Center for Neuroscience and Artificial Intelligence Baylor College of Medicine|Department of Neuroscience Baylor College of Medicine|Jan and Dan Duncan Neurological Research Institute;

    Institute for Ophthalmic Research University of Tübingen;

    Center for Neuroscience and Artificial Intelligence Baylor College of Medicine|Department of Neuroscience Baylor College of Medicine;

    Department of Neuroscience Baylor College of Medicine;

    Center for Neuroscience and Artificial Intelligence Baylor College of Medicine|Department of Neuroscience Baylor College of Medicine;

    Allen Institute for Brain Science;

    Allen Institute for Brain Science;

    Department of Cell and Molecular Biology Karolinska Institutet;

    Institute for Ophthalmic Research University of Tübingen|Center for Integrative Neuroscience University of Tübingen|Institute for Bioinformatics and Medical Informatics University of Tübingen|Bernstein Center for Computational Neuroscience University of Tübingen;

    Center for Neuroscience and Artificial Intelligence Baylor College of Medicine|Department of Neuroscience Baylor College of Medicine;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);美国《生物学医学文摘》(MEDLINE);美国《化学文摘》(CA);
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