Cell atlas of mouse brain-spinal cord connectome

项目总结 尽管已经致力于确定大脑中神经细胞的类型，但系统性的 缺乏对脑-脊髓连接体及其相关脊髓神经元类型的研究。在这个项目中，一个 由七个实验室组成的团队建议使用高度创新和多学科的方法来系统地 根据脊髓的解剖、连通性、神经元形态、 分子同一性和电生理特性。在目标1中，我们将使用新开发的AAV 顺行跨突触标记法标记接受下行输入的脊髓神经元 不同的大脑区域，并使用逆行病毒示踪剂AAVretro标记投射到 限定的大脑区域。这些标记的神经元将在完整的整个脊髓中用新的 开发了快速3D光片显微镜技术，目标是在切片制备中进行记录。这个 将比较轴突侧支模式、树突形态和电生理特性。 在不同的输入/输出定义的脊髓神经元组之间。在目标2中，基因表达模式 标记的神经元将通过序列条码FISH(SeqFISH)原位确定，并带有候选标记 从在线资源或从单细胞分类和RNA测序(Dropseq)获得的基因。在Aim 3中，所有 收集的数据包括连接性、解剖细胞类型分布图、神经元形态、分子 特性和电生理特性将用于分类与以下相关的脊髓神经元类型 Brain，并将建立一个开放源代码的数据门户，允许用户搜索、查看和分析 多模式、一体化的单元格类型特定数据。我们的目标是共同构建一个全面的细胞- 小鼠脑-脊髓连接体的类型图谱。

PROJECT SUMMARY Although great efforts have been dedicated to characterizing neuronal cell types in the brain, systematic studies on the brain-spinal cord connectome and associated spinal neuronal types are lacking. In this project, a team of seven laboratories proposes to use a highly innovative and multidisciplinary approach to systematically characterize neuronal types in the spinal cord based on their anatomy, connectivity, neuronal morphologies, molecular identities, and electrophysiological properties. In Aim 1, we will use a newly developed AAV anterograde transsynaptic tagging method to label spinal cord neurons that receive descending inputs from different brain regions, and use a retrograde viral tracer, AAVretro, to label spinal neurons that project to defined brain regions. These tagged neurons will be imaged in the intact whole spinal cord with a newly developed fast 3D light sheet microscopy technique, and targeted for recording in slice preparations. The axonal collateral patterns, dendritic morphologies, and electrophysiological properties will be compared between different input/output-defined spinal neuron groups. In Aim 2, the gene expression patterns of the tagged neurons will be determined in situ by sequential bar-coded FISH (seqFISH), with candidate marker genes obtained from online resources, or from single-cell sorting and RNA sequencing (Dropseq). In Aim 3, all collected data on connectivity, anatomical cell type distribution map, neuronal morphologies, molecular identities, and electrophysiological properties will be used for classifying spinal neuron types connected with brain, and an open-source data portal will be established which will allow users to search, view, and analyze the multi-modal and integrative cell-type specific data. Together, we aim to construct a comprehensive cell- type atlas of the mouse brain-spinal cord connectome.