Langlieb Jonah, Sachdev Nina S, Balderrama Karol S, Nadaf Naeem M, Raj Mukund, Murray Evan, Webber James T, Vanderburg Charles, Gazestani Vahid, Tward Daniel, Mezias Chris, Li Xu, Cable Dylan M, Norton Tabitha, Mitra Partha, Chen Fei, Macosko Evan Z
Broad Institute of Harvard and MIT, Cambridge, MA USA.
Departments of Computational Medicine and Neurology, University of California Los Angeles, Los Angeles, CA USA.
bioRxiv. 2023 Mar 13:2023.03.06.531307. doi: 10.1101/2023.03.06.531307.
The function of the mammalian brain relies upon the specification and spatial positioning of diversely specialized cell types. Yet, the molecular identities of the cell types, and their positions within individual anatomical structures, remain incompletely known. To construct a comprehensive atlas of cell types in each brain structure, we paired high-throughput single-nucleus RNA-seq with Slide-seq-a recently developed spatial transcriptomics method with near-cellular resolution-across the entire mouse brain. Integration of these datasets revealed the cell type composition of each neuroanatomical structure. Cell type diversity was found to be remarkably high in the midbrain, hindbrain, and hypothalamus, with most clusters requiring a combination of at least three discrete gene expression markers to uniquely define them. Using these data, we developed a framework for genetically accessing each cell type, comprehensively characterized neuropeptide and neurotransmitter signaling, elucidated region-specific specializations in activity-regulated gene expression, and ascertained the heritability enrichment of neurological and psychiatric phenotypes. These data, available as an online resource (BrainCellData.org) should find diverse applications across neuroscience, including the construction of new genetic tools, and the prioritization of specific cell types and circuits in the study of brain diseases.
哺乳动物大脑的功能依赖于多种特殊细胞类型的特化和空间定位。然而,细胞类型的分子身份及其在各个解剖结构中的位置仍不完全清楚。为了构建每个脑结构中细胞类型的综合图谱,我们将高通量单核RNA测序与Slide-seq(一种最近开发的具有近细胞分辨率的空间转录组学方法)相结合,覆盖整个小鼠大脑。这些数据集的整合揭示了每个神经解剖结构的细胞类型组成。发现中脑、后脑和下丘脑中的细胞类型多样性非常高,大多数细胞簇需要至少三种离散基因表达标记的组合才能唯一地定义它们。利用这些数据,我们开发了一个框架,用于通过基因手段获取每种细胞类型,全面表征神经肽和神经递质信号传导,阐明活动调节基因表达中的区域特异性特化,并确定神经和精神表型的遗传力富集情况。这些数据作为在线资源(BrainCellData.org)提供,应能在神经科学领域找到多种应用,包括构建新的遗传工具,以及在脑疾病研究中确定特定细胞类型和神经回路的优先级。