An anatomical cell type atlas of gene expression, morphology and connectivity

基因表达、形态和连接性的解剖细胞类型图谱

• 批准号: 9416011
• 负责人: Hongkui Zeng
• 金额: $ 296.68万
• 依托单位: ALLEN INSTITUTE
• 依托单位国家: 美国
• 资助国家: 美国
• 起止时间: 至
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/9416011
• 关键词: Accounting; Adult; Alpha Cell; Anatomy; Area; Atlases; Biological Assay; Brain; Brain Mapping; Brain imaging; Brain region; Catalogs; Cells; Cellular Morphology; Censuses; Classification Scheme; Collaborations; Collection; Computing Methodologies; Coupling; Critical Pathways; Data; Data Set; Female; Fluorescent in Situ Hybridization; Functional Imaging; Gene Expression; Generations; Genes; Image; Injection of therapeutic agent; Institutes; Label; Location; Maps; Methods; Modality; Morphology; Mus; Neurons; Output; Pattern; Population; Production; Property; Rabies; Research; Resolution; Seeds; Sex Characteristics; Social Behavior; Standardization; Synapses; System; TimeLine; Tissues; brain cell; cell type; combinatorial; experimental study; fluorescence imaging; imaging approach; imaging system; improved; in vivo; information processing; male; reconstruction; scale up; sex; sexual dimorphism; transcriptome sequencing; transcriptomics; transgene expression

Project Summary (Research Segment 2) The brain circuit is an intricately interconnected network of numerous cell types. To understand the principles of information processing in the brain circuit, it is essential to determine a catalog of cell types, how they are distributed throughout the brain, and how they are connected to each other. A cell's precise location within the brain (where is it?), its specific dendritic and axonal morphology (what does it look like?), and its structural connectivity with other cells in circuits and networks (who does it connect to?) are all critical anatomical factors which contribute to the definition and accounting of different cell types. We will produce comprehensive anatomical cell census data from brains of adult male and female mice, leveraging our existing mouse brain reference and connectivity atlases, and employing three major scalable approaches. We will map the spatial organization of transcriptomic cell types identified in Research Segment 1 using multiplexed error-robust fluorescence in situ hybridization (MERFISH) with combinatorial marker gene sets identified in the single-cell RNA-seq experiments. Furthermore, we will use MERFISH to determine the microenvironment, tissue composition and ratio of various cell types. We will generate full neuronal morphologies of representative cell types in major brain regions, using two different high-throughput and high-resolution whole-brain fluorescent imaging approaches and semi-automated morphology reconstruction methods. These systematically collected data will be used to discover rules underlying cell types as defined by their full dendritic and axonal morphologies. We will use an optimized rabies tracing system to do monosynaptic, retrograde trans-synaptic tracing to map whole-brain inputs to genetically-identified cell populations brain-wide. By combining this with the Allen Institute's already created anterograde projectome, we will be able to generate a first iteration of the mesoscale, input/output circuit wiring diagram. These different types of anatomical data will be integrated with each other and with other cell type characterization data modalities in a variety of ways, including coupling rabies tracing, full neuronal morphology, or in vivo functional imaging with multiplexed FISH, to derive an integrated cell type classification scheme.

项目摘要（研究部分2） 脑电路是许多细胞类型的错综复杂的互连网络。了解原则 大脑电路中的信息处理，必须确定细胞类型的目录，它们的状态至关重要 分布在整个大脑中，以及它们如何相互连接。单元在 大脑（在哪里？），其特定的树突状和轴突形态（看起来像什么？）及其结构性 与电路和网络中其他单元格的连通性（它连接到谁？）都是关键的解剖因素 这有助于不同细胞类型的定义和会计。我们将产生全面的 来自成年雄性和雌性小鼠大脑的解剖细胞普查数据，利用我们现有的小鼠脑 参考和连通性地图集，采用三种主要可扩展方法。我们将绘制空间 使用多路复用误解在研究段1中确定的转录组细胞类型的组织 荧光原位杂交（Merfish）与在单细胞中鉴定的组合标记基因集 RNA-seq实验。此外，我们将使用Merfish确定微环境，组织 各种细胞类型的组成和比率。我们将产生代表性细胞的完整神经元形态 主要大脑区域的类型，使用两种不同的高通量和高分辨率全脑荧光 成像方法和半自动形态重建方法。这些系统收集 数据将用于发现由其完整的树突和轴突定义的细胞类型的基础规则 形态。我们将使用优化的狂犬病追踪系统进行单突触，逆行反式突触 追踪以将全脑输入映射到遗传识别的细胞群体脑脑中。通过将其与 艾伦学院（Allen Institute 中尺度，输入/输出电路接线图。这些不同类型的解剖数据将与 彼此以及其他细胞类型表征数据模式的各种方式，包括耦合 狂犬病追踪，完整的神经元形态或带有多重鱼的体内功能成像，以得出 集成细胞类型分类方案。