Dendritome mapping of genetically-defined and sparsely-labeled cortical and striatal projection neurons

遗传定义和稀疏标记的皮质和纹状体投射神经元的树突状图谱

基本信息

批准号：
9768581
负责人：
Hong-Wei Dong
金额：
$ 84.16万
依托单位：
UNIVERSITY OF CALIFORNIA LOS ANGELES
依托单位国家：
美国
项目类别：
财政年份：
2018
资助国家：
美国
起止时间：
2018-09-01 至 2023-05-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/9768581
关键词：
3-Dimensional Adult Age Anatomy Atlases Axon BRAIN initiative Brain Cells Censuses Classification Communities Computer Hardware Computer software Corpus striatum structure Custom Data Data Set Databases Dendrites Dendritic Spines Development Dyes Frequencies Generations Genetic Genotype Golgi Apparatus Grant Image Image Analysis Imagery Imaging Device Initiator Codon Label Maps Membrane Methods Mitotic Molecular Molecular Profiling Monsters Morphology Mosaicism Mus National Institute of Mental Health Neuroglia Neurons Neurosciences Research Pathway interactions Population Presynaptic Terminals Property Proteins RBP4 gene Reference Standards Reporter Resolution Translations Virus Visualization software Work base bioimaging body position brain cell brain research cell type computerized tools cost data access data integration digital hippocampal pyramidal neuron image processing informatics tool innovation logarithm molecular marker next generation novel novel strategies postnatal programs reconstruction single-cell RNA sequencing tool

项目摘要

PROJECT SUMMARY Integrating molecular, morphological, and connectomic properties is critical for unbiased classification of neuronal cell types in the mammalian brain. Here we propose a novel approach to classify neuronal cell types by brainwide comprehensive profiling of the dendritic morphology of genetically-defined neurons in the mouse brain. We have developed an innovative mouse genetic tool, called Mosaicism with Repeat Frameshift (or MORF), which enables sparsely and stochastically labeling of genetically-defined neurons in mice. MORF reporter mice can label in exquisite detail single neurons from dendrite and spines to axons and axonal terminals at a labeling frequency of 1-5% of a given neuronal population. We propose to cross our new MORF lines with Cre mouse lines for striatal medium spiny neurons (MSNs) of direct- and indirect pathways, and for cortical pyramidal neurons of distinct cortical layers (i.e. L2/3/4, L5 and L6). Each MORF/Cre mouse will allow us to image the detailed dendritic morphology for thousands of genetically-defined striatal and cortical neurons (i.e. dendritome). We have also developed and streamlined imaging and computational tools to acquire and register brainwide single neuron morphological data onto a standard reference mouse brain atlas. We will digitally reconstruct hundreds of thousands of MORF-labeled neurons using our novel program called G-Cut. Reconstructed neurons will subsequently used for morphology based clustering to define new morphological subtypes, which in turn can be analyzed for the expression of novel molecular markers neuronal cell types (e.g. from single cell RNA-sequencing). Finally, we will disseminate the data to the Brain Cell Data Center (BCDC) for data integration with those from other BRAIN Initiative Cell Census Network (BICCN) and for data access by the broader neuroscience research community. In addition to dendritome data generation and analyses, we will further advance our MORF method by generating new MORF reporter mouse lines with logarithmic fold decrease in the Cre- dependent labeling frequencies, which will permit imaging of the complete, brainwide morphology of genetically-defined single neurons that include both dendritic and axonal arborization. Such tool should greatly facilitate the neuronal morphology based cell type classification. Finally, we will develop integrated computer hardware and software for domain-specific computing for automated image processing and neuronal reconstruction, a major bottleneck in analyzing large bioimage datasets. Altogether we will provide rich dendritome information to enable unbiased, morphology-based neuronal cell type classification, and novel mouse genetic tools and computer software and hardware to advance the field of large-scale neuronal morphological imaging and analyses for the comprehensive study of the mammalian brain.

项目概要整合分子、形态和连接组学特性对于公正的分析至关重要哺乳动物大脑中神经元细胞类型的分类。在这里，我们提出了一种新颖的方法通过全脑范围内树突形态的综合分析来对神经元细胞类型进行分类小鼠大脑中基因定义的神经元。我们开发了一种创新的小鼠遗传工具，称为具有重复移码的马赛克（或 MORF），它可以实现稀疏且随机的标记小鼠中基因定义的神经元。 MORF 报告小鼠可以精确地标记单个神经元树突和棘到轴突和轴突末端的标记频率为给定神经元的 1-5% 人口。我们建议将我们的新 MORF 品系与 Cre 小鼠品系杂交，用于纹状体中型多棘神经元（MSN）的直接和间接通路，以及不同皮质层的皮质锥体神经元（即。 L2/3/4、L5 和 L6)。每只 MORF/Cre 小鼠都可以让我们对详细的树突形态进行成像数千个基因定义的纹状体和皮质神经元（即树突状体）。我们还开发并简化的成像和计算工具来获取和记录全脑单个神经元将形态学数据保存到标准参考小鼠大脑图谱上。我们将以数字方式重建数百个使用我们名为 G-Cut 的新颖程序对数千个 MORF 标记的神经元进行分析。重建的神经元将随后用于基于形态学的聚类来定义新的形态学亚型，进而可以分析新分子标记神经元细胞类型的表达（例如来自单细胞 RNA 测序）。最后，我们将数据传播到脑细胞数据中心（BCDC）获取数据与其他 BRAIN Initiative 细胞普查网络 (BICCN) 的集成以及数据访问更广泛的神经科学研究界。除了树突组数据生成和分析之外，我们还将进一步推进我们的 MORF 方法通过生成新的 MORF 报告小鼠品系，Cre- 中的对数倍数减少依赖的标记频率，这将允许对完整的全脑形态进行成像遗传定义的单个神经元，包括树突状和轴突分枝。这样的工具应该极大地促进了基于神经元形态的细胞类型分类。最后我们将开发用于自动化图像领域特定计算的集成计算机硬件和软件处理和神经元重建，这是分析大型生物图像数据集的主要瓶颈。总而言之，我们将提供丰富的树突组信息，以实现公正的、基于形态的神经元细胞类型分类、新型小鼠遗传工具和计算机软件和硬件以推进大规模神经元形态成像和分析领域的综合研究哺乳动物的大脑。