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：
10407481
负责人：
Hong-Wei Dong
金额：
$ 83.74万
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 2024-05-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/10407481
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 Genotype Golgi Apparatus Grant Image 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 Visualization software Work base bioimaging body position brain cell brain research cell type computerized tools cost data access data centers data integration digital hippocampal pyramidal neuron image processing informatics tool innovation logarithm molecular marker mouse genetics 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.

项目摘要整合分子，形态和连接特性对于无偏见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对树突形态的全面分析对神经元细胞类型进行分类小鼠大脑中的遗传定义神经元。我们已经开发了一种创新的小鼠遗传工具，用重复移码（或MORF）称为镶嵌物，可以稀疏和随机标记小鼠遗传定义的神经元的。 MORF记者小鼠可以用精美的细节标记单个神经元树突和刺轴突和轴突末端的标记频率为1-5％的给定神经元人口。我们建议将新的MORF线与纹状体介质神经元的CRE小鼠线越过直接和间接途径的（MSN），以及不同皮层层的皮质锥体神经元（即 L2/3/4，L5和L6）。每种Morf/Cre鼠标都将使我们能够为详细的树突形态成像成千上万的遗传定义的纹状体和皮质神经元（即树枝状神经元）。我们也发展了简化的成像和计算工具以获取和注册全能的单神经元形态学数据到标准参考小鼠脑图集。我们将数字地重建数百个使用我们的新型程序G-Cut的成千上万个MORF标记的神经元。重建神经元会随后用于基于形态学的聚类来定义新的形态亚型，而这又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序列）。最后，我们将数据传播到脑细胞数据中心（BCDC）以获取数据与其他大脑倡议细胞普查网络（BICCN）的集成，并通过更广泛的神经科学研究社区。除了树枝状数据生成和分析外，我们还将进一步提高MORF 通过生成具有对数折叠的新的MORF报道鼠标线，CRE- 依赖标记频率，这将允许成像完整的，脑形的形态遗传定义的单神经元，包括树突状和轴突树木。这样的工具应该极大地促进了基于神经元的细胞类型分类。最后，我们将发展用于自动图像的域特异性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。我们将共同提供丰富的树枝状信息，以实现公正的基于形态的神经元细胞类型分类以及新颖的鼠标遗传工具以及计算机软件以及硬件以推进大规模神经元形态成像和分析的领域，用于综合研究哺乳动物的大脑。