Comprehensive Classification Of Neuronal Subtypes By Single Cell Transcriptomics

单细胞转录组学对神经元亚型的综合分类

• 批准号: 8822370
• 负责人: AVIV REGEV
• 金额: $ 136.25万
• 依托单位: HARVARD UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2014
• 资助国家: 美国
• 起止时间: 2014-09-26 至 2017-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8822370
• 关键词: Address; Brain; Brain region; Calcium; Categories; Cell Separation; Cells; Censuses; Classification; Computer Analysis; Computing Methodologies; Data; Decision Trees; Dissection; Emerging Technologies; Ensure; Equipment and supply inventories; Functional disorder; Gene Combinations; Gene Expression Profile; Genes; Goals; Habenula; Image; In Situ Hybridization; Lead; Learning; Libraries; Maps; Measures; Methods; Modeling; Molecular; Morphology; Mus; Neurons; Pattern; RNA; Reagent; Retina; Structure; Surveys; Taxonomy; Technology; Testing; Tissues; Transcript; Translating; Work; Zebrafish; base; brain cell; cell type; computer framework; cost; falls; high risk; insight; interest; molecular marker; novel diagnostics; novel therapeutics; predictive modeling; public health relevance; scale up; transcriptome sequencing; transcriptomics

 DESCRIPTION (provided by applicant): To understand the brain, we need a "parts list" of its cell types. The list will need to integrate molecular, functional and morphological data, but of these, molecular classification is best suited for comprehensive categorization and the only approach that can lead directly to genetically accessing the types; such access is essential in order to mark and manipulate neurons and to allow rigorous comparison of neurons from normal and diseased brains. We will apply the emerging method of single-cell transcriptional profiling (scRNA-seq) to this task. We will first rigorously compare and optimize cutting- edge methods for cell isolation, transcriptional profiling, and computational analysis to establish an efficientand effective pipeline for categorization. Then, we will apply our suite of methods to two brain regions - mouse retina and zebrafish habenula - that differ in several ways but share key features: they are accessible and compact and it is feasible to map their cell types comprehensively. In each case, we will perform unbiased and exhaustive profiling of 1,000's of neurons, to ensure that even rare classes of neurons are included in the survey. We will validate gene modules obtained from profiling by in situ hybridization, integrate them with structural and functional data, and provide standardized and comprehensive maps of cell type. Finally, we will apply what we have learned to a larger region, the mouse habenula. Profiling and classification in this structure will not only provide a stringent test of our ability to scale up our methods, bu also allow us to ask two important and interesting questions: to what extent cell types are conserved across species (zebrafish vs. mouse habenula) and to what extent cell types are conserved across regions (mouse retina vs. habenula). Together, insights, methods and reagents obtained in this work will provide an essential toolkit for tackling the whole brain.

 描述（由申请人提供）：为了了解大脑，我们需要一个细胞类型的“部件列表”。该列表将需要整合分子，功能和形态学数据，但其中，分子分类最适合全面分类，也是唯一可以直接导致遗传访问类型的方法;这种访问对于标记和操纵神经元以及允许对正常和患病大脑的神经元进行严格比较至关重要。我们将应用新兴的单细胞转录谱分析（scRNA-seq）方法来完成这项任务。我们将首先严格比较和优化细胞分离、转录谱分析和计算分析的尖端方法，以建立一个高效和有效的分类管道。然后，我们将把我们的一套方法应用于两个大脑区域--小鼠视网膜和斑马鱼缰核--它们在几个方面不同，但有着共同的关键特征：它们是可访问的、紧凑的，全面绘制它们的细胞类型是可行的。在每种情况下，我们将对1,000个神经元进行无偏和详尽的分析，以确保即使是罕见的神经元也包括在调查中。我们将通过原位杂交验证从分析中获得的基因模块，将其与结构和功能数据相结合，并提供标准化和全面的细胞类型图谱。最后，我们将把我们所学到的应用到一个更大的区域，小鼠缰核。在这种结构中进行分析和分类不仅可以对我们扩大方法的能力进行严格的测试，而且还可以让我们提出两个重要而有趣的问题：细胞类型在物种之间的保守程度（斑马鱼与小鼠缰核）以及细胞类型在区域之间的保守程度（小鼠视网膜与缰核）。总之，这项工作中获得的见解，方法和试剂将为解决整个大脑提供一个必不可少的工具包。