Functionally guided adult whole brain cell atlas in human and NHP

人类和 NHP 的功能引导成人全脑细胞图谱

基本信息

批准号：
10523848
负责人：
Ed Lein
金额：
$ 2286.45万
依托单位：
ALLEN INSTITUTE
依托单位国家：
美国
项目类别：
财政年份：
2022
资助国家：
美国
起止时间：
2022-08-22 至 2027-06-30
项目状态：
未结题

来源：
https://reporter.nih.gov/project-details/10523848
关键词：
ATAC-seq Acute Adult Anatomy Animal Model Architecture Atlases Automobile Driving Basic Science Behavior Behavioral Biological Assay Biomedical Research Brain Brain Diseases Brain region Callithrix Cell Nucleus Cell physiology Cells Characteristics Classification Clinical Communities Complex Consensus Consent Coupled Data Data Analyses Development Didelphidae Disease Enhancers Ensure Foundations Freezing Functional Imaging Functional Magnetic Resonance Imaging Genes Genetic Genomics Goals Hippocampus (Brain)Histologic Human Image Individual Knowledge Label Link Macaca Magnetic Resonance Imaging Mammals Maps Measures Methods Modeling Molecular Molecular Analysis Molecular Profiling Monkeys Moods Morphology Mus Nerve Tissue Neurons Neurosciences Ontology Organism Outcome Pan Genus Pattern Perception Phenotype Population Primates Property Reference Standards Regulator Genes Research Resected Resources Rodent Salvelinus Sampling Slice Specimen Structure Subcellular Anatomy Taxonomy Techniques Technology Tissues Variant Visualization software Work base brain cell brain circuitry brain tissue cell type cohort comparative computerized data processing data integration data management data mining data resource data standards data visualization electrical property end of life epigenomics human disease human model human subject human tissue in vivo in vivo imaging inter-individual variation member multimodality nervous system disorder neuroethics neuroimaging nonhuman primate patch sequencing sex single cell technology study population tool transcriptome transcriptome sequencing transcriptomics

项目摘要

Progress in treating brain disorders has been frustratingly slow, in large part due to the extraordinary complexity of the human brain and its inaccessibility to study. Remarkable advances in technologies for studying individual cells, most notably single cell genomics, have revolutionized the study of complex nervous tissues and have been used to map cellular diversity across the entire mouse brain with cell types defined by their specific patterns of gene usage and gene regulatory mechanisms. These highly scalable methods have been successfully applied to brain tissue from human and other species and are ready to be applied to whole brains from humans and non-human primates. A major challenge with studying the human brain is bridging fields and scales from functional MRI and macroscale connectomics to histological, cellular and molecular analyses. Bridging these domains is essential to creating a transformative new cell atlas that will describe the cellular and molecular underpinnings of the functional organization of the human brain. An important recent development from single cell genomic analysis is that cell types can be aligned across species and are highly conserved across mammals from mice to humans, although more similar in evolutionarily closer primates than in rodents. This finding amplifies the value of primate species in helping to understand human brains and infer cellular properties that cannot be measured in humans. The current proposal brings together a unique team of world leaders to tackle the challenge of creating a new human and non-human primate cell atlas linked to functional brain architecture. Single cell transcriptomic, epigenomic and spatial transcriptomics will be used to classify and spatially map cell types across the entire human, macaque and marmoset brain, sampling based on brain maps derived from structural and functional imaging. Function-localizing fMRI in macaques will allow the direct analysis of cellular correlates of functional topography. Advances in spatial transcriptomics will allow an unprecedented whole primate brain map of cell types. Unique access to macaque tissues for analysis of cellular anatomy and physiology allows the characterization of molecularly-defined cell types in many brain regions. Similar techniques will be applied to living neurosurgically-derived human brain tissues, coupled with enhancer-AAV based tools to allow selective genetic labeling of cell types. Finally, profiling regions central to perception, behavior and mood across many individuals and diverse mammals will link genetic, environmental and evolutionary factors to cellular variation. The outcome of these efforts will produce a new reference classification for cell types across the whole human and NHP brain, spatial maps of molecularly defined cell types, and phenotypic characterization of fundamental brain cell types. The classification will align homologous cell types from mice, marmosets, macaques and humans, allowing inference and comparison of cellular properties across species. Furthermore, data will be aligned in common coordinate frameworks, allowing creation of new atlases spanning structural, functional, cellular and molecular information. All data and analyses will be distributed to the research community, including a formal cell ontology of cell types across species and visualization tools for broad community access.

治疗脑部疾病的进展一直令人沮丧，这在很大程度上是由于特殊的复杂性人脑及其学习的无法访问。研究单个细胞的技术的显着进步，大多数特别是单细胞基因组学，彻底改变了复杂神经组织的研究，并已用于映射细胞整个小鼠大脑的多样性具有细胞类型，这些细胞类型由它们的基因使用和基因调节的特定模式定义机制。这些高度可扩展的方法已成功地应用于人类和其他物种的脑组织并准备好应用于人类和非人类灵长类动物的全脑中。研究人的大脑正在桥接领域和尺度从功能性MRI和宏观连接组学到组织学，细胞和分子分析。桥接这些域对于创建一个变革性的新单元图是至关重要的人脑功能组织的细胞和分子基础。最近的重要单细胞基因组分析的发展是可以对细胞类型进行对齐，并且是高度保守的跨小鼠到人类的哺乳动物，尽管在进化的近距离灵长类动物上比啮齿动物更相似。这个发现放大灵长类动物在帮助理解人的大脑和推断细胞特性方面的价值在人类中测量。当前的提议汇集了一个独特的世界领导人团队，以应对创建新人类和的挑战非人类灵长类动物细胞图集与功能性脑结构有关。单细胞转录组，表观基因组和空间转录组学将用于对整个人，猕猴和斑驳的细胞类型进行分类和空间映射大脑，基于从结构和功能成像中得出的大脑图采样。猕猴中的功能定位fMRI 将允许直接分析功能地形的细胞相关性。空间转录组学的进步将允许一个空前的整个细胞类型的灵长类动物大脑图。独特进入猕猴组织以分析细胞解剖学和生理允许在许多大脑区域中表征分子定义的细胞类型。相似的技术将应用于活的神经外科衍生的人脑组织，并与基于增强剂-AAV的工具相结合允许细胞类型的选择性遗传标记。最后，分析区域的核心，行为和情绪的核心许多个体和多样化的哺乳动物将将遗传，环境和进化论因子与细胞变异联系起来。这些努力的结果将为整个人类和NHP的细胞类型产生新的参考分类大脑，分子定义的细胞类型的空间图以及基本脑细胞类型的表型表征。这分类将使小鼠，棉花糖，猕猴和人类的同源细胞类型对齐，从而推断和比较物种跨物种的细胞特性。此外，数据将在通用坐标框架中对齐，允许创建涵盖结构，功能，细胞和分子信息的新地图集。所有数据和分析将分发给研究界，包括跨物种细胞类型的形式细胞本体和可视化广泛社区访问的工具。