Center for Multiomic Human Brain Cell Atlas

多组学人脑细胞图谱中心

基本信息

批准号：
10523973
负责人：
M MARGARITA BEHRENS
金额：
$ 2532万
依托单位：
SALK INSTITUTE FOR BIOLOGICAL STUDIES
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：
2022-09-01 至 2027-06-30
项目状态：
未结题

来源：
https://reporter.nih.gov/project-details/10523973
关键词：
3-Dimensional Address Adult Anatomy Atlases Autopsy BRAIN initiative Behavioral Biological Assay Brain Brain Mapping Brain Pathology Brain region Categories Cell physiology Cells Censuses Chromatin Communities Complex Cytosine DNA DNA Methylation DNA analysis Data Data Analyses Data Set Dependovirus Enhancers Gene Expression Gene Expression Profile Generations Genes Genetic Genetic Transcription Genome Genomics Goals Heterochromatin Histones Human Individual Joints Location Maps Mediating Methods Mitotic Molecular Morphology Mus Neuroanatomy Neuroglia Neurons Nucleic Acid Regulatory Sequences Physiological Population Heterogeneity Production Property RNA Records Regulation Regulator Genes Regulatory Element Resolution Sampling Series Small Nuclear RNA Spatial Distribution Specimen Structure Surveys Technology Testing Tissue Sample Tissues Transcript Untranslated RNA Validation Visualization base brain cell brain tissue cell type cohesion cost effective data integration data management data portal epigenome epigenomics experimental study genetic analysis genetic variant histone modification imaging approach improved large scale data molecular imaging multidisciplinary multimodality multiple omics nervous system disorder neural circuit neurochemistry neuropsychiatric disorder programs promoter single cell analysis success tool transcriptome transcriptomics

项目摘要

Abstract Understanding cell identities and their spatial distributions throughout different regions of the human brain is a fundamental step when trying to integrate physiological, behavioral, neurochemical and molecular data. At present, although major categories of the cell-types present in the human brain have been defined molecularly, the different subtypes within these categories along with their locations are far from understood. Gene expression drives cell programs and states that underlie distinct brain functions. Open chromatin and modified histones mark gene-regulatory elements that control cell type-specific gene expression patterns. Cytosine DNA methylation (mC) is a stable epigenomic signature that persists in post-mitotic cells throughout their lifetime, defining their cellular identity. Single-cell gene expression, open chromatin profiles and DNA methylation assays have been successfully used to identify distinct cell types in an unbiased fashion in heterogeneous tissues including the human brain. This UM1 proposal builds on our earlier successes in mouse brain mapping to produce detailed single-cell multimomic and spatial cell maps at the single-cell level across 100 anatomically defined regions in the human brain. Profiling human brain samples will permit the discovery of unique gene expression patterns for each molecularly-defined cell type, identify their spatial organization, and their specific non-coding DNA regulatory regions. Multi-modal integration between epigenomic and transcriptomic signatures will allow the identification of new cell types and unique cell-type markers that will rapidly be made available to the entire community. This UM1 project will also provide new tools for genetic access of previously inaccessible brain regions as well as facilitate the functional analysis of genetic variants associated with neuropsychiatric and neurological disorders.

抽象的了解细胞身份及其在人脑不同地区的空间分布是一个试图整合生理，行为，神经化学和分子数据时的基本步骤。在目前，尽管人脑中存在的细胞类型的主要类型已被定义这些类别中的不同子类型及其位置远非理解。基因表达驱动细胞程序，并指出具有不同大脑功能的基础。打开染色质和修饰的组蛋白标记控制细胞类型特异性基因表达模式的基因调节元件。胞嘧啶DNA 甲基化（MC）是一种稳定的表观基因组学特征，在其一生中持续存在于有丝质细胞中，定义其细胞身份。单细胞基因表达，开放染色质谱和DNA甲基化测定法已成功用于以异质组织中公正的方式识别不同的细胞类型包括人脑。这个UM1提案建立在我们早期在鼠标脑映射到的成功基础上在100个解剖学上，在单细胞水平上产生详细的单细胞和空间细胞图定义人类大脑中的区域。分析人脑样品将允许发现独特的基因每种分子定义的细胞类型的表达模式，识别其空间组织及其特定非编码DNA调节区域。表观基因组和转录组特征之间的多模式整合将允许识别新的单元格类型和独特的单元格标记，这些标记将迅速提供给整个社区。该UM1项目还将为以前无法访问的遗传获取提供新的工具大脑区域以及促进与神经精神病学相关的遗传变异的功能分析神经系统疾病。