Single cell transcriptional and epigenomic atlas of the macaque brain across the lifespan

猕猴整个生命周期的单细胞转录和表观基因组图谱

• 批准号: 10248566
• 负责人: MICHAEL L PLATT
• 金额: $ 160.81万
• 依托单位: UNIVERSITY OF WASHINGTON
• 依托单位国家: 美国
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-09-17 至 2023-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10248566
• 关键词: ATAC-seq; Adult; Age; Anatomy; Animal Model; Animals; Area; Atlases; Biological Models; Brain; Brain Diseases; Brain region; Cell Nucleus; Cell physiology; Cells; Cercopithecidae; Chromatin; Communities; Complex; Data; Data Set; Development; Disease; Epigenetic Process; Etiology; Exhibits; Female; Freezing; Future; Gene Expression Profiling; Genes; Genetic Transcription; Human; Individual; Intervention; Island; Longevity; Macaca; Macaca mulatta; Maps; Methods; Molecular; Molecular Analysis; Molecular Profiling; Mus; Neurobiology; Neurodevelopmental Disorder; Neurophysiology - biologic function; Organ; Population; Population Research; Primates; Protocols documentation; Puerto Rico; Research; Research Personnel; Resolution; Resources; Sample Size; Sampling; Social Behavior; Structure; Study models; Surveys; System; Variant; biobank; brain cell; brain tissue; cell type; cognitive function; combinatorial; computational pipelines; cost; epigenetic profiling; epigenome; epigenomics; experimental study; fly; gene expression database; indexing; male; neurobehavioral; neuropsychiatric disorder; new technology; nonhuman primate; novel; sample collection; sex; social group; transcriptome; transcriptome sequencing

ABSTRACT / SUMMARY New technologies are enabling molecular profiling of single brain cells at remarkable throughput. However, these new methods have yet to be extensively applied to the brains of model organisms that bridge the evolutionary distance between mouse and human, including the most common nonhuman primate model system - the rhesus macaque. Here we propose to generate an anatomically resolved, single cell atlas of the epigenome (5.5 million cells) and transcriptome (11 million cells) of the rhesus macaque brain. We will apply two methods, recently developed in our labs, that rely on “combinatorial indexing” to cost-effectively profile the epigenomes (sci-ATAC-seq) and transcriptomes (sci-RNA-seq) of large numbers of cells or nuclei. As our first aim, we will generate high resolution, single cell epigenetic and transcriptional atlases of one male and one female rhesus macaque brain. Specifically, we will profile chromatin accessibility in 750,000 nuclei (sci-ATAC- seq) and transcription in 1,500,000 nuclei (sci-RNA-seq) from each of two macaque brains (for a total of 4.5 million cells). These will be obtained from 25 anatomically dissected brain regions (30,000 sci-ATAC-seq and 60,000 sci-RNA-seq profiles per region per brain). As our second aim, we will extend these atlases to span the primate lifespan. Specifically, we will perform single cell epigenetic and transcriptional profiling of the brains of 50 additional rhesus macaques (25 regions per brain; 3,200 sci-ATAC-seq and 6,400 sci-RNA-seq profiles per individual/region, for a total of 12 million molecularly profiled cells). This large sample size will allow us to characterize natural variation in chromatin accessibility and transcription within each cell type, between individuals, sexes, and across the natural lifespan of rhesus macaques. At 16.5 million cells, our rhesus macaque brain atlas will comprise the largest transcriptional and epigenomic single cell dataset of any primate organ to date. Our data will be rapidly shared with BICCN and the broader community. We anticipate it will be an essential resource, complementary to other efforts, for identifying the distribution and function of key cell types across the primate brain, allowing for the development of cell type- and region-specific molecular interventions that will help us understand brain function and the etiology, and potentially the treatment, of brain disorders.

摘要/摘要 新技术正在以惊人的吞吐量实现单个脑细胞的分子图谱。然而， 这些新方法尚未广泛应用于连接 老鼠和人之间的进化距离，包括最常见的非人类灵长类动物模型 系统--恒河猴。在这里，我们建议生成一个解剖分解的，单细胞图谱 猕猴脑的表观基因组(550万个细胞)和转录组(1100万个细胞)。我们会申请 我们的实验室最近开发了两种方法，它们依赖于“组合索引”来经济高效地描述 大量细胞或细胞核的表观基因组(SCI-ATAC-SEQ)和转录体(SCI-RNA-SEQ)。作为我们的第一个 目的，我们将生成高分辨率的单细胞表观遗传和转录图谱 雌性恒河猴的大脑。具体地说，我们将描述75万个细胞核中染色质的可及性(SCI-ATAC- 序列)和转录(SCI-RNA-SEQ)，从两个猕猴的脑(总共4.5个)的每一个核中转录 百万个细胞)。这些数据将从25个解剖的大脑区域(30,000个SCI-ATAC-SEQ和 每个大脑每个区域60,000个SCI-RNA-SEQ图谱)。作为我们的第二个目标，我们将扩展这些地图集，以跨越 灵长类动物的寿命。具体地说，我们将对脑部进行单细胞表观遗传学和转录图谱分析 增加50只恒河猴(每个大脑25个区域；每个3,200个SCI-ATAC-SEQ和6,400个SCI-RNA-SEQ图谱 个人/地区，总共有1200万个分子图谱细胞)。如此大的样本量将使我们能够 描述每种细胞类型之间染色质可及性和转录的自然变化 个体、性别和恒河猴的自然寿命。有1650万个细胞，我们的恒河猴 猕猴脑图谱将包含灵长类动物中最大的转录和表观基因组单细胞数据集 到目前为止的器官。我们的数据将迅速与BICCN和更广泛的社区共享。我们预计这将是 作为其他工作的补充，用于确定关键细胞的分布和功能的基本资源 灵长类动物大脑中的各种类型，允许细胞类型和区域特定的分子的发展 干预措施将帮助我们了解大脑的功能和病因，以及潜在的治疗方法 精神错乱。