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/总结 新技术使单脑细胞的分子分析具有显著的通量。然而，在这方面， 这些新方法还没有被广泛应用于模型生物的大脑， 小鼠和人类之间的进化距离，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学上分辨的，单细胞的图集， 恒河猴大脑的表观基因组（550万个细胞）和转录组（1100万个细胞）。我们将应用 两种方法，最近在我们的实验室开发，依赖于“组合索引”，以成本效益的概况， 大量细胞或细胞核的表观基因组（sci-ATAC-seq）和转录组（sci-RNA-seq）。作为我们的第一 目的，我们将产生一个男性和一个男性的高分辨率，单细胞表观遗传和转录图谱， 雌性恒河猴的大脑具体地说，我们将在750，000个细胞核中分析染色质可及性（sci-ATAC-2000）。 seq）和在来自两只猕猴脑中的每一个的1，500，000个核中的转录（sci-RNA-seq）（总共4.5 百万个细胞）。这些将从25个解剖学解剖的脑区域（30，000个sci-ATAC-seq和30，000个sci-ATAC-seq）获得。 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， 灵长类动物的寿命具体来说，我们将对大脑进行单细胞表观遗传和转录分析， 另外50只恒河猴（每个大脑25个区域;每个大脑3，200个sci-ATAC-seq和6，400个sci-RNA-seq图谱） 个体/区域，总共1200万个分子轮廓细胞）。这一大样本量将使我们能够 表征每种细胞类型内染色质可及性和转录的自然变化， 个体、性别和恒河猴的整个自然寿命。我们的恒河猴有一千六百五十万个细胞 猕猴脑图谱将包括任何灵长类动物中最大的转录和表观基因组单细胞数据集 器官至今我们的数据将迅速与BICCN和更广泛的社区共享。我们预计， 一个重要的资源，补充其他努力，为确定分布和功能的关键细胞 灵长类动物大脑中的细胞类型，允许细胞类型和区域特异性分子的发展 干预措施，这将有助于我们了解脑功能和病因，并可能治疗，脑 紊乱