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Ultra-high Throughout Single Cell Multi-omic Analysis of Histone Modifications and Transcriptome in Mouse and Human Brains

小鼠和人脑组蛋白修饰和转录组的超高通量单细胞多组学分析

基本信息

批准号：
10369242
负责人：
M MARGARITA BEHRENS
金额：
$ 319.96万
依托单位：
UNIVERSITY OF CALIFORNIA, SAN DIEGO
依托单位国家：
美国
项目类别：
财政年份：
2021
资助国家：
美国
起止时间：
2021-09-13 至 2024-09-12
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/10369242
关键词：
Address Adult Atlases Automation BRAIN initiative Bar Codes Benchmarking Biological Assay Brain Brain region Catalogs Cell Nucleus Cells Censuses Chromatin Complementary DNA Complex Corpus striatum structure DNA Development Epigenetic Process Female Gene Expression Generations Genetic Transcription Goals Hippocampus (Brain)Histones Human Individual Joints Lead Libraries Ligation MFGE8 gene Maps Measures Memory Methods Mus Nuclear Performance Prefrontal Cortex Procedures Production Protocols documentation Publishing RNA Reaction Regulator Genes Research Resolution Reverse Transcription Sampling Series Structure Technology Testing base brain cell cell type combinatorial data resource epigenome frontal lobe histone modification large scale data male methylome multiple omics neural network programs single cell analysis spatiotemporal tool transcriptome

项目摘要

Histone modification carries rich epigenetic information that constitutes a mechanism of cellular memory. Single cell analysis of histone modification in conjunction with transcriptome could help uncover this critical layer of cellular memory and lead to better definition of cell types and states in the brain. Here, we propose to develop an ultra-high throughput method, known as Paired-Tag, for joint profiling of histone modifications and transcriptome in single cells. In preliminary studies, we have demonstrated the feasibility and utility of this method by applying it to the adult mouse frontal cortex and hippocampus. In the proposed research, we will further develop and optimize Paired-Tag to enable automation and support large-scale data production project. Additionally, we will implement a series of quantitative QC metrics to benchmark the performance of the new Paired-Tag procedure against existing Paired-Tag procedures. We will then use the optimized experimental procedure to generate adult mouse brain cell atlas of histone modifications and transcriptome at single cell resolution. We will additionally characterize the dynamic changes in histone modifications and transcriptome at single cell resolution in the mouse brain across multiple developmental stages. Finally, to demonstrate proof of principle of Paired-Tag for analysis of human brains, we will use it to assay the prefrontal cortex (BA46) in adult human brains from 3 males and 3 females.

组蛋白修饰携带丰富的表观遗传信息，构成细胞记忆机制。结合转录组对组蛋白修饰的单细胞分析可以帮助揭示这一关键的细胞记忆层，并导致更好地定义细胞类型和大脑状态。在此，我们建议开发一种超高通量的方法，称为配对标签，用于组蛋白修饰的联合分析和单细胞中的转录组。在初步研究中，我们已经证明了这种方法通过将其应用于成年小鼠额叶皮层和海马体。在这项研究中，我们将进一步开发和优化配对标签，以实现自动化并支持大规模数据生产项目此外，我们将实施一系列定量QC指标，以衡量新的配对标签程序与现有的配对标签程序。然后，我们将使用优化的生成组蛋白修饰和转录组的成年小鼠脑细胞图谱的实验程序单细胞分辨率。我们还将描述组蛋白修饰的动态变化，在小鼠大脑中，跨多个发育阶段的单细胞分辨率的转录组。最后为为了证明配对标签分析人脑的原理，我们将用它来分析前额叶来自3名男性和3名女性的成年人脑中的皮质（BA46）。