High-throughput Single Cell Co-assay of Histone Modifications and Transcriptome

组蛋白修饰和转录组的高通量单细胞联合测定

基本信息

批准号：
10324108
负责人：
Bing Ren
金额：
$ 35万
依托单位：
EPIGENOME TECHNOLOGIES, INC.
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：
2021-09-15 至 2022-08-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/10324108
关键词：
Address Adoption Adult Antibodies Architecture Bar Codes Benchmarking Biological Assay Biomedical Research Biopsy Biopsy Specimen Brain Glioblastoma Cell Nucleus Cells ChIP-seq Chromatin Chromosomes Clinical Collection Communities Complementary DNA Complex DNA DNA Methylation Data Development Disease Gene Expression Gene Expression Profile Gene Expression Profiling Generations Genes Genetic Materials Genetic Transcription Goals Heterogeneity Hippocampus (Brain)Histones Homeostasis Human Individual Joints Label Laboratories Lead Libraries Ligation Malignant Neoplasms Maps Memory Methods Modality Molecular Profiling Mus Nature Nuclear Nuclear RNA Organism Pathogenesis Pathologic Performance Phase Population Procedures Production Proteins Protocols documentation Reaction Reagent Regulator Genes Research Resolution Reverse Transcription Sampling Series Signal Transduction Small Business Technology Transfer Research Techniques Technology Time Tissues Transposase Work base brain cell brain tissue cancer cell cell type combinatorial epigenome epigenomics experimental study frontal lobe histone modification improved multiple omics neoplastic cell next generation novel phase 1 study preservation programs spatiotemporal tool transcription factor transcriptome transcriptome sequencing tumor tumorigenesis virtual

项目摘要

Abstract Epigenome analysis can help dissect the transcriptional regulatory sequences that control spatiotemporal patterns of gene expression during anima development and disease pathogenesis, but a major challenge to epigenome analysis is the heterogeneity of primary tissues. Conventional epigenome assays that take bulk tissues as input only produce population average signals. To address this major bottleneck, we propose to develop an ultra-high throughput single-cell multi-omics method, Paired-Tag, for joint profiling of histone modifications and transcriptome. In preliminary experiments, we have demonstrated the feasibility and utility of this method through analysis of the nuclear transcriptome and multiple histone modifications at single cell resolution in the adult mouse frontal cortex and hippocampus. In the proposed study, we will further optimize the current Paired-Tag protocol and demonstrate its utility in cancer epigenome analysis. If successful, the research would add a major toolkit for the production of cell-type-resolved maps of chromatin state and transcriptome in complex tissues and enable next generation epigenome analysis of tumor samples.

抽象的表观基因组分析可以帮助剖析控制时空的转录调控序列动物发育和疾病发病机制期间基因表达的模式，但一个重大挑战表观基因组分析是原代组织的异质性。传统的表观基因组检测需要大量的时间组织作为输入仅产生群体平均信号。为了解决这个主要瓶颈，我们建议开发一种超高通量单细胞多组学方法 Paired-Tag，用于组蛋白的联合分析修饰和转录组。在初步实验中，我们已经证明了该方法的可行性和实用性。该方法通过分析单细胞的核转录组和多个组蛋白修饰成年小鼠额叶皮层和海马体的分辨率。在拟议的研究中，我们将进一步优化当前的配对标签协议并展示了其在癌症表观基因组分析中的实用性。如果成功的话，研究将添加一个主要工具包，用于生成细胞类型解析的染色质状态图和复杂组织中的转录组，并实现肿瘤样本的下一代表观基因组分析。