Defining the epigenetic landscape at single cell resolution

以单细胞分辨率定义表观遗传景观

• 批准号: 9757785
• 负责人: Andrew Adey
• 金额: $ 38.23万
• 依托单位: OREGON HEALTH & SCIENCE UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-08-01 至 2022-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9757785
• 关键词: Biological Sciences; Catalogs; Cell physiology; Cells; Chromatin; Communities; Complex; DNA Methylation; Development; Disease; Epigenetic Process; Equilibrium; Equipment; Event; Exhibits; Gene Expression Profiling; Genetic Transcription; Genome; Goals; Individual; Logic; Methods; Organism; Phenotype; Population; Property; Regulatory Element; Research; Resolution; Role; Structure; System; Technology; Tissues; Variant; base; cell type; cost effective; epigenome; epigenomics; genome-wide; tool

PROJECT SUMMARY The epigenetic landscape is driven by thousands of properties influencing transcription and defining cell state and function. This landscape is established and maintained by a complex configuration of dozens of epigenetic marks and properties that continually influence one another. When the balance is disrupted the result can be the programmed transition to a new state, such as in development, or the progression into a disease state. We aim to apply systems-based logic to understand the most basic circuitry of a cell and how the configuration of that circuitry locks it in place in its functional role, or drives its differentiation. It has long been established that the smallest functional unit of an organism or tissue is the cell; however the majority of research is carried out at the tissue level by pooling thousands to millions of cells and assuming homogeneity. This strategy results in the obfuscation of latent cell subtypes, for which dozens may be present in any individual population, as has been revealed by new advances in single cell transcriptional profiling. We have developed a platform for assessing multiple epigenomic properties genome-wide at the single cell level in high throughput. This platform does not require specialized equipment, is inexpensive, and is highly robust and versatile. We plan to continue the development of this platform to profile active regulatory elements and genome structural variation in single cells, and to adapt the technology to interrogate DNA methylation, chromatin organization, and other epigenetic properties. In addition to our aims of distributing these tools to broadly benefit the life sciences community, we will apply these methods to catalogue epigenomic cell subtypes, with a focus on populations that exhibit strong evidence for the presence of latent subpopulations, and to chart the precise ordering of events during an epigenomic reprograming cascade. These efforts will not only be of broad use to the life sciences community, but allow us to ascribe causal relationships between factors that may ultimately impart phenotypic consequences such as the initiation of a disease state.

项目摘要 表观遗传景观是由数千个影响转录和定义细胞状态的特性驱动的 和功能。通过数十个表观遗传的复杂构型建立和维护此景观 不断影响彼此的标记和属性。当余额破坏时，结果可能是 编程的过渡到新状态，例如发育或发展为疾病状态。我们 旨在应用基于系统的逻辑以了解单元格的最基本电路以及如何配置 该电路将其锁定在其功能作用上，或者驱动其分化。长期以来已经确定 生物体或组织的最小功能单位是细胞。但是大多数研究是进行的 在组织水平上，通过将数千至数百万个细胞汇总并假设同质性。此策略导致 潜在细胞亚型的混淆，在任何个体中可能存在数十种，如 单细胞转录分析的新进展揭示了。我们已经开发了一个平台 在高吞吐量中评估单细胞水平的多种表观基因组特性。这个平台 不需要专门的设备，价格便宜，并且非常健壮且通用。我们计划继续 该平台的开发介绍了单个平台的主动调节元素和基因组结构变化 细胞，并适应该技术以询问DNA甲基化，染色质组织和其他 表观遗传特性。除了我们分发这些工具以广泛利益生命科学的目标外 社区，我们将将这些方法应用于分类的表观基因组细胞亚型，重点是种群 这表明存在潜在亚群的有力证据，并绘制了确切的排序 表观基因组重编程级联反应期间的事件。这些努力不仅将广泛使用 科学社区，但允许我们将因果关系归因于可能最终赋予的因素 表型后果，例如疾病状态的启动。