PARALLEL ANALYSIS OF TRANSCRIPTION AND PROTEIN-DNAINTERACTIONS IN SINGLE CNS CELLS

项目摘要 大脑是身体中最复杂的器官，由数百个分子组成，生理上， 解剖学上不同的细胞最近，已经开发出可以经济有效地测量mRNA的方法， 在数以万计的单细胞丰度，这导致了一场革命， 大脑中新型细胞的分类。但这些方法只能测量基因调控的一个方面 - mRNA水平。为了充分理解在大脑中发挥作用的转录网络， 还绘制了转录因子和染色质修饰剂在无数细胞中的全基因组结合位置， 大脑中存在不同的细胞类型。我们建议开发一种方法，同时映射转录 因子结合并测量来自脑中单个细胞的mRNA丰度。为此，我们将调整我们的 用于测量DNA相互作用蛋白与现有单细胞谱的结合的基于转座子的方法 方法.这项技术，单细胞电话卡，建立在我们以前开发的转座子电话卡 方法，但显着扩展的方法，允许在异质细胞群体中使用，而无需先验 细胞类型的定义我们建议在这里开发新的鼠标线兼容广泛的现有的 小鼠中的资源，以及适用于模型物种的病毒和质粒试剂，并分发这些 对社区的贡献最后，由于我们将开发的工具会生成新类型的数据，因此我们将开发一个用户- 用于数据可视化和分析TF或染色质修饰蛋白结合数据的友好软件 多种细胞类型。如果这些技术要在全球范围内得到广泛应用， 社区我们的主要目标是使转录因子结合和mRNA的平行分析 大脑中数万个单细胞的表达水平。 !

PROJECT SUMMARY The brain is the most complex organ in the body, consisting of hundreds of molecularly, physiologically, and anatomically distinct cells. Recently, methods have been developed that can cost-effectively measure mRNA abundance in tens of thousands of single cells, and this has led to a revolution in the identification and classification of new types of cells in the brain. But these methods only measure one aspect of gene regulation – mRNA levels. To fully understand the transcriptional networks that function in the brain, it will be important to also map the genome-wide binding locations of transcription factors and chromatin modifiers in the myriad of different cell types present in the brain. We propose to develop a method to simultaneously map transcription factor binding and measure mRNA abundance from single cells in the brain. To do so, we will adapt our transposon based methods for measuring the binding of DNA interacting proteins to existing single cell profiling methods. This technology, single-cell Calling Cards, builds on our previously developed transposon Calling Card method, but significantly extends the method allowing use in populations of heterogeneous cells, without a priori definition of cell type. We propose here to develop new mouse lines compatible with the wide range of existing resources in mouse, as well as viral and plasmid reagents applicable across model species, and distribute these to the community. Finally, since the tools we will develop generate new types of data, we will develop a user- friendly software for data visualization and analysis of TFs or chromatin modifying proteins binding data across multiple cell types. Robust resources for analysis are crucial if these technologies are to find broad use in the community. Our primary goal is to enable the parallel analysis of transcription factor binding and mRNA expression levels from tens of thousands of single cells in the brain. !