Mapping protein signatures to single allele chromatin topologies at genomic resolution

间期染色质在染色体区域、活性区室和非活性区室中分层组织， 拓扑关联域（TADs）。基因表达受调控染色质元件（增强子）控制 和启动子），其结合转录因子并在转录因子边界内相互作用，但不跨越转录因子边界。的最新进展 单细胞生物学已经揭示了染色质拓扑结构和蛋白质中大量细胞间变异性 覆盖尽管TADs似乎在人群水平上描绘了功能单位，但它们的边界只出现在 从细胞的大集合的平均属性。即使在没有边界的情况下， 整体水平。类似地，单细胞ChIP-seq已经揭示了在增强子中具有不同表观遗传特征的亚状态， 干细胞群。但是，目前还没有一种通过阅读蛋白质覆盖率来将拓扑和功能变异联系起来的方法 和表观遗传标记同时从单细胞染色质痕迹。在这里，我们将利用最近的进展， 多重染色质成像和单分子超分辨率显微镜来填补这一空白。在Aim I中，我们将 表征多重染色质成像中序列分辨率和空间精度之间的权衡。我们将 然后使用优化的条件将超分辨蛋白质信号映射到基因组分辨率的染色质拓扑结构。在Aim中 第二，我们将扩展检测的能力，同时检测多种蛋白质的签名。此类组合 在基因组分辨率上的调节元件的蛋白质特征的数据不能通过任何其它单细胞获得 比色法我们将通过对两种稳定的基因进行作图，进一步表征该检测试剂盒在挑战性条件下的性能。 整合的，广泛的组蛋白修饰和瞬时结合序列特异性转录因子， 未结合部分染色质。使用计算聚类策略，我们将通过染色质拓扑结构对数据进行分层 以确定结构变异是否由特定的蛋白质因子驱动，例如转录因子，其协调长- 射程增强剂相互作用。最后，我们将建立协议和技术解决方案，以加快收购， 包括100 - 1000个单等位基因的统计学上有意义的数据集的处理和可视化。所得 数据集将提供前所未有的深入了解细胞间染色质变异的分子机制 拓扑结构，并作为一个强大的假设发生器，研究单细胞基因组结构-功能 关系。

Interphase chromatin is hierarchically organized in chromosome territories, active and inactive compartments, and topologically associating domains (TADs). Gene expression is controlled by regulatory chromatin elements (enhancers and promoters) that bind transcription factors and interact within, but not across TAD boundaries. Recent advances in single cell biology have revealed a tremendous amount of cell-to-cell variability in both chromatin topology and protein coverage. Even though TADs appear to delineate functional units at the population level, their boundaries only emerge as average properties from large ensembles of cells. TAD-like structures persist even in the absence of boundaries at the ensemble level. Similarly, single cell ChIP-seq has revealed sub-states with distinct epigenetic profiles at enhancers in a population of stem cells. But no assay exists to link topological and functional variability by reading out protein coverage and epigenetic signatures simultaneously from single cell chromatin traces. Here, we will leverage recent advances in multiplexed chromatin imaging and single molecule super-resolution microscopy to fill in this gap. In Aim I, we will characterize the tradeoff between sequence resolution and spatial precision in multiplexed chromatin imaging. We will then use optimized conditions to map super-resolved protein signal to chromatin topologies at genomic resolution. In Aim II, we will extend the capabilities of the assay to detect multiple protein signatures simultaneously. Such combinatorial data on protein signatures of regulatory elements at genomic resolution is not available through any other single cell assay. We will further characterize the performance of the assay under challenging conditions by mapping both stably integrated, widespread histone modifications and transiently binding sequence-specific transcription factors with a sizable unbound fraction to chromatin. Using computational clustering strategies, we will stratify the data by chromatin topology to determine if structural variation is driven by specific protein factors such as transcription factors that orchestrate long- range enhancer interactions. Finally, we will establish protocols and technological solutions to accelerate acquisition, processing, and visualization of statistically meaningful datasets comprising 100s-1000s of single alleles. The resulting datasets will provide unprecedented insight into the molecular mechanisms underlying cell-to-cell variability in chromatin topology and serve as a powerful hypothesis generator for investigating single cell genome structure-function relationships.