In vivo spatiotemporal mapping of genome-wide motions and gene-level transcriptional activity via integrated experimental platform and data-analytical pipeline

总结： 人类基因组高度动态，但其运动原理尚不清楚。在当地， 染色质经历与诸如以下过程相关的不断重塑和重排： 转录、复制和DNA修复。在大的长度尺度上，染色质动力学在微米以上是一致的 和秒。局部基因水平的过程如何促进全核染色质运动仍然是一个未知的问题。 开放的问题。为了解决这个问题，我们的总体方法是映射空间和时间分辨率 染色质动力学在体内哺乳动物细胞的细胞核中，同时将其与运动和 真实的时间的特定基因组位点的转录活性。为此，我们将开发横切工具 将来自物理科学的协同定量方法与最新的 分子生物学和生物化学的技术。我们将建立一个综合的实验和分析 能够在体内真实的实时同时测量核宽和基因特异性运动的平台 (Aim 1）。具体来说，我们将建立一个数据收集和分析管道映射染色质运动 在体内使用位移相关光谱（DCS）的核，同时监测的运动， 通过CRISPR/dCas 9技术可视化基因，并通过新的机器学习辅助算法进行跟踪。在 此外，我们的平台将监测跨细胞核和切换染色质的时空异质性， 跟踪基因的转录活性。利用这个集成平台，我们将解决 基因水平的转录活性如何影响全基因组运动的问题（目标2）。我们将测量 整个基因组的染色质运动和压实图，同时确定 特定基因（MUC 4、IL 6）的局部致密化和移动性作为其转录活性的函数。我们 这些发现将为基因和基因组水平的复杂性和相互关联性描绘一幅新的图景。 动态和空间异质性。最后，我们将扩展这种方法来研究间期染色质 小鼠胚胎干细胞分化前后的动力学和致密化（Aim 3）。通过 将基因水平的活动与全基因组的压缩和运动联系起来，这些结果将具有重要的意义。 阐明染色质动力学在基因调控和表达中的作用。而且这样的 这些知识将为哺乳动物细胞中染色质动力学的机制图像提供框架。

Summary: The human genome is highly dynamic, yet the principles governing its movement are not known. Locally, chromatin undergoes constant remodeling and rearrangement associated with processes such as transcription, replication and DNA repair. At large length scales, chromatin dynamics is coherent over microns and seconds. How the local gene-level processes contribute to nucleus-wide chromatin motions remains an open question. To address this question, our overall approach is to map spatially and temporally resolved chromatin dynamics across the nucleus in mammalian cells in vivo, while connecting it with motion and transcriptional activity of specific genomic loci in real time. To do so, we will develop crosscutting tools integrating synergistically quantitative approaches derived from the physical sciences with the latest techniques from molecular biology and biochemistry. We will build an integrated experimental and analytical platform enabling simultaneous measurements of nucleus-wide and gene-specific motions in real time in vivo (Aim 1). Specifically, we will establish a data collection and analytical pipeline mapping chromatin motions across the nucleus in vivo using displacement correlation spectroscopy (DCS), while monitoring motions of genes visualized by CRISPR/dCas9 technology and tracked via new machine-learning assisted algorithms. In addition, our platform will monitor the spatiotemporal heterogeneity of chromatin across nucleus and toggle transcriptional activity of the tracked genes. Using this integrated platform, we will address the fundamental question of how gene-level transcription activity contributes to genome-wide motions (Aim 2). We will measure maps of chromatin motions and compaction across the whole genome, while simultaneously determining the local compaction and mobility of specific genes (MUC4, IL6) as a function of their transcriptional activity. Our findings will paint a new picture of the complexity and interconnectedness of gene- and genome-level dynamics and spatial heterogeneity. Finally, we will extend this approach to study interphase chromatin dynamics and compaction before and after cell differentiation of mouse embryonic stem cells (Aim 3). By linking gene-level activity to genome-wide compaction and motions, these results will have important implications for elucidating the role of chromatin dynamics in gene regulation and expression. Moreover, such knowledge will provide a framework for a mechanistic picture of chromatin dynamics in mammalian cells.