Regulation of mammalian genome architecture and mobility

在这个项目中，我们计划研究哺乳动物基因组的结构和流动性。我们和其他人已经证明，基因组的不同组织水平可以在基因组复制过程中被可视化为复制子和复制子簇，可能分别对应于DNA环和Mbp拓扑相关结构域（TADs）。这将使我们能够研究不同的表观遗传状态和不同的亚核空间定位模式如何影响基因组结构和迁移。此外，我们将比较来自不同细胞类型和哺乳动物物种的数据，多能细胞和体细胞，并将利用缺乏已知表观遗传/染色质因子或药物抑制的细胞来探索潜在的调节因子。最后，我们将研究基因组迁移是否受到基因组代谢的影响。将开发基于深度学习的自动化图像分析的新型计算方法，用于准确定量染色质高阶结构及其基于不同分辨率水平的显微镜数据的流动性。这项工作应该提供关于哺乳动物基因组的组织和流动性以及这如何调节或被基因组过程调节的见解。

In this project, we plan to investigate the architecture and mobility of the mammalian genome. We and others have shown that different levels of organization of the genome can be visualized during duplication of the genome as replicons and clusters thereof, likely corresponding to DNA loops and Mbp topologically associated domains (TADs), respectively. This will now allow us to investigate how different epigenetic states and different subnuclear spatial localization patterns impact genome architecture and mobility. We will additionally compare data from different cell types and mammalian species, pluripotent versus somatic cells, and will probe potential regulators using cells deficient on known epigenetic/chromatin factors or pharmacological inhibition. Finally, we will investigate whether genome mobility is affected by genome metabolism. Novel computational methods for automated image analysis based on deep learning will be developed for accurate quantification of the chromatin higher-order structures and their mobility based on microscopy data at different resolution levels. This work should provide insights on the organization and mobility of the mammalian genome and how this regulates or is regulated by genomic processes.