Lineage-Specific Mechanisms of Cell Cycle Timing Control

项目摘要 几十年来对动物发育和体外人类细胞培养的研究已经产生了许多观察到的严密 细胞周期的持续时间与其特性或其后代的命运之间的关系。这些链接 为理解细胞遗传程序之间的调控关系提供了一个独特的机会 命运和细胞周期的调控，这两个问题都是研究组织发育的中心问题 动态平衡、再生和增殖性疾病，如癌症。线虫线虫秀丽线虫 已经成为研究细胞命运调节和细胞周期控制的强大模型，这是由于它的 基因易驯化，透明的身体和胚胎，以及刻板的细胞谱系。与大多数线虫一样，C. 在同一性别的每个个体中，线虫的体细胞数量是相等的或固定的。细胞在未来的命运 因此，野生动物可以完全根据它的血统历史来确定，我们已经为其制定了血统历史 通过3D时间流逝显微镜进行自动重建的广泛工具和方法。使用线虫 以及导致细胞命运与其谱系的转变的遗传扰动，与 自动化血统追踪和空间转录切分方法，我们将通过以下方式研究其机制 哪个细胞的命运影响干细胞细胞周期的持续时间，以及 细胞周期的持续时间会影响细胞的命运。 本提案中描述的工作代表了一种考虑这些联系的新方法，通过我们的 发现细胞结构的谱系追踪技术和定量方法的发展 血统。以此专业知识以及我们的图像资源和与其他工具的协作为基础 开发人员、理论家和发育生物学家，我们将继续推进最先进的谱系- 解决了后生动物发育的研究。特别是，使用我们在深度学习技术方面的进步来 在转基因仍然不可能的非模式物种中启用免标签自动谱系追踪，或者 困难，我们将利用进化的方法来理解基因网络的设计原理。 在早期胚胎中驱动细胞命运决定和控制细胞周期进程的基因。在接下来的五年里，我们 将在C.完成细胞周期计时和细胞命运之间相互依赖关系的详细描述。 线虫胚胎，在野生型和突变型C. 在细胞命运图案被扰乱的优雅，并完成重建和定量分析 本文报道了日本血吸虫、太平洋血吸虫和中国血吸虫的胚胎谱系。从长远来看，我们计划延长我们的 对这些物种的分子分析也是如此，首先是从盘尾藻开始，将其作为研究 细胞命运控制网络的进化及其与细胞周期调节因子的相互作用。这些洞察力将 对我们理解发展过程具有广泛的价值，我们将建立的资源将 为其他人解决新兴模型系统中的各种问题提供便利。

Project Summary Decades of studying animal development and in vitro human cell culture have produced many observed tight correlations between the duration of a cell’s cycle and its identity or the fates of its progeny. These links represent a unique opportunity to understand the regulatory relationships between genetic programs of cell fate and the regulation of the cell cycle, both central questions in the study of development, tissue homeostasis, regeneration, and proliferative disorders such as cancer. The nematode Caenorhabditis elegans has been a powerful model in which to study the regulation of cell fate and cell cycle control owing to its genetic tractability, transparent body and embryo, and stereotyped cell lineage. Like most nematodes, C. elegans exhibits eutely or a fixed number of somatic cells in each individual of the same sex. Cell fate in the wild-type animal can thus be determined solely on the basis of its lineage history, for which we have developed extensive tools and approaches for automated reconstruction via 3D timelapse microscopy. Using C. elegans and genetic perturbations that result in transformations of cell fate with its lineage, in combination with automated lineage tracing and spatial transcriptomics approaches, we will investigate the mechanisms by which cell fate influences the duration of a stem cell’s cell cycle as well as the mechanisms by which the duration of a cell cycle can influence cell fate. The work described in this proposal represents a novel approach to considering these links, enabled by our development of lineage tracing technologies and quantitative approaches to discovering structure in cell lineages. Building on this expertise, as well as our imaging resources and collaborations with other tools developers, theorists, and developmental biologists, we will continue to advance the state-of-the-art in lineage- resolved studies of metazoan development. In particular, using our advances in deep learning techniques to enable label-free automated lineage tracing in non-model species in which transgenesis remains impossible or difficult, we will leverage an evolutionary approach to understanding the design principles of gene networks that drive cell fate decisions and control cell cycle progression in the early embryo. Over the next five years we will complete detailed characterizations of co-dependencies between cell cycle timing and cell fate in the C. elegans embryo, create a molecular atlas of cell fate and cell cycle regulation in wild type and mutant C. elegans where cell fate patterning is perturbed, and complete the reconstruction and quantitative analysis of the embryonic lineages of S. stercoralis, P. pacificus, and C. angaria. In the long term, we plan to extend our molecular analyses to these species as well, beginning with C. angaria as an attractive model for studying the evolution of cell fate control networks and their interactions with regulators of the cell cycle. These insights will be of broad value to our understanding of developmental processes, and the resources we will establish will facilitate the work of others on diverse problems in emerging model systems.