Decoding Genome Instability by Combining Accurate Mapping and Predictive Modeling

摘要 DNA双链断裂（DSB）是最致命的DNA损伤形式，并导致衰老和癌症。主 自发DSB的来源是复制应激，即DNA复制中的畸变导致减慢或停滞 复制的叉子。复制应激可以直接或间接引起DSB，细胞对它的反应是 通常是异质的，这导致难以解释的DSB模式。为了克服这一挑战，我们 将使用计算机模拟来分析DSB数据并推断DSB创建的潜在机制。我们将 （1）i-BLESS：最敏感的技术，并在此基础上扩展我们在上一个资助期开发的技术： DSB检测方法，允许在100，000个细胞中检测1个DSB;（2）定量DSB测序：唯一的 允许对绝对DSB频率（DSB/细胞）进行精确的全基因组测量的方法;以及（3） DNA复制的大规模计算机模拟，准确地复制单细胞和 全人口数据。具体来说，我们将使用创新的计算方法和 目的：1）阐明DNA复制的时空调控机制 以及它的干扰如何导致复制压力。2)阐明并量化复制压力的后果， 3）表征由以下引起的DSB的细胞群体分布的异质性： 复制应力和推断其潜在的机制。我们研究的大规模将使我们能够把每一个 将个别结果纳入所取得的所有其他结果的更广泛背景，从而加深对它的解释， 允许对获得的DSB景观和推断的调节复制的途径进行分类。采取 总之，我们的研究结果将导致对引起和预防的机制的系统级理解 复制应力和DSB。我们的项目将通过量化基因组不稳定性的研究提高到一个新的水平 复制压力的机制以及它们如何导致DSB。我们的工作还将提供方法和 计算工具，以进一步研究基因组的不稳定性，并铺平道路，利用这些知识来指导 治疗决定。

ABSTRACT DNA double-strand breaks (DSBs) are the most lethal form of DNA damage and drive aging and cancer. A main source of spontaneous DSBs is replication stress, i.e. aberrations in DNA replication leading to slowing or stalling of replication forks. Replication stress can cause DSBs both directly and indirectly, and cells’ reaction to it is often heterogeneous, which leads to DSB patterns that are difficult to interpret. To overcome this challenge, we will use computer simulations to analyze DSB data and infer underlying mechanisms of DSB creation. We will build on and expand techniques we developed in the previous funding period: (1) i-BLESS: the most sensitive DSB detection method, allowing detection of 1 DSB in 100,000 cells; (2) quantitative DSB sequencing: the only approach that allows precise genome-wide measurement of absolute DSB frequencies (DSBs/cell); and (3) Repli-Sim: massive computer simulations of DNA replication that accurately reproduce both single-cell and population-wide data. Specifically, we will use a combination of innovative computational methods and experiments in the following Aims: 1) Elucidate the mechanisms of spatiotemporal regulation of DNA replication and how its disturbance causes replication stress. 2) Clarify and quantify consequences of replication stress and classify resulting DSBs 3) Characterize heterogeneity of cell population distribution of DSBs resulting from replication stress and infer its underlying mechanisms. The large-scale of our study will allow us to put each individual result into much broader context of all other results obtained, thus deepening its interpretation and allowing for classification of obtained DSB landscapes and inferred pathways regulating replication. Taken together, our results will lead to a system-level understanding of the mechanisms that cause and prevent replication stress and DSBs. Our project will raise the study of genomic instability to a new level by quantifying the mechanisms of replication stress and how they lead to DSBs. Our work will also provide methods and computational tools to further study genome instability and pave the way to use this knowledge to guide therapeutic decisions.