Decoding gemome instability by combining accurate mapping and predictive modeling

描述(申请人提供)：尽管有许多关于DNA双链断裂(DSB)形成机制的研究，但我们对它们的了解非常不完整。到目前为止，DSB的形成只在特定的基因座上得到了广泛的研究，但在很大程度上还没有在全基因组水平上进行探索。这是因为缺乏系统的全基因组研究来客观地测试和比较所提出的DSB形成机制，以及缺乏通过直接DSB标记获得的高分辨率DSB全基因组图谱来验证它们。与合作者合作，我们最近开发了一种原位标记DSB的方法，然后进行深度测序(BLSE)，并使用它在人类细胞中绘制DSB的图谱，分辨率比以前获得的高2-3个数量级。我们的结果表明，假设驱动的分析高分辨率基因组区域的BLISE可以帮助探索基因组不稳定的基础全基因组。我们发现DSB最常发生在形成DNA二级结构或高度转录的区域。两者都可能导致复制分叉的崩溃，最终导致DSB-前者通过DNA二级结构上的分叉停滞，后者由于复制-转录碰撞(RTC)或RNA-DNA杂交体(R-环)的形成。因此，我们假设大多数观察到的DSB可以归因于至少三个主要的、非互斥的内源性原因之一：1)DNA二级结构上的停滞或2)RTC，或3)共转录R环的形成。我们将通过追求三个具体目标来检验这一假说并阐明这些机制的相对重要性：1)量化DNA二级结构上的分叉失速对DSB形成的影响；2)估计RTC对DSB形成的贡献；以及3)阐明R环对DSB形成的影响。本申请中提出的工作主要是计算性的。该项目的主要创新在于开发了预测模型，该模型将首次全面评估在不同条件下人类细胞中分叉失速、RTC和R环形成对基因组不稳定性的贡献。为了构建这样的模型，并收集数据以告知和验证它们，我们将结合几种尖端的计算和分子生物学方法。计算方法将主要来自理论物理，实验方法将包括DNA梳理、CHIP-SEQ和用于R-环检测的新的DIP-SEQ方法。我们期待我们的研究将揭示人类细胞中DSB形成机制和背景的复杂和细微差别的图景，并将该领域从研究DSB的个别例子转移到实现对DSB形成机制的系统的、全基因组的理解，并量化它们的相对重要性。这样的进展最终应该允许将DSB定位信号用于诊断和预后目的。我们还将为超越DNA修复和复制领域的未来研究提供强大的软件工具、实验方法和丰富的数据集。

DESCRIPTION (provided by applicant): Despite many studies on the mechanisms of DNA double-strand breaks (DSB) formation, our knowledge of them is very incomplete. To date, DSB formation has been extensively studied only at specific loci but remains largely unexplored at the genome-wide level. This is owing to the lack of systematic, genome-wide studies to objectively test and compare the proposed mechanisms of DSB formation, as well as the lack of high- resolution genome-wide maps of DSBs obtained by direct DSB labeling to validate them. Working with collaborators, we have recently developed a method to label DSBs in situ followed by deep sequencing (BLESS), and used it to map DSBs in human cells with a resolution 2-3 orders of magnitude better than previously achieved. Our results show that hypothesis-driven analysis of high-resolution genomic regions identified by BLESS can help explore the basis of genomic instability genome-wide. We discovered that DSBs happen most often in regions that form DNA secondary structures or are highly transcribed. Both may cause collapse of the replication fork, eventually leading to DSBs - the former via fork stalling on DNA secondary structures, the latter because of replication-transcription collisions (RTCs) or formation of RNA-DNA hybrids (R-loops). We therefore hypothesize that the majority of the observed DSBs can be attributed to at least one of three main, non-mutually exclusive endogenous causes: collapse of fork due to 1) stalling on DNA secondary structures or 2) RTCs, or 3) co-transcriptional R-loop formation. We will test this hypothesis and clarify the relative importance of these mechanisms by pursuing three Specific Aims: 1) Quantify how fork stalling on DNA secondary structures impacts DSB formation; 2) Estimate the contribution of RTCs to DSB formation; and 3) Clarify the influence of R-loops on DSB formation. The work proposed in this application is primarily computational. The main innovation of this project lies in developing predictive models that will provide the first comprehensive evaluation of the contributions of fork stalling, RTCs and R-loop formation to genomic instability in various conditions in human cells. To construct such models - and to gather the data both to inform and verify them - we will combine several cutting-edge computational and molecular biology methods. The computational methods will be mostly adapted from theoretical physics and experimental methods will include DNA combing, ChIP-Seq and novel DRIP-Seq method for R-loops detection in addition to our BLESS method. We expect that our research will reveal a complex and nuanced picture of the mechanisms and context of DSB formation in human cells and move the field from studying individual examples of DSBs to achieving a systematic, genome-wide understanding of DSB formation mechanisms, and quantification of their relative importance. Such progress should eventually allow use of DSB localization signatures for diagnostic and prognostic purposes. We will also provide powerful software tools, experimental methods and rich datasets for future studies going beyond the DNA repair and replication fields.