Understanding spontaneous mitotic crossover by single-cell multi-omics

项目摘要/摘要 同源重组(HR)对于修复DNA双链断裂(DSB)非常重要，因此是一种 胚胎发育、减数分裂和抑制肿瘤发生的基本过程。人力资源也可能是一把双刃剑 剑：未修复的断裂会导致细胞死亡；人力资源的错误，特别是交叉类型的错误，可能会导致 广泛的基因组重排。而HR在诱导DSB修复过程中的生化过程 已通过各种方法阐明，关于自发性HR仍然存在两个关键差距：1)病变驱动 自发的有丝分裂HR(例如，除了DSB之外，单链缺口启动的复制中的模板切换 还可以促进HR)；以及2)决定HR是否无差错的HR合作伙伴选择。两个差距 是相互关联的，因为HR伴侣的选择可能取决于起始病变的类型。是什么决定了 HR是否没有错误是一个基本的问题，什么是管理基因组完整性的。一个主要的技术障碍 缺乏可扩展的、全基因组的工具来研究许多突变体中罕见的自发HR事件。要扩大规模 YJ2。在全基因组HR图谱的努力下，我开发了SCI-L3，它使单细胞的线性扩增成为可能 可扩展到1 M个细胞的基因组，使每个突变体能够生成数百个单细胞全球HR图 成千上万的变种人。此外，基因分析需要检测基因组中的“伤疤”作为修复的痕迹(例如， 在癌症突变特征研究中)，在相同的姐妹染色单体之间错失99%的无差错HR。 因此，迫切需要无偏见的全球检测方法，既能检测突变的HR，又能检测无差错的HR。我最近 通过开发SCI-L3-Strand-seq作为第一个可伸缩的人力资源映射工具，解决了这一差距 姐妹染色单体。我们的中心愿景是确定自发的有丝分裂交叉如何导致基因组 通过可扩展的单细胞分析进行重排。在区域1中，我们将使用SCI-L3来探索完整的突变空间 在杂交酵母二倍体中。通过以集合的方式在所有单个突变体中生成HR图(160个单细胞HR MAP/6,000个突变体)，我们可以同时测试和生成数千个关于 不同的损伤和途径在全基因组范围内驱动不同类型的基因组不稳定事件。在区域2中，我们 关注HR是否没有错误的决定因素：HR伴侣选择等位基因姐妹染色单体、等位基因 同源和非等位基因重复。使用SCI-L3-Strand-Seq，我们建议映射所有七类交叉 两个系统的结果：哺乳动物细胞系和小鼠胚胎。在细胞系中，我们将在全基因组范围内进行研究 在野生型和数百人中无错误和突变HR结果的分布 人力资源相关基因的扰动，以确定影响人力资源伴侣选择的因素，包括(表观)基因组 背景、3D基因组组织和HR基因敲除。我们还将在体内开发SCI-L3-Strand-Seq/RNA 共同分析小鼠胚胎HR伴侣选择中的细胞类型变异。总而言之，这项建议旨在 有丝分裂交叉结果的成本效益、大规模并行和全基因组作图 通过开发和应用先进的单细胞多组学工具，研究遗传扰动和细胞类型。

PROJECT SUMMARY/ABSTRACT Homologous recombination (HR) is important for repairing DNA double strand breaks (DSB), and thus is an essential process in embryonic development, meiosis and suppressing tumorigenesis. HR can also be a doubleedged sword: unrepaired breaks lead to cell death; errors by HR, particularly the crossover type, can cause extensive genome rearrangements. While the biochemical process of HR in the repair of an induced DSB has been elucidated by various methods, two critical gaps remain regarding spontaneous HR: 1) the lesions driving spontaneous mitotic HR (e.g. in addition to DSBs, template switching in replication initiated by single-strand nicks can also promote HR); and 2) HR partner choice that determines whether HR is error-free or not. The two gaps are inter-related as HR partner choice could depend on the types of initiating lesions. What determines whether HR is error-free or not is a fundamental question of what governs genome integrity. A maior technical roadblock is the lack of scalable, genome-wide tools for studying rare spontaneous HR events in many mutants. To scale YJ2. genome-wide HR mapping efforts, I developed sci-L3, which enables linear amplification of single-cell genomes that scales to 1 M cells, enabling generating hundreds of single-cell global HR maps per mutant for thousands of mutants. Moreover, genetic assays require detecting "scars" in the genome as traces of repair (e.g. in cancer mutational signature studies), which miss 99% of error-free HR between identical sister chromatids. There is thus a critical need for unbiased global assays that detect both mutational and error-free HR. I recently addressed this gap by developing sci-L3-Strand-seq as the first scalable mapping tool for HR between identical sister chromatids. Our central vision is to determine how spontaneous mitotic crossovers cause genome rearrangements by scalable single-cell assays. In Area1, we will use sci-L3 to explore the full mutant space in hybrid yeast diploids. By generating HR maps in all the single mutants in a pooled manner (160 single-cell HR maps/mutant for 6,000 mutants), we can simultaneously test and generate thousands of hypotheses regarding different lesions and pathways that drive different types of genome instability events genome-wide. In Area2, we focus on a deciding factor for whether HR is error-free or not: HR partner choice of allelic sister chromatid, allelic homolog and non-allelic repeats. With sci-L3-Strand-seq, we propose to map all the seven classes of crossover outcomes in two systems: mammalian cell lines and mouse embryos. In cell lines, we will investigate genomewide distributions of both error-free and mutational HR outcomes in the wild-type as well as hundreds of perturbations of HR-related genes to determine factors affecting HR partner choice including (epi)genomic contexts, 3D genome organization and HR gene knockdown. We will also develop in vivo sci-L3-Strand-seq/RNA co-assay to dissect cell-type variation in HR partner choice in mouse embryos. In sum, this proposal pursues cost-effective, massively parallel and genome-wide mapping of mitotic crossover outcomes as functions of genetic perturbations and cell types by developing and applying advanced single-cell multi-omics tools.