Understanding spontaneous mitotic crossover by single-cell multi-omics

项目概要/摘要 同源重组（HR）对于修复DNA双链断裂（DSB）是重要的，并且因此是一种有效的方法。 胚胎发育、减数分裂和抑制肿瘤发生的重要过程。HR也可以是双- 锋利的剑：未修复的断裂导致细胞死亡; HR的错误，特别是交叉类型，可能导致 广泛的基因组重排虽然HR在诱导DSB修复中的生化过程 通过各种方法阐明，关于自发性HR仍存在两个关键差距：1） 自发有丝分裂HR（例如，除DSB外，复制中由单链切口引发的模板转换 也可以促进人力资源）;和2）人力资源合作伙伴的选择，决定了人力资源是否是无差错的。的两个间隙 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是否无误是一个决定基因组完整性的基本问题。一个主要的技术障碍 缺乏可扩展的全基因组工具来研究许多突变体中罕见的自发HR事件。按比例 在全基因组HR作图工作的基础上，我开发了sci-L3，它能够线性扩增单细胞 基因组可扩展到100万个细胞，能够为每个突变体生成数百个单细胞全局HR图谱， 成千上万的变种人此外，基因测定需要检测基因组中的“疤痕”作为修复的痕迹（例如， 在癌症突变特征研究中），其错过了相同姐妹染色单体之间99%的无错误HR。 因此，迫切需要无偏倚的全球检测方法，以检测突变和无错误的HR。 通过开发sci-L3-Strand-seq作为第一个可扩展的HR映射工具， 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测定来检测重排。在Area 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。通过以合并的方式在所有单突变体中生成HR图谱（160个单细胞HR 6，000个突变体的地图/突变体），我们可以同时测试并生成数千个关于 不同的病变和途径，驱动不同类型的基因组不稳定性事件全基因组。在区域2中，我们 关注HR是否无差错的决定因素：HR伴侣选择等位基因姐妹染色单体，等位基因 同源物和非等位重复。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，我们将研究基因组- 无错误和突变HR结果在野生型中的广泛分布，以及数百个 HR相关基因的干扰，以确定影响HR伴侣选择的因素，包括（epi）基因组 上下文、3D基因组组织和HR基因敲除。我们还将开发体内sci-L3-Strand-seq/RNA 共测定以剖析小鼠胚胎中HR伴侣选择中的细胞类型变化。总而言之，这项建议力求 有丝分裂交叉结果的成本效益，大规模平行和全基因组作图， 通过开发和应用先进的单细胞多组学工具，

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 double- edged 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 major technical roadblock is the lack of scalable, genome-wide tools for studying rare spontaneous HR events in many mutants. To scale up genome-wide HR mapping efforts, I developed sci-L3, which enables linear amplification of single-cell genomes that scales to 1M 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 genome- wide 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.