RNA-guided Genome Rearrangement: Experiments Coupled with Discrete Models

描述（由申请人提供）：基因组重排发生在进化规模上，以及在广泛的真核细胞分化的发育规模上。即使在癌症中，在体细胞谱系中也经常观察到戏剧性的DNA重排。本项目研究基因组重排事件，使用纤毛虫作为模式生物，因为它们在档案种系核向专门从事基因表达的体细胞核的分化过程中经历了大规模的基因组重排。正如pi最近显示的那样，协调这一组装过程的一般机制是由母体RNA模板指导的，母体RNA模板可以通过具有刚性4价顶点的空间图来建模，作为重组时DNA的物理表示，顶点的平滑模拟了实际的重组。本项目通过4个具体目标，将实验和理论发现穿插在一起，相互加强。了解rna引导DNA重排的基本生物学原理，并测试特定蛋白质在重排过程中的作用。2. 研究和模拟复杂的基因组重排，如重叠的基因。3. 比较不同物种之间的基因组重排图，并开发数学工具来识别不同物种基因组重排之间的异同和解读途径。4. 基于计算和分析基因重组途径的结和（空间）图论，发展数学技术来识别和测量重排过程的结构模式和复杂性。本研究将在全基因组范围内研究基于rna的DNA重排的基本生物学和理论，这将对基因解聚过程和更广泛地影响重组的因素提供深刻的见解。从理论上讲，利用空间图来模拟DNA分子在重组时刻的三维结构，并应用了结理论的方法，如多项式不变量、连接和属范围。

DESCRIPTION (provided by applicant): Genome rearrangements occur on an evolutionary scale, as well as on a developmental scale in a wide range of differentiating eukaryotic cells. Even in cancer, dramatic DNA rearrangements are frequently observed in somatic cell lineages. This project studies genome rearrangement events using ciliates as model organisms because they undergo massive genome rearrangement during differentiation of an archival germline nucleus into a somatic nucleus that specializes in gene expression. The general mechanism that orchestrates this process of assembly, as recently shown by the PIs, is guided by maternal RNA templates that can be modeled by spatial graphs with rigid 4-valent vertices as a physical representation of the DNA at the time of recombination, and smoothing of the vertices models the actual recombination. The project interlaces experimental and theoretical findings with their mutual reinforcement through 4 specific aims: 1. Understand basic biology of RNA-guided DNA rearrangement and test the role of specific proteins in the rearrangement process. 2. Examine and model unscrambling of complex genome rearrangements, such as overlapping genes. 3. Compare the genome rearrangement maps between different species, and develop mathematical tools for identifying the similarities and differences between genome rearrangements and unscrambling pathways in different species. 4. Develop mathematical techniques to identify and measure structural patterns and complexities of rearrangement processes based on knot and (spatial) graph theory for computing and analyzing gene recombination pathways. The proposed research investigates the basic biology and theory of RNA-based DNA rearrangements on a genome-wide scale, which may offer tremendous insight into the process of gene descrambling and better understanding of factors that influence recombination more generally. Theoretically, spatial graphs are used to model 3D structures of the DNA molecules at the moment of recombination, and methods from knot theory are applied, such as polynomial invariants, linking, and genus ranges.