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，以及在广泛的分化真核细胞的发育规模上。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。该项目使用纤毛虫作为模式生物来研究基因组重排事件，因为纤毛虫在档案生殖细胞核分化为专门用于基因表达的体细胞核期间经历了大规模的基因组重排。正如PI最近所显示的那样，协调这一组装过程的一般机制是由母体RNA模板指导的，该模板可以通过空间图建模，该空间图具有刚性4价顶点作为重组时DNA的物理表示，并且顶点的平滑模拟了实际的重组。该项目通过4个具体目标将实验和理论研究结果相互加强：1。了解RNA引导的DNA重排的基本生物学，并测试特定蛋白质在重排过程中的作用。2.检查和模型解读复杂的基因组重排，如重叠基因。3.比较不同物种之间的基因组重排图，并开发数学工具，用于识别不同物种基因组重排和解读途径之间的异同。4.发展数学技术，以识别和测量结构模式和基于结和（空间）图论的重排过程的复杂性，用于计算和分析基因重组途径。拟议的研究在全基因组范围内调查基于RNA的DNA重排的基础生物学和理论，这可能会对基因解扰过程提供巨大的洞察力，并更好地理解影响重组的因素。从理论上讲，空间图用于在重组时对DNA分子的3D结构进行建模，并应用结理论的方法，例如多项式不变量，链接和属范围。

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.