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Collaborative Research: Discrete and Topological Models for Template-Guided Genome Rearrangements

合作研究：模板引导基因组重排的离散拓扑模型

基本信息

批准号：
1764366
负责人：
Laura Landweber
金额：
$ 57.03万
依托单位：
Columbia University
依托单位国家：
美国
项目类别：
Continuing Grant
财政年份：
2018
资助国家：
美国
起止时间：
2018-08-01 至 2022-07-31
项目状态：
已结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=1764366&HistoricalAwards=false
关键词：
Collaborative Research Discrete Topological Models

项目摘要

One of the breakthroughs of 21st century science is the precise genome editing that is enabled through RNA templates. The societal impact of understanding template-guided genome rearrangement is potentially enormous, both as a natural phenomenon that, when mis-guided, can lead to disease, and that if harnessed could lead to the next generation of tools for genome editing. This project seeks to learn from both theory and experiments how a mechanism for RNA-templated DNA recombination sculpts the assembly of genetic information in certain species of ciliates, the organisms with the greatest levels of natural genome editing. Through use of high-throughput experimental tools and novel mathematical concepts based on knot theory and discrete mathematics, the project will gain temporal and structural insight into the process of programmed genome reorganization, including genome-wide surveys of DNA-- DNA and DNA--RNA contacts during somatic development in ciliates. The proposed research will impact postdoctoral, graduate and undergraduate education in mathematics, biology, and chemistry, with at least two postdocs, three PhDs and several senior theses expected to result from this project. Because the ciliate Oxytricha undergoes hundreds of thousands of programmed DNA rearrangements during development, more than any other known organism, we use Oxytricha and its close relatives as a tractable lab model to study template-guided genome rearrangements. This project increases our understanding of template-guided chromosomal DNA rearrangements, both during the process of nuclear development and across the evolutionary steps that gave rise to scrambled genomes. Previous studies have shown that the general mechanism that orchestrates this rearrangement process is guided by maternal RNA templates that can be mathematically modeled by spatial graphs, while the rearrangement pathways can be modeled as paths in a directed acyclic graph whose vertices are the spatial graphs. The project approaches the problem through the lens of the intermediate molecules, as well as the higher level interactions that arise during rearrangement, and it will examine both experimentally and theoretically the global rearrangement pathways. Specific aims include: 1. Experimental dissection of the temporal order of events and the formation of DNA-- DNA and DNA--RNA interactions during genome rearrangement. 2. Build mathematical methods for genome rearrangements using graph based descriptions of the changes in the intermediates. 3. Develop mathematical models to measure differences in underlying scrambling patterns, as well as differences in possible rearrangement pathways between different species. 4. Initiate mathematical techniques based on graph theory, knot theory and algebraic topology that provide understanding of the structural patterns of the genome unscrambling pathways.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

21世纪世纪科学的突破之一是通过RNA模板实现的精确基因组编辑。理解模板引导的基因组重排的社会影响可能是巨大的，这既是一种自然现象，如果被误导，可能导致疾病，如果被利用，可能会导致下一代基因组编辑工具。该项目旨在从理论和实验中了解RNA模板DNA重组机制如何塑造某些纤毛虫物种中遗传信息的组装，纤毛虫是具有最高水平天然基因组编辑的生物体。通过使用高通量实验工具和基于纽结理论和离散数学的新数学概念，该项目将获得对程序化基因组重组过程的时间和结构洞察力，包括纤毛虫体细胞发育期间DNA- DNA和DNA-RNA接触的全基因组调查。拟议的研究将影响数学，生物学和化学的博士后，研究生和本科生教育，预计至少有两名博士后，三名博士和几篇高级论文将从该项目中产生。由于纤毛虫Oxytricha在发育过程中经历了数十万次程序化的DNA重排，比任何其他已知的生物都要多，我们使用Oxytricha及其近亲作为易于处理的实验室模型来研究模板引导的基因组重排。该项目增加了我们对模板引导的染色体DNA重排的理解，无论是在核发育过程中还是在产生混乱基因组的进化步骤中。先前的研究表明，编排这种重排过程的一般机制是由母体RNA模板指导的，这些模板可以通过空间图进行数学建模，而重排途径可以建模为有向无环图中的路径，该有向无环图的顶点是空间图。该项目通过中间分子的透镜以及重排过程中出现的更高级别的相互作用来解决问题，并将在实验和理论上研究全局重排途径。具体目标包括：1.实验解剖的时间顺序的事件和形成的DNA- DNA和DNA-RNA相互作用在基因组重排。2.建立基因组重排的数学方法，使用基于中间体变化的图形描述。3.开发数学模型来测量潜在的混乱模式的差异，以及不同物种之间可能的重排途径的差异。4.该奖项反映了NSF的法定使命，并通过使用基金会的智力价值和更广泛的影响审查标准进行评估，被认为值得支持。