Bioinformatics for the polyploidization-fractionation cycle in angiosperms

被子植物多倍化-分级循环的生物信息学

• 批准号: RGPIN-2016-05585
• 负责人: Sankoff, David
• 金额: $ 5.46万
• 依托单位: University of Ottawa
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2020
• 资助国家: 加拿大
• 起止时间: 2020-01-01 至 2021-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=709818
• 关键词: Bioinformatics; polyploidization; fractionation; cycle; angiosperms

Over the scale of millions of years, biological evolution entails not only mutations in individual genes, but also the rearrangement of the order of the genes on the chromosomes compared to other species descended from their common ancestor. In addition, and especially in plant genomes, the entire genome may be doubled, and the excess genes deleted in a seemingly unpredictable way. We model all these processes mathematically and develop combinatorial algorithms and statistical analyses to understand the rearrangement of gene order within and between chromosomes. This is applied to understand the evolution of genomes, particularly of crops and other flowering plants. Focusing on combinatorial algorithms, probability modeling and extensive collaborative analysis of flowering plant genomes, we propose to provide a comprehensive formal understanding of a wide range of phenomena connected to the evolution of chromosomes, specifically at the level of gene order. This development of a battery of formal combinatorial, mathematical and statistical tools will be thoroughly integrated with our work on the genomes of a large number of individual species. Our approaches should directly impact thinking within computational biology and should lead to useful ideas for biological research, as well as new discoveries about the genomes of many flowering plants.

在数百万年的时间尺度上，生物进化不仅需要单个基因的突变，而且还需要染色体上基因顺序的重新排列，与其他物种相比，这些基因来自他们共同的祖先。此外，特别是在植物基因组中，整个基因组可能会加倍，多余的基因以一种看似不可预测的方式删除。 我们对所有这些过程进行数学建模，并开发组合算法和统计分析，以了解染色体内和染色体之间的基因顺序重排。这被应用于理解基因组的进化，特别是农作物和其他开花植物。 专注于组合算法，概率建模和显花植物基因组的广泛的协作分析，我们建议提供一个全面的正式了解广泛的现象连接到染色体的进化，特别是在基因顺序的水平。这一系列正式的组合、数学和统计工具的开发将与我们对大量单个物种基因组的研究彻底结合起来。我们的方法应该直接影响计算生物学的思维，并为生物学研究带来有用的想法，以及对许多开花植物基因组的新发现。