Computational models, algorithms and methods for comparative genomics, applied to pathogens and anopheles mosquitoes genomes

应用于病原体和按蚊基因组的比较基因组学计算模型、算法和方法

• 批准号: RGPIN-2017-03986
• 负责人: Chauve, Cedric
• 金额: $ 1.89万
• 依托单位: Simon Fraser University
• 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=709840
• 关键词: Computational; models; algorithms; methods; comparative; Computational; models; algorithms; methods; comparative

Genome rearrangements are rare evolutionary events that alter the order of genes along chromosomes. They can be related to the development of virulence in pathogens, the emergence of new species or the adaptation to new environmental conditions or ecological niches. Over the last 10 years, my collaborators and I, as well as other groups, have made significan t advances in the development of already widely applicable methods for inferring gene order evolution scenarios and ancestral gene orders. The primary goal of my proposed research program is to expand the existing corpus of methods to reconstruct ancestral gene orders to address some of the remaining challenges. I will develop a comprehensive suite of mathematical models, computational algorithms, software, and data analysis procedures and pipelines, providing to life scientists efficient and relevant tools to investigate the evolution of the structural genome (gene content, gene order) of related groups of species. To be relevant to large--scale comparative genomics projects, these tools will be developed within a general evolutionary model, that includes gene duplication and loss, horizontal gene transfer and introgression, and genome rearrangements. Moreover, to handle data sets composed of genomes available in various levels of completion in terms of assemblies, I will develop methods that use sequencing data of various kinds and reconstruct jointly, in an integrative framework, gene family evolution, ancestral gene order and improved extant and ancient genome scaffolds. While these methods will be applicable to many large--scale data sets, I will study in depth a data set of eighteen genomes of Anopheles mosquitoes, the vector of the malaria parasite. In particular, I will complement the generic approaches described above in order to handle some very specific issues related to Anopheles (and insects in general) evolution, such as polymorphic inversions and introgression. This will result in improved data sets of genome assemblies, gene trees and ancestral gene orders of Anopheles genomes that will be valuable resources for the mosquito biology community. The second field of application that will be investigated is the pathogen Yersinia pestis, the agent of the bubonic plague. Yersinia pestis is an interesting species for studying genome rearrangement in pathogens, and is of particular interest due to the recent sequencing of several ancient strains involved in historical pandemics (the Justinian Plague and the Black Death). My goal is to take advantage of this unique data set of ancient and extant sequenced genomes to develop novel methods integrating aDNA in pathogen comparative genomics, with an application to refine our understanding of the evolution of a highly dynamic human pathogen at a historical time--scale.

基因组重排是罕见的进化事件，它改变了沿染色体的基因的顺序。它们可能与病原体中毒力的发展，新物种的出现或适应新的环境条件或生态壁ni。在过去的十年中，我和我的合作者以及其他群体在开发已经广泛适用的方法来推断基因顺序演化方案和祖先基因订单方面取得了显着进步。 我提出的研究计划的主要目标是扩大现有方法的现有方法，以重建祖先基因订单，以应对其余的挑战。我将开发一套全面的数学模型，计算算法，软件和数据分析程序和管道，为生活科学家提供有效且相关的工具，以研究相关物种相关群体的结构基因组（基因含量，基因序列）的演变。为了与大规模的比较基因组学项目相关，这些工具将在一般进化模型中开发，其中包括基因复制和损失，水平基因转移和渗入和基因组重排。此外，为了处理由组件以各种完整级别可用的基因组组成的数据集，我将开发使用各种的测序数据，并在一个集成框架，基因家族进化，祖先基因顺序和改进的现实和现代基因组脚手架中共同重建的测序数据并共同重建。 尽管这些方法将适用于许多大型数据集，但我将深入研究十八个基因组蚊子的数据集，这是疟原虫寄生虫的媒介。特别是，我将补充上述通用方法，以处理与蚊子（和昆虫）进化相关的一些非常具体的问题，例如多态性反转和渗入。这将导致改进的基因组组件，基因树和祖先基因顺序的数据集的数据集基因组的基因组，这些基因组将成为蚊子生物学界的宝贵资源。 将要研究的第二个应用领域是鼠疫的病原体耶尔森氏病。耶尔森宫是一种有趣的物种，用于研究病原体中的基因组重排，并且由于最近对历史大流行病（贾斯汀尼亚瘟疫和黑死亡）涉及的几种古老菌株的测序特别感兴趣。我的目标是利用这种古老和现存的测序基因组的独特数据集，以开发在病原体比较基因组学中整合ADNA的新方法，并应用了我们对在历史时期（规模）中对高度动态人类病原体的演变的理解。