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

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.

基因组重排是一种罕见的进化事件，它改变了沿着染色体的基因顺序。它们可能与病原体毒性的发展、新物种的出现或对新环境条件或生态位的适应有关。在过去的10年里，我和我的合作者，以及其他小组，在开发已经广泛应用的推断基因顺序进化情景和祖先基因顺序的方法方面取得了重大进展。 我提出的研究计划的主要目标是扩展现有的方法库来重建祖先基因顺序，以解决一些剩余的挑战。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，为生命科学家提供有效和相关的工具来研究相关物种组的结构基因组（基因内容，基因顺序）的进化。为了与大规模比较基因组学项目相关，这些工具将在一般进化模型内开发，包括基因复制和丢失、水平基因转移和渗入以及基因组重排。此外，处理数据集组成的基因组可在不同水平的完成方面的组件，我将开发的方法，使用各种测序数据和重建联合，在一个综合的框架，基因家族进化，祖先基因的顺序和改进的现存和古老的基因组支架。 虽然这些方法将适用于许多大规模的数据集，我将深入研究按蚊的十八个基因组的数据集，疟疾寄生虫的载体。特别是，我将补充上述的通用方法，以处理一些非常具体的问题有关的按蚊（和昆虫一般）的演变，如多态性反转和基因渗入。这将导致改进的基因组组装数据集，基因树和按蚊基因组的祖先基因顺序，这将是蚊子生物界的宝贵资源。 第二个应用领域将被调查的是病原体鼠疫耶尔森氏菌，代理的腺鼠疫。鼠疫耶尔森氏菌是研究病原体基因组重排的有趣物种，并且由于最近对历史流行病（查士丁尼鼠疫和黑死病）中涉及的几种古老菌株的测序而特别感兴趣。我的目标是利用这一独特的古老和现存的测序基因组数据集，开发新的方法，将aDNA整合到病原体比较基因组学中，并应用于完善我们对历史时间尺度上高度动态的人类病原体进化的理解。