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Bayesian Inference of Clonal Expansions in a Dated Phylogeny
Systematic Biology ( IF 6.5 ) Pub Date : 2021-11-30 , DOI: 10.1093/sysbio/syab095
David Helekal 1 , Alice Ledda 2 , Erik Volz 3 , David Wyllie 4 , Xavier Didelot 5
Affiliation  

Microbial population genetics models often assume that all lineages are constrained by the same population size dynamics over time. However, many neutral and selective events can invalidate this assumption and can contribute to the clonal expansion of a specific lineage relative to the rest of the population. Such differential phylodynamic properties between lineages result in asymmetries and imbalances in phylogenetic trees that are sometimes described informally but which are difficult to analyze formally. To this end, we developed a model of how clonal expansions occur and affect the branching patterns of a phylogeny. We show how the parameters of this model can be inferred from a given dated phylogeny using Bayesian statistics, which allows us to assess the probability that one or more clonal expansion events occurred. For each putative clonal expansion event, we estimate its date of emergence and subsequent phylodynamic trajectory, including its long-term evolutionary potential which is important to determine how much effort should be placed on specific control measures. We demonstrate the applicability of our methodology on simulated and real data sets. Inference under our clonal expansion model can reveal important features in the evolution and epidemiology of infectious disease pathogens. [Clonal expansion; genomic epidemiology; microbial population genomics; phylodynamics.]

中文翻译:

过时系统发育中克隆扩展的贝叶斯推断

微生物种群遗传学模型通常假设所有谱系随着时间的推移受到相同种群大小动态的约束。然而,许多中性和选择性事件会使这一假设无效,并可能导致特定谱系相对于其他人群的克隆扩张。谱系之间的这种差异系统动力学特性导致系统发育树的不对称和不平衡,这些系统发育树有时被非正式地描述,但难以正式分析。为此,我们开发了一个模型,说明克隆扩展如何发生并影响系统发育的分支模式。我们展示了如何使用贝叶斯统计从给定的系统发育中推断出该模型的参数,这使我们能够评估发生一个或多个克隆扩展事件的概率。对于每个假定的克隆扩展事件,我们估计其出现日期和随后的系统动力学轨迹,包括其长期进化潜力,这对于确定应在具体控制措施上投入多少努力很重要。我们展示了我们的方法在模拟和真实数据集上的适用性。我们的克隆扩展模型下的推断可以揭示传染病病原体进化和流行病学的重要特征。[克隆扩展;基因组流行病学;微生物种群基因组学;系统动力学。] 我们展示了我们的方法在模拟和真实数据集上的适用性。我们的克隆扩展模型下的推断可以揭示传染病病原体进化和流行病学的重要特征。[克隆扩展;基因组流行病学;微生物种群基因组学;系统动力学。] 我们展示了我们的方法在模拟和真实数据集上的适用性。我们的克隆扩展模型下的推断可以揭示传染病病原体进化和流行病学的重要特征。[克隆扩展;基因组流行病学;微生物种群基因组学;系统动力学。]
更新日期:2021-11-30
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