Phylodynamics beyond neutrality: the impact of incomplete purifying selection on viral phylogenies and inference.

IF 4.7 2区 生物学 Q1 BIOLOGY Philosophical Transactions of the Royal Society B: Biological Sciences Pub Date : 2025-02-13 Epub Date: 2025-02-20 DOI:10.1098/rstb.2023.0314
Katia Koelle, David A Rasmussen
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Abstract

Viral phylodynamics focuses on using sequence data to make inferences about the population dynamics of viral diseases. These inferences commonly include estimation of growth rates, reproduction numbers and times of most recent common ancestor. With few exceptions, existing phylodynamic inference approaches assume that all observed and ancestral viral genetic variation is fitness-neutral. This assumption is commonly violated, with a large body of analyses indicating that fitness varies substantially among genotypes circulating in viral populations. Here, we focus on fitness variation arising from deleterious mutations, asking whether incomplete purifying selection of deleterious mutations has the potential to bias phylodynamic inference. We use simulations of an exponentially growing population to explore how incomplete purifying selection distorts tree shape and shifts the distribution of mutations over trees. We find that incomplete purifying selection strongly shapes the distribution of mutations while only weakly impacting tree shape. Despite incomplete purifying selection shifting the distribution of deleterious mutations, we find little discernible bias in estimates of viral growth rates and times of the most recent common ancestor. Our results reassuringly indicate that existing phylodynamic inference approaches that assume neutrality may nevertheless yield accurate epidemiological estimates in the face of incomplete purifying selection. More work is needed to assess the robustness of these findings to alternative epidemiological parametrizations.This article is part of the theme issue ''"A mathematical theory of evolution": phylogenetic models dating back 100 years'.

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中性以外的系统动力学:不完全纯化选择对病毒系统发育和推断的影响。
病毒系统动力学侧重于使用序列数据来推断病毒性疾病的种群动态。这些推论通常包括对最近的共同祖先的生长速率、繁殖数量和时间的估计。除了少数例外,现有的系统动力学推断方法假设所有观察到的和祖先的病毒遗传变异都是适应度中性的。这一假设通常是被违背的,大量的分析表明,在病毒种群中传播的基因型之间的适应度存在很大差异。在这里,我们关注有害突变引起的适应度变异,询问有害突变的不完全净化选择是否有可能偏差系统动力学推断。我们使用指数增长种群的模拟来探索不完全净化选择是如何扭曲树木形状和改变树木突变分布的。我们发现,不完全净化选择对突变分布的影响很大,而对树形的影响很小。尽管不完全的净化选择改变了有害突变的分布,但我们发现在估计病毒生长速度和最近共同祖先的时间方面几乎没有明显的偏差。我们的结果令人放心地表明,假设中立的现有系统动力学推断方法在面对不完全净化选择时仍可能产生准确的流行病学估计。需要更多的工作来评估这些发现对其他流行病学参数化的稳健性。这篇文章是主题“进化的数学理论”的一部分:追溯到100年前的系统发育模型。
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CiteScore
11.80
自引率
1.60%
发文量
365
审稿时长
3 months
期刊介绍: The journal publishes topics across the life sciences. As long as the core subject lies within the biological sciences, some issues may also include content crossing into other areas such as the physical sciences, social sciences, biophysics, policy, economics etc. Issues generally sit within four broad areas (although many issues sit across these areas): Organismal, environmental and evolutionary biology Neuroscience and cognition Cellular, molecular and developmental biology Health and disease.
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