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Bayesian Inference of Ancestral Host–Parasite Interactions under a Phylogenetic Model of Host Repertoire Evolution
Systematic Biology ( IF 6.1 ) Pub Date : 2020-03-19 , DOI: 10.1093/sysbio/syaa019
Mariana P Braga 1, 2 , Michael J Landis 2, 3 , Sören Nylin 1 , Niklas Janz 1 , Fredrik Ronquist 4
Affiliation  

Abstract Intimate ecological interactions, such as those between parasites and their hosts, may persist over long time spans, coupling the evolutionary histories of the lineages involved. Most methods that reconstruct the coevolutionary history of such interactions make the simplifying assumption that parasites have a single host. Many methods also focus on congruence between host and parasite phylogenies, using cospeciation as the null model. However, there is an increasing body of evidence suggesting that the host ranges of parasites are more complex: that host ranges often include more than one host and evolve via gains and losses of hosts rather than through cospeciation alone. Here, we develop a Bayesian approach for inferring coevolutionary history based on a model accommodating these complexities. Specifically, a parasite is assumed to have a host repertoire, which includes both potential hosts and one or more actual hosts. Over time, potential hosts can be added or lost, and potential hosts can develop into actual hosts or vice versa. Thus, host colonization is modeled as a two-step process that may potentially be influenced by host relatedness. We first explore the statistical behavior of our model by simulating evolution of host–parasite interactions under a range of parameter values. We then use our approach, implemented in the program RevBayes, to infer the coevolutionary history between 34 Nymphalini butterfly species and 25 angiosperm families. Our analysis suggests that host relatedness among angiosperm families influences how easily Nymphalini lineages gain new hosts. [Ancestral hosts; coevolution; herbivorous insects; probabilistic modeling.]

中文翻译:


宿主谱系进化的系统发育模型下祖先宿主与寄生虫相互作用的贝叶斯推断



摘要 亲密的生态相互作用,例如寄生虫与其宿主之间的相互作用,可能会持续很长一段时间,从而与所涉及的谱系的进化历史耦合起来。大多数重建此类相互作用的共同进化历史的方法都做出了简化的假设,即寄生虫具有单一宿主。许多方法还关注宿主和寄生虫系统发育之间的一致性,使用共种作为零模型。然而,越来越多的证据表明寄生虫的宿主范围更加复杂:宿主范围通常包括多个宿主,并且通过宿主的获得和损失而不是仅通过共种而进化。在这里,我们开发了一种贝叶斯方法,基于适应这些复杂性的模型来推断共同进化历史。具体来说,假设寄生虫具有宿主库,其中包括潜在宿主和一个或多个实际宿主。随着时间的推移,潜在的主机可能会增加或丢失,潜在的主机可能会发展成为实际的主机,反之亦然。因此,宿主定植被建模为一个两步过程,可能会受到宿主相关性的影响。我们首先通过模拟一系列参数值下宿主-寄生虫相互作用的进化来探索模型的统计行为。然后,我们使用 RevBayes 程序中实施的方法来推断 34 个蛱蝶物种和 25 个被子植物科之间的共同进化历史。我们的分析表明,被子植物家族之间的宿主相关性影响蛱蝶谱系获得新宿主的难易程度。 【祖宗主人;共同进化;草食性昆虫;概率建模。]
更新日期:2020-03-19
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