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Combining allele frequency and tree-based approaches improves phylogeographic inference from natural history collections

机译:将等位基因频率和基于树的方法相结合可改善自然历史记录的系统地理学推断

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摘要

Model selection approaches in phylogeography have allowed researchers to evaluate the support for competing demographic histories, which provides a mode of inference and a measure of uncertainty in understanding climatic and spatial influences on intraspecific diversity. Here, to rank all models in the comparison set, and determine what proportion of the total support the top-ranked model garners, we conduct model selection using two analytical approaches –allele frequency-based, implemented in fastsimcoal2, and gene tree-based, implemented in PHRAPL. We then expand this model-selection framework by including an assessment of absolute fit of the models to the data. For this, we utilize DNA isolated from existing natural history collections that span the distribution of red alder (Alnus rubra) in the Pacific Northwest of North America to generate genomic data for the evaluation of 13 demographic scenarios. The quality of DNA recovered from herbarium specimen leaf tissue was assessed for its utility and effectiveness in demographic model selection, specifically in the two approaches mentioned. We present strong support for the use of herbarium tissue in the generation of genomic DNA, albeit with the inclusion of additional quality control checks prior to library preparation and analyses with multiple approaches that incorporate various data. Analyses with allele frequency spectra and gene trees predominantly support A. rubra having experienced an ancient vicariance event with intermittent and frequent gene flow between the disjunct populations. Additionally, the data consistently fit the most frequently selected model, corroborating the model selection techniques. Finally, these results suggest that the A. rubra disjunct populations do not represent separate species.
机译:系统地理学中的模型选择方法使研究人员能够评估对相互竞争的人口历史的支持,这为理解气候和空间对种内多样性的影响提供了一种推断方式和一种不确定性度量。在这里,为了对比较集中的所有模型进行排名,并确定在支持最高排名的模型获得者中所占的总比例,我们使用两种分析方法进行模型选择:基于等位基因频率的方法(在fastsimcoal2中实现)和基于基因树的方法,在PHRAPL中实施。然后,我们通过评估模型与数据的绝对契合度来扩展此模型选择框架。为此,我们利用从现有自然历史记录中分离的DNA跨越北美al西北太平洋赤al鱼(Alnus rubra)的分布来生成基因组数据,以评估13种人口情况。从植物标本室标本叶片组织中回收的DNA的质量,评估了其在人口统计学模型选择中的效用和有效性,特别是在上述两种方法中。我们提供大力支持在植物基因组DNA的生成中使用植物标本馆组织,尽管在准备文库之前进行了其他质量控制检查,并采用多种方法结合了多种数据进行了分析。用等位基因频谱和基因树进行的分析主要支持A. rubra,它经历了一次古老的变异事件,在离散种群之间出现了间歇性和频繁的基因流动。此外,数据始终符合最常选择的模型,从而证实了模型选择技术。最后,这些结果表明,红曲霉分离种群不代表单独的物种。

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