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Using multiple analytical methods to improve phylogenetic hypotheses in Minaria (Apocynaceae)

机译:使用多种分析方法改善Minaria(Apocynaceae)的系统发育假设

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摘要

Metastelmatinae is a neotropical subtribe of Asclepiadoideae (Apocynaceae), comprising 13 genera and around 260 species whose phylogenetic relationships are often unresolved or incongruent between plastid and nuclear datasets. The genus Minaria is one of the first lineages to emerge in the Metastelmatinae and is highly supported based on plastid markers. It comprises 21 species, most of which are endemic to small areas with open vegetation in the Espinha?o Range, Brazil. In the work presented here, we use plastid (rps16, trnH-psbA, trnS-trnG, and trnD-trnT) and nuclear (ITS and ETS) datasets to investigate the relationships within Minaria. We show that the three methods mostly used in phylogenetic studies, namely, maximum parsimony, maximum likelihood, and Bayesian Inference, have different performances and that a pluralistic analytical approach combining results from them can increase tree resolution and clade confidence, providing valuable phylogenetic information.
机译:Metastelmatinae是马兜铃科(Apocynaceae)的新热带亚族,包括13个属和大约260个种,其系统发生关系在质体和核数据集之间通常是不可分辨的或不一致的。 Minaria属是最早出现在Metastelmatinae中的谱系之一,并基于质体标记得到高度支持。它包括21种,其中大多数为巴西Espinha?o山脉中开放植被的小区域所特有。在此处介绍的工作中,我们使用质体(rps16,trnH-psbA,trnS-trnG和trnD-trnT)和核能(ITS和ETS)数据集来研究Minaria之间的关系。我们表明,系统发育研究中最常用的三种方法,即最大简约性,最大似然性和贝叶斯推断,具有不同的性能,并且将它们的结果结合起来的多元分析方法可以提高树的分辨率和进化枝的置信度,从而提供有价值的系统发育信息。

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