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通用伪迹影响系统发育树的分支,而非通用标度律。

Universal artifacts affect the branching of phylogenetic trees, not universal scaling laws.

作者信息

Altaba Cristian R

机构信息

Laboratory of Human Systematics, University of the Balearic Islands, Balearic Islands, Spain.

出版信息

PLoS One. 2009;4(2):e4611. doi: 10.1371/journal.pone.0004611. Epub 2009 Feb 26.

DOI:10.1371/journal.pone.0004611
PMID:19242549
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC2644784/
Abstract

BACKGROUND

The superficial resemblance of phylogenetic trees to other branching structures allows searching for macroevolutionary patterns. However, such trees are just statistical inferences of particular historical events. Recent meta-analyses report finding regularities in the branching pattern of phylogenetic trees. But is this supported by evidence, or are such regularities just methodological artifacts? If so, is there any signal in a phylogeny?

METHODOLOGY

In order to evaluate the impact of polytomies and imbalance on tree shape, the distribution of all binary and polytomic trees of up to 7 taxa was assessed in tree-shape space. The relationship between the proportion of outgroups and the amount of imbalance introduced with them was assessed applying four different tree-building methods to 100 combinations from a set of 10 ingroup and 9 outgroup species, and performing covariance analyses. The relevance of this analysis was explored taking 61 published phylogenies, based on nucleic acid sequences and involving various taxa, taxonomic levels, and tree-building methods.

PRINCIPAL FINDINGS

All methods of phylogenetic inference are quite sensitive to the artifacts introduced by outgroups. However, published phylogenies appear to be subject to a rather effective, albeit rather intuitive control against such artifacts. The data and methods used to build phylogenetic trees are varied, so any meta-analysis is subject to pitfalls due to their uneven intrinsic merits, which translate into artifacts in tree shape. The binary branching pattern is an imposition of methods, and seldom reflects true relationships in intraspecific analyses, yielding artifactual polytomies in short trees. Above the species level, the departure of real trees from simplistic random models is caused at least by two natural factors--uneven speciation and extinction rates; and artifacts such as choice of taxa included in the analysis, and imbalance introduced by outgroups and basal paraphyletic taxa. This artifactual imbalance accounts for tree shape convergence of large trees.

SIGNIFICANCE

There is no evidence for any universal scaling in the tree of life. Instead, there is a need for improved methods of tree analysis that can be used to discriminate the noise due to outgroups from the phylogenetic signal within the taxon of interest, and to evaluate realistic models of evolution, correcting the retrospective perspective and explicitly recognizing extinction as a driving force. Artifacts are pervasive, and can only be overcome through understanding the structure and biological meaning of phylogenetic trees. Catalan Abstract in Translation S1.

摘要

背景

系统发育树与其他分支结构表面上的相似性使得人们能够探寻宏观进化模式。然而,此类树仅仅是特定历史事件的统计推断。近期的荟萃分析报告称在系统发育树的分支模式中发现了规律。但这有证据支持吗?还是说这些规律仅仅是方法上的人为产物?如果是这样,系统发育中是否存在任何信号呢?

方法

为了评估多歧分支和不平衡对树形的影响,在树形空间中评估了多达7个分类单元的所有二叉树和多歧树的分布。通过对一组10个内群物种和9个外群物种的100种组合应用四种不同的建树方法,并进行协方差分析,评估了外群比例与它们所引入的不平衡量之间的关系。基于61篇已发表的基于核酸序列且涉及各种分类单元、分类等级和建树方法的系统发育研究,探讨了该分析的相关性。

主要发现

所有系统发育推断方法对外群引入的人为因素都相当敏感。然而,已发表的系统发育研究似乎受到了一种相当有效(尽管相当直观)的针对此类人为因素的控制。用于构建系统发育树的数据和方法各不相同,因此任何荟萃分析都因内在优点参差不齐而容易陷入陷阱,这在树形上表现为人工产物。二叉分支模式是方法的一种强制规定,在种内分析中很少能反映真实关系,在短树中会产生人为的多歧分支。在物种水平之上,真实的树与简单随机模型的偏差至少由两个自然因素导致——物种形成和灭绝速率不均;以及诸如分析中所包含的分类单元选择、外群和基部并系分类单元引入的不平衡等人为因素。这种人为的不平衡导致了大树的树形趋同。

意义

没有证据表明生命之树存在任何普遍的尺度关系。相反,需要改进树分析方法,以便能够区分外群引起的噪声和感兴趣分类单元内的系统发育信号,并评估现实的进化模型,纠正回顾性视角并明确将灭绝视为驱动力。人为因素普遍存在,只有通过理解系统发育树的结构和生物学意义才能克服。加泰罗尼亚语摘要翻译S1。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ad23/2644784/d011d078ef79/pone.0004611.g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ad23/2644784/1acf1dbc20b8/pone.0004611.g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ad23/2644784/205593a5eff9/pone.0004611.g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ad23/2644784/5de85f90181d/pone.0004611.g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ad23/2644784/111fca8bc4a6/pone.0004611.g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ad23/2644784/d011d078ef79/pone.0004611.g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ad23/2644784/1acf1dbc20b8/pone.0004611.g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ad23/2644784/205593a5eff9/pone.0004611.g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ad23/2644784/5de85f90181d/pone.0004611.g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ad23/2644784/111fca8bc4a6/pone.0004611.g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ad23/2644784/d011d078ef79/pone.0004611.g005.jpg

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