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用于检测差异多样化率的全树方法。

Whole-tree methods for detecting differential diversification rates.

作者信息

Chan Kai M A, Moore Brian R

机构信息

Department of Ecology and Evolutionary Biology, Princeton University, New Jersey 08544-1003, USA.

出版信息

Syst Biol. 2002 Dec;51(6):855-65. doi: 10.1080/10635150290102555.

Abstract

Prolific cladogenesis, adaptive radiation, species selection, key innovations, and mass extinctions are a few examples of biological phenomena that lead to differential diversification among lineages. Central to the study of differential diversification rates is the ability to distinguish chance variation from that which requires deterministic explanation. To detect diversification rate variation among lineages, we propose a number of methods that incorporate information on the topological distribution of species diversity from all internal nodes of a phylogenetic tree. These whole-tree methods (M(Pi), M(Sigma), and M(R)) are explicitly connected to a null model of random diversification--the equal-rates Markov (ERM) random branching model--and an alternative model of differential diversification: M(Pi) is based on the product of individual nodal ERM probabilities; M(Sigma) is based on the sum of individual nodal ERM probabilities, and M(R) is based on a transformation of ERM probabilities that corresponds to a formalized system that orders trees by their relative symmetry. These methods have been implemented in a freely available computer program, SYMMETREE, to detect clades with variable diversification rates, thereby allowing the study of biological processes correlated with and possibly causal to shifts in diversification rate. Application of these methods to several published phylogenies demonstrates their ability to contend with relatively large, incompletely resolved trees. These topology-based methods do not require estimates of relative branch lengths, which should facilitate the analysis of phylogenies, such as supertrees, for which such data are unreliable or unavailable.

摘要

多产的种系发生、适应性辐射、物种选择、关键创新和大规模灭绝是导致谱系间差异多样化的一些生物现象的例子。差异多样化速率研究的核心是能够区分偶然变异和需要确定性解释的变异。为了检测谱系间的多样化速率变化,我们提出了一些方法,这些方法整合了来自系统发育树所有内部节点的物种多样性拓扑分布信息。这些全树方法(M(Pi)、M(Sigma)和M(R))明确地与随机多样化的零模型——等速率马尔可夫(ERM)随机分支模型——以及差异多样化的替代模型相关联:M(Pi)基于各个节点ERM概率的乘积;M(Sigma)基于各个节点ERM概率的总和,而M(R)基于与通过相对对称性对树进行排序的形式化系统相对应的ERM概率变换。这些方法已在一个免费的计算机程序SYMMETREE中实现,以检测具有可变多样化速率的分支,从而允许研究与多样化速率变化相关且可能是其原因的生物过程。将这些方法应用于几篇已发表的系统发育树表明它们能够处理相对较大、未完全解析的树。这些基于拓扑的方法不需要估计相对分支长度,这应该有助于对系统发育树(如超级树)进行分析,因为对于这些树,此类数据不可靠或无法获得。

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