期刊
MOLECULAR PHYLOGENETICS AND EVOLUTION
卷 49, 期 3, 页码 832-842出版社
ACADEMIC PRESS INC ELSEVIER SCIENCE
DOI: 10.1016/j.ympev.2008.09.008
关键词
COAL; Gene flow; Estimating species phylogenies; Incomplete lineage sorting; Minimizing deep coalescence; Rhododendron
Incomplete lineage sorting has been documented across a diverse set of taxa ranging from song birds to conifers. Such patterns are expected theoretically for species characterized by certain life history characteristics (e.g. long generation times) and those influenced by certain historical demographic events (e.g. recent divergences). A number of methods to estimate the underlying species phylogeny from a set of gene trees have been proposed and shown to be effective when incomplete lineage sorting has occurred. The further effects of gene flow on those methods, however, remain to be investigated. Here, we focus on the performance of three methods of species tree inference, ESP-COAL, minimizing deep coalescence (MDC), and concatenation, when incomplete lineage sorting and gene flow jointly confound the relationship between gene and species trees. Performance was investigated using Monte Carlo coalescent simulations under four models (n-island, stepping stone, parapatric, and allopatric) and three magnitudes of gene flow (N(e)m = 0.01, 0.10, 1.00). Although results varied by the model and magnitude of gene flow, methods incorporating aspects of the coalescent process (ESP-COAL and MDC) performed well, with probabilities of identifying the correct species tree topology typically increasing to greater than 0.75 when five more loci are sampled. The only exceptions to that pattern included gene flow at moderate to high magnitudes under the n-island and stepping stone models. Concatenation performs poorly relative to the other methods. We extend these results to a discussion of the importance of species and population phylogenies to the fields of molecular systematics and phylogeography using an empirical example from Rhododendron. (C) 2008 Elsevier Inc. All rights reserved.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据