Analyzing the phylogeny of poplars based on molecular data

基于分子数据的杨树系统发育分析

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Abstract

Methods for constructing trees using DNA sequences, known as molecular phylogenetics, have been applied to analyses of phylogenetic origin, evolutionary relatedness and taxonomic classification. Combining data sequenced in this study and downloaded from GenBank, we sampled 112 (chloroplast data) / 122 (ITS data) specimens belonging to 49 (chloroplast data) / 46 (ITS data) poplar species or hybrids from six (chloroplast data) / five sections (ITS data). Maximum parsimony and Bayesian inference were used to analyze phylogenetic relationships within the genus Populus based on eight chloroplast combinations and ITS regions. The results suggested that Bayesian inference might be more suitable for the phylogenetic reconstruction of Populus. All Populus species could be divided into two clades: clade 1, including subclades 1 and 2, and clade 2, including subclades 3 and 4. Species within clade 1, involving five sections except for Leuce, clustered coinciding with their two specific main geographical distribution areas: China (subclade 1) and North America (subclade 2). Clustering in subclade 3, section Leuce was confirmed to be of monophyletic origin and independent evolution. Its two subsections, namely Albidae and Trepidae, could be separated by chloroplast data but had frequent gene flow based on ITS data. Phylogeny analysis based on chloroplast data demonstrated once more that section Aigeiros was paraphyletic and further showed that the P. deltoides lineage is restricted in subclade 2 and that P. nigra lineage, located in subclade 3, originated from a hybrid of which an Albidae ancestor species was the material parent. Similarly, section Tacamahaca was found to be paraphyletic and had two lineages: a clade 1 lineage, such as P. cathayana, and a clade 2 lineage, such as P. simonii. Section Leucoides was paraphyletic and closely linked to section Tacamahaca. Their section boundaries were not conclusively delimitated by sequencing information.

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