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Unraveling reticulate evolution in North American Dryopteris (Dryopteridaceae)

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      Abstract

      Background

      The thirteen species of Dryopteris in North America have long been suspected of having undergone a complicated history of reticulate evolution via allopolyploid hybridization. Various explanations for the origins of the allopolyploid taxa have been suggested, and though most lines of evidence have supported the so-called “semicristata” hypothesis, contention over the group’s history has continued in several recent, conflicting studies.

      Results

      Sequence data from nine plastid and two nuclear markers were collected from 73 accessions representing 35 species of Dryopteris. Sequences from each of the allopolyploids are most closely related to their progenitor species as predicted by the “semicristata” hypothesis. Allotetraploid D. campyloptera appears to be derived from a hybrid between diploid D. expansa and D. intermedia; D. celsa, from diploid D. ludoviciana x D. goldiana; and D. carthusiana and D. cristata, from diploid “D. semicristata” x D. intermedia and D. ludoviciana, respectively. Allohexaploid D. clintoniana appears to be derived from D. cristata x D.goldiana. The earliest estimated dates of formation of the allopolyploids, based on divergence time analyses, were within the last 6 Ma. We found no evidence for recurrent formation of any of the allopolyploids. The sexual allopolyploid taxa are derived from crosses between parents that show intermediate levels of genetic divergence relative to all pairs of potential progenitors. In addition, the four allotetraploids are transgressive with respect to geographic range relative to one or both of their parents (their ranges extend beyond those of the parents), suggesting that ecological advantages in novel habitats or regions may promote long-term regional coexistence of the hybrid taxa with their progenitors.

      Conclusions

      This study provides the first thorough evaluation of the North American complex of woodferns using extensive sampling of taxa and genetic markers. Phylogenies produced from each of three datasets (one plastid and two nuclear) support the “semicristata” hypothesis, including the existence of a missing diploid progenitor, and allow us to reject all competing hypotheses. This study demonstrates the value of using multiple, biparentally inherited markers to evaluate reticulate complexes, assess the frequency of recurrent polyploidization, and determine the relative importance of introgression vs. hybridization in shaping the histories of such groups.

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      Most cited references 88

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      MrBayes 3: Bayesian phylogenetic inference under mixed models.

      MrBayes 3 performs Bayesian phylogenetic analysis combining information from different data partitions or subsets evolving under different stochastic evolutionary models. This allows the user to analyze heterogeneous data sets consisting of different data types-e.g. morphological, nucleotide, and protein-and to explore a wide variety of structured models mixing partition-unique and shared parameters. The program employs MPI to parallelize Metropolis coupling on Macintosh or UNIX clusters.
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        RAxML-VI-HPC: maximum likelihood-based phylogenetic analyses with thousands of taxa and mixed models.

        RAxML-VI-HPC (randomized axelerated maximum likelihood for high performance computing) is a sequential and parallel program for inference of large phylogenies with maximum likelihood (ML). Low-level technical optimizations, a modification of the search algorithm, and the use of the GTR+CAT approximation as replacement for GTR+Gamma yield a program that is between 2.7 and 52 times faster than the previous version of RAxML. A large-scale performance comparison with GARLI, PHYML, IQPNNI and MrBayes on real data containing 1000 up to 6722 taxa shows that RAxML requires at least 5.6 times less main memory and yields better trees in similar times than the best competing program (GARLI) on datasets up to 2500 taxa. On datasets > or =4000 taxa it also runs 2-3 times faster than GARLI. RAxML has been parallelized with MPI to conduct parallel multiple bootstraps and inferences on distinct starting trees. The program has been used to compute ML trees on two of the largest alignments to date containing 25,057 (1463 bp) and 2182 (51,089 bp) taxa, respectively. icwww.epfl.ch/~stamatak
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          BEAST: Bayesian evolutionary analysis by sampling trees

          Background The evolutionary analysis of molecular sequence variation is a statistical enterprise. This is reflected in the increased use of probabilistic models for phylogenetic inference, multiple sequence alignment, and molecular population genetics. Here we present BEAST: a fast, flexible software architecture for Bayesian analysis of molecular sequences related by an evolutionary tree. A large number of popular stochastic models of sequence evolution are provided and tree-based models suitable for both within- and between-species sequence data are implemented. Results BEAST version 1.4.6 consists of 81000 lines of Java source code, 779 classes and 81 packages. It provides models for DNA and protein sequence evolution, highly parametric coalescent analysis, relaxed clock phylogenetics, non-contemporaneous sequence data, statistical alignment and a wide range of options for prior distributions. BEAST source code is object-oriented, modular in design and freely available at under the GNU LGPL license. Conclusion BEAST is a powerful and flexible evolutionary analysis package for molecular sequence variation. It also provides a resource for the further development of new models and statistical methods of evolutionary analysis.
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            Author and article information

            Affiliations
            [1]Department of Botany, University of Wisconsin-Madison, 430 Lincoln Drive, Madison, WI, 53706, USA
            [2]Department of Botany, National Museum of Natural History, MRC 166, Smithsonian Institution, Washington, DC, 20013-7012, USA
            Contributors
            Journal
            BMC Evol Biol
            BMC Evol. Biol
            BMC Evolutionary Biology
            BioMed Central
            1471-2148
            2012
            30 June 2012
            : 12
            : 104
            Copyright ©2012 Sessa et al.; licensee BioMed Central Ltd.

            This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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