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      Phylogenetic relationships of typical antbirds (Thamnophilidae) and test of incongruence based on Bayes factors

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          Abstract

          Background

          The typical antbirds (Thamnophilidae) form a monophyletic and diverse family of suboscine passerines that inhabit neotropical forests. However, the phylogenetic relationships within this assemblage are poorly understood. Herein, we present a hypothesis of the generic relationships of this group based on Bayesian inference analyses of two nuclear introns and the mitochondrial cytochrome b gene. The level of phylogenetic congruence between the individual genes has been investigated utilizing Bayes factors. We also explore how changes in the substitution models affected the observed incongruence between partitions of our data set.

          Results

          The phylogenetic analysis supports both novel relationships, as well as traditional groupings. Among the more interesting novel relationship suggested is that the Terenura antwrens, the wing-banded antbird ( Myrmornis torquata), the spot-winged antshrike ( Pygiptila stellaris) and the russet antshrike ( Thamnistes anabatinus) are sisters to all other typical antbirds. The remaining genera fall into two major clades. The first includes antshrikes, antvireos and the Herpsilochmus antwrens, while the second clade consists of most antwren genera, the Myrmeciza antbirds, the "professional" ant-following antbirds, and allied species. Our results also support previously suggested polyphyly of Myrmotherula antwrens and Myrmeciza antbirds. The tests of phylogenetic incongruence, using Bayes factors, clearly suggests that allowing the gene partitions to have separate topology parameters clearly increased the model likelihood. However, changing a component of the nucleotide substitution model had much higher impact on the model likelihood.

          Conclusions

          The phylogenetic results are in broad agreement with traditional classification of the typical antbirds, but some relationships are unexpected based on external morphology. In these cases their true affinities may have been obscured by convergent evolution and morphological adaptations to new habitats or food sources, and genera like Myrmeciza antbirds and the Myrmotherula antwrens obviously need taxonomic revisions. Although, Bayes factors seem promising for evaluating the relative contribution of components to an evolutionary model, the results suggests that even if strong evidence for a model allowing separate topology parameters is found, this might not mean strong evidence for separate gene phylogenies, as long as vital components of the substitution model are still missing.

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          Most cited references74

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          Dating of the human-ape splitting by a molecular clock of mitochondrial DNA.

          A new statistical method for estimating divergence dates of species from DNA sequence data by a molecular clock approach is developed. This method takes into account effectively the information contained in a set of DNA sequence data. The molecular clock of mitochondrial DNA (mtDNA) was calibrated by setting the date of divergence between primates and ungulates at the Cretaceous-Tertiary boundary (65 million years ago), when the extinction of dinosaurs occurred. A generalized least-squares method was applied in fitting a model to mtDNA sequence data, and the clock gave dates of 92.3 +/- 11.7, 13.3 +/- 1.5, 10.9 +/- 1.2, 3.7 +/- 0.6, and 2.7 +/- 0.6 million years ago (where the second of each pair of numbers is the standard deviation) for the separation of mouse, gibbon, orangutan, gorilla, and chimpanzee, respectively, from the line leading to humans. Although there is some uncertainty in the clock, this dating may pose a problem for the widely believed hypothesis that the pipedal creature Australopithecus afarensis, which lived some 3.7 million years ago at Laetoli in Tanzania and at Hadar in Ethiopia, was ancestral to man and evolved after the human-ape splitting. Another likelier possibility is that mtDNA was transferred through hybridization between a proto-human and a proto-chimpanzee after the former had developed bipedalism.
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            Bayesian phylogenetic analysis of combined data.

            The recent development of Bayesian phylogenetic inference using Markov chain Monte Carlo (MCMC) techniques has facilitated the exploration of parameter-rich evolutionary models. At the same time, stochastic models have become more realistic (and complex) and have been extended to new types of data, such as morphology. Based on this foundation, we developed a Bayesian MCMC approach to the analysis of combined data sets and explored its utility in inferring relationships among gall wasps based on data from morphology and four genes (nuclear and mitochondrial, ribosomal and protein coding). Examined models range in complexity from those recognizing only a morphological and a molecular partition to those having complex substitution models with independent parameters for each gene. Bayesian MCMC analysis deals efficiently with complex models: convergence occurs faster and more predictably for complex models, mixing is adequate for all parameters even under very complex models, and the parameter update cycle is virtually unaffected by model partitioning across sites. Morphology contributed only 5% of the characters in the data set but nevertheless influenced the combined-data tree, supporting the utility of morphological data in multigene analyses. We used Bayesian criteria (Bayes factors) to show that process heterogeneity across data partitions is a significant model component, although not as important as among-site rate variation. More complex evolutionary models are associated with more topological uncertainty and less conflict between morphology and molecules. Bayes factors sometimes favor simpler models over considerably more parameter-rich models, but the best model overall is also the most complex and Bayes factors do not support exclusion of apparently weak parameters from this model. Thus, Bayes factors appear to be useful for selecting among complex models, but it is still unclear whether their use strikes a reasonable balance between model complexity and error in parameter estimates.
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              The general stochastic model of nucleotide substitution.

              DNA sequence evolution through nucleotide substitution may be assimilated to a stationary Markov process. The fundamental equations of the general model, with 12 independent substitution parameters, are used to obtain a formula which corrects the effect of multiple and parallel substitutions on the measure of evolutionary divergence between two homologous sequences. We show that only reversible models, with six independent parameters, allow the calculation of the substitution rates. Simulation experiments on DNA sequence evolution through nucleotide substitution call into question the effectiveness of the general model (and of any other more detailed description); nevertheless, the general model results are slightly superior to any of its particular cases.
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                Author and article information

                Journal
                BMC Evol Biol
                BMC Evolutionary Biology
                BioMed Central (London )
                1471-2148
                2004
                30 July 2004
                : 4
                : 23
                Affiliations
                [1 ]Department of Vertebrate Zoology and Molecular Systematics Laboratory, Swedish Museum of Natural History, P.O. Box 50007, SE-104 05, Stockholm, Sweden
                [2 ]Department of Zoology, University of Stockholm, SE-106 91 Stockholm, Sweden
                [3 ]Vertebrate Department, Zoological Museum, University of Copenhagen, Universitetsparken 15, DK-2100 Copenhagen Ø, Denmark
                [4 ]Department of Systematic Zoology, Evolutionary Biology, Centre, Uppsala University, Uppsala, Sweden
                Article
                1471-2148-4-23
                10.1186/1471-2148-4-23
                509417
                15283860
                aeec0582-80f4-4953-a928-3d7a02d2a24e
                Copyright © 2004 Irestedt 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.

                History
                : 26 April 2004
                : 30 July 2004
                Categories
                Research Article

                Evolutionary Biology
                Evolutionary Biology

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