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Bayesian phylogenetic analysis of combined data
Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Evolution, Genomics and Systematics, Systematic Zoology.
Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Evolution, Genomics and Systematics, Systematic Zoology.
2004 (English)In: Systematic Biology, ISSN 1063-5157, E-ISSN 1076-836X, Vol. 53, no 1, 47-67 p.Article in journal (Other (popular science, discussion, etc.)) Published
Abstract [en]

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.

Place, publisher, year, edition, pages
2004. Vol. 53, no 1, 47-67 p.
National Category
Natural Sciences
Identifiers
URN: urn:nbn:se:uu:diva-91351DOI: 10.1080/10635150490264699PubMedID: 14965900OAI: oai:DiVA.org:uu-91351DiVA: diva2:164053
Available from: 2004-02-11 Created: 2004-02-11 Last updated: 2017-12-14Bibliographically approved
In thesis
1. Bayesian Phylogenetics and the Evolution of Gall Wasps
Open this publication in new window or tab >>Bayesian Phylogenetics and the Evolution of Gall Wasps
2004 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

This thesis concerns the phylogenetic relationships and the evolution of the gall-inducing wasps belonging to the family Cynipidae. Several previous studies have used morphological data to reconstruct the evolution of the family. DNA sequences from several mitochondrial and nuclear genes where obtained and the first molecular, and combined molecular and morphological, analyses of higher-level relationships in the Cynipidae is presented. A Bayesian approach to data analysis is adopted, and models allowing combined analysis of heterogeneous data, such as multiple DNA data sets and morphology, are developed. The performance of these models is evaluated using methods that allow the estimation of posterior model probabilities, thus allowing selection of most probable models for the use in phylogenetics. The use of Bayesian model averaging in phylogenetics, as opposed to model selection, is also discussed.

It is shown that Bayesian MCMC analysis deals efficiently with complex models and that morphology can influence combined-data analyses, despite being outnumbered by DNA data. This emphasizes the utility and potential importance of using morphological data in statistical analyses of phylogeny.

The DNA-based and combined-data analyses of cynipid relationships differ from previous studies in two important respects. First, it was previously believed that there was a monophyletic clade of woody rosid gallers but the new results place the non-oak gallers in this assemblage (tribes Pediaspidini, Diplolepidini, and Eschatocerini) outside the rest of the Cynipidae. Second, earlier studies have lent strong support to the monophyly of the inquilines (tribe Synergini), gall wasps that develop inside the galls of other species. The new analyses suggest that the inquilines either originated several times independently, or that some inquilines secondarily regained the ability to induce galls. Possible reasons for the incongruence between morphological and DNA data is discussed in terms of heterogeneity in evolutionary rates among lineages, and convergent evolution of morphological characters.

Place, publisher, year, edition, pages
Uppsala: Acta Universitatis Upsaliensis, 2004. 43 p.
Series
Comprehensive Summaries of Uppsala Dissertations from the Faculty of Science and Technology, ISSN 1104-232X ; 937
Keyword
Biology, Bayesian analysis, Bayes factors, Cynipidae, gall wasps, MCMC, model averaging, model selection, phylogeny, total evidence, Biologi
National Category
Biological Sciences
Identifiers
urn:nbn:se:uu:diva-3996 (URN)91-554-5872-6 (ISBN)
Public defence
2004-03-04, Lindahlsalen, Evolutionsbiologiskt centrum, Norbyvägen 18, Uppsala, 13:00 (English)
Opponent
Supervisors
Available from: 2004-02-11 Created: 2004-02-11 Last updated: 2009-04-02Bibliographically approved

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