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Öğe DISSECT: an assignment-free Bayesian discovery method for species delimitation under the multispecies coalescent(Oxford Univ Press, 2015) Jones, Graham; Aydin, Zeynep; Oxelman, BengtMotivation: The multispecies coalescent model provides a formal framework for the assignment of individual organisms to species, where the species are modeled as the branches of the sp tree. None of the available approaches so far have simultaneously co-estimated all the relevant parameters in the model, without restricting the parameter space by requiring a guide tree and/or prior assignment of individuals to clusters or species. Results: We present DISSECT, which explores the full space of possible clusterings of individuals and species tree topologies in a Bayesian framework. It uses an approximation to avoid the need for reversible-jump Markov Chain Monte Carlo, in the form of a prior that is a modification of the birth-death prior for the species tree. It incorporates a spike near zero in the density for node heights. The model has two extra parameters: one controls the degree of approximation and the second controls the prior distribution on the numbers of species. It is implemented as part of BEAST and requires only a few changes from a standard *BEAST analysis. The method is evaluated on simulated data and demonstrated on an empirical dataset. The method is shown to be insensitive to the degree of approximation, but quite sensitive to the second parameter, suggesting that large numbers of sequences are needed to draw firm conclusions.Öğe Marginal Likelihood Estimate Comparisons to Obtain Optimal Species Delimitations in Silene sect. Cryptoneurae (Caryophyllaceae)(PUBLIC LIBRARY SCIENCE, 1160 BATTERY STREET, STE 100, SAN FRANCISCO, CA 94111 USA, 2014) Aydın, Zeynep; Marcussen, Thomas; Ertekin, Alaattin Selçuk; Oxelman, BengtCoalescent-based inference of phylogenetic relationships among species takes into account gene tree incongruence due to incomplete lineage sorting, but for such methods to make sense species have to be correctly delimited. Because alternative assignments of individuals to species result in different parametric models, model selection methods can be applied to optimise model of species classification. In a Bayesian framework, Bayes factors (BF), based on marginal likelihood estimates, can be used to test a range of possible classifications for the group under study. Here, we explore BF and the Akaike Information Criterion (AIC) to discriminate between different species classifications in the flowering plant lineage Silene sect. Cryptoneurae (Caryophyllaceae). We estimated marginal likelihoods for different species classification models via the Path Sampling (PS), Stepping Stone sampling (SS), and Harmonic Mean Estimator (HME) methods implemented in BEAST. To select among alternative species classification models a posterior simulation-based analog of the AIC through Markov chain Monte Carlo analysis (AICM) was also performed. The results are compared to outcomes from the software BP&P. Our results agree with another recent study that marginal likelihood estimates from PS and SS methods are useful for comparing different species classifications, and strongly support the recognition of the newly described species S. ertekinii.Öğe A new section of Silene (Caryophyllaceae) including a new species from South Anatolia, Turkey(Magnolia Press, 2014) Aydin, Zeynep; Ertekin, Alaattin Selcuk; Langstrom, Elisabeth; Oxelman, BengtSilene section Cryptoneurae (Caryophyllaceae) and S. ertekinii from Western Antalya, Turkey, are described as new taxa on the basis of morphological and molecular investigations. Nuclear ITS and chloroplast rps16 DNA sequences clearly support the recognition of the new section. Inclusiveness and characterization of the new section is discussed and described, and a key for the included species is provided. Diagnostic characters of the new species S. ertekinii are given and its relation to the other species of the section is discussed.Öğe Recombination provides evidence for ancient hybridisation in the Silene aegyptiaca (Caryophyllaceae) complex(Springer Verlag, 2017) Pfeil, Bernard E.; Toprak, Zeynep; Oxelman, BengtRecombination events among distinct alleles complicate phylogenetic estimation. Various in vivo and in vitro processes can bring distinct alleles into the same genome to then undergo recombination, which may subsequently mislead phylogenetic inference if not assessed properly. Among the processes bringing divergent alleles together, hybridisation is perhaps the simplest and most likely, but alternatives need to be considered before hybridisation can be accepted as the underlying cause. Such alternatives include the presence of paralogues or deeply coalescing alleles, as well as amplification artefacts. Here, we document a recombination event that apparently took place between two divergent lineages of the Silene aegyptiaca complex in the flowering plant family Caryophyllaceae. We evaluate several possible mechanisms that might be responsible for the observed pattern. An ancient introgressive hybridisation event was the simplest explanation for the observations, compatible with geographic proximity of the affected lineages, whereas paralogy and deep coalescence are difficult to reconcile with the evidence obtained from a species tree of the group based on six different, non-recombinant genes and gene trees inferred using two partitions of the recombinant locus.Öğe Species delimitation without prior knowledge: DISSECT reveals extensive cryptic speciation in the Silene aegyptiaca complex (Caryophyllaceae)(Academic Press Inc Elsevier Science, 2016) Toprak, Zeynep; Pfeil, Bernard E.; Jones, Graham; Marcussen, Thomas; Ertekin, Alaattin Selcuk; Oxelman, BengtSpecies delimitation is a major focus of biosystematics. In recent years, considerable progress has been achieved with the development of the multispecies coalescent (MSC) model, where species constitute the branches of the species tree or network. However, researchers are faced with the limitation that the MSC method of choice often requires a priori assignment of individuals to species. This not only introduces subjectivitiy into the analyses, but may also lead to meaningless species tree hypotheses, if the allele-to-species assignments are inaccurate. DISSECT is a recently introduced method that does not require a priori allele-to-species assignments, but instead examines the posterior probabilities of groupings (clusterings) of individuals under study. Using the DISSECT approach, we analysed genetic data from 75 individual plants belonging to the Silene aegyptiaca species complex that has previously been divided into 3-5 species. Marginal likelihood estimates from *BEAST analyses, run with predefined species classifications, strongly favour those compatible with the DISSECT result over those from morphology- and geography-based taxonomy. We found at least nine species, including several cryptic ones, for which no clear geographical or morphological patterns are correlated. However, the limited data and the possibility of unmodelled processes mean there is still much uncertainty about the true number of MSC species, and for taxonomic purposes, other criteria might be relevant. Nevertheless, we argue that the approach signifies an important step towards objective and testable species delimitations in any organismal group. In particular, it makes it possible to avoid biologically irrelevant species classifications. (C) 2016 Elsevier Inc. All rights reserved.
