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      Multiple radiations of spiny mice (Rodentia: Acomys) in dry open habitats of Afro-Arabia: evidence from a multi-locus phylogeny

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          Abstract

          Background

          Spiny mice of the genus Acomys are distributed mainly in dry open habitats in Africa and the Middle East, and they are widely used as model taxa for various biological disciplines (e.g. ecology, physiology and evolutionary biology). Despite their importance, large distribution and abundance in local communities, the phylogeny and the species limits in the genus are poorly resolved, and this is especially true for sub-Saharan taxa. The main aims of this study are (1) to reconstruct phylogenetic relationships of Acomys based on the largest available multilocus dataset (700 genotyped individuals from 282 localities), (2) to identify the main biogeographical divides in the distribution of Acomys diversity in dry open habitats in Afro-Arabia, (3) to reconstruct the historical biogeography of the genus, and finally (4) to estimate the species richness of the genus by application of the phylogenetic species concept.

          Results

          The multilocus phylogeny based on four genetic markers shows presence of five major groups of Acomys called here subspinosus, spinosissimus, russatus, wilsoni and cahirinus groups. Three of these major groups ( spinosissimus, wilsoni and cahirinus) are further sub-structured to phylogenetic lineages with predominantly parapatric distributions. Combination of alternative species delimitation methods suggests the existence of 26 molecular operational taxonomic units (MOTUs), potentially corresponding to separate species. The highest genetic diversity was found in Eastern Africa. The origin of the genus Acomys is dated to late Miocene ( ca. 8.7 Ma), when the first split occurred between spiny mice of eastern (Somali-Masai) and south-eastern (Zambezian) savannas. Further diversification, mostly in Plio-Pleistocene, and the current distribution of Acomys were influenced by the interplay of global climatic factors (e.g. , Messinian salinity crisis, intensification of Northern Hemisphere glaciation) with local geomorphology (mountain chains, aridity belts, water bodies). Combination of divergence dating, species distribution modelling and historical biogeography analysis suggests repeated “out-of-East-Africa” dispersal events into western Africa, the Mediterranean region and Arabia.

          Conclusions

          The genus Acomys is very suitable model for historical phylogeographic and biogeographic reconstructions of dry non-forested environments in Afro-Arabia. We provide the most thorough phylogenetic reconstruction of the genus and identify major factors that influenced its evolutionary history since the late Miocene. We also highlight the urgent need of integrative taxonomic revision of east African taxa.

          Electronic supplementary material

          The online version of this article (10.1186/s12862-019-1380-9) contains supplementary material, which is available to authorized users.

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          Most cited references126

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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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            MTML-msBayes: Approximate Bayesian comparative phylogeographic inference from multiple taxa and multiple loci with rate heterogeneity

            Background MTML-msBayes uses hierarchical approximate Bayesian computation (HABC) under a coalescent model to infer temporal patterns of divergence and gene flow across codistributed taxon-pairs. Under a model of multiple codistributed taxa that diverge into taxon-pairs with subsequent gene flow or isolation, one can estimate hyper-parameters that quantify the mean and variability in divergence times or test models of migration and isolation. The software uses multi-locus DNA sequence data collected from multiple taxon-pairs and allows variation across taxa in demographic parameters as well as heterogeneity in DNA mutation rates across loci. The method also allows a flexible sampling scheme: different numbers of loci of varying length can be sampled from different taxon-pairs. Results Simulation tests reveal increasing power with increasing numbers of loci when attempting to distinguish temporal congruence from incongruence in divergence times across taxon-pairs. These results are robust to DNA mutation rate heterogeneity. Estimating mean divergence times and testing simultaneous divergence was less accurate with migration, but improved if one specified the correct migration model. Simulation validation tests demonstrated that one can detect the correct migration or isolation model with high probability, and that this HABC model testing procedure was greatly improved by incorporating a summary statistic originally developed for this task (Wakeley's ΨW ). The method is applied to an empirical data set of three Australian avian taxon-pairs and a result of simultaneous divergence with some subsequent gene flow is inferred. Conclusions To retain flexibility and compatibility with existing bioinformatics tools, MTML-msBayes is a pipeline software package consisting of Perl, C and R programs that are executed via the command line. Source code and binaries are available for download at http://msbayes.sourceforge.net/ under an open source license (GNU Public License).
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              Model selection in historical biogeography reveals that founder-event speciation is a crucial process in Island Clades.

              Founder-event speciation, where a rare jump dispersal event founds a new genetically isolated lineage, has long been considered crucial by many historical biogeographers, but its importance is disputed within the vicariance school. Probabilistic modeling of geographic range evolution creates the potential to test different biogeographical models against data using standard statistical model choice procedures, as long as multiple models are available. I re-implement the Dispersal-Extinction-Cladogenesis (DEC) model of LAGRANGE in the R package BioGeoBEARS, and modify it to create a new model, DEC + J, which adds founder-event speciation, the importance of which is governed by a new free parameter, [Formula: see text]. The identifiability of DEC and DEC + J is tested on data sets simulated under a wide range of macroevolutionary models where geography evolves jointly with lineage birth/death events. The results confirm that DEC and DEC + J are identifiable even though these models ignore the fact that molecular phylogenies are missing many cladogenesis and extinction events. The simulations also indicate that DEC will have substantially increased errors in ancestral range estimation and parameter inference when the true model includes + J. DEC and DEC + J are compared on 13 empirical data sets drawn from studies of island clades. Likelihood-ratio tests indicate that all clades reject DEC, and AICc model weights show large to overwhelming support for DEC + J, for the first time verifying the importance of founder-event speciation in island clades via statistical model choice. Under DEC + J, ancestral nodes are usually estimated to have ranges occupying only one island, rather than the widespread ancestors often favored by DEC. These results indicate that the assumptions of historical biogeography models can have large impacts on inference and require testing and comparison with statistical methods. © The Author(s) 2014. Published by Oxford University Press, on behalf of the Society of Systematic Biologists. All rights reserved. For Permissions, please email: journals.permissions@oup.com.
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                Author and article information

                Contributors
                tatiana.aghova@gmail.com
                klpr@post.cz
                sumbera@prf.jcu.cz
                frynta@centrum.cz
                llavrenchenko@gmail.com
                meheretu.yonas@mu.edu.et
                jovanas@seznam.cz
                jan.votypka@natur.cuni.cz
                jsyombua04@yahoo.com
                modryd@vfu.cz
                bryja@brno.cas.cz
                Journal
                BMC Evol Biol
                BMC Evol. Biol
                BMC Evolutionary Biology
                BioMed Central (London )
                1471-2148
                4 March 2019
                4 March 2019
                2019
                : 19
                : 69
                Affiliations
                [1 ]ISNI 0000 0000 9663 9052, GRID grid.448077.8, Institute of Vertebrate Biology of the Czech Academy of Sciences, ; 603 65 Brno, Czech Republic
                [2 ]ISNI 0000 0001 2243 1723, GRID grid.425401.6, Department of Zoology, National Museum, ; 115 79 Prague, Czech Republic
                [3 ]ISNI 0000 0004 1937 116X, GRID grid.4491.8, Department of Zoology, Faculty of Science, , Charles University, ; 128 44 Prague, Czech Republic
                [4 ]ISNI 0000 0001 2166 4904, GRID grid.14509.39, Department of Zoology, Faculty of Science, , University of South Bohemia, ; 370 05 České Budějovice, Czech Republic
                [5 ]ISNI 0000 0001 1088 7934, GRID grid.437665.5, A. N. Severtsov Institute of Ecology and Evolution RAS, ; 119071 Moscow, Russia
                [6 ]ISNI 0000 0001 1539 8988, GRID grid.30820.39, Department of Biology and Institute of Mountain Research and Development, , Mekelle University, ; P.O. Box 3102, Mekelle, Tigray Ethiopia
                [7 ]ISNI 0000 0004 1937 116X, GRID grid.4491.8, Department of Parasitology, Faculty of Science, , Charles University, ; 128 44 Prague, Czech Republic
                [8 ]GRID grid.448361.c, Institute of Parasitology, Biology Centre of the Czech Academy of Sciences, ; 370 05 České Budějovice, Czech Republic
                [9 ]ISNI 0000 0001 2019 0495, GRID grid.10604.33, Department of Land Resource Management and Agricultural Technology, College of Agriculture and Veterinary Sciences, , University of Nairobi, ; Nairobi, Kenya
                [10 ]ISNI 0000 0001 1009 2154, GRID grid.412968.0, Department of Pathology and Parasitology, Faculty of Veterinary Medicine, , University of Veterinary and Pharmaceutical Sciences, ; 612 42 Brno, Czech Republic
                [11 ]ISNI 0000 0001 2194 0956, GRID grid.10267.32, Department of Botany and Zoology, Faculty of Science, , Masaryk University, ; 602 00 Brno, Czech Republic
                Author information
                http://orcid.org/0000-0002-4184-4678
                Article
                1380
                10.1186/s12862-019-1380-9
                6399835
                30832573
                38e20e85-4ece-47a7-a4a3-54f4fb57670f
                © The Author(s). 2019

                Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

                History
                : 16 May 2018
                : 1 February 2019
                Funding
                Funded by: FundRef http://dx.doi.org/10.13039/501100001824, Grantová Agentura České Republiky;
                Award ID: 15-20229S
                Funded by: FundRef http://dx.doi.org/10.13039/501100005619, Ministerstvo Kultury;
                Award ID: 00023272
                Funded by: FundRef http://dx.doi.org/10.13039/501100002261, Russian Foundation for Basic Research;
                Award ID: 18-04-00563-a
                Categories
                Research Article
                Custom metadata
                © The Author(s) 2019

                Evolutionary Biology
                acomys,savanna,biogeography,africa,arabia,sahara,somali-masai,zambezian savanna,plio-pleistocene

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