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      The Silk roads: phylogeography of Central Asian dice snakes (Serpentes: Natricidae) shaped by rivers in deserts and mountain valleys

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          Abstract

          Influenced by rapid changes in climate and landscape features since the Miocene, widely distributed species provide suitable models to study the environmental impact on their evolution and current genetic diversity. The dice snake Natrix tessellata, widely distributed in the Western Palearctic is one such species. We aimed to resolve a detailed phylogeography of N. tessellata with a focus on the Central Asian clade with 4 and the Anatolia clade with 3 mitochondrial lineages, trace their origin, and correlate the environmental changes that affected their distribution through time. The expected time of divergence of both clades began at 3.7 Mya in the Pliocene, reaching lineage differentiation approximately 1 million years later. The genetic diversity in both clades is rich, suggesting different ancestral areas, glacial refugia, demographic changes, and colonization routes. The Caspian lineage is the most widespread lineage in Central Asia, distributed around the Caspian Sea and reaching the foothills of the Hindu Kush Mountains in Afghanistan, and Eastern European lowlands in the west. Its distribution is limited by deserts, mountains, and cold steppe environments. Similarly, Kazakhstan and Uzbekistan lineages followed the Amu Darya and the Syr Darya water systems in Central Asia, with ranges delimited by the large Kyzylkum and Karakum deserts. On the western side, there are several lineages within the Anatolia clade that converged in the central part of the peninsula with 2 being endemic to Western Asia. The distribution of both main clades was affected by expansion from their Pleistocene glacial refugia around the Caspian Sea and in the valleys of Central Asia as well as by environmental changes, mostly through aridification.

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          RAxML version 8: a tool for phylogenetic analysis and post-analysis of large phylogenies

          Motivation: Phylogenies are increasingly used in all fields of medical and biological research. Moreover, because of the next-generation sequencing revolution, datasets used for conducting phylogenetic analyses grow at an unprecedented pace. RAxML (Randomized Axelerated Maximum Likelihood) is a popular program for phylogenetic analyses of large datasets under maximum likelihood. Since the last RAxML paper in 2006, it has been continuously maintained and extended to accommodate the increasingly growing input datasets and to serve the needs of the user community. Results: I present some of the most notable new features and extensions of RAxML, such as a substantial extension of substitution models and supported data types, the introduction of SSE3, AVX and AVX2 vector intrinsics, techniques for reducing the memory requirements of the code and a plethora of operations for conducting post-analyses on sets of trees. In addition, an up-to-date 50-page user manual covering all new RAxML options is available. Availability and implementation: The code is available under GNU GPL at https://github.com/stamatak/standard-RAxML. Contact: alexandros.stamatakis@h-its.org Supplementary information: Supplementary data are available at Bioinformatics online.
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            MrBayes 3.2: Efficient Bayesian Phylogenetic Inference and Model Choice Across a Large Model Space

            Since its introduction in 2001, MrBayes has grown in popularity as a software package for Bayesian phylogenetic inference using Markov chain Monte Carlo (MCMC) methods. With this note, we announce the release of version 3.2, a major upgrade to the latest official release presented in 2003. The new version provides convergence diagnostics and allows multiple analyses to be run in parallel with convergence progress monitored on the fly. The introduction of new proposals and automatic optimization of tuning parameters has improved convergence for many problems. The new version also sports significantly faster likelihood calculations through streaming single-instruction-multiple-data extensions (SSE) and support of the BEAGLE library, allowing likelihood calculations to be delegated to graphics processing units (GPUs) on compatible hardware. Speedup factors range from around 2 with SSE code to more than 50 with BEAGLE for codon problems. Checkpointing across all models allows long runs to be completed even when an analysis is prematurely terminated. New models include relaxed clocks, dating, model averaging across time-reversible substitution models, and support for hard, negative, and partial (backbone) tree constraints. Inference of species trees from gene trees is supported by full incorporation of the Bayesian estimation of species trees (BEST) algorithms. Marginal model likelihoods for Bayes factor tests can be estimated accurately across the entire model space using the stepping stone method. The new version provides more output options than previously, including samples of ancestral states, site rates, site d N /d S rations, branch rates, and node dates. A wide range of statistics on tree parameters can also be output for visualization in FigTree and compatible software.
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              The meaning and use of the area under a receiver operating characteristic (ROC) curve.

              A representation and interpretation of the area under a receiver operating characteristic (ROC) curve obtained by the "rating" method, or by mathematical predictions based on patient characteristics, is presented. It is shown that in such a setting the area represents the probability that a randomly chosen diseased subject is (correctly) rated or ranked with greater suspicion than a randomly chosen non-diseased subject. Moreover, this probability of a correct ranking is the same quantity that is estimated by the already well-studied nonparametric Wilcoxon statistic. These two relationships are exploited to (a) provide rapid closed-form expressions for the approximate magnitude of the sampling variability, i.e., standard error that one uses to accompany the area under a smoothed ROC curve, (b) guide in determining the size of the sample required to provide a sufficiently reliable estimate of this area, and (c) determine how large sample sizes should be to ensure that one can statistically detect differences in the accuracy of diagnostic techniques.
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                Author and article information

                Contributors
                Role: Handling Editor
                Journal
                Curr Zool
                Curr Zool
                czoolo
                Current Zoology
                Oxford University Press (UK )
                1674-5507
                2396-9814
                April 2024
                14 March 2023
                14 March 2023
                : 70
                : 2
                : 150-162
                Affiliations
                Department of Zoology, Comenius University in Bratislava , Bratislava, Slovakia
                Global Biology , Birr, Switzerland
                Pakistan Museum of Natural History , Shakarparian, Islamabad, Pakistan
                Severtsov Institute of Ecology and Evolution, Russian Academy of Sciences , Moscow, Russia
                T. I. Vyazemski Karadag Scientific Station—Nature Reserve—Branch of A.O. Kovalevsky Institute of Biology of the Southern Seas , Theodosia, Crimea
                Zoological Institute of the RAS , Saint Petersbourg, Russia
                Institute of Zoology, Academy of Sciences of the Republic of Uzbekistan , Yunusabad, Tashkent, Uzbekistan
                Museum Koenig Bonn, LIB—Leibniz Institute for the Analysis of Biodiversity Change , Bonn, Germany
                UFZ – Helmholtz Centre for Environmental Research, Department of Conservation Biology , Permoserstrasse 15, 04318 Leipzig, Germany
                Author notes
                Address correspondence to Daniel Jablonski. E-mail: daniel.jablonski@ 123456uniba.sk
                Address correspondence to Sylvia Hofmann. E-mail: s.hofmann@ 123456leibniz-lib.de .
                Author information
                https://orcid.org/0000-0002-5394-0114
                https://orcid.org/0000-0003-0621-9049
                Article
                zoad008
                10.1093/cz/zoad008
                11078056
                38726254
                22bf587e-0193-4de6-903b-a9eeed5a05c2
                © The Author(s) 2023. Published by Oxford University Press on behalf of Editorial Office, Current Zoology.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial License ( https://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com

                History
                : 02 October 2022
                : 02 March 2023
                : 12 May 2023
                Page count
                Pages: 13
                Funding
                Funded by: Slovak Research and Development Agency, DOI 10.13039/501100005357;
                Award ID: APVV-19-0076
                Award ID: VEGA 1/0242/21
                Funded by: Scientific Grant Agency, DOI 10.13039/501100006109;
                Funded by: German Research Foundation, DOI 10.13039/501100001659;
                Award ID: HO 3792/8-1
                Funded by: National Environmental Protection Agency;
                Award ID: 12429
                Award ID: 12455
                Categories
                Original Articles
                AcademicSubjects/SCI01080
                AcademicSubjects/SCI01130
                AcademicSubjects/SCI01130

                biogeography,colonization,eurasia,genetic diversity,mitochondrial dna,paratethys,refugia,water snakes

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