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      Multiple contact zones and karyotypic evolution in a neotropical frog species complex

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          Abstract

          Previous studies of DNA sequence and karyotypic data have revealed high genetic diversity in the Physalaemus cuvieri – Physalaemus ephippifer species complex—a group of small leptodactylid frogs in South America. To date, seven major genetic lineages have been recognized in this group, with species delimitation tests supporting four to seven of them as valid species. Among these, only P. ephippifer shows heteromorphic sex chromosomes, but the implications of cytogenetic divergence for the evolution of this group are unknown. We analyzed karyotypic, mitochondrial DNA, and 3RAD genomic data to characterize a putative contact zone between P. ephippifer and P. cuvieri Lineage 1, finding evidence for admixture and karyotypic evolution. We also describe preliminary evidence for admixture between two other members of this species complex—Lineage 1 and Lineage 3 of P. cuvieri. Our study sheds new light on evolutionary relationships in the P. cuvieri – P. ephippifer species complex, suggesting an important role of karyotypic divergence in its evolutionary history and underscoring the importance of hybridization as a mechanism of sex chromosome evolution in amphibians.

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          MEGA7: Molecular Evolutionary Genetics Analysis Version 7.0 for Bigger Datasets.

          We present the latest version of the Molecular Evolutionary Genetics Analysis (Mega) software, which contains many sophisticated methods and tools for phylogenomics and phylomedicine. In this major upgrade, Mega has been optimized for use on 64-bit computing systems for analyzing larger datasets. Researchers can now explore and analyze tens of thousands of sequences in Mega The new version also provides an advanced wizard for building timetrees and includes a new functionality to automatically predict gene duplication events in gene family trees. The 64-bit Mega is made available in two interfaces: graphical and command line. The graphical user interface (GUI) is a native Microsoft Windows application that can also be used on Mac OS X. The command line Mega is available as native applications for Windows, Linux, and Mac OS X. They are intended for use in high-throughput and scripted analysis. Both versions are available from www.megasoftware.net free of charge.
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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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              Detecting the number of clusters of individuals using the software structure: a simulation study

              The identification of genetically homogeneous groups of individuals is a long standing issue in population genetics. A recent Bayesian algorithm implemented in the software STRUCTURE allows the identification of such groups. However, the ability of this algorithm to detect the true number of clusters (K) in a sample of individuals when patterns of dispersal among populations are not homogeneous has not been tested. The goal of this study is to carry out such tests, using various dispersal scenarios from data generated with an individual-based model. We found that in most cases the estimated 'log probability of data' does not provide a correct estimation of the number of clusters, K. However, using an ad hoc statistic DeltaK based on the rate of change in the log probability of data between successive K values, we found that STRUCTURE accurately detects the uppermost hierarchical level of structure for the scenarios we tested. As might be expected, the results are sensitive to the type of genetic marker used (AFLP vs. microsatellite), the number of loci scored, the number of populations sampled, and the number of individuals typed in each sample.
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                Author and article information

                Contributors
                lucashenriquebs18@gmail.com
                Journal
                Sci Rep
                Sci Rep
                Scientific Reports
                Nature Publishing Group UK (London )
                2045-2322
                11 January 2024
                11 January 2024
                2024
                : 14
                : 1119
                Affiliations
                [1 ]GRID grid.411087.b, ISNI 0000 0001 0723 2494, Laboratório de Estudos Cromossômicos (LabEsC), Departamento de Biologia Estrutural e Funcional, Instituto de Biologia, , Universidade Estadual de Campinas (UNICAMP), ; Campinas, SP 13083-863 Brazil
                [2 ]Department of Ecology, Evolution, and Organismal Biology, Kennesaw State University, ( https://ror.org/00jeqjx33) Kennesaw, GA USA
                [3 ]Laboratorio de Genética Evolutiva “Dr. Claudio J. Bidau”, Instituto de Biología Subtropical (CONICET-UNaM), Facultad de Ciencias Exactas, Químicas y Naturales, Universidad Nacional de Misiones, ( https://ror.org/03kr8x191) Posadas, Misiones Argentina
                [4 ]Departamento de Biologia, Centro de Ciências Biológicas e da Saúde, Universidade Federal do Maranhão (UFMA), ( https://ror.org/043fhe951) Campus do Bacanga, São Luís, MA 65080-040 Brazil
                [5 ]GRID grid.501791.b, Instituto de Biología Subtropical (CONICET-UNaM), ; Puerto Iguazú, Argentina
                [6 ]Departamento de Biodiversidade and Centro de Aquicultura (CAUNESP), Instituto de Biociências, Universidade Estadual Paulista, ( https://ror.org/00987cb86) Rio Claro, SP Brazil
                Article
                51421
                10.1038/s41598-024-51421-z
                10784582
                38212602
                d39010d1-4e83-41a5-92d2-3226d321321a
                © The Author(s) 2024

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 10 July 2023
                : 4 January 2024
                Funding
                Funded by: Brazilian Agency São Paulo Research Foundation
                Award ID: #2017/15842-8
                Award Recipient :
                Categories
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                Custom metadata
                © Springer Nature Limited 2024

                Uncategorized
                chromosomes,population genetics,speciation,cytogenetics
                Uncategorized
                chromosomes, population genetics, speciation, cytogenetics

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