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      The out-of-India hypothesis: evidence from an ancient centipede genus, Rhysida (Chilopoda: Scolopendromorpha) from the Oriental Region, and systematics of Indian species

      1 , 2 , 1
      Zoological Journal of the Linnean Society
      Oxford University Press (OUP)

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          Abstract

          The Oriental Region has been a focus of biogeographical research for more than two centuries. We examined systematics and biogeography of the centipede genus Rhysida in this region. A robust species hypothesis for the Indian subcontinental and Southeast Asian Rhysida clade uses molecular, morphological and distribution data. Twelve species are recognized in two monophyletic species complexes, eight belonging to the Rhysida immarginata and four to the Rhysida longipes species complex. They include Rhysida aspinosa, Rhysida crassispina, R. immarginata, R. longipes and seven new species, five of which are formally named in this paper: Rhysida ikhalama, Rhysida konda, Rhysida lewisi, Rhysida pazhuthara and Rhysida sada The nine Rhysida species are documented taxonomically and their morphological variation is reviewed. An integrative systematic approach reveals that diversity of Rhysida in the Indian subcontinent has been underestimated. Both species complexes started to diversify in the Early to Late Cretaceous in the Indian subcontinent. The out-of-India hypothesis is supported in both clades, because Southeast Asian species are nested in Indian subcontinental clades. Historical biogeographical analyses suggest two independent post-collision dispersal events, one in the immarginata clade and another where R. longipes expanded its range into Southeast Asia.

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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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            MUSCLE: multiple sequence alignment with high accuracy and high throughput.

            We describe MUSCLE, a new computer program for creating multiple alignments of protein sequences. Elements of the algorithm include fast distance estimation using kmer counting, progressive alignment using a new profile function we call the log-expectation score, and refinement using tree-dependent restricted partitioning. The speed and accuracy of MUSCLE are compared with T-Coffee, MAFFT and CLUSTALW on four test sets of reference alignments: BAliBASE, SABmark, SMART and a new benchmark, PREFAB. MUSCLE achieves the highest, or joint highest, rank in accuracy on each of these sets. Without refinement, MUSCLE achieves average accuracy statistically indistinguishable from T-Coffee and MAFFT, and is the fastest of the tested methods for large numbers of sequences, aligning 5000 sequences of average length 350 in 7 min on a current desktop computer. The MUSCLE program, source code and PREFAB test data are freely available at http://www.drive5. com/muscle.
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              Posterior Summarization in Bayesian Phylogenetics Using Tracer 1.7

              Abstract Bayesian inference of phylogeny using Markov chain Monte Carlo (MCMC) plays a central role in understanding evolutionary history from molecular sequence data. Visualizing and analyzing the MCMC-generated samples from the posterior distribution is a key step in any non-trivial Bayesian inference. We present the software package Tracer (version 1.7) for visualizing and analyzing the MCMC trace files generated through Bayesian phylogenetic inference. Tracer provides kernel density estimation, multivariate visualization, demographic trajectory reconstruction, conditional posterior distribution summary, and more. Tracer is open-source and available at http://beast.community/tracer.
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                Author and article information

                Contributors
                (View ORCID Profile)
                Journal
                Zoological Journal of the Linnean Society
                Oxford University Press (OUP)
                0024-4082
                1096-3642
                July 2020
                June 27 2020
                December 16 2019
                July 2020
                June 27 2020
                December 16 2019
                : 189
                : 3
                : 828-861
                Affiliations
                [1 ]The Natural History Museum, London, UK
                [2 ]Centre for Ecological Sciences, Indian Institute of Science, Bangalore, India
                Article
                10.1093/zoolinnean/zlz138
                3881cabd-146b-4365-8bf0-8f55176c7b59
                © 2019

                https://academic.oup.com/journals/pages/open_access/funder_policies/chorus/standard_publication_model

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