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      Species of Ergasilus von Nordmann, 1832 (Copepoda: Ergasilidae) from cichlid fishes in Lake Tanganyika

      research-article
      , ,
      Parasitology
      Cambridge University Press
      Africa, cichlids, diversity, parasitic crustaceans, Tanganyika

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          Abstract

          Abstract

          Ergasilus (von Nordmann, 1832) (Ergasilidae) is a species-rich group of parasitic copepods with a wide distribution in freshwater, marine and brackish environments. Up to now, 9 species of Ergasilus are known from cichlid fishes in Africa. In this study, 5 species, including 3 new, were collected from the gills of 12 cichlid species (11 genera: Bathybates, Ctenochromis, Eretmodus, Gnathochromis, Lamprologus, Neolamprologus, Ophthalmotilapia, Perissodus, Simochromis, Spathodus and Tanganicodus) of the northeastern shore of Lake Tanganyika in Burundi, namely E. macrodactylus (Sars, 1909), E. megacheir (Sars, 1909), E. caparti n. sp., E. parasarsi n. sp. and E. parvus n. sp. All species found were identified and described on the basis of adult female specimens using an integrative taxonomy approach mixing morphological characterization and molecular analyses of 2 ribosomal DNA markers (partial 18S and 28S rDNA sequences). An identification key for Ergasilus species from Lake Tanganyika is included. This study provides the first molecular data for Ergasilus species in Africa. The phylogenetic analyses suggest that the Ergasilus species parasitizing Lake Tanganyikan cichlids form a well-supported clade within the Ergasilidae. However, their phylogenetic relationships with other congeners still remain unclear due to a lack of molecular data for this diverse genus.

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          MAFFT Multiple Sequence Alignment Software Version 7: Improvements in Performance and Usability

          We report a major update of the MAFFT multiple sequence alignment program. This version has several new features, including options for adding unaligned sequences into an existing alignment, adjustment of direction in nucleotide alignment, constrained alignment and parallel processing, which were implemented after the previous major update. This report shows actual examples to explain how these features work, alone and in combination. Some examples incorrectly aligned by MAFFT are also shown to clarify its limitations. We discuss how to avoid misalignments, and our ongoing efforts to overcome such limitations.
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            IQ-TREE: A Fast and Effective Stochastic Algorithm for Estimating Maximum-Likelihood Phylogenies

            Large phylogenomics data sets require fast tree inference methods, especially for maximum-likelihood (ML) phylogenies. Fast programs exist, but due to inherent heuristics to find optimal trees, it is not clear whether the best tree is found. Thus, there is need for additional approaches that employ different search strategies to find ML trees and that are at the same time as fast as currently available ML programs. We show that a combination of hill-climbing approaches and a stochastic perturbation method can be time-efficiently implemented. If we allow the same CPU time as RAxML and PhyML, then our software IQ-TREE found higher likelihoods between 62.2% and 87.1% of the studied alignments, thus efficiently exploring the tree-space. If we use the IQ-TREE stopping rule, RAxML and PhyML are faster in 75.7% and 47.1% of the DNA alignments and 42.2% and 100% of the protein alignments, respectively. However, the range of obtaining higher likelihoods with IQ-TREE improves to 73.3-97.1%.
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              MEGA11: Molecular Evolutionary Genetics Analysis Version 11

              The Molecular Evolutionary Genetics Analysis (MEGA) software has matured to contain a large collection of methods and tools of computational molecular evolution. Here, we describe new additions that make MEGA a more comprehensive tool for building timetrees of species, pathogens, and gene families using rapid relaxed-clock methods. Methods for estimating divergence times and confidence intervals are implemented to use probability densities for calibration constraints for node-dating and sequence sampling dates for tip-dating analyses. They are supported by new options for tagging sequences with spatiotemporal sampling information, an expanded interactive Node Calibrations Editor , and an extended Tree Explorer to display timetrees. Also added is a Bayesian method for estimating neutral evolutionary probabilities of alleles in a species using multispecies sequence alignments and a machine learning method to test for the autocorrelation of evolutionary rates in phylogenies. The computer memory requirements for the maximum likelihood analysis are reduced significantly through reprogramming, and the graphical user interface has been made more responsive and interactive for very big data sets. These enhancements will improve the user experience, quality of results, and the pace of biological discovery. Natively compiled graphical user interface and command-line versions of MEGA11 are available for Microsoft Windows, Linux, and macOS from www.megasoftware.net .
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                Author and article information

                Journal
                Parasitology
                Parasitology
                PAR
                Parasitology
                Cambridge University Press (Cambridge, UK )
                0031-1820
                1469-8161
                June 2023
                20 March 2023
                : 150
                : 7
                : 579-598
                Affiliations
                [1]Department of Botany and Zoology, Faculty of Science, Masaryk University , Kotlářská 2, 611 37, Brno, Czech Republic
                Author notes
                Author for correspondence: Robert Míč, E-mail: 392384@ 123456muni.cz
                Author information
                https://orcid.org/0000-0001-7757-0632
                Article
                S0031182023000239
                10.1017/S0031182023000239
                10260305
                36938816
                cfbf22cc-b4b9-4ebc-bf89-cd33015b4313
                © The Author(s) 2023

                This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted re-use, distribution and reproduction, provided the original article is properly cited.

                History
                : 30 October 2022
                : 24 February 2023
                : 02 March 2023
                Page count
                Figures: 12, Tables: 9, References: 88, Pages: 20
                Categories
                Research Article

                Parasitology
                africa,cichlids,diversity,parasitic crustaceans,tanganyika
                Parasitology
                africa, cichlids, diversity, parasitic crustaceans, tanganyika

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