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      A Novel Parasitoid of Marine Dinoflagellates, Pararosarium dinoexitiosum gen. et sp. nov. (Perkinsozoa, Alveolata), Showing Characteristic Beaded Sporocytes

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      Frontiers in Microbiology
      Frontiers Media S.A.
      host range, parasitism, life cycle, phylogeny, ultrastructure

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          Abstract

          The phylum Perkinsozoa is known as an exclusively parasitic group within alveolates and is widely distributed in various aquatic environments from marine to freshwater environments. Nonetheless, their morphology, life cycle, the identity of the host, and physiological characteristics remain still poorly understood. During intensive sampling along the west coast of Korea in October and November 2017, a new parasitoid, which shares several characteristics with the extant families Perkinsidae and Parviluciferaceae, was discovered and three strains of the new parasitoid were successfully established in cultures. Cross-infection experiments showed that among the examined planktonic groups, only dinoflagellates were susceptible to the new parasitoid, with infections observed in species belonging to eight genera. Even though the new parasitoid shared many morphological and developmental characteristics with other Perkinsozoan parasites, it differed from them by its densely packed trophocyte structure without a large vacuole or hyaline material during the growth stage. These characteristics are common among Parviluciferaceae members. Furthermore, through palintomic extracellular sporogenesis, it produced characteristic interconnected sporocytes resembling a string of beads. Phylogenetic analyses based on the small subunit and large subunit ribosomal DNA sequences revealed that the new parasitoid was distantly related to the family Parviluciferaceae and was more closely related to the families Perkinsidae and Xcellidae. Morphological, ultrastructural, and molecular data on the new parasitoid raised the need to erect a new family, i.e., Pararosariidae, within the phylum Perkinsozoa with Pararosarium dinoexitiosum gen. et sp. nov. as the type species. The isolation and establishment in culture of the new parasitoid outside the family Parviluciferaceae in the present study would contribute to the better understanding of the diversity of Perkinsozoan parasites and provide useful material for comparisons to other parasite species in the further study.

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          Most cited references55

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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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            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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              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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                Author and article information

                Contributors
                Journal
                Front Microbiol
                Front Microbiol
                Front. Microbiol.
                Frontiers in Microbiology
                Frontiers Media S.A.
                1664-302X
                29 November 2021
                2021
                : 12
                : 748092
                Affiliations
                LOHABE, Department of Oceanography, Chonnam National University , Gwangju, South Korea
                Author notes

                Edited by: Gordon T. Taylor, Stony Brook University, United States

                Reviewed by: Fatma Gomaa, Woods Hole Oceanographic Institution, United States; Taylor Sehein, Woods Hole Oceanographic Institution, United States, contributed to the review of FG; Elisabet Alacid, University of Oxford, United Kingdom

                *Correspondence: Myung Gil Park, mpark@ 123456chonnam.ac.kr

                This article was submitted to Aquatic Microbiology, a section of the journal Frontiers in Microbiology

                Article
                10.3389/fmicb.2021.748092
                8667275
                34912310
                1c1e15f9-3644-4bc2-86cb-4ce835a20985
                Copyright © 2021 Jeon and Park.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

                History
                : 27 July 2021
                : 09 November 2021
                Page count
                Figures: 10, Tables: 1, Equations: 0, References: 55, Pages: 15, Words: 10950
                Funding
                Funded by: National Research Foundation of Korea, doi 10.13039/501100003725;
                Categories
                Microbiology
                Original Research

                Microbiology & Virology
                host range,parasitism,life cycle,phylogeny,ultrastructure
                Microbiology & Virology
                host range, parasitism, life cycle, phylogeny, ultrastructure

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