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      Novel Symbiotic Association Between Euwallacea Ambrosia Beetle and Fusarium Fungus on Fig Trees in Japan

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          Abstract

          Ficus carica plantations in Japan were first reported to be infested by an ambrosia beetle species, identified as Euwallacea interjectus, in 1996. The purpose of this study was to determine the symbiotic fungi of female adults of E. interjectus emerging from F. carica trees infected with fig wilt disease (FWD). Dispersal adults (51 females) of E. interjectus, which were collected from logs of an infested fig tree in Hiroshima Prefecture, Western Japan, were separated into three respective body parts (head, thorax, and abdomen) and used for fungal isolation. Isolated fungi were identified based on the morphological characteristics and DNA sequence data. Over 13 species of associated fungi were detected, of which a specific fungus, Fusarium kuroshium, was dominant in female head (including oral mycangia). The plant-pathogenic fungus of FWD, Ceratocystis ficicola, was not observed within any body parts of E. interjectus. We further discussed the relationship among E. interjectus and its associated fungi in fig tree.

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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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            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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              ModelFinder: Fast Model Selection for Accurate Phylogenetic Estimates

              Model-based molecular phylogenetics plays an important role in comparisons of genomic data, and model selection is a key step in all such analyses. We present ModelFinder, a fast model-selection method that greatly improves the accuracy of phylogenetic estimates. The improvement is achieved by incorporating a model of rate-heterogeneity across sites not previously considered in this context, and by allowing concurrent searches of model-space and tree-space.
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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
                28 September 2021
                2021
                : 12
                : 725210
                Affiliations
                [1] 1Laboratory of Forest Protection, Graduate School of Bioagricultural Sciences, Nagoya University , Nagoya, Japan
                [2] 2Department of Forest Microbiology, Forestry and Forest Products Research Institute (FFPRI) , Tsukuba, Japan
                Author notes

                Edited by: Hassan Salem, Max Planck Institute for Developmental Biology, Max Planck Society (MPG), Germany

                Reviewed by: Zvi Mendel, Agricultural Research Organization (ARO), Israel; Kin-Ming (Clement) Tsui, Weill Cornell Medicine - Qatar, Qatar

                *Correspondence: Hisashi Kajimura, kajimura@ 123456agr.nagoya-u.ac.jp

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

                Article
                10.3389/fmicb.2021.725210
                8506114
                34650529
                fb079f88-0a08-41dc-a6b9-383ba60af9f6
                Copyright © 2021 Jiang, Masuya and Kajimura.

                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
                : 15 June 2021
                : 17 August 2021
                Page count
                Figures: 3, Tables: 2, Equations: 2, References: 71, Pages: 10, Words: 7914
                Funding
                Funded by: Japan Society for the Promotion of Science, doi 10.13039/501100001691;
                Award ID: 17H03831
                Award ID: 18KK0180
                Award ID: 19H02994
                Award ID: 20H03026
                Categories
                Microbiology
                Original Research

                Microbiology & Virology
                ambrosia fusarium clade,euwallacea interjectus,fig wilt disease,fusarium kuroshium,fusarium solani species complex,multi-gene phylogeny,mycangia

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