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      Alternaria species in section Alternaria associated with Iris plants in China

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          Abstract

          Plants of the Iris genus have been widely cultivated because of their medicinal, ornamental, and economic values. It commonly suffers from Alternaria leaf spot or blight disease leading to considerable losses for their commercial values. During an investigation of 14 provinces or municipalities of China from 2014 to 2022, a total of 122 Alternaria strains in section Alternaria were obtained from diseased leaves of Iris spp.. Among them, 12 representative strains were selected and identified based on morphological characterization and multi-locus phylogenetic analysis, which encompassed the internal transcribed spacer of rDNA region (ITS), glyceraldehyde-3-phosphate dehydrogenase ( GAPDH), translation elongation factor 1 alpha ( TEF1), RNA polymerase second largest subunit ( RPB2), Alternaria major allergen gene ( Alt a 1), an anonymous gene region (OPA10-2), and endopolygalacturonase gene ( EndoPG). The strains comprised two known species of A. alternata and A. iridicola, and two new species of A. setosae and A. tectorum, which were described and illustrated here. Their pathogenicity evaluated on Iris setosa indicated that all the strains could induce typical Alternaria leaf spot or blight symptoms. The results showed that the virulence was variable among those four species, from which A. tectorum sp. nov. was the most virulent one, followed by A. setosae sp. nov., A. iridicola and A. alternata.

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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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            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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              AMPLIFICATION AND DIRECT SEQUENCING OF FUNGAL RIBOSOMAL RNA GENES FOR PHYLOGENETICS

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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
                21 October 2022
                2022
                : 13
                : 1036950
                Affiliations
                [1] 1Department of Plant Protection, College of Agriculture, Yangtze University , Jingzhou, China
                [2] 2National Key Laboratory of Wheat and Maize Crop Science, Agronomy College, Henan Agricultural University , Zhengzhou, China
                Author notes

                Edited by: Nakarin Suwannarach, Chiang Mai University, Thailand

                Reviewed by: Danushka Sandaruwan Tennakoon, Chiang Mai University, Thailand; Rungtiwa Phookamsak, Kunming Institute of Botany (CAS), China; Mingkwan Doilom, Zhongkai University of Agriculture and Engineering, China

                *Correspondence: Jian-Xin Deng, djxin555@ 123456yangtzeu.edu.cn

                This article was submitted to Microbe and Virus Interactions with Plants, a section of the journal Frontiers in Microbiology

                Article
                10.3389/fmicb.2022.1036950
                9635052
                9cd65feb-490e-432b-9fd4-962156fbb642
                Copyright © 2022 Gou, Aung, Htun, Huang and Deng.

                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
                : 05 September 2022
                : 03 October 2022
                Page count
                Figures: 7, Tables: 4, Equations: 0, References: 63, Pages: 14, Words: 7553
                Funding
                Funded by: National Natural Science Foundation of China , doi 10.13039/501100001809;
                Award ID: 31400014
                Award ID: 32270022
                Categories
                Microbiology
                Original Research

                Microbiology & Virology
                alternaria,iris,morphology,phylogenetic analysis,pathogenicity
                Microbiology & Virology
                alternaria, iris, morphology, phylogenetic analysis, pathogenicity

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