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      Geographic Distribution, Genetic Variability and Biological Properties of Rice Orange Leaf Phytoplasma in Southeast Asia

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          Abstract

          Rice orange leaf phytoplasma (ROLP) causes clear orange to yellowish leaf discoloration and severe stunting in rice seedlings. The ecological and biological characteristics of ROLP are largely unknown because the disease has not widely caused serious problems in rice cultivated areas, thereby leading to the low accumulation of research data. However, in the past decade, the disease became a threat to rice production, particularly in South China and India; it has also been recognised in other Asian countries, such as Vietnam, Thailand and the Philippines. Here, we observed the occurrence of ROLP in paddies of the Southeast Asian counties (Cambodia, Vietnam and the Philippines) and found that the isolates in the Philippines and Vietnam were monophyletic, while those in India, Thailand and Cambodia were more diverse, suggesting their potential origins. In Cambodia, it was revealed that following polymerase chain reaction (PCR) detection, the known ROLP-insect vectors, N. virescens Distant and Recilia dorsalis Motchulsky, were ROLP-positive, indicating their roles in pathogen dispersal. Moreover, fluorescent and scanning electron microscopy revealed the intensive accumulation of the phytoplasma in phloem tissues and massive accumulation of storage starch in vascular bundle sheath and parenchyma. Altogether, this study illustrated the genetic variability of global ROLP isolates and the pathogen’s biological impact on rice tissue.

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          Most cited references42

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          New algorithms and methods to estimate maximum-likelihood phylogenies: assessing the performance of PhyML 3.0.

          PhyML is a phylogeny software based on the maximum-likelihood principle. Early PhyML versions used a fast algorithm performing nearest neighbor interchanges to improve a reasonable starting tree topology. Since the original publication (Guindon S., Gascuel O. 2003. A simple, fast and accurate algorithm to estimate large phylogenies by maximum likelihood. Syst. Biol. 52:696-704), PhyML has been widely used (>2500 citations in ISI Web of Science) because of its simplicity and a fair compromise between accuracy and speed. In the meantime, research around PhyML has continued, and this article describes the new algorithms and methods implemented in the program. First, we introduce a new algorithm to search the tree space with user-defined intensity using subtree pruning and regrafting topological moves. The parsimony criterion is used here to filter out the least promising topology modifications with respect to the likelihood function. The analysis of a large collection of real nucleotide and amino acid data sets of various sizes demonstrates the good performance of this method. Second, we describe a new test to assess the support of the data for internal branches of a phylogeny. This approach extends the recently proposed approximate likelihood-ratio test and relies on a nonparametric, Shimodaira-Hasegawa-like procedure. A detailed analysis of real alignments sheds light on the links between this new approach and the more classical nonparametric bootstrap method. Overall, our tests show that the last version (3.0) of PhyML is fast, accurate, stable, and ready to use. A Web server and binary files are available from http://www.atgc-montpellier.fr/phyml/.
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            MAFFT online service: multiple sequence alignment, interactive sequence choice and visualization

            Abstract This article describes several features in the MAFFT online service for multiple sequence alignment (MSA). As a result of recent advances in sequencing technologies, huge numbers of biological sequences are available and the need for MSAs with large numbers of sequences is increasing. To extract biologically relevant information from such data, sophistication of algorithms is necessary but not sufficient. Intuitive and interactive tools for experimental biologists to semiautomatically handle large data are becoming important. We are working on development of MAFFT toward these two directions. Here, we explain (i) the Web interface for recently developed options for large data and (ii) interactive usage to refine sequence data sets and MSAs.
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              'Candidatus Phytoplasma', a taxon for the wall-less, non-helical prokaryotes that colonize plant phloem and insects.

              The trivial name 'phytoplasma' has been adopted to collectively name wall-less, non-helical prokaryotes that colonize plant phloem and insects, which were formerly known as mycoplasma-like organisms. Although phytoplasmas have not yet been cultivated in vitro, phylogenetic analyses based on various conserved genes have shown that they represent a distinct, monophyletic clade within the class Mollicutes. It is proposed here to accommodate phytoplasmas within the novel genus 'Candidatus (Ca.) Phytoplasma'. Given the diversity within 'Ca. Phytoplasma', several subtaxa are needed to accommodate organisms that share 97.5% similar to those of other 'Ca. Phytoplasma' species, are characterized by distinctive biological, phytopathological and genetic properties. These include 'Ca. Phytoplasma pyri' (associated with pear decline), 'Ca. Phytoplasma prunorum' (associated with European stone fruit yellows), 'Ca. Phytoplasma spartii' (associated with spartium witches'-broom), 'Ca. Phytoplasma rhamni' (associated with buckthorn witches'-broom), 'Ca. Phytoplasma allocasuarinae' (associated with allocasuarina yellows), 'Ca. Phytoplasma ulmi' (associated with elm yellows) and an additional taxon for the stolbur phytoplasma. Conversely, some organisms, despite their 16S rRNA gene sequence being <97.5% similar to that of any other 'Ca. Phytoplasma' species, are not presently described as Candidatus species, due to their poor overall characterization.
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                Author and article information

                Contributors
                Role: Academic Editor
                Journal
                Pathogens
                Pathogens
                pathogens
                Pathogens
                MDPI
                2076-0817
                04 February 2021
                February 2021
                : 10
                : 2
                : 169
                Affiliations
                [1 ]Department of Crop Protection, Faculty of Agronomy, Royal University of Agriculture, Ministry of Agriculture, Forestry and Fisheries, Dangkor District, Phnom Penh 370, Cambodia; osocheath@ 123456rua.edu.kh
                [2 ]Nagoya University Asian Satellite Campuses Institute—Cambodian Campus, Royal University of Agriculture, Dangkor District, Phnom Penh 370, Cambodia; soriya.kcj@ 123456gmail.com (S.R.); I.Choi@ 123456irri.org (I.-R.C.)
                [3 ]Rice Breeding Platform, International Rice Research Institute, Los Baños, Laguna 4031, Philippines; G.Jonson@ 123456irri.org
                [4 ]Department of Agricultural and Food Sciences, University of Bologna, Viale G. Fanin, 40127 Bologna, Italy; matteo.calassanzio@ 123456gmail.com
                [5 ]Renolab Good Laboratory Practice, A Tentamus Company, Via XXV Aprile, San Giorgio di Piano, 40016 Bologna, Italy
                [6 ]General Directorate of Agriculture, Ministry of Agriculture, Forestry and Fisheries, Tuol Kork, Phnom Penh 370, Cambodia; thyrith72@ 123456gmail.com (C.C.); chhay.ipm@ 123456gmail.com (C.N.)
                [7 ]Department of Plant Production Sciences, Graduate School of Bioagricultural Sciences, Nagoya University, Chikusa-ku, Nagoya 464-8601, Japan; oitaka@ 123456agr.nagoya-u.ac.jp (T.O.); isato@ 123456agr.nagoya-u.ac.jp (I.S.); dtakemo@ 123456agr.nagoya-u.ac.jp (D.T.); totanaka@ 123456agr.nagoya-u.ac.jp (T.T.)
                [8 ]International Rice Research Institute—Korea Office, National Institute of Crop Science, Wanju-Gun 235, Jeollabuk-Do, Korea
                Author notes
                Author information
                https://orcid.org/0000-0003-0097-8634
                Article
                pathogens-10-00169
                10.3390/pathogens10020169
                7913950
                33557226
                27bf6036-39af-44df-b775-04cfa7e8e33b
                © 2021 by the authors.

                Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ( http://creativecommons.org/licenses/by/4.0/).

                History
                : 25 December 2020
                : 29 January 2021
                Categories
                Article

                rice orange leaf phytoplasma,candidatus phytoplasma asteris 16sri-b subgroup,genetic divergence,dapi staining,scanning electron microscopy,storage starch accumulation

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