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      The Genus Pratylenchus (Nematoda: Pratylenchidae) in Israel: From Taxonomy to Control Practices

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          Abstract

          Due to Israel’s successful agricultural production and diverse climatic conditions, plant-parasitic nematodes are flourishing. The occurrence of new, previously unidentified species in Israel or of suggested new species worldwide is a consequence of the continuous withdrawal of efficient nematicides. Among plant-parasitic nematodes, migratory endoparasitic species of the genus Pratylenchus are widely distributed in vegetable and crop fields in Israel and are associated with major reductions in quality and yield. This review focuses on the occurrence, distribution, diagnosis, pathogenicity, and phylogeny of all Pratylenchus species recorded over the last few decades on different crops grown throughout Israel—covering early information from nematologists to recent reports involving the use of molecular phylogenetic methodologies. We explore the accepted distinction between Pratylenchus thornei and Pratylenchus mediterraneus isolated from Israel’s northern Negev region, and address the confusion concerning the findings related to these Pratylenchus species. Our recent sampling from the northern Negev revealed the occurrence of both P. thornei and P. mediterraneus on the basis of molecular identification, indicating P. mediterraneus as a sister species of P. thornei and their potential occurrence in a mixed infection. Finally, the efficiencies of common control measures taken to reduce Pratylenchus’ devastating damage in protected crops and field crops is discussed.

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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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            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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              A rapid bootstrap algorithm for the RAxML Web servers.

              Despite recent advances achieved by application of high-performance computing methods and novel algorithmic techniques to maximum likelihood (ML)-based inference programs, the major computational bottleneck still consists in the computation of bootstrap support values. Conducting a probably insufficient number of 100 bootstrap (BS) analyses with current ML programs on large datasets-either with respect to the number of taxa or base pairs-can easily require a month of run time. Therefore, we have developed, implemented, and thoroughly tested rapid bootstrap heuristics in RAxML (Randomized Axelerated Maximum Likelihood) that are more than an order of magnitude faster than current algorithms. These new heuristics can contribute to resolving the computational bottleneck and improve current methodology in phylogenetic analyses. Computational experiments to assess the performance and relative accuracy of these heuristics were conducted on 22 diverse DNA and AA (amino acid), single gene as well as multigene, real-world alignments containing 125 up to 7764 sequences. The standard BS (SBS) and rapid BS (RBS) values drawn on the best-scoring ML tree are highly correlated and show almost identical average support values. The weighted RF (Robinson-Foulds) distance between SBS- and RBS-based consensus trees was smaller than 6% in all cases (average 4%). More importantly, RBS inferences are between 8 and 20 times faster (average 14.73) than SBS analyses with RAxML and between 18 and 495 times faster than BS analyses with competing programs, such as PHYML or GARLI. Moreover, this performance improvement increases with alignment size. Finally, we have set up two freely accessible Web servers for this significantly improved version of RAxML that provide access to the 200-CPU cluster of the Vital-IT unit at the Swiss Institute of Bioinformatics and the 128-CPU cluster of the CIPRES project at the San Diego Supercomputer Center. These Web servers offer the possibility to conduct large-scale phylogenetic inferences to a large part of the community that does not have access to, or the expertise to use, high-performance computing resources.
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                Author and article information

                Journal
                Plants (Basel)
                Plants (Basel)
                plants
                Plants
                MDPI
                2223-7747
                02 November 2020
                November 2020
                : 9
                : 11
                : 1475
                Affiliations
                [1 ]Volcani Center, Department of Entomology, Nematology and Chemistry Units, Agricultural Research Organization (ARO), Rishon Lezion 15159, Israel; pbucki@ 123456volcani.agri.gov.il (P.B.); xueqing4083@ 123456gmail.com (X.Q.)
                [2 ]Department of Plant Protection, Nanjing Agricultural University, Nanjing 210095, China
                [3 ]Institute for Sustainable Agriculture, Spanish National Research Council, 14004 Cordoba, Spain; p.castillo@ 123456csic.es
                [4 ]Volcani Center, Laboratory for Pest Management Research, Institute of Agricultural Engineering, ARO, Rishon Lezion 15159, Israel; agamliel@ 123456volcani.agri.gov.il
                [5 ]Extension Service (Shaham), Israel Ministry of Agriculture and Rural Development, Rishon Lezion 15159, Israel; svetyd@ 123456gmail.com (S.D.); tamalon6@ 123456gmail.com (T.A.)
                Author notes
                Author information
                https://orcid.org/0000-0003-0256-876X
                Article
                plants-09-01475
                10.3390/plants9111475
                7716202
                33147883
                3f9ca258-015a-4d27-9b64-42a2116d9737
                © 2020 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
                : 11 October 2020
                : 29 October 2020
                Categories
                Review

                pratylenchus,root lesion nematode,pathogenicity,distribution,molecular phylogeny,taxonomy,control management practices

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