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      Lack of an Intron in Cytochrome b and Overexpression of Sterol 14α-Demethylase Indicate a Potential Risk for QoI and DMI Resistance Development in Neophysopella spp. on Grapes

      1 , 1 , 2 , 1 , 2 , 3
      Phytopathology®
      Scientific Societies

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          Abstract

          Asian grapevine leaf rust, caused by Neophysopella meliosmae-myrianthae and N. tropicalis, is often controlled by quinone outside inhibitor (QoI) and demethylation inhibitor (DMI) fungicides in Brazil. Here, we evaluated the sensitivity of 55 Neophysopella spp. isolates to pyraclostrobin (QoI) and tebuconazole (DMI). To elucidate the resistance mechanisms, we analyzed the sequences of the cytochrome b (CYTB) and cytochrome P450 sterol 14α-demethylase (CYP51) target proteins of QoI and DMI fungicides, respectively. The CYP51 expression levels were also determined in a selection of isolates. In leaf disc assays, the mean 50% effective concentration (EC 50) value for pyraclostrobin was about 0.040 µg/ml for both species. CYTB sequences were identical among all 55 isolates, which did not contain an intron immediately after codon 143. No amino acid substitution was identified at codons 129, 137, and 143. The mean EC 50 value for tebuconazole was 0.62 µg/ml for N. tropicalis and 0.46 µg/ml for N. meliosmae-myrianthae, and no CYP51 sequence variation was identified among isolates of the same species. However, five N. meliosmae-myrianthae isolates grew on leaf discs treated at 10 µg/ml tebuconazole, and these were further exposed to tebuconazole selection pressure. Tebuconazole-adapted laboratory isolates of N. meliosmae-myrianthae showed an eight- to 25-fold increase in resistance after four rounds of selection that was not associated with CYP51 target alterations. In comparison with sensitive isolates, CYP51 expression was induced in the presence of tebuconazole in three out of four tebuconazole-adapted isolates tested. These results suggest a potential risk for QoI and DMI resistance development in Neophysopella spp.

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          Analysis of relative gene expression data using real-time quantitative PCR and the 2(-Delta Delta C(T)) Method.

          The two most commonly used methods to analyze data from real-time, quantitative PCR experiments are absolute quantification and relative quantification. Absolute quantification determines the input copy number, usually by relating the PCR signal to a standard curve. Relative quantification relates the PCR signal of the target transcript in a treatment group to that of another sample such as an untreated control. The 2(-Delta Delta C(T)) method is a convenient way to analyze the relative changes in gene expression from real-time quantitative PCR experiments. The purpose of this report is to present the derivation, assumptions, and applications of the 2(-Delta Delta C(T)) method. In addition, we present the derivation and applications of two variations of the 2(-Delta Delta C(T)) method that may be useful in the analysis of real-time, quantitative PCR data. Copyright 2001 Elsevier Science (USA).
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            MEGA X: Molecular Evolutionary Genetics Analysis across Computing Platforms.

            The Molecular Evolutionary Genetics Analysis (Mega) software implements many analytical methods and tools for phylogenomics and phylomedicine. Here, we report a transformation of Mega to enable cross-platform use on Microsoft Windows and Linux operating systems. Mega X does not require virtualization or emulation software and provides a uniform user experience across platforms. Mega X has additionally been upgraded to use multiple computing cores for many molecular evolutionary analyses. Mega X is available in two interfaces (graphical and command line) and can be downloaded from www.megasoftware.net free of charge.
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              Geneious Basic: An integrated and extendable desktop software platform for the organization and analysis of sequence data

              Summary: The two main functions of bioinformatics are the organization and analysis of biological data using computational resources. Geneious Basic has been designed to be an easy-to-use and flexible desktop software application framework for the organization and analysis of biological data, with a focus on molecular sequences and related data types. It integrates numerous industry-standard discovery analysis tools, with interactive visualizations to generate publication-ready images. One key contribution to researchers in the life sciences is the Geneious public application programming interface (API) that affords the ability to leverage the existing framework of the Geneious Basic software platform for virtually unlimited extension and customization. The result is an increase in the speed and quality of development of computation tools for the life sciences, due to the functionality and graphical user interface available to the developer through the public API. Geneious Basic represents an ideal platform for the bioinformatics community to leverage existing components and to integrate their own specific requirements for the discovery, analysis and visualization of biological data. Availability and implementation: Binaries and public API freely available for download at http://www.geneious.com/basic, implemented in Java and supported on Linux, Apple OSX and MS Windows. The software is also available from the Bio-Linux package repository at http://nebc.nerc.ac.uk/news/geneiousonbl. Contact: peter@biomatters.com
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                Author and article information

                Contributors
                (View ORCID Profile)
                (View ORCID Profile)
                Journal
                Phytopathology®
                Phytopathology®
                Scientific Societies
                0031-949X
                1943-7684
                October 2021
                October 2021
                : 111
                : 10
                : 1726-1734
                Affiliations
                [1 ]Department of Plant Pathology and Nematology, “Luiz de Queiroz” College of Agriculture, University of São Paulo, Piracicaba, São Paulo, 13418-900, Brazil
                [2 ]Biointeractions and Crop Protection Department, Rothamsted Research, Harpenden, Hertfordshire, AL5 2JQ, United Kingdom
                [3 ]National Institute of Agricultural Botany, Cambridge, Cambridgeshire, CB3 0LE, United Kingdom
                Article
                10.1094/PHYTO-11-20-0514-R
                2fe047c1-5843-490c-a8ca-6e395bfeeba5
                © 2021
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