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      CsWAKL08, a pathogen-induced wall-associated receptor-like kinase in sweet orange, confers resistance to citrus bacterial canker via ROS control and JA signaling

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          Abstract

          Citrus bacterial canker (CBC) is a disease resulting from Xanthomonas citri subsp. citri (Xcc) infection and poses a grave threat to citrus production worldwide. Wall-associated receptor-like kinases (WAKLs) are proteins with a central role in resisting a range of fungal and bacterial diseases. The roles of WAKLs in the context of CBC resistance, however, remain unclear. Here, we explored the role of CsWAKL08, which confers resistance to CBC, and we additionally analyzed the molecular mechanisms of CsWAKL08-mediated CBC resistance. Based on systematic annotation and induced expression analysis of the CsWAKL family in Citrus sinensis, CsWAKL08 was identified as a candidate that can be upregulated by Xcc infection in the CBC-resistant variety. CsWAKL08 can also be induced by the phytohormones salicylic acid (SA) and methyl jasmonic acid (MeJA) and spans the plasma membrane. Overexpression of CsWAKL08 resulted in strong CBC resistance in transgenic sweet oranges, whereas silencing of CsWAKL08 resulted in susceptibility to CBC. The peroxidase (POD) and superoxide dismutase (SOD) activities were significantly enhanced in the CsWAKL08-overexpressing plants compared to the control plants, thereby mediating reactive oxygen species (ROS) homeostasis in the transgenic plants. Moreover, the JA levels and the expression of JA biosynthesis and JA responsive genes were substantially elevated in the CsWAKL08 overexpression plants relative to the controls upon Xcc infection. Based on these findings, we conclude that the wall-associated receptor-like kinase CsWAKL08 positively regulates CBC resistance through a mechanism involving ROS control and JA signaling. These results further highlight the importance of this kinase family in plant pathogen resistance.

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          Prediction of protein subcellular localization.

          Because the protein's function is usually related to its subcellular localization, the ability to predict subcellular localization directly from protein sequences will be useful for inferring protein functions. Recent years have seen a surging interest in the development of novel computational tools to predict subcellular localization. At present, these approaches, based on a wide range of algorithms, have achieved varying degrees of success for specific organisms and for certain localization categories. A number of authors have noticed that sequence similarity is useful in predicting subcellular localization. For example, Nair and Rost (Protein Sci 2002;11:2836-2847) have carried out extensive analysis of the relation between sequence similarity and identity in subcellular localization, and have found a close relationship between them above a certain similarity threshold. However, many existing benchmark data sets used for the prediction accuracy assessment contain highly homologous sequences-some data sets comprising sequences up to 80-90% sequence identity. Using these benchmark test data will surely lead to overestimation of the performance of the methods considered. Here, we develop an approach based on a two-level support vector machine (SVM) system: the first level comprises a number of SVM classifiers, each based on a specific type of feature vectors derived from sequences; the second level SVM classifier functions as the jury machine to generate the probability distribution of decisions for possible localizations. We compare our approach with a global sequence alignment approach and other existing approaches for two benchmark data sets-one comprising prokaryotic sequences and the other eukaryotic sequences. Furthermore, we carried out all-against-all sequence alignment for several data sets to investigate the relationship between sequence homology and subcellular localization. Our results, which are consistent with previous studies, indicate that the homology search approach performs well down to 30% sequence identity, although its performance deteriorates considerably for sequences sharing lower sequence identity. A data set of high homology levels will undoubtedly lead to biased assessment of the performances of the predictive approaches-especially those relying on homology search or sequence annotations. Our two-level classification system based on SVM does not rely on homology search; therefore, its performance remains relatively unaffected by sequence homology. When compared with other approaches, our approach performed significantly better. Furthermore, we also develop a practical hybrid method, which combines the two-level SVM classifier and the homology search method, as a general tool for the sequence annotation of subcellular localization.
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            Plant PRRs and the activation of innate immune signaling.

            Despite being sessile organisms constantly exposed to potential pathogens and pests, plants are surprisingly resilient to infections. Plants can detect invaders via the recognition of pathogen-associated molecular patterns (PAMPs) by pattern recognition receptors (PRRs). Plant PRRs are surface-localized receptor-like kinases, which comprise a ligand-binding ectodomain and an intracellular kinase domain, or receptor-like proteins, which do not exhibit any known intracellular signaling domain. In this review, we summarize recent discoveries that shed light on the molecular mechanisms underlying ligand perception and subsequent activation of plant PRRs. Notably, plant PRRs appear as central components of multiprotein complexes at the plasma membrane that contain additional transmembrane and cytosolic kinases required for the initiation and specificity of immune signaling. PRR complexes are under tight control by protein phosphatases, E3 ligases, and other regulatory proteins, illustrating the exquisite and complex regulation of these molecular machines whose proper activation underlines a crucial layer of plant immunity. Copyright © 2014 Elsevier Inc. All rights reserved.
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              Functional analysis of the Arabidopsis PAL gene family in plant growth, development, and response to environmental stress.

              Phenylalanine ammonia-lyase (PAL) catalyzes the first step of the phenylpropanoid pathway, which produces precursors to a variety of important secondary metabolites. Arabidopsis (Arabidopsis thaliana) contains four PAL genes (PAL1-PAL4), but there has been no genetic analysis to assess the biological functions of the entire gene family. Here, we report the generation and analysis of combined mutations for the four Arabidopsis PAL genes. Contrary to a previous report, we found that three independent pal1 pal2 double mutants were fertile and generated yellow seeds due to the lack of condensed tannin pigments in the seed coat. The pal1 pal2 double mutants were also deficient in anthocyanin pigments in various plant tissues, which accumulate in wild-type plants under stress conditions. Thus, PAL1 and PAL2 have a redundant role in flavonoid biosynthesis. Furthermore, the pal1 pal2 double mutants were more sensitive to ultraviolet-B light but more tolerant to drought than wild-type plants. We have also generated two independent pal1 pal2 pal3 pal4 quadruple knockout mutants, which are stunted and sterile. The quadruple knockout mutants still contained about 10% of the wild-type PAL activity, which might result from one or more leaky pal mutant genes or from other unknown PAL genes. The quadruple mutants also accumulated substantially reduced levels of salicylic acid and displayed increased susceptibility to a virulent strain of the bacterial pathogen Pseudomonas syringae. These results provide further evidence for both distinct and overlapping roles of the Arabidopsis PAL genes in plant growth, development, and responses to environmental stresses.
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                Author and article information

                Contributors
                chenshanchun@cric.cn
                heyongrui@cric.cn
                Journal
                Hortic Res
                Hortic Res
                Horticulture Research
                Nature Publishing Group UK (London )
                2662-6810
                2052-7276
                1 April 2020
                1 April 2020
                2020
                : 7
                : 42
                Affiliations
                GRID grid.263906.8, Citrus Research Institute, , Southwest University/Chinese Academy of Agricultural Sciences, ; Chongqing, 400712 China
                Author information
                http://orcid.org/0000-0001-7522-0444
                Article
                263
                10.1038/s41438-020-0263-y
                7109087
                32257228
                71b1bc95-155a-4c50-b065-b02ce33e3440
                © The Author(s) 2020

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 27 August 2019
                : 20 January 2020
                : 29 January 2020
                Funding
                Funded by: FundRef https://doi.org/10.13039/501100010038, Earmarked Fund for China Agriculture Research System;
                Award ID: CARS-26
                Award Recipient :
                Categories
                Article
                Custom metadata
                © The Author(s) 2020

                plant physiology,plant stress responses
                plant physiology, plant stress responses

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