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      Cucumber mosaic virus infection as a potential selective pressure on Arabidopsis thaliana populations

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          Abstract

          It has been proposed that in wild ecosystems viruses are often plant mutualists, whereas agroecosystems favour pathogenicity. We seek evidence for virus pathogenicity in wild ecosystems through the analysis of plant-virus coevolution, which requires a negative effect of infection on the host fitness. We focus on the interaction between Arabidopsis thaliana and Cucumber mosaic virus (CMV), which is significant in nature. We studied the genetic diversity of A. thaliana for two defence traits, resistance and tolerance, to CMV. A set of 185 individuals collected in 76 A. thaliana Iberian wild populations were inoculated with different CMV strains. Resistance was estimated from the level of virus multiplication in infected plants, and tolerance from the effect of infection on host progeny production. Resistance and tolerance to CMV showed substantial genetic variation within and between host populations, and depended on the virus x host genotype interaction, two conditions for coevolution. Resistance and tolerance were co-occurring independent traits that have evolved independently from related life-history traits involved in adaptation to climate. The comparison of the genetic structure for resistance and tolerance with that for neutral traits ( Q ST / F ST analyses) indicated that both defence traits are likely under uniform selection. These results strongly suggest that CMV infection selects for defence on A. thaliana populations, and support plant-virus coevolution. Thus, we propose that CMV infection reduces host fitness under the field conditions of the wild A. thaliana populations studied.

          Author summary

          Plant-virus coevolution has not been demonstrated in any wild system, and it has been proposed that viruses often would be mutualistic symbionts, rather than pathogens, in wild plant ecosystems. We analyse if viruses are virulent pathogens of plants in wild ecosystems and, consequently, plants have evolved defences against virus infection. To test this hypothesis, we studied the genetic diversity of Arabidopsis thaliana for two defence traits, resistance and tolerance, to Cucumber mosaic virus (CMV) at a regional scale in the Iberian Peninsula. Resistance and tolerance to CMV showed substantial genetic variation within and between host populations, and depended on the virus x host genotype interaction, two conditions for coevolution. Resistance and tolerance were independent traits that co-occurred at the population and regional scales, and that have evolved independently from other adaptive life-history traits. Analyses also indicated that resistance and tolerance are likely under selection, most likely due to virus infection. These results support a hypothesis of plant-virus coevolution and contribute to demonstrate that plant viruses may be virulent parasites of plants in wild ecosystems.

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          Biological and biomedical implications of the co-evolution of pathogens and their hosts.

          Co-evolution between host and pathogen is, in principle, a powerful determinant of the biology and genetics of infection and disease. Yet co-evolution has proven difficult to demonstrate rigorously in practice, and co-evolutionary thinking is only just beginning to inform medical or veterinary research in any meaningful way, even though it can have a major influence on how genetic variation in biomedically important traits is interpreted. Improving our understanding of the biomedical significance of co-evolution will require changing the way in which we look for it, complementing the phenomenological approach traditionally favored by evolutionary biologists with the exploitation of the extensive data becoming available on the molecular biology and molecular genetics of host-pathogen interactions.
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            Modifying the t Test for Assessing the Correlation Between Two Spatial Processes

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              Regression analysis of spatial data.

              Many of the most interesting questions ecologists ask lead to analyses of spatial data. Yet, perhaps confused by the large number of statistical models and fitting methods available, many ecologists seem to believe this is best left to specialists. Here, we describe the issues that need consideration when analysing spatial data and illustrate these using simulation studies. Our comparative analysis involves using methods including generalized least squares, spatial filters, wavelet revised models, conditional autoregressive models and generalized additive mixed models to estimate regression coefficients from synthetic but realistic data sets, including some which violate standard regression assumptions. We assess the performance of each method using two measures and using statistical error rates for model selection. Methods that performed well included generalized least squares family of models and a Bayesian implementation of the conditional auto-regressive model. Ordinary least squares also performed adequately in the absence of model selection, but had poorly controlled Type I error rates and so did not show the improvements in performance under model selection when using the above methods. Removing large-scale spatial trends in the response led to poor performance. These are empirical results; hence extrapolation of these findings to other situations should be performed cautiously. Nevertheless, our simulation-based approach provides much stronger evidence for comparative analysis than assessments based on single or small numbers of data sets, and should be considered a necessary foundation for statements of this type in future.
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                Author and article information

                Contributors
                Role: Formal analysisRole: InvestigationRole: Writing – original draft
                Role: ConceptualizationRole: InvestigationRole: Writing – review & editing
                Role: ConceptualizationRole: Funding acquisitionRole: InvestigationRole: Writing – review & editing
                Role: Editor
                Journal
                PLoS Pathog
                PLoS Pathog
                plos
                plospath
                PLoS Pathogens
                Public Library of Science (San Francisco, CA USA )
                1553-7366
                1553-7374
                28 May 2019
                May 2019
                : 15
                : 5
                : e1007810
                Affiliations
                [1 ] Centro de Biotecnología y Genómica de Plantas (UPM-INIA), and E.T.S.I. Agronómica, Alimentaria y de Biosistemas, Campus de Montegancedo, Universidad Politécnica de Madrid, Pozuelo de Alarcón (Madrid), Spain
                [2 ] Departamento de Genética Molecular de Plantas, Centro Nacional de Biotecnología, Consejo Superior de Investigaciones Científicas (CNB-CSIC), Campus Universidad Autónoma, Cantoblanco, Madrid, Spain
                Institute of Microbiology, CHINA
                Author notes

                The authors have declared that no competing interests exist.

                [¤]

                Current address: Fisiología Vegetal, Departamento Ciencias Farmacéuticas y de la Salud, Facultad de Farmacia, Universidad San Pablo-CEU, Boadilla del Monte (Madrid), Spain and Servicio de Reumatología, Hospital Universitario de la Princesa, Instituto de Investigación Sanitaria (IIS-IP), Madrid, Spain.

                Author information
                http://orcid.org/0000-0002-4738-5556
                http://orcid.org/0000-0002-5327-3200
                Article
                PPATHOGENS-D-19-00106
                10.1371/journal.ppat.1007810
                6555541
                31136630
                1c14b691-68b8-4667-bcad-1b0f1c48059a
                © 2019 Montes et al

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 17 January 2019
                : 1 May 2019
                Page count
                Figures: 5, Tables: 2, Pages: 24
                Funding
                Funded by: funder-id http://dx.doi.org/10.13039/501100011033, Agencia Estatal de Investigación;
                Award ID: BFU2015-64018-R
                Award Recipient :
                Funded by: funder-id http://dx.doi.org/10.13039/501100011033, Agencia Estatal de Investigación;
                Award ID: BIO2016-75754-P
                Award Recipient :
                Funded by: Ministerio de Educacion y Ciencia (ES)
                Award ID: BES-2009-026698
                Award Recipient :
                This work was funded by grants BFU2015-64018-R (Plan Estatal de I+D+i, MINECO, Spain) to FGA, and BIO2016-75754-P (Agencia Estatal de Investigación, Spain and FEDER, UE) to CAB. NM was in receipt of a FPI contract (BES-2009-026698) from MEC, Spain. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Research Article
                Research and Analysis Methods
                Animal Studies
                Experimental Organism Systems
                Model Organisms
                Arabidopsis Thaliana
                Research and Analysis Methods
                Model Organisms
                Arabidopsis Thaliana
                Biology and Life Sciences
                Organisms
                Eukaryota
                Plants
                Brassica
                Arabidopsis Thaliana
                Research and Analysis Methods
                Animal Studies
                Experimental Organism Systems
                Plant and Algal Models
                Arabidopsis Thaliana
                Biology and Life Sciences
                Evolutionary Biology
                Population Genetics
                Biology and Life Sciences
                Genetics
                Population Genetics
                Biology and Life Sciences
                Population Biology
                Population Genetics
                Biology and Life Sciences
                Plant Science
                Plant Pathology
                Plant Pathogens
                Plant Viral Pathogens
                Biology and Life Sciences
                Evolutionary Biology
                Population Genetics
                Genetic Polymorphism
                Biology and Life Sciences
                Genetics
                Population Genetics
                Genetic Polymorphism
                Biology and Life Sciences
                Population Biology
                Population Genetics
                Genetic Polymorphism
                Biology and Life Sciences
                Plant Science
                Plant Anatomy
                Seeds
                Biology and Life Sciences
                Evolutionary Biology
                Evolutionary Processes
                Coevolution
                Medicine and Health Sciences
                Pathology and Laboratory Medicine
                Pathogenesis
                Host-Pathogen Interactions
                Biology and Life Sciences
                Plant Science
                Plant Pathology
                Plant Pathogens
                Plant Fungal Pathogens
                Custom metadata
                vor-update-to-uncorrected-proof
                2019-06-07
                All relevant data are within the manuscript and its Supporting Information files.

                Infectious disease & Microbiology
                Infectious disease & Microbiology

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