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      Genome Analysis of Two Newly Emerged Potato Late Blight Isolates Sheds Light on Pathogen Adaptation and Provides Tools for Disease Management

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          Abstract

          Phytophthora infestans, the causal agent of the Irish Potato Famine in the 1840s, is one of the most destructive crop pathogens that threaten global food security. Host resistance (R) genes may help to control the disease, but recognition by through the gene products can be evaded by newly emerging isolates. Such isolates are dangerous as they may cause disease outbreaks under favorable conditions. However, our lack of knowledge about adaptation in these isolates jeopardizes an apt response to resistance breakdown. Here we performed genome and transcriptome sequencing of HB1501 and HN1602, two field isolates from distinct Chinese geographic regions. We found extensive polymorphisms in these isolates, including gene copy number variations, nucleotide polymorphisms, and gene expression changes. Effector encoding genes, which contribute to virulence, show distinct expression landscapes in P. infestans isolates HB1501 and HN1602. In particular, polymorphisms at multiple effectors required for recognition (Avr loci) enabled these isolates to overcome corresponding R gene based resistance. Although the isolates evolved multiple strategies to evade recognition, we experimentally verified that several R genes such as R8, RB, and Rpi-vnt1.1 remain effective against these isolates and are valuable to potato breeding in the future. In summary, rapid characterization of the adaptation in emerging field isolates through genomic tools inform rational agricultural management to prevent potential future epidemics.

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          Most cited references51

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          TBtools - an integrative toolkit developed for interactive analyses of big biological data

          The rapid development of high-throughput sequencing techniques has led biology into the big-data era. Data analyses using various bioinformatics tools rely on programming and command-line environments, which are challenging and time-consuming for most wet-lab biologists. Here, we present TBtools (a Toolkit for Biologists integrating various biological data-handling tools), a stand-alone software with a user-friendly interface. The toolkit incorporates over 130 functions, which are designed to meet the increasing demand for big-data analyses, ranging from bulk sequence processing to interactive data visualization. A wide variety of graphs can be prepared in TBtools using a new plotting engine ("JIGplot") developed to maximize their interactive ability; this engine allows quick point-and-click modification of almost every graphic feature. TBtools is platform-independent software that can be run under all operating systems with Java Runtime Environment 1.6 or newer. It is freely available to non-commercial users at https://github.com/CJ-Chen/TBtools/releases.
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            The plant immune system.

            Many plant-associated microbes are pathogens that impair plant growth and reproduction. Plants respond to infection using a two-branched innate immune system. The first branch recognizes and responds to molecules common to many classes of microbes, including non-pathogens. The second responds to pathogen virulence factors, either directly or through their effects on host targets. These plant immune systems, and the pathogen molecules to which they respond, provide extraordinary insights into molecular recognition, cell biology and evolution across biological kingdoms. A detailed understanding of plant immune function will underpin crop improvement for food, fibre and biofuels production.
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              Pathogen population genetics, evolutionary potential, and durable resistance.

              We hypothesize that the evolutionary potential of a pathogen population is reflected in its population genetic structure. Pathogen populations with a high evolutionary potential are more likely to overcome genetic resistance than pathogen populations with a low evolutionary potential. We propose a flexible framework to predict the evolutionary potential of pathogen populations based on analysis of their genetic structure. According to this framework, pathogens that pose the greatest risk of breaking down resistance genes have a mixed reproduction system, a high potential for genotype flow, large effective population sizes, and high mutation rates. The lowest risk pathogens are those with strict asexual reproduction, low potential for gene flow, small effective population sizes, and low mutation rates. We present examples of high-risk and low-risk pathogens. We propose general guidelines for a rational approach to breed durable resistance according to the evolutionary potential of the pathogen.

                Author and article information

                Contributors
                Journal
                Phytopathology®
                Phytopathology®
                Scientific Societies
                0031-949X
                1943-7684
                January 2021
                January 2021
                : 111
                : 1
                : 96-107
                Affiliations
                [1 ]Department of Plant Pathology, Nanjing Agricultural University, Nanjing, 210095, China
                [2 ]Key Laboratory of Integrated Management of Crop Diseases and Pests, Ministry of Education, Nanjing, 210095, China
                [3 ]Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Guangdong Laboratory for Lingnan Modern Agriculture, Shenzhen, 518120, China
                [4 ]National Agro-Tech Extension and Service Center, Maizidian Street, No. 20, Beijing, 100125, China
                [5 ]Key Laboratory of Plant Immunity, Nanjing Agricultural University, Nanjing, 210095, China
                [6 ]Plant Breeding, Wageningen University and Research, Wageningen 6708 PB, The Netherlands
                Article
                10.1094/PHYTO-05-20-0208-FI
                33026300
                a80d4c1b-fe78-4bb8-b877-cac2bdbc2057
                © 2021
                History

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