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Jeger M, Hamelin F, Cunniffe N. Emerging Themes and Approaches in Plant Virus Epidemiology. PHYTOPATHOLOGY 2023; 113:1630-1646. [PMID: 36647183 DOI: 10.1094/phyto-10-22-0378-v] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/05/2023]
Abstract
Plant diseases caused by viruses share many common features with those caused by other pathogen taxa in terms of the host-pathogen interaction, but there are also distinctive features in epidemiology, most apparent where transmission is by vectors. Consequently, the host-virus-vector-environment interaction presents a continuing challenge in attempts to understand and predict the course of plant virus epidemics. Theoretical concepts, based on the underlying biology, can be expressed in mathematical models and tested through quantitative assessments of epidemics in the field; this remains a goal in understanding why plant virus epidemics occur and how they can be controlled. To this end, this review identifies recent emerging themes and approaches to fill in knowledge gaps in plant virus epidemiology. We review quantitative work on the impact of climatic fluctuations and change on plants, viruses, and vectors under different scenarios where impacts on the individual components of the plant-virus-vector interaction may vary disproportionately; there is a continuing, sometimes discordant, debate on host resistance and tolerance as plant defense mechanisms, including aspects of farmer behavior and attitudes toward disease management that may affect deployment in crops; disentangling host-virus-vector-environment interactions, as these contribute to temporal and spatial disease progress in field populations; computational techniques for estimating epidemiological parameters from field observations; and the use of optimal control analysis to assess disease control options. We end by proposing new challenges and questions in plant virus epidemiology.
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Affiliation(s)
- Mike Jeger
- Department of Life Sciences, Imperial College London, Silwood Park, U.K
| | - Fred Hamelin
- IGEPP INRAE, University of Rennes, Rennes, France
| | - Nik Cunniffe
- Department of Plant Sciences, University of Cambridge, Cambridge, U.K
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Alcalá Briseño RI, Batuman O, Brawner J, Cuellar WJ, Delaquis E, Etherton BA, French-Monar RD, Kreuze JF, Navarrete I, Ogero K, Plex Sulá AI, Yilmaz S, Garrett KA. Translating virome analyses to support biosecurity, on-farm management, and crop breeding. FRONTIERS IN PLANT SCIENCE 2023; 14:1056603. [PMID: 36998684 PMCID: PMC10043385 DOI: 10.3389/fpls.2023.1056603] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 09/29/2022] [Accepted: 02/14/2023] [Indexed: 06/19/2023]
Abstract
Virome analysis via high-throughput sequencing (HTS) allows rapid and massive virus identification and diagnoses, expanding our focus from individual samples to the ecological distribution of viruses in agroecological landscapes. Decreases in sequencing costs combined with technological advances, such as automation and robotics, allow for efficient processing and analysis of numerous samples in plant disease clinics, tissue culture laboratories, and breeding programs. There are many opportunities for translating virome analysis to support plant health. For example, virome analysis can be employed in the development of biosecurity strategies and policies, including the implementation of virome risk assessments to support regulation and reduce the movement of infected plant material. A challenge is to identify which new viruses discovered through HTS require regulation and which can be allowed to move in germplasm and trade. On-farm management strategies can incorporate information from high-throughput surveillance, monitoring for new and known viruses across scales, to rapidly identify important agricultural viruses and understand their abundance and spread. Virome indexing programs can be used to generate clean germplasm and seed, crucial for the maintenance of seed system production and health, particularly in vegetatively propagated crops such as roots, tubers, and bananas. Virome analysis in breeding programs can provide insight into virus expression levels by generating relative abundance data, aiding in breeding cultivars resistant, or at least tolerant, to viruses. The integration of network analysis and machine learning techniques can facilitate designing and implementing management strategies, using novel forms of information to provide a scalable, replicable, and practical approach to developing management strategies for viromes. In the long run, these management strategies will be designed by generating sequence databases and building on the foundation of pre-existing knowledge about virus taxonomy, distribution, and host range. In conclusion, virome analysis will support the early adoption and implementation of integrated control strategies, impacting global markets, reducing the risk of introducing novel viruses, and limiting virus spread. The effective translation of virome analysis depends on capacity building to make benefits available globally.
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Affiliation(s)
- Ricardo I. Alcalá Briseño
- Plant Pathology Department, University of Florida, Gainesville, FL, United States
- Global Food Systems Institute, University of Florida, Gainesville, FL, United States
- Emerging Pathogens Institute, University of Florida, Gainesville, FL, United States
- Plant Pathology Department, Oregon State University, Corvallis, OR, United States
| | - Ozgur Batuman
- Plant Pathology Department, University of Florida, Gainesville, FL, United States
- Southwest Florida Research and Education Center (SWFREC), Immokalee, FL, United States
| | - Jeremy Brawner
- Plant Pathology Department, University of Florida, Gainesville, FL, United States
| | - Wilmer J. Cuellar
- International Center for Tropical Agriculture (CIAT), Cali, Colombia
| | - Erik Delaquis
- International Center for Tropical Agriculture (CIAT), Vientiane, Laos
| | - Berea A. Etherton
- Plant Pathology Department, University of Florida, Gainesville, FL, United States
- Global Food Systems Institute, University of Florida, Gainesville, FL, United States
- Emerging Pathogens Institute, University of Florida, Gainesville, FL, United States
| | | | - Jan F. Kreuze
- Crop and System Sciences Division, International Potato Center (CIP), Lima, Peru
| | - Israel Navarrete
- Crop and System Sciences Division, International Potato Center (CIP), Quito, Ecuador
| | - Kwame Ogero
- Crop and System Sciences Division, International Potato Center (CIP), Mwanza, Tanzania
| | - Aaron I. Plex Sulá
- Plant Pathology Department, University of Florida, Gainesville, FL, United States
- Global Food Systems Institute, University of Florida, Gainesville, FL, United States
- Emerging Pathogens Institute, University of Florida, Gainesville, FL, United States
| | - Salih Yilmaz
- Plant Pathology Department, University of Florida, Gainesville, FL, United States
- Southwest Florida Research and Education Center (SWFREC), Immokalee, FL, United States
| | - Karen A. Garrett
- Plant Pathology Department, University of Florida, Gainesville, FL, United States
- Global Food Systems Institute, University of Florida, Gainesville, FL, United States
- Emerging Pathogens Institute, University of Florida, Gainesville, FL, United States
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Garrett KA, Bebber DP, Etherton BA, Gold KM, Plex Sulá AI, Selvaraj MG. Climate Change Effects on Pathogen Emergence: Artificial Intelligence to Translate Big Data for Mitigation. ANNUAL REVIEW OF PHYTOPATHOLOGY 2022; 60:357-378. [PMID: 35650670 DOI: 10.1146/annurev-phyto-021021-042636] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/20/2023]
Abstract
Plant pathology has developed a wide range of concepts and tools for improving plant disease management, including models for understanding and responding to new risks from climate change. Most of these tools can be improved using new advances in artificial intelligence (AI), such as machine learning to integrate massive data sets in predictive models. There is the potential to develop automated analyses of risk that alert decision-makers, from farm managers to national plant protection organizations, to the likely need for action and provide decision support for targeting responses. We review machine-learning applications in plant pathology and synthesize ideas for the next steps to make the most of these tools in digital agriculture. Global projects, such as the proposed global surveillance system for plant disease, will be strengthened by the integration of the wide range of new data, including data from tools like remote sensors, that are used to evaluate the risk ofplant disease. There is exciting potential for the use of AI to strengthen global capacity building as well, from image analysis for disease diagnostics and associated management recommendations on farmers' phones to future training methodologies for plant pathologists that are customized in real-time for management needs in response to the current risks. International cooperation in integrating data and models will help develop the most effective responses to new challenges from climate change.
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Affiliation(s)
- K A Garrett
- Plant Pathology Department, University of Florida, Gainesville, Florida, USA;
- Food Systems Institute, University of Florida, Gainesville, Florida, USA
- Emerging Pathogens Institute, University of Florida, Gainesville, Florida, USA
| | - D P Bebber
- Department of Biosciences, University of Exeter, Exeter, United Kingdom
| | - B A Etherton
- Plant Pathology Department, University of Florida, Gainesville, Florida, USA;
- Food Systems Institute, University of Florida, Gainesville, Florida, USA
- Emerging Pathogens Institute, University of Florida, Gainesville, Florida, USA
| | - K M Gold
- Plant Pathology and Plant Microbe Biology Section, School of Integrative Plant Sciences, Cornell AgriTech, Cornell University, Geneva, New York, USA
| | - A I Plex Sulá
- Plant Pathology Department, University of Florida, Gainesville, Florida, USA;
- Food Systems Institute, University of Florida, Gainesville, Florida, USA
- Emerging Pathogens Institute, University of Florida, Gainesville, Florida, USA
| | - M G Selvaraj
- The Alliance of Bioversity International and the International Center for Tropical Agriculture (CIAT), Cali, Colombia
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