Effectiveness of quantitative resistance conferred by the genetic background of pepper in the control of root‐knot nematodes and influence onto durability of <i>Me1‐</i> and <i>Me3</i>‐resistant genes in greenhouse conditions

Sánchez-Solana, Fulgencio; Ros, C.; Guerrero, María del Mar; Martínez, V.; Lacasa, Carmen María; Hernández, Ana; Palloix, Alain; Lacasa, A.

doi:10.1111/pbr.12517

Cited by 2 publications

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“…In contrast, when a major gene was combined with a quantitative resistance with a 50% efficiency, the breakdown of the major gene was nearly as quick as if the major gene was alone, regardless of the pathogen life-history trait targeted by the quantitative resistance ( Fig 5A , column 3 to 6, and inset). This conclusion is consistent with the results of an experimental study on pepper resistance against root-knot nematode [ 121 ], but differs from those of other studies carried out on different pathosystems, showing that a quantitative resistant background can significantly increase the durability of a cultivar carrying a major gene for resistance [ 122 – 124 ]. In order to test if this difference could be due to our assumption that quantitative resistance has a 50% efficiency, we replicated the numerical experiment with higher efficiencies (ρ w = 60%, 70%, 80%, 90%).…”

Section: Resultssupporting

confidence: 83%

Assessing the durability and efficiency of landscape-based strategies to deploy plant resistance to pathogens

et al. 2018

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Genetically-controlled plant resistance can reduce the damage caused by pathogens. However, pathogens have the ability to evolve and overcome such resistance. This often occurs quickly after resistance is deployed, resulting in significant crop losses and a continuing need to develop new resistant cultivars. To tackle this issue, several strategies have been proposed to constrain the evolution of pathogen populations and thus increase genetic resistance durability. These strategies mainly rely on varying different combinations of resistance sources across time (crop rotations) and space. The spatial scale of deployment can vary from multiple resistance sources occurring in a single cultivar (pyramiding), in different cultivars within the same field (cultivar mixtures) or in different fields (mosaics). However, experimental comparison of the efficiency (i.e. ability to reduce disease impact) and durability (i.e. ability to limit pathogen evolution and delay resistance breakdown) of landscape-scale deployment strategies presents major logistical challenges. Therefore, we developed a spatially explicit stochastic model able to assess the epidemiological and evolutionary outcomes of the four major deployment options described above, including both qualitative resistance (i.e. major genes) and quantitative resistance traits against several components of pathogen aggressiveness: infection rate, latent period duration, propagule production rate, and infectious period duration. This model, implemented in the R package landsepi, provides a new and useful tool to assess the performance of a wide range of deployment options, and helps investigate the effect of landscape, epidemiological and evolutionary parameters. This article describes the model and its parameterisation for rust diseases of cereal crops, caused by fungi of the genus Puccinia. To illustrate the model, we use it to assess the epidemiological and evolutionary potential of the combination of a major gene and different traits of quantitative resistance. The comparison of the four major deployment strategies described above will be the objective of future studies.

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Section: Resultssupporting

confidence: 83%

Assessing the durability and efficiency of landscape-based strategies to deploy plant resistance to pathogens

et al. 2018

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“…In contrast, when a major gene was combined with a quantitative resistance with a 50% efficiency, the breakdown of the major gene was nearly as quick as if the major gene was alone, regardless of the pathogen life-history trait targeted by the quantitative resistance ( Fig 5A, column 3 to 6, and inset). This conclusion is consistent with the results of an experimental study on pepper resistance against root-knot nematode [121], but differs from those of other studies carried out on different pathosystems, showing that a quantitative resistant background can significantly increase the durability of a cultivar carrying a major gene for resistance [122][123][124]. In order to test if this difference could be due to our assumption that quantitative resistance has a 50% efficiency, we replicated the numerical experiment with higher efficiencies (ρw=60%, 70%, 80%, 90%).…”

Section: What Is the Durability Of A Major Gene Alone Or Combined Witsupporting

confidence: 92%

Assessing the durability and efficiency of landscape-based strategies to deploy plant resistance to pathogens

Rimbaud¹,

Papaïx²,

Rey³

et al. 2018

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Genetically-controlled plant resistance can reduce the damage caused by pathogens. However, pathogens have the ability to evolve and overcome such resistance. This often occurs quickly after resistance is deployed, resulting in significant crop losses and a continuing need to develop new resistant cultivars. To tackle this issue, several strategies have been proposed to constrain the evolution of pathogen populations and thus increase genetic resistance durability. These strategies mainly rely on varying different combinations of resistance sources across time (crop rotations) and space. The spatial scale of deployment can vary from multiple resistance sources occurring in a single cultivar (pyramiding), in different cultivars within the same field (cultivar mixtures) or in different fields (mosaics). However, experimental comparison of the efficiency (i.e. ability to reduce disease impact) and durability (i.e. ability to limit pathogen evolution and delay resistance breakdown) of landscapescale deployment strategies presents major logistical challenges.Therefore, we developed a spatially explicit stochastic model able to assess the epidemiological and evolutionary outcomes of the four major deployment options described above, including both qualitative resistance (i.e. major genes) and quantitative resistance traits against several components of pathogen aggressiveness: infection rate, latent period duration, propagule production rate, and infectious period duration. This model, implemented in the R package landsepi, provides a new and useful tool to assess the performance of a wide range of deployment options, and helps investigate the effect of landscape, epidemiological and evolutionary parameters.This article describes the model and its parameterisation for rust diseases of cereal crops, caused by fungi of the genus Puccinia. To illustrate the model, we use it to assess the epidemiological and evolutionary potential of the combination of a major gene and different traits of quantitative resistance. The comparison of the four major deployment strategies described above will be the objective of future studies.not peer-reviewed) is the author/funder. All rights reserved. No reuse allowed without permission.The copyright holder for this preprint (which was . http://dx.doi.org/10.1101/260836 doi: bioRxiv preprint first posted online Feb. 6, 2018; 2 Key words: demo-genetic modelling; deployment strategies; durable plant resistance; pathogen evolution; quantitative resistance; rust of wheat; spatially explicit stochastic modelling; spatiotemporal simulation model. Author summaryThere are many recent examples which demonstrate the evolutionary potential of plant pathogens to overcome the resistances deployed in agricultural landscapes to protect our crops. Increasingly, it is recognised that how resistance is deployed spatially and temporally can impact on rates of pathogen evolution and resistance breakdown. Such deployment strategies are mainly based on the combination of several sources of resistance ...

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Effectiveness of quantitative resistance conferred by the genetic background of pepper in the control of root‐knot nematodes and influence onto durability of Me1‐ and Me3‐resistant genes in greenhouse conditions

Cited by 2 publications

References 28 publications

Assessing the durability and efficiency of landscape-based strategies to deploy plant resistance to pathogens

Assessing the durability and efficiency of landscape-based strategies to deploy plant resistance to pathogens

Assessing the durability and efficiency of landscape-based strategies to deploy plant resistance to pathogens

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