When Does Spatial Diversification Usefully Maximize the Durability of Crop Disease Resistance?

Maximizing the durability of crop disease resistance genes in the face of pathogen evolution is a major challenge in modern agricultural epidemiology. Spatial diversification in the deployment of resistance genes, where susceptible and resistant fields are more closely intermixed, is predicted to drive lower epidemic intensities over evolutionary timescales. This is due to an increase in the strength of dilution effects, caused by pathogen inoculum challenging host tissue to which it is not well-specialized. The factors that interact with and determine the magnitude of this spatial suppressive effect are not currently well understood, however, leading to uncertainty over the pathosystems where such a strategy is most likely to be cost-effective. We model the effect on landscape scale disease dynamics of spatial heterogeneity in the arrangement of fields planted with either susceptible or resistant cultivars, and the way in which this effect depends on the parameters governing the pathosystem of interest. Our multiseason semidiscrete epidemiological model tracks spatial spread of wild-type and resistance-breaking pathogen strains, and incorporates a localized reservoir of inoculum, as well as the effects of within and between field transmission. The pathogen dispersal characteristics, any fitness cost(s) of the resistance-breaking trait, the efficacy of host resistance, and the length of the timeframe of interest all influence the strength of the spatial diversification effect. A key result is that spatial diversification has the strongest beneficial effect at intermediate fitness costs of the resistance-breaking trait, an effect driven by a complex set of nonlinear interactions. On the other hand, however, if the resistance-breaking strain is not fit enough to invade the landscape, then a partially effective resistance gene can result in spatial diversification actually worsening the epidemic. These results allow us to make general predictions of the types of system for which spatial diversification is most likely to be cost-effective, paving the way for potential economic modeling and pathosystem specific evaluation. These results highlight the importance of studying the effect of genetics on landscape scale spatial dynamics within host−pathogen disease systems. [Formula: see text] Copyright © 2020 The Author(s). This is an open access article distributed under the CC BY 4.0 International license .

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When does spatial diversification usefully maximise the durability of crop disease resistance?

10.1101/540013 ◽

2019 ◽

Cited By ~ 2

Author(s):

Benjamin Watkinson-Powell ◽

Christopher A. Gilligan ◽

Nik J. Cunniffe

Keyword(s):

Disease Resistance ◽

Resistance Genes ◽

Spatial Dynamics ◽

Cost Effective ◽

Landscape Scale ◽

Economic Modelling ◽

Resistance Breaking ◽

Crop Disease ◽

Spatial Diversification ◽

The Way

1AbstractMaximising the durability of crop disease resistance genes in the face of pathogen evolution is a major challenge in modern agricultural epidemiology. Spatial diversification in the deployment of resistance genes, where susceptible and resistant fields are more closely intermixed, is predicted to drive lower epidemic intensities over evolutionary timescales. This is due to an increase in the strength of dilution effects, caused by pathogen inoculum challenging host tissue to which it is not well-specialised. The factors that interact with and determine the magnitude of this spatial effect are not currently well understood however, leading to uncertainty over the pathosystems where such a strategy is most likely to be cost-effective. We model the effect on landscape scale disease dynamics of spatial heterogeneity in the arrangement of fields planted with either susceptible or resistant cultivars, and the way in which this effect depends on the parameters governing the pathosystem of interest. Our multi-season semi-discrete epidemiological model tracks spatial spread of wild-type and resistance breaking pathogen strains, and incorporates a localised reservoir of inoculum, as well as the effects of within and between field transmission. The pathogen dispersal characteristics, any fitness cost(s) of the resistance breaking trait, the efficacy of host resistance, and the length of the timeframe of interest, all influence the strength of the spatial diversification effect. These interactions, which are often complex and non-linear in nature, produce substantial variation in the predicted yield gain from the use of a spatial diversification strategy. This in turn allows us to make general predictions of the types of system for which spatial diversification is most likely to be cost-effective, paving the way for potential economic modelling and pathosystem specific evaluation. These results highlight the importance of studying the effect of genetics on landscape scale spatial dynamics within host-pathogen disease systems.

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The role of minimum disease resistance standards for the control of cereal diseases

Australian Journal of Agricultural Research ◽

10.1071/ar06143 ◽

2007 ◽

Vol 58 (6) ◽

pp. 588 ◽

Cited By ~ 4

Author(s):

Hugh Wallwork

Keyword(s):

Disease Resistance ◽

Resistance Genes ◽

Rust Resistance ◽

Historical Background ◽

Wheat Varieties ◽

Cereal Diseases ◽

The Way

A set of Minimum Disease resistance Standards (MDS) has been developed for rust resistance in new wheat varieties in Australia. These standards aim to provide protection to growers from varieties that produce large amounts of inoculum and, more specifically, protect the usefulness of resistance genes by reducing the probability of new pathotypes evolving with virulences that can overcome them. This paper provides a historical background to the establishment of MDS in Australia, the rationale for its introduction and the appropriateness of different resistance scales, problems that have been encountered, and the way forward to fully implement MDS. A brief consideration is also given as to which other wheat and barley diseases MDS may usefully be applied to.

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Tracking disease resistance deployment in potato breeding by enrichment sequencing

10.1101/360644 ◽

2018 ◽

Cited By ~ 1

Author(s):

Miles R Armstrong ◽

Jack Vossen ◽

Tze Yin Lim ◽

Ronald C B Hutten ◽

Jianfei Xu ◽

...

Keyword(s):

Disease Resistance ◽

Resistance Genes ◽

Potato Breeding ◽

Crop Improvement ◽

Resistance Breeding ◽

Cost Effective ◽

Complete Sequence ◽

Gene Enrichment ◽

Disease Resistance Breeding ◽

Late Blight Pathogen

SummaryFollowing the molecular characterisation of functional disease resistance genes in recent years, methods to track and verify the integrity of multiple genes in varieties are needed for crop improvement through resistance stacking. Diagnostic resistance gene enrichment sequencing (dRenSeq) enables the high-confidence identification and complete sequence validation of known functional resistance genes in crops. As demonstrated for tetraploid potato varieties, the methodology is more robust and cost-effective in monitoring resistances than whole-genome sequencing and can be used to appraise (trans)gene integrity efficiently. All currently known NB-LRRs effective against viruses, nematodes and the late blight pathogen Phytophthora infestans can be tracked with dRenSeq in potato and hitherto unknown polymorphisms have been identified. The methodology provides a means to improve the speed and efficiency of future disease resistance breeding in crops by directing parental and progeny selection towards effective combinations of resistance genes.

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The Arabidopsis RPS4 bacterial-resistance gene is a member of the TIR-NBS-LRR family of disease-resistance genes

The Plant Journal ◽

10.1046/j.1365-313x.1999.t01-1-00600.x ◽

1999 ◽

Vol 20 (3) ◽

pp. 265-277 ◽

Cited By ~ 224

Author(s):

Walter Gassmann ◽

Matthew E. Hinsch ◽

Brian J. Staskawicz

Keyword(s):

Disease Resistance ◽

Resistance Gene ◽

Resistance Genes ◽

Bacterial Resistance ◽

Disease Resistance Genes

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Genome-Wide Analysis of NBS-Encoding Disease Resistance Genes in Maize Inbred Line B73

ACTA AGRONOMICA SINICA ◽

10.3724/sp.j.1006.2009.00566 ◽

2009 ◽

Vol 35 (3) ◽

pp. 566-570 ◽

Cited By ~ 1

Author(s):

Jie-Ming WANG ◽

Hai-Yang JIANG ◽

Yang ZHAO ◽

Yan XIANG ◽

Su-Wen ZHU ◽

...

Keyword(s):

Disease Resistance ◽

Inbred Line ◽

Resistance Genes ◽

Disease Resistance Genes ◽

Maize Inbred Line ◽

Genome Wide Analysis ◽

Genome Wide

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Comparative Mapping of Three Bacterial, Three Fungal, and One Virus Disease-resistance Genes in Common Bean

HortScience ◽

10.21273/hortsci.33.3.547a ◽

1998 ◽

Vol 33 (3) ◽

pp. 547a-547

Author(s):

Geunhwa Jung ◽

James Nienhuis ◽

Dermot P. Coyne ◽

H.M. Ariyarathne

Keyword(s):

Disease Resistance ◽

Common Bean ◽

Pseudomonas Syringae ◽

Resistance Genes ◽

Fungal Pathogens ◽

Xanthomonas Campestris ◽

Virus Disease ◽

Disease Resistance Genes ◽

Brown Spot ◽

Viral Pathogen

Common bacterial blight (CBB), bacterial brown spot (BBS), and halo blight (HB), incited by the bacterial pathogens Xanthomonas campestris pv. phaseoli (Smith) Dye, Pseodomonas syringae pv. syringa, and Pseudomonas syringae pv. phaseolicola, respectively are important diseases of common bean. In addition three fungal pathogens, web blight (WB) Thanatephorus cucumeris, rust Uromyces appendiculatus, and white mold (WM) Sclerotinia sclerotiorum, are also destructive diseases attacking common bean. Bean common mosaic virus is also one of most major virus disease. Resistance genes (QTLs and major genes) to three bacterial (CBB, BBS, and HB), three fungal (WB, rust, and WM), and one viral pathogen (BCMV) were previously mapped in two common bean populations (BAC 6 × HT 7719 and Belneb RR-1 × A55). The objective of this research was to use an integrated RAPD map of the two populations to compare the positions and effect of resistance QTL in common bean. Results indicate that two chromosomal regions associated with QTL for CBB resistance mapped in both populations. The same chromosomal regions associated with QTL for disease resistance to different pathogens or same pathogens were detected in the integrated population.

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Identification of Three Putative Signal Transduction Genes Involved in R Gene-Specified Disease Resistance in Arabidopsis

Genetics ◽

10.1093/genetics/152.1.401 ◽

1999 ◽

Vol 152 (1) ◽

pp. 401-412 ◽

Cited By ~ 1

Author(s):

Randall F Warren ◽

Peter M Merritt ◽

Eric Holub ◽

Roger W Innes

Keyword(s):

Disease Resistance ◽

Pseudomonas Syringae ◽

Resistance Genes ◽

Virulent Strain ◽

Disease Resistance Genes ◽

Avirulence Gene ◽

Detectable Effect ◽

Disease Resistance Gene ◽

Protein Functions ◽

Signal Transduction Genes

Abstract The RPS5 disease resistance gene of Arabidopsis mediates recognition of Pseudomonas syringae strains that possess the avirulence gene avrPphB. By screening for loss of RPS5-specified resistance, we identified five pbs (avrPphB susceptible) mutants that represent three different genes. Mutations in PBS1 completely blocked RPS5-mediated resistance, but had little to no effect on resistance specified by other disease resistance genes, suggesting that PBS1 facilitates recognition of the avrPphB protein. The pbs2 mutation dramatically reduced resistance mediated by the RPS5 and RPM1 resistance genes, but had no detectable effect on resistance mediated by RPS4 and had an intermediate effect on RPS2-mediated resistance. The pbs2 mutation also had varying effects on resistance mediated by seven different RPP (recognition of Peronospora parasitica) genes. These data indicate that the PBS2 protein functions in a pathway that is important only to a subset of disease-resistance genes. The pbs3 mutation partially suppressed all four P. syringae-resistance genes (RPS5, RPM1, RPS2, and RPS4), and it had weak-to-intermediate effects on the RPP genes. In addition, the pbs3 mutant allowed higher bacterial growth in response to a virulent strain of P. syringae, indicating that the PBS3 gene product functions in a pathway involved in restricting the spread of both virulent and avirulent pathogens. The pbs mutations are recessive and have been mapped to chromosomes I (pbs2) and V (pbs1 and pbs3).

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Organization, Expression and Evolution of a Disease Resistance Gene Cluster in Soybean

Genetics ◽

10.1093/genetics/162.4.1961 ◽

2002 ◽

Vol 162 (4) ◽

pp. 1961-1977

Author(s):

Michelle A Graham ◽

Laura Fredrick Marek ◽

Randy C Shoemaker

Keyword(s):

Disease Resistance ◽

Resistance Gene ◽

Resistance Genes ◽

Developmental Stages ◽

Gene Evolution ◽

Pcr Amplification ◽

Disease Resistance Genes ◽

Disease Resistance Gene ◽

R Genes ◽

Specific Primers

Abstract PCR amplification was previously used to identify a cluster of resistance gene analogues (RGAs) on soybean linkage group J. Resistance to powdery mildew (Rmd-c), Phytophthora stem and root rot (Rps2), and an ineffective nodulation gene (Rj2) map within this cluster. BAC fingerprinting and RGA-specific primers were used to develop a contig of BAC clones spanning this region in cultivar “Williams 82” [rps2, Rmd (adult onset), rj2]. Two cDNAs with homology to the TIR/NBD/LRR family of R-genes have also been mapped to opposite ends of a BAC in the contig Gm_Isb001_091F11 (BAC 91F11). Sequence analyses of BAC 91F11 identified 16 different resistance-like gene (RLG) sequences with homology to the TIR/NBD/LRR family of disease resistance genes. Four of these RLGs represent two potentially novel classes of disease resistance genes: TIR/NBD domains fused inframe to a putative defense-related protein (NtPRp27-like) and TIR domains fused inframe to soybean calmodulin Ca2+-binding domains. RT-PCR analyses using gene-specific primers allowed us to monitor the expression of individual genes in different tissues and developmental stages. Three genes appeared to be constitutively expressed, while three were differentially expressed. Analyses of the R-genes within this BAC suggest that R-gene evolution in soybean is a complex and dynamic process.

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