Breakdown of resistance to the fungal disease, blackleg, is averted in commercial canola (Brassica napus) crops in Australia

Wouw, Angela P. Van de; Marcroft, S. J.; Ware, A. H.; Lindbeck, Kurt; Khangura, Ravjit; Howlett, Barbara J.

doi:10.1016/j.fcr.2014.06.023

Cited by 63 publications

(56 citation statements)

References 39 publications

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“…Van de Wouw et al (2014) confirmed the advantage of characterizing and then rotating oilseed rape (canola) cultivars carrying different blackleg resistance genes (Grains Research and Development Corporation 2014). In the current study it is disconcerting that by year 5 (2012), blackleg disease levels of all cultivars (''susceptible'', ''moderately resistant'' and ''resistant'') were similar (data not shown).…”

Section: Blackleg Disease Levelsmentioning

confidence: 77%

“…Therefore, we are compelled to reject our hypothesis that the latter practices would mitigate yield reductions in continuous canola. Research similar to that described by Marcroft et al (2012) and Van de Wouw et al (2014) from Australia may provide information that would enable Canadian canola producers to partially mitigate disease risks and yield reductions in high-frequency canola rotations.…”

Section: Canola Seed Yieldmentioning

confidence: 99%

“…& De Not.] resistance genes to prevent blackleg resistance breakdown has been reported in Australia (Marcroft et al 2012; Van de Wouw et al 2014). Although specific disease resistance genes in canola cultivars are not publicly disclosed in Canada, differences may exist among cultivars.…”

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confidence: 99%

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Canola cultivar mixtures and rotations do not mitigate the negative impacts of continuous canola

et al. 2015

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Harker, K. N., O'Donovan, J. T., Turkington, T. K., Blackshaw, R. E., Lupwayi, N. Z., Smith, E. G., Dosdall, L. M., Hall, L. M., Kutcher, H. R., Willenborg, C. J., Peng, G., Irvine, R. B. and Mohr, R. 2015. Canola cultivar mixtures and rotations do not mitigate the negative impacts of continuous canola. Can. J. Plant Sci. 95: 1085–1099. High-frequency canola (Brassica napus L.) rotations increase canola production risks. From 2008 to 2013, direct-seeded experiments involving several variations of continuous canola were compared with wheat (Triticum aestivum L.) and field pea (Pisum sativum L.) rotated with canola at five western Canada locations. Continuous canola rotations involved sequences of different herbicide-resistant canola and two-cultivar mixtures of herbicide-resistant canola from different sources in the same year. Fertilizers, herbicides, and insecticides were applied as required for optimal production of all crops. Rotating herbicide-resistant canola types over years or mixing two cultivars of the same herbicide-resistant type provided no pest management, yield or seed quality advantages compared with planting the same herbicide-resistant cultivar type each year. In 2013, weed biomass was lower in canola preceded by other crops than most continuous canola treatments. Compared with continuous canola, when 1 or 2 yr of wheat or field pea and wheat were inserted into 3-yr rotation cycles, 2010 root maggot damage was reduced 6% and 2013 blackleg [Leptosphaeria maculans (Desmaz.) Ces. & De Not.] incidence and severity were reduced 53 and 54%, respectively. Furthermore, yields were 22% higher when canola was grown only once in 3 yr compared with continuous canola and the wheat–canola–canola rotation. The most important mitigation strategy to ensure long-term sustainable canola production is to rotate canola with other crops.

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Section: Blackleg Disease Levelsmentioning

confidence: 77%

Section: Canola Seed Yieldmentioning

confidence: 99%

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Canola cultivar mixtures and rotations do not mitigate the negative impacts of continuous canola

et al. 2015

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“…These results demonstrate that, even at the local scale of our experiment, we were able to detect the signature of adaptation to host resistance deployment, as repeatedly observed in larger‐scale cropping situations. For example, in L. maculans , previous studies have documented adaptation to the genes Rlm1 in Europe and Australia (Rouxel et al., 2001; ); LepR3 ( Rlm1 ) and LepR1 in Australia (Sprague et al., 2006; Van de Wouw et al., 2014, 2017); Rlm7 in Europe (Balesdent et al., 2015; Leflon, 2013; Winter & Koopmann, 2016); Rlm3 in Canada (Zhang et al., 2016). …”

Section: Discussionmentioning

confidence: 99%

Spatio‐temporal connectivity and host resistance influence evolutionary and epidemiological dynamics of the canola pathogen Leptosphaeria maculans

Bousset

Sprague

Thrall

et al. 2018

Evolutionary Applications

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Genetic, physiological and physical homogenization of agricultural landscapes creates ideal environments for plant pathogens to proliferate and rapidly evolve. Thus, a critical challenge in plant pathology and epidemiology is to design durable and effective strategies to protect cropping systems from damage caused by pathogens. Theoretical studies suggest that spatio‐temporal variation in the diversity and distribution of resistant hosts across agricultural landscapes may have strong effects on the epidemiology and evolutionary potential of crop pathogens. However, we lack empirical tests of spatio‐temporal deployment of host resistance to pathogens can be best used to manage disease epidemics and disrupt pathogen evolutionary dynamics in real‐world systems. In a field experiment, we simulated how differences in Brassica napus resistance deployment strategies and landscape connectivity influence epidemic severity and Leptosphaeria maculans pathogen population composition. Host plant resistance, spatio‐temporal connectivity [stubble loads], and genetic connectivity of the inoculum source [composition of canola stubble mixtures] jointly impacted epidemiology (disease severity) and pathogen evolution (population composition). Changes in population composition were consistent with directional selection for the ability to infect the host (infectivity), leading to changes in pathotype (multilocus phenotypes) and infectivity frequencies. We repeatedly observed decreases in the frequency of unnecessary infectivity, suggesting that carrying multiple infectivity genes is costly for the pathogen. From an applied perspective, our results indicate that varying resistance genes in space and time can be used to help control disease, even when resistance has already been overcome. Furthermore, our approach extends our ability to test not only for the efficacy of host varieties in a given year, but also for durability over multiple cropping seasons, given variation in the combination of resistance genes deployed.

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“…After candidate effector genes have been identified and validated, detailed analyses of effector profiles (effectoromics) can be conducted at the population level to guide resistance breeding strategies, as recently described for global populations of Parastagonospora nodorum (68), regional populations of Leptosphaeria maculans in Australia (99), and local populations of P. infestans (101). This practice is the modern equivalent of the race typing (pathotyping) conducted for many fungal and oomycete pathogens by earlier generations of plant pathology researchers.…”

Section: Identifying Genes Under Selectionmentioning

confidence: 99%

Population Genomics of Fungal and Oomycete Pathogens

Grünwald

McDonald

Milgroom

2016

Annu. Rev. Phytopathol.

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We are entering a new era in plant pathology in which whole-genome sequences of many individuals of a pathogen species are becoming readily available. Population genomics aims to discover genetic mechanisms underlying phenotypes associated with adaptive traits such as pathogenicity, virulence, fungicide resistance, and host specialization, as genome sequences or large numbers of single nucleotide polymorphisms become readily available from multiple individuals of the same species. This emerging field encompasses detailed genetic analyses of natural populations, comparative genomic analyses of closely related species, identification of genes under selection, and linkage analyses involving association studies in natural populations or segregating populations resulting from crosses. The era of pathogen population genomics will provide new opportunities and challenges, requiring new computational and analytical tools. This review focuses on conceptual and methodological issues as well as the approaches to answering questions in population genomics. The major steps start with defining relevant biological and evolutionary questions, followed by sampling, genotyping, and phenotyping, and ending in analytical methods and interpretations. We provide examples of recent applications of population genomics to fungal and oomycete plant pathogens.

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Breakdown of resistance to the fungal disease, blackleg, is averted in commercial canola (Brassica napus) crops in Australia

Cited by 63 publications

References 39 publications

Canola cultivar mixtures and rotations do not mitigate the negative impacts of continuous canola

Canola cultivar mixtures and rotations do not mitigate the negative impacts of continuous canola

Spatio‐temporal connectivity and host resistance influence evolutionary and epidemiological dynamics of the canola pathogen Leptosphaeria maculans

Population Genomics of Fungal and Oomycete Pathogens

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