Rimbaud Loup, Papaïx Julien, Barrett Luke G, Burdon Jeremy J, Thrall Peter H
CSIRO Agriculture and Food Canberra Australian Capital Territory Australia.
BioSP, INRA Avignon France.
Evol Appl. 2018 Sep 17;11(10):1791-1810. doi: 10.1111/eva.12681. eCollection 2018 Dec.
Once deployed uniformly in the field, genetically controlled plant resistance is often quickly overcome by pathogens, resulting in dramatic losses. Several strategies have been proposed to constrain the evolutionary potential of pathogens and thus increase resistance durability. These strategies can be classified into four categories, depending on whether resistance sources are varied across time (rotations) or combined in space in the same cultivar (pyramiding), in different cultivars within a field (cultivar mixtures) or among fields (mosaics). Despite their potential to differentially affect both pathogen epidemiology and evolution, to date the four categories of deployment strategies have never been directly compared together within a single theoretical or experimental framework, with regard to efficiency (ability to reduce disease impact) and durability (ability to limit pathogen evolution and delay resistance breakdown). Here, we used a spatially explicit stochastic demogenetic model, implemented in the R package , to assess the epidemiological and evolutionary outcomes of these deployment strategies when two major resistance genes are present. We varied parameters related to pathogen evolutionary potential (mutation probability and associated fitness costs) and landscape organization (mostly the relative proportion of each cultivar in the landscape and levels of spatial or temporal aggregation). Our results, broadly focused on qualitative resistance to rust fungi of cereal crops, show that evolutionary and epidemiological control are not necessarily correlated and that no deployment strategy is universally optimal. Pyramiding two major genes offered the highest durability, but at high mutation probabilities, mosaics, mixtures and rotations can perform better in delaying the establishment of a universally infective superpathogen. All strategies offered the same short-term epidemiological control, whereas rotations provided the best long-term option, after all sources of resistance had broken down. This study also highlights the significant impact of landscape organization and pathogen evolutionary ability in considering the optimal design of a deployment strategy.
一旦在田间均匀部署,基因控制的植物抗性往往会很快被病原体克服,从而导致巨大损失。人们提出了几种策略来限制病原体的进化潜力,从而提高抗性的持久性。根据抗性来源是随时间变化(轮作)还是在同一品种中在空间上组合(基因叠加)、在田间不同品种中(品种混合)或在不同田间(镶嵌),这些策略可分为四类。尽管它们有可能以不同方式影响病原体的流行病学和进化,但迄今为止,这四类部署策略从未在单一的理论或实验框架内,就效率(降低病害影响的能力)和持久性(限制病原体进化和延缓抗性丧失的能力)进行过直接比较。在这里,我们使用在R软件包中实现的空间明确的随机种群遗传模型,来评估当存在两个主要抗性基因时这些部署策略的流行病学和进化结果。我们改变了与病原体进化潜力(突变概率和相关适合度代价)和景观组织(主要是景观中每个品种的相对比例以及空间或时间聚集水平)相关的参数。我们的结果主要集中在对谷物作物锈病真菌的定性抗性上,表明进化控制和流行病学控制不一定相关,而且没有一种部署策略是普遍最优的。叠加两个主要基因提供了最高的持久性,但在高突变概率下,镶嵌、混合和轮作在延缓普遍感染性超级病原体的出现方面可能表现得更好。所有策略在短期内提供相同的流行病学控制,而在所有抗性来源都失效后,轮作提供了最佳的长期选择。这项研究还强调了景观组织和病原体进化能力在考虑部署策略的最优设计方面的重大影响。