Cultivar mixtures for the simultaneous management of multiple diseases: tan spot and leaf rust of wheat

Crop Diversification to Control Rust in Faba Bean Caused by Uromyces viciae-fabae

Uromyces viciae-fabae is a highly specific biotrophic fungus that causes faba bean rust, one of the major diseases affecting this crop. We have assessed the feasibility of using intercropping (faba bean mixed with either pea, wheat or barley) or mixtures of susceptible and resistant cultivars to control rust both under field and controlled conditions. The results of four field intercropping experiments showed a significant reduction in rust severity on faba bean when intercropped with barley (average 22% reduction) but not with the other combinations. This reduction was also confirmed in studies under controlled conditions. The barrier effect of barley appears as the main mechanism explaining rust suppression. Additional experiments under controlled conditions showed that intercropping with barley did not influence the N content of faba bean and that different levels of N nutrition had no impact on rust severity in any case. The cultivar mixture field experiments showed that rust severity in the susceptible cultivar decreased as the proportion of the resistant cultivar in the mixture increased. The importance of the barrier effect of the resistant cultivars was determined in an experiment under controlled conditions. It can be concluded that crop diversification offers great potential to reduce rust in faba bean.

Genetic composition and diversity of Arabica coffee in the crop's center of origin and its impact on four major fungal diseases

Conventional wisdom states that genetic variation reduces disease levels in plant populations. Nevertheless, crop species have been subject to a gradual loss of genetic variation through selection for specific traits during breeding, thereby increasing their vulnerability to biotic stresses such as pathogens. We explored how genetic variation in Arabica coffee sites in southwestern Ethiopia was related to the incidence of four major fungal diseases. Sixty sites were selected along a gradient of management intensity, ranging from nearly wild to intensively managed coffee stands. We used genotyping-by-sequencing of pooled leaf samples (pool-GBS) derived from 16 individual coffee shrubs in each of the sixty sites to assess the variation in genetic composition (multivariate: reference allele frequency) and genetic diversity (univariate: mean expected heterozygosity) between sites. We found that genetic composition had a clear spatial pattern and that genetic diversity was higher in less managed sites. The incidence of the four fungal diseases was related to the genetic composition of the coffee stands, but in a specific way for each disease. In contrast, genetic diversity was only related to the within-site variation of coffee berry disease, but not to the mean incidence of any of the four diseases across sites. Given that fungal diseases are major challenges of Arabica coffee in its native range, our findings that genetic composition of coffee sites impacted the major fungal diseases may serve as baseline information to study the molecular basis of disease resistance in coffee. Overall, our study illustrates the need to consider both host genetic composition and genetic diversity when investigating the genetic basis for variation in disease levels.

Genetic diversity and disease: The past, present, and future of an old idea

Why do infectious diseases erupt in some host populations and not others? This question has spawned independent fields of research in evolution, ecology, public health, agriculture, and conservation. In the search for environmental and genetic factors that predict variation in parasitism, one hypothesis stands out for its generality and longevity: genetically homogeneous host populations are more likely to experience severe parasitism than genetically diverse populations. In this perspective piece, I draw on overlapping ideas from evolutionary biology, agriculture, and conservation to capture the far-reaching implications of the link between genetic diversity and disease. I first summarize the development of this hypothesis and the results of experimental tests. Given the convincing support for the protective effect of genetic diversity, I then address the following questions: (1) Where has this idea been put to use, in a basic and applied sense, and how can we better use genetic diversity to limit disease spread? (2) What new hypotheses does the established disease-diversity relationship compel us to test? I conclude that monitoring, preserving, and augmenting genetic diversity is one of our most promising evolutionarily informed strategies for buffering wild, domesticated, and human populations against future outbreaks.

Factors Influencing Rust (Melampsora apocyni) Intensity on Cultivated and Wild Apocynum venetum in Altay Prefecture, China

Rust (Melampsora apocyni) on Apocynum venetum is the major constraint to the commercial development of this medicinal herb. To determine the factors influencing rust intensity (maximum disease index [DI_max]), rust was investigated from 2011 to 2015 in both cultivated and wild A. venetum plants. Partial least squares path modeling (PLS-PM) was used to analyze the paths and extent of the factors related to pathogen, environment, and host that affect rust intensity. DI_max exhibited considerable variations across years and study sites, with variations linked to various factors fostering disease development. PLS-PM explained 80.0 and 70.1% of variations in DI_max in cultivated and wild plants, respectively. Precipitation was the key factor determining DI_max in both cultivated and wild plants (path coefficient [PC] = 0.313 and 0.544, respectively). In addition, the topsoil water content in cultivated plants and the total vegetation coverage in wild plants were also critical determinants of DI_max via their effects on the microclimatic factor (contribution coefficients [CC] = 0.681 and 0.989, respectively; PC = 0.831 and 0.231, respectively). In both cultivated and wild plants, host factors were mainly dominated by A. venetum density (CC = 0.989 and 0.894, respectively), and their effect on DI_max via the microclimatic factor (PC = 0.841 and 0.862, respectively) exceeded that via the inoculum factor (PC = 0.705 and 0.130, respectively). However, the indirect effects led to DI_max variation, while the dilution effect on host (CC = 0.154) from weed in wild plants led to the indirect effect size in wild plants of 0.200, which was lower than -0.699 in cultivated plants.

Contrasting plant height can improve the control of rain-borne diseases in wheat cultivar mixture: modelling splash dispersal in 3-D canopies

Background and Aims

Growing cultivars differing by their disease resistance level together (cultivar mixtures) can reduce the propagation of diseases. Although architectural characteristics of cultivars are little considered in mixture design, they could have an effect on disease, in particular through spore dispersal by rain splash, which occurs over short distances. The objective of this work was to assess the impact of plant height of wheat cultivars in mixtures on splash dispersal of Zymoseptoria tritici, which causes septoria tritici leaf blotch.

Methods

We used a modelling approach involving an explicit description of canopy architecture and splash dispersal processes. The dispersal model computed raindrop interception by a virtual canopy as well as the production, transport and interception of splash droplets carrying inoculum. We designed 3-D virtual canopies composed of susceptible and resistant plants, according to field measurements at the flowering stage. In numerical experiments, we tested different heights of virtual cultivars making up binary mixtures to assess the influence of this architectural trait on dispersal patterns of spore-carrying droplets.

Key Results

Inoculum interception decreased exponentially with the height relative to the main inoculum source (lower diseased leaves of susceptible plants), and little inoculum was intercepted further than 40 cm above the inoculum source. Consequently, tall plants intercepted less inoculum than smaller ones. Plants with twice the standard height intercepted 33 % less inoculum than standard height plants. In cases when the height of suscpeptible plants was doubled, inoculum interception by resistant leaves was 40 % higher. This physical barrier to spore-carrying droplet trajectories reduced inoculum interception by tall susceptible plants and was modulated by plant height differences between cultivars of a binary mixture.

Conclusions

These results suggest that mixture effects on spore dispersal could be modulated by an adequate choice of architectural characteristics of cultivars. In particular, even small differences in plant height could reduce spore dispersal.

IPSIM-Web, An Online Resource for Promoting Qualitative Aggregative Hierarchical Network Models to Predict Plant Disease Risk: Application to Brown Rust on Wheat

A qualitative pest modeling platform, named Injury Profile Simulator (IPSIM), provides a tool to design aggregative hierarchical network models to predict the risk of pest injuries, including diseases, on a given crop based on variables related to cropping practices as well as soil and weather environment at the field level. The IPSIM platform enables modelers to combine data from various sources (literature, survey, experiments, and so on), expert knowledge, and simulation to build a network-based model. The overall structure of the platform is fully described at the IPSIM-Web website ( www6.inra.fr/ipsim ). A new module called IPSIM-Wheat-brown rust is reported in this article as an example of how to use the system to build and test the predictive quality of a prediction model. Model performance was evaluated for a dataset comprising 1,788 disease observations at 13 French cereal-growing regions over 15 years. Accuracy of the predictions was 85% and the agreement with actual values was 0.66 based on Cohen's κ. The new model provides risk information for farmers and agronomists to make scientifically sound tactical (within-season) decisions. In addition, the model may be of use for ex post diagnoses of diseases in commercial fields. The limitations of the model such as low precision and threshold effects as well as the benefits, including the integration of different sources of information, transparency, flexibility, and a user-friendly interface, are discussed.

History, Epidemic Evolution, and Model Burn-In for a Network of Annual Invasion: Soybean Rust

Ecological history may be an important driver of epidemics and disease emergence. We evaluated the role of history and two related concepts, the evolution of epidemics and the burn-in period required for fitting a model to epidemic observations, for the U.S. soybean rust epidemic (caused by Phakopsora pachyrhizi). This disease allows evaluation of replicate epidemics because the pathogen reinvades the United States each year. We used a new maximum likelihood estimation approach for fitting the network model based on observed U.S. epidemics. We evaluated the model burn-in period by comparing model fit based on each combination of other years of observation. When the miss error rates were weighted by 0.9 and false alarm error rates by 0.1, the mean error rate did decline, for most years, as more years were used to construct models. Models based on observations in years closer in time to the season being estimated gave lower miss error rates for later epidemic years. The weighted mean error rate was lower in backcasting than in forecasting, reflecting how the epidemic had evolved. Ongoing epidemic evolution, and potential model failure, can occur because of changes in climate, host resistance and spatial patterns, or pathogen evolution.

Super-races are not likely to dominate a fungal population within a life time of a perennial crop plantation of cultivar mixtures: a simulation study

BACKGROUND

Deployment of cultivars with different resistance in mixtures is one means to manage plant diseases and prolong the life of resistance genes. One major concern in adopting mixtures is the development of 'super-races' that can overcome many resistance genes present in the mixture. A stochastic simulation model was developed to study the dynamics of virulence alleles in two-cultivar mixtures of perennial crops, focusing on the effects of cost of virulence and pathogen reproduction mechanism. The simulated mechanism of virulence has characteristics of both major and minor genes.

RESULTS

Random genetic drift due to repeated population crashes during the overwintering phase led to fixation of a single fungal genotype (in terms of its virulence), often within 100 seasons. Overall, cost of virulence is most important in determining the virulence dynamics under the present model formulation. With cost of virulence incorporated, nearly all simulation runs ended up with a single fungal genotype that can infect only one of the two cultivars. In absence of cost of virulence, most of the simulation runs ended up with fungal genotypes that can infect both host cultivars but in many cases do not contain the maximum possible number of virulence alleles due to random drift. A minimum of 20% sexual reproduction between strains from different cultivars is necessary to ensure that the final fixed strains are able to infect both cultivars. Although the number of virulence alleles in the final genotype and the time to fixation are affected by simulation factors, most of the variability was among replicate simulation runs (i.e. stochastic in nature). The time to fixation is generally long relative to cropping cycles.

CONCLUSIONS

A single fungal genotype will dominate a population due to the bottleneck in overwintering with cost of virulence primarily determining whether the dominant genotype can infect both cultivars. However, the dominant genotype is unlikely to accumulate all the virulence alleles due to genetic drift. The risk of emergence and spread of super-races is insufficiently great to prevent the use of cultivar mixtures of perennial crops as a means to reduce disease development provided that host resistance structure in mixtures is altered every cropping cycle.

Pathogen populations evolve to greater race complexity in agricultural systems--evidence from analysis of Rhynchosporium secalis virulence data

Fitness cost associated with pathogens carrying unnecessary virulence alleles is the fundamental assumption for preventing the emergence of complex races in plant pathogen populations but this hypothesis has rarely been tested empirically on a temporal and spatial scale which is sufficient to distinguish evolutionary signals from experimental error. We analyzed virulence characteristics of ≈ 1000 isolates of the barley pathogen Rhynchosporium secalis collected from different parts of the United Kingdom between 1984 and 2005. We found a gradual increase in race complexity over time with a significant correlation between sampling date and race complexity of the pathogen (r(20) = 0.71, p = 0.0002) and an average loss of 0.1 avirulence alleles (corresponding to an average gain of 0.1 virulence alleles) each year. We also found a positive and significant correlation between barley cultivar diversity and R. secalis virulence variation. The conditions assumed to favour complex races were not present in the United Kingdom and we hypothesize that the increase in race complexity is attributable to the combination of natural selection and genetic drift. Host resistance selects for corresponding virulence alleles to fixation or dominant frequency. Because of the weak fitness penalty of carrying the unnecessary virulence alleles, genetic drift associated with other evolutionary forces such as hitch-hiking maintains the frequency of the dominant virulence alleles even after the corresponding resistance factors cease to be used.

Identifying highly connected counties compensates for resource limitations when evaluating national spread of an invasive pathogen

Surveying invasive species can be highly resource intensive, yet near-real-time evaluations of invasion progress are important resources for management planning. In the case of the soybean rust invasion of the United States, a linked monitoring, prediction, and communication network saved U.S. soybean growers approximately $200 M/yr. Modeling of future movement of the pathogen (Phakopsora pachyrhizi) was based on data about current disease locations from an extensive network of sentinel plots. We developed a dynamic network model for U.S. soybean rust epidemics, with counties as nodes and link weights a function of host hectarage and wind speed and direction. We used the network model to compare four strategies for selecting an optimal subset of sentinel plots, listed here in order of increasing performance: random selection, zonal selection (based on more heavily weighting regions nearer the south, where the pathogen overwinters), frequency-based selection (based on how frequently the county had been infected in the past), and frequency-based selection weighted by the node strength of the sentinel plot in the network model. When dynamic network properties such as node strength are characterized for invasive species, this information can be used to reduce the resources necessary to survey and predict invasion progress.

Transcriptome-based differentiation of closely-related Miscanthus lines

Background

Distinguishing between individuals is critical to those conducting animal/plant breeding, food safety/quality research, diagnostic and clinical testing, and evolutionary biology studies. Classical genetic identification studies are based on marker polymorphisms, but polymorphism-based techniques are time and labor intensive and often cannot distinguish between closely related individuals. Illumina sequencing technologies provide the detailed sequence data required for rapid and efficient differentiation of related species, lines/cultivars, and individuals in a cost-effective manner. Here we describe the use of Illumina high-throughput exome sequencing, coupled with SNP mapping, as a rapid means of distinguishing between related cultivars of the lignocellulosic bioenergy crop giant miscanthus (Miscanthus × giganteus). We provide the first exome sequence database for Miscanthus species complete with Gene Ontology (GO) functional annotations.

Results

A SNP comparative analysis of rhizome-derived cDNA sequences was successfully utilized to distinguish three Miscanthus × giganteus cultivars from each other and from other Miscanthus species. Moreover, the resulting phylogenetic tree generated from SNP frequency data parallels the known breeding history of the plants examined. Some of the giant miscanthus plants exhibit considerable sequence divergence.

Conclusions

Here we describe an analysis of Miscanthus in which high-throughput exome sequencing was utilized to differentiate between closely related genotypes despite the current lack of a reference genome sequence. We functionally annotated the exome sequences and provide resources to support Miscanthus systems biology. In addition, we demonstrate the use of the commercial high-performance cloud computing to do computational GO annotation.

Biodiversity effects on yield and unsown species invasion in a temperate forage ecosystem

BACKGROUND AND AIMS

Current agricultural practices are based on growing monocultures or binary mixtures over large areas, with a resultant impoverishing effect on biodiversity at several trophic levels. The effects of increasing the biodiversity of a sward mixture on dry matter yield and unsown species invasion were studied.

METHODS

A field experiment involving four grassland species [two grasses--perennial ryegrass (Lolium perenne) and cocksfoot (Dactylis glomerata)--and two legumes--red clover (Trifolium pratense) and white clover (Trifolium repens)], grown in monocultures and mixtures in accordance with a simplex design, was carried out. The legumes were included either as single varieties or as one of two broad genetic-base composites. The experiment was harvested three times a year over three years; dry matter yield and yield of unsown species were determined at each harvest. Yields of individual species and interactions between all species present were estimated through a statistical modelling approach.

KEY RESULTS

Species diversity produced a strong positive yield effect that resulted in transgressive over-yielding in the second and third years. Using broad genetic-base composites of the legumes had a small impact on yield and species interactions. Invasion by unsown species was strongly reduced by species diversity, but species identity was also important. Cocksfoot and white clover (with the exception of one broad genetic-base composite) reduced invasion, while red clover was the most invaded species.

CONCLUSIONS

The results show that it is possible to increase, and stabilize, the yield of a grassland crop and reduce invasion by unsown species by increasing its species diversity.

Genetic diversity of Daphnia magna populations enhances resistance to parasites

The diversity-disease hypothesis states that decreased genetic diversity in host populations increases the incidence of diseases caused by pathogens (= monoculture effect) and eventually influences ecosystem functioning. The monoculture effect is well-known from crop studies and may be partially specific to the artificial situation in agriculture. The effect received little attention in animal populations of different diversities. Compared with plants, animals are mobile and exhibiting social interactions. We followed the spread of a microsporidian parasite in semi-natural outdoor Daphnia magna populations of low and high genetic diversity. We used randomly selected, naturally occurring host genotypes. Host populations of low diversity were initially monoclonal, while the host populations of high diversity started with 10 genotypes per replicate. We found that the parasite spread significantly better in host populations of low diversity compared with host populations of high diversity, independent of parasite diversity. The difference was visible over a 3-year period. Host genotypic diversity did not affect host population density. Our experiment demonstrated a monoculture effect in independently replicated semi-natural zooplankton populations, indicating that the monoculture effect may be relevant beyond agriculture.

Reactions of Perennial Grain Accessions to Four Major Cereal Pathogens of the Great Plains

Methods of disease management used in annual grain crops, especially cultural practices designed to disrupt the disease cycle of a particular pathogen, will not necessarily be applicable to perennial grain crops. Resistance to multiple pathogens, therefore, will clearly be important in disease management. The objective of this research was to evaluate disease resistance in 10 perennial grain accessions (one to two accessions of each: perennial wheat (Thinopyrum sp. × Triticum aestivum), intermediate wheatgrass (Thinopyrum intermedium), perennial rye (Secale montanum), hexaploid triticale (Triticum turgidum × S. montanum), octoploid triticale (Triticum aestivum × S. montanum), tetraploid perennial rye (Secale cereale × S. montanum), and tall wheat-grass (Thinopyrum ponticum)) to tan spot (caused by Pyrenophora tritici-repentis), take-all (caused by Gaeumannomyces graminis var. tritici), wheat streak mosaic, and barley yellow dwarf, four important diseases of the Great Plains. Several of the grasses were resistant to tan spot, barley yellow dwarf, and wheat streak mosaic. Indeed, the wild grasses and perennial donors T. intermedium (including BFPMC1), T. ponticum, and S. montanum, in addition to Permontra, a tetraploid perennial rye, were highly resistant to all three diseases. Additionally, the remaining grasses tested were also more resistant to tan spot than the susceptible wheat control. However, none of the 10 grass accessions appeared highly resistant to take-all, and substantial losses in biomass were observed, although such effects may be moderated under field conditions due to the potential for take-all decline in perennial plantings.

Competition, facilitation, and niche differentiation in two foliar pathogens

We studied competition between the obligate biotroph Puccinia triticina (designated here as Puccinia) and the facultative saprophyte Pyrenophora tritici-repentis (designated here as Pyrenophora) in older and younger leaves in a set of three host genotypes selected to be resistant to Puccinia only, Pyrenophora only, or neither. Age-related resistance is important for both of these pathogens. The facultative saprophyte Pyrenophora was generally a stronger competitor than the biotrophic Puccinia, even experiencing facilitation from the presence of Puccinia when Pyrenophora had the advantage of earlier inoculation. Both pathogen species produced the most spores when they were introduced before the competing species and more spores when introduced simultaneously compared to after the competitor. The pre-interactive niche of Puccinia was larger than the post-interactive niche and sporulation by Puccinia was substantially reduced in environments in which Pyrenophora had high sporulation rates. The pre-interactive niche of Pyrenophora was similar to the post-interactive niche and Pyrenophora had proportionally lower reductions in sporulation due to interspecific competition in the pre-interactive niche.