Impact of initial pathogen density on resistance and tolerance in a polymorphic disease resistance gene system in Arabidopsis thaliana

A Genome-Wide Association study in Arabidopsis thaliana to decipher the adaptive genetics of quantitative disease resistance in a native heterogeneous environment

Pathogens are often the main selective agents acting in plant communities, thereby influencing the distribution of polymorphism at loci affecting resistance within and among natural plant populations. In addition, the outcome of plant-pathogen interactions can be drastically affected by abiotic and biotic factors at different spatial and temporal grains. The characterization of the adaptive genetic architecture of disease resistance in native heterogeneous environments is however still missing. In this study, we conducted an in situ Genome-Wide Association study in the spatially heterogeneous native habitat of a highly genetically polymorphic local mapping population of Arabidopsis thaliana, to unravel the adaptive genetic architecture of quantitative disease resistance. Disease resistance largely differed among three native soils and was affected by the presence of the grass Poa annua. The observation of strong crossing reactions norms among the 195 A. thaliana genotypes for disease resistance among micro-habitats, combined with a negative fecundity-disease resistance relationship in each micro-habitat, suggest that alternative local genotypes of A. thaliana are favored under contrasting environmental conditions at the scale of few meters. A complex genetic architecture was detected for disease resistance and fecundity. However, only few QTLs were common between these two traits. Heterogeneous selection in this local population should therefore promote the maintenance of polymorphism at only few candidate resistance genes.

Tolerance and overcompensation to infection by Phytophthora infestans in the wild perennial climber Solanum dulcamara

Studies of infection by Phytophthora infestans-the causal agent of potato late blight-in wild species can provide novel insights into plant defense responses, and indicate how wild plants might be influenced by recurrent epidemics in agricultural fields. In the present study, our aim was to investigate if different clones of Solanum dulcamara (a relative of potato) collected in the wild differ in resistance and tolerance to infection by a common European isolate of P. infestans. We performed infection experiments with six S. dulcamara genotypes (clones) both in the laboratory and in the field and measured the degree of infection and plant performance traits. In the laboratory, the six evaluated genotypes varied from resistant to susceptible, as measured by degree of infection 20 days post infection. Two of the four genotypes susceptible to infection showed a quadratic (concave downward) relationship between the degree of infection and shoot length, with maximum shoot length at intermediate values of infection. This result suggests overcompensation, that is, an increase in growth in infected individuals. The number of leaves decreased with increasing degree of infection, but at different rates in the four susceptible genotypes, indicating genetic variation for tolerance. In the field, the inoculated genotypes did not show any disease symptoms, but plant biomass at the end of the growing season was higher for inoculated plants than for controls, in-line with the overcompensation detected in the laboratory. We conclude that in S. dulcamara there are indications of genetic variation for both resistance and tolerance to P. infestans infection. Moreover, some genotypes displayed overcompensation. Learning about plant tolerance and overcompensation to infection by pathogens can help broaden our understanding of plant defense in natural populations and help develop more sustainable plant protection strategies for economically important crop diseases.

Dissection of the molecular bases of genotype x environment interactions: a study of phenotypic plasticity of Saccharomyces cerevisiae in grape juices

Background

The ability of a genotype to produce different phenotypes according to its surrounding environment is known as phenotypic plasticity. Within different individuals of the same species, phenotypic plasticity can vary greatly. This contrasting response is caused by gene-by-environment interactions (GxE). Understanding GxE interactions is particularly important in agronomy, since selected breeds and varieties may have divergent phenotypes according to their growing environment. Industrial microbes such as Saccharomyces cerevisiae are also faced with a large range of fermentation conditions that affect their technological properties. Finding the molecular determinism of such variations is a critical task for better understanding the genetic bases of phenotypic plasticity and can also be helpful in order to improve breeding methods.

Results

In this study we implemented a QTL mapping program using two independent cross (~ 100 progeny) in order to investigate the molecular basis of yeast phenotypic response in a wine fermentation context. Thanks to whole genome sequencing approaches, both crosses were genotyped, providing saturated genetic maps of thousands of markers. Linkage analyses allowed the detection of 78 QTLs including 21 with significant interaction with the environmental conditions. Molecular dissection of a major QTL demonstrated that the sulfite pump Ssu1p has a pleiotropic effect and impacts the phenotypic plasticity of several traits.

Conclusions

The detection of QTLs and their interactions with environment emphasizes the complexity of yeast industrial traits. The validation of the interaction of SSU1 allelic variants with the nature of the fermented juice increases knowledge about the impact of the sulfite pump during fermentation. All together these results pave the way for exploiting and deciphering the genetic determinism of phenotypic plasticity.

Electronic supplementary material

The online version of this article (10.1186/s12864-018-5145-4) contains supplementary material, which is available to authorized users.

Bayesian estimation and use of high-throughput remote sensing indices for quantitative genetic analyses of leaf growth

We develop Bayesian function-valued trait models that mathematically isolate genetic mechanisms underlying leaf growth trajectories by factoring out genotype-specific differences in photosynthesis. Remote sensing data can be used instead of leaf-level physiological measurements. Characterizing the genetic basis of traits that vary during ontogeny and affect plant performance is a major goal in evolutionary biology and agronomy. Describing genetic programs that specifically regulate morphological traits can be complicated by genotypic differences in physiological traits. We describe the growth trajectories of leaves using novel Bayesian function-valued trait (FVT) modeling approaches in Brassica rapa recombinant inbred lines raised in heterogeneous field settings. While frequentist approaches estimate parameter values by treating each experimental replicate discretely, Bayesian models can utilize information in the global dataset, potentially leading to more robust trait estimation. We illustrate this principle by estimating growth asymptotes in the face of missing data and comparing heritabilities of growth trajectory parameters estimated by Bayesian and frequentist approaches. Using pseudo-Bayes factors, we compare the performance of an initial Bayesian logistic growth model and a model that incorporates carbon assimilation (A _max) as a cofactor, thus statistically accounting for genotypic differences in carbon resources. We further evaluate two remotely sensed spectroradiometric indices, photochemical reflectance (pri2) and MERIS Terrestrial Chlorophyll Index (mtci) as covariates in lieu of A _max, because these two indices were genetically correlated with A _max across years and treatments yet allow much higher throughput compared to direct leaf-level gas-exchange measurements. For leaf lengths in uncrowded settings, including A _max improves model fit over the initial model. The mtci and pri2 indices also outperform direct A _max measurements. Of particular importance for evolutionary biologists and plant breeders, hierarchical Bayesian models estimating FVT parameters improve heritabilities compared to frequentist approaches.

Recombination Rate Heterogeneity within Arabidopsis Disease Resistance Genes

Meiotic crossover frequency varies extensively along chromosomes and is typically concentrated in hotspots. As recombination increases genetic diversity, hotspots are predicted to occur at immunity genes, where variation may be beneficial. A major component of plant immunity is recognition of pathogen Avirulence (Avr) effectors by resistance (R) genes that encode NBS-LRR domain proteins. Therefore, we sought to test whether NBS-LRR genes would overlap with meiotic crossover hotspots using experimental genetics in Arabidopsis thaliana. NBS-LRR genes tend to physically cluster in plant genomes; for example, in Arabidopsis most are located in large clusters on the south arms of chromosomes 1 and 5. We experimentally mapped 1,439 crossovers within these clusters and observed NBS-LRR gene associated hotspots, which were also detected as historical hotspots via analysis of linkage disequilibrium. However, we also observed NBS-LRR gene coldspots, which in some cases correlate with structural heterozygosity. To study recombination at the fine-scale we used high-throughput sequencing to analyze ~1,000 crossovers within the RESISTANCE TO ALBUGO CANDIDA1 (RAC1) R gene hotspot. This revealed elevated intragenic crossovers, overlapping nucleosome-occupied exons that encode the TIR, NBS and LRR domains. The highest RAC1 recombination frequency was promoter-proximal and overlapped CTT-repeat DNA sequence motifs, which have previously been associated with plant crossover hotspots. Additionally, we show a significant influence of natural genetic variation on NBS-LRR cluster recombination rates, using crosses between Arabidopsis ecotypes. In conclusion, we show that a subset of NBS-LRR genes are strong hotspots, whereas others are coldspots. This reveals a complex recombination landscape in Arabidopsis NBS-LRR genes, which we propose results from varying coevolutionary pressures exerted by host-pathogen relationships, and is influenced by structural heterozygosity.

Mechanisms of quantitative disease resistance in plants

Quantitative disease resistance (QDR) causes the reduction, but not absence, of disease, and is a major type of disease resistance for many crop species. QDR results in a continuous distribution of disease scores across a segregating population, and is typically due to many genes with small effects. It may also be a source of durable resistance. The past decade has seen significant progress in cloning genes underlying QDR. In this review, we focus on these recently cloned genes and identify new themes of QDR emerging from these studies.

The Genetics Underlying Natural Variation in the Biotic Interactions of Arabidopsis thaliana: The Challenges of Linking Evolutionary Genetics and Community Ecology

In the context of global change, predicting the responses of plant communities in an ever-changing biotic environment calls for a multipronged approach at the interface of evolutionary genetics and community ecology. However, our understanding of the genetic basis of natural variation involved in mediating biotic interactions, and associated adaptive dynamics of focal plants in their natural communities, is still in its infancy. Here, we review the genetic and molecular bases of natural variation in the response to biotic interactions (viruses, bacteria, fungi, oomycetes, herbivores, and plants) in the model plant Arabidopsis thaliana as well as the adaptive value of these bases. Among the 60 identified genes are a number that encode nucleotide-binding site leucine-rich repeat (NBS-LRR)-type proteins, consistent with early examples of plant defense genes. However, recent studies have revealed an extensive diversity in the molecular mechanisms of defense. Many types of genetic variants associate with phenotypic variation in biotic interactions, even among the genes of large effect that tend to be identified. In general, we found that (i) balancing selection rather than directional selection explains the observed patterns of genetic diversity within A. thaliana and (ii) the cost/benefit tradeoffs of adaptive alleles can be strongly dependent on both genomic and environmental contexts. Finally, because A. thaliana rarely interacts with only one biotic partner in nature, we highlight the benefit of exploring diffuse biotic interactions rather than tightly associated host-enemy pairs. This challenge would help to improve our understanding of coevolutionary quantitative genetics within the context of realistic community complexity.

Modeling development and quantitative trait mapping reveal independent genetic modules for leaf size and shape

Improved predictions of fitness and yield may be obtained by characterizing the genetic controls and environmental dependencies of organismal ontogeny. Elucidating the shape of growth curves may reveal novel genetic controls that single-time-point (STP) analyses do not because, in theory, infinite numbers of growth curves can result in the same final measurement. We measured leaf lengths and widths in Brassica rapa recombinant inbred lines (RILs) throughout ontogeny. We modeled leaf growth and allometry as function valued traits (FVT), and examined genetic correlations between these traits and aspects of phenology, physiology, circadian rhythms and fitness. We used RNA-seq to construct a SNP linkage map and mapped trait quantitative trait loci (QTL). We found genetic trade-offs between leaf size and growth rate FVT and uncovered differences in genotypic and QTL correlations involving FVT vs STPs. We identified leaf shape (allometry) as a genetic module independent of length and width and identified selection on FVT parameters of development. Leaf shape is associated with venation features that affect desiccation resistance. The genetic independence of leaf shape from other leaf traits may therefore enable crop optimization in leaf shape without negative effects on traits such as size, growth rate, duration or gas exchange.

The cost of phage resistance in a plant pathogenic bacterium is context-dependent

Parasites are ubiquitous features of living systems and many parasites severely reduce the fecundity or longevity of their hosts. This parasite-imposed selection on host populations should strongly favor the evolution of host resistance, but hosts typically face a trade-off between investment in reproductive fitness and investment in defense against parasites. The magnitude of such a trade-off is likely to be context-dependent, and accordingly costs that are key in shaping evolution in nature may not be easily observable in an artificial environment. We set out to assess the costs of phage resistance for a plant pathogenic bacterium in its natural plant host versus in a nutrient-rich, artificial medium. We demonstrate that mutants of Pseudomonas syringae that have evolved resistance via a single mutational step pay a substantial cost for this resistance when grown on their tomato plant hosts, but do not realize any measurable growth rate costs in nutrient-rich media. This work demonstrates that resistance to phage can significantly alter bacterial growth within plant hosts, and therefore that phage-mediated selection in nature is likely to be an important component of bacterial pathogenicity.

Expanding the eco-evolutionary context of herbicide resistance research

The potential for human-driven evolution in economically and environmentally important organisms in medicine, agriculture and conservation management is now widely recognised. The evolution of herbicide resistance in weeds is a classic example of rapid adaptation in the face of human-mediated selection. Management strategies that aim to slow or prevent the evolution of herbicide resistance must be informed by an understanding of the ecological and evolutionary factors that drive selection in weed populations. Here, we argue for a greater focus on the ultimate causes of selection for resistance in herbicide resistance studies. The emerging fields of eco-evolutionary dynamics and applied evolutionary biology offer a means to achieve this goal and to consider herbicide resistance in a broader and sometimes novel context. Four relevant research questions are presented, which examine (i) the impact of herbicide dose on selection for resistance, (ii) plant fitness in herbicide resistance studies, (iii) the efficacy of herbicide rotations and mixtures and (iv) the impacts of gene flow on resistance evolution and spread. In all cases, fundamental ecology and evolution have the potential to offer new insights into herbicide resistance evolution and management.

Mapping QTL conferring resistance in maize to gray leaf spot disease caused by Cercospora zeina

BACKGROUND

Gray leaf spot (GLS) is a globally important foliar disease of maize. Cercospora zeina, one of the two fungal species that cause the disease, is prevalent in southern Africa, China, Brazil and the eastern corn belt of the USA. Identification of QTL for GLS resistance in subtropical germplasm is important to support breeding programmes in developing countries where C. zeina limits production of this staple food crop.

RESULTS

A maize RIL population (F7:S6) from a cross between CML444 and SC Malawi was field-tested under GLS disease pressure at five field sites over three seasons in KwaZulu-Natal, South Africa. Thirty QTL identified from eleven field trials (environments) were consolidated to seven QTL for GLS resistance based on their expression in at least two environments and location in the same core maize bins. Four GLS resistance alleles were derived from the more resistant parent CML444 (bin 1.10, 4.08, 9.04/9.05, 10.06/10.07), whereas the remainder were from SC Malawi (bin 6.06/6.07, 7.02/7.03, 9.06). QTLs in bin 4.08 and bin 6.06/6.07 were also detected as joint QTLs, each explained more than 11% of the phenotypic variation, and were identified in four and seven environments, respectively. Common markers were used to allocate GLS QTL from eleven previous studies to bins on the IBM2005 map, and GLS QTL "hotspots" were noted. Bin 4.08 and 7.02/7.03 GLS QTL from this study overlapped with hotspots, whereas the bin 6.06/6.07 and bin 9.06 QTLs appeared to be unique. QTL for flowering time (bin 1.07, 4.09) in this population did not correspond to QTL for GLS resistance.

CONCLUSIONS

QTL mapping of a RIL population from the subtropical maize parents CML444 and SC Malawi identified seven QTL for resistance to gray leaf spot disease caused by C. zeina. These QTL together with QTL from eleven studies were allocated to bins on the IBM2005 map to provide a basis for comparison. Hotspots of GLS QTL were identified on chromosomes one, two, four, five and seven, with QTL in the current study overlapping with two of these. Two QTL from this study did not overlap with previously reported QTL.

Breeding for resistances to Ralstonia solanacearum

Ralstonia solanacearum is one of the most devastating bacterial plant pathogens due to its large host range, worldwide geographic distribution and persistence in fields. This soilborne pathogen is the causal agent of bacterial wilt and it can infect major agricultural crops thereby reducing significantly their yield. To favor infection, the bacterium delivers, through the type three secretion system, effectors that manipulate plant immunity. In this review, the relative efficiency of control strategies and existing resistances to R. solanacearum will be presented. Then, the genetic and molecular insights gained from the study of bacterial wilt in model plants will be described. Finally, I will explore how the knowledge gathered from unraveling avirulence and virulence mechanisms of R. solanacearum effectors could help to develop more durable resistances in crop plants toward this destructive pathogen.

Gene-for-gene tolerance to bacterial wilt in Arabidopsis

Bacterial wilt caused by Ralstonia solanacearum is a disease of widespread economic importance that affects numerous plant species, including Arabidopsis thaliana. We describe a pathosystem between A. thaliana and biovar 3 phylotype I strain BCCF402 of R. solanacearum isolated from Eucalyptus trees. A. thaliana accession Be-0 was susceptible and accession Kil-0 was tolerant. Kil-0 exhibited no wilting symptoms and no significant reduction in fitness (biomass, seed yield, and germination efficiency) after inoculation with R. solanacearum BCCF402, despite high bacterial numbers in planta. This was in contrast to the well-characterized resistance response in the accession Nd-1, which limits bacterial multiplication at early stages of infection and does not wilt. R. solanacearum BCCF402 was highly virulent because the susceptible accession Be-0 was completely wilted after inoculation. Genetic analyses, allelism studies with Nd-1, and RRS1 cleaved amplified polymorphic sequence marker analysis showed that the tolerance phenotype in Kil-0 was dependent upon the resistance gene RRS1. Knockout and complementation studies of the R. solanacearum BCCF402 effector PopP2 confirmed that the tolerance response in Kil-0 was dependent upon the RRS1-PopP2 interaction. Our data indicate that the gene-for-gene interaction between RRS1 and PopP2 can contribute to tolerance, as well as resistance, which makes it a useful model system for evolutionary studies of the arms race between plants and bacterial pathogens. In addition, the results alert biotechnologists to the risk that deployment of RRS1 in transgenic crops may result in persistence of the pathogen in the field.

Genetics and evolution of function-valued traits: understanding environmentally responsive phenotypes

Many central questions in ecology and evolutionary biology require characterizing phenotypes that change with time and environmental conditions. Such traits are inherently functions, and new 'function-valued' methods use the order, spacing, and functional nature of the data typically ignored by traditional univariate and multivariate analyses. These rapidly developing methods account for the continuous change in traits of interest in response to other variables, and are superior to traditional summary-based analyses for growth trajectories, morphological shapes, and environmentally sensitive phenotypes. Here, we explain how function-valued methods make flexible use of data and lead to new biological insights. These approaches frequently offer enhanced statistical power, a natural basis of interpretation, and are applicable to many existing data sets. We also illustrate applications of function-valued methods to address ecological, evolutionary, and behavioral hypotheses, and highlight future directions.

Adaptive value of phenological traits in stressful environments: predictions based on seed production and laboratory natural selection

Phenological traits often show variation within and among natural populations of annual plants. Nevertheless, the adaptive value of post-anthesis traits is seldom tested. In this study, we estimated the adaptive values of pre- and post-anthesis traits in two stressful environments (water stress and interspecific competition), using the selfing annual species Arabidopsis thaliana. By estimating seed production and by performing laboratory natural selection (LNS), we assessed the strength and nature (directional, disruptive and stabilizing) of selection acting on phenological traits in A. thaliana under the two tested stress conditions, each with four intensities. Both the type of stress and its intensity affected the strength and nature of selection, as did genetic constraints among phenological traits. Under water stress, both experimental approaches demonstrated directional selection for a shorter life cycle, although bolting time imposes a genetic constraint on the length of the interval between bolting and anthesis. Under interspecific competition, results from the two experimental approaches showed discrepancies. Estimation of seed production predicted directional selection toward early pre-anthesis traits and long post-anthesis periods. In contrast, the LNS approach suggested neutrality for all phenological traits. This study opens questions on adaptation in complex natural environment where many selective pressures act simultaneously.

The impact of temperature on balancing immune responsiveness and growth in Arabidopsis

Plants have evolved polymorphic immune receptors to recognize pathogens causing disease. However, triggering of resistance needs to be tuned to the local environment to maintain a balance between defense and growth. We consider here the impact of temperature as a key environmental factor influencing immune pathway activation in Arabidopsis. Genetic compensatory and molecular buffering mechanisms affecting the diversification, functionality and subcellular dynamics of immune receptors, reveal multiple points at which temperature intersects with host resistance signaling systems, including a role of at least one receptor in sensing temperature change. Analysis of temperature-dependent autoimmunity caused by allelic mismatches in hybrids of evolutionary diverged Arabidopsis accessions is illuminating processes by which plants maintain 'poise' between immune responsiveness and fitness in natural populations.

Adaptation to climate across the Arabidopsis thaliana genome

Understanding the genetic bases and modes of adaptation to current climatic conditions is essential to accurately predict responses to future environmental change. We conducted a genome-wide scan to identify climate-adaptive genetic loci and pathways in the plant Arabidopsis thaliana. Amino acid-changing variants were significantly enriched among the loci strongly correlated with climate, suggesting that our scan effectively detects adaptive alleles. Moreover, from our results, we successfully predicted relative fitness among a set of geographically diverse A. thaliana accessions when grown together in a common environment. Our results provide a set of candidates for dissecting the molecular bases of climate adaptations, as well as insights about the prevalence of selective sweeps, which has implications for predicting the rate of adaptation.

Cheating, trade-offs and the evolution of aggressiveness in a natural pathogen population

The evolutionary dynamics of pathogens are critically important for disease outcomes, prevalence and emergence. In this study we investigate ecological conditions that may promote the long-term maintenance of virulence polymorphisms in pathogen populations. Recent theory predicts that evolution towards increased virulence can be reversed if less-aggressive social 'cheats' exploit more aggressive 'cooperator' pathogens. However, there is no evidence that social exploitation operates within natural pathogen populations. We show that for the bacterium Pseudomonas syringae, major polymorphisms for pathogenicity are maintained at unexpectedly high frequencies in populations infecting the host Arabidopsis thaliana. Experiments reveal that less-aggressive strains substantially increase their growth potential in mixed infections and have a fitness advantage in non-host environments. These results suggest that niche differentiation can contribute to the maintenance of virulence polymorphisms, and that both within-host and between-host growth rates modulate cheating and cooperation in P. syringae populations.

Plant-parasite coevolution: bridging the gap between genetics and ecology

We review current ideas about coevolution of plants and parasites, particularly processes that generate genetic diversity. Frequencies of host resistance and parasite virulence alleles that interact in gene-for-gene (GFG) relationships coevolve in the familiar boom-and-bust cycle, in which resistance is selected when virulence is rare, and virulence is selected when resistance is common. The cycle can result in stable polymorphism when diverse ecological and epidemiological factors cause negative direct frequency-dependent selection (ndFDS) on host resistance, parasite virulence, or both, such that the benefit of a trait to fitness declines as its frequency increases. Polymorphism can also be stabilized by overdominance, when heterozygous hosts have greater resistance than homozygotes to diverse pathogens. Genetic diversity can also persist in the form of statistical polymorphism, sustained by random processes acting on gene frequencies and population size. Stable polymorphism allows alleles to be long-lived and genetic variation to be detectable in natural populations. In agriculture, many of the factors promoting stability in host-parasite interactions have been lost, leading to arms races of host defenses and parasite effectors.

Towards identifying genes underlying ecologically relevant traits in Arabidopsis thaliana

A major challenge in evolutionary biology and plant breeding is to identify the genetic basis of complex quantitative traits, including those that contribute to adaptive variation. Here we review the development of new methods and resources to fine-map intraspecific genetic variation that underlies natural phenotypic variation in plants. In particular, the analysis of 107 quantitative traits reported in the first genome-wide association mapping study in Arabidopsis thaliana sets the stage for an exciting time in our understanding of plant adaptation. We also argue for the need to place phenotype-genotype association studies in an ecological context if one is to predict the evolutionary trajectories of plant species.

Maladaptation in wild populations of the generalist plant pathogen Pseudomonas syringae

Multihost pathogens occur widely on both natural and agriculturally managed hosts. Despite the importance of such generalists, evolutionary studies of host-pathogen interactions have largely focused on tightly coupled interactions between species pairs. We characterized resistance in a collection of Arabidopsis thaliana hosts, including 24 accessions collected from the Midwest USA and 24 from around the world, and patterns of virulence in a collection of Pseudomonas syringae strains, including 24 strains collected from wild Midwest populations of A. thaliana (residents) and 18 from an array of cultivated species (nonresidents). All of the nonresident strains and half of the resident strains elicited a resistance response on one or more A. thaliana accessions. The resident strains that failed to elicit any resistance response possessed an alternative type III secretion system (T3SS) that is unable to deliver effectors into plant host cells; as a result, these seemingly nonpathogenic strains are incapable of engaging in gene for gene interactions with A. thaliana. The remaining resident strains triggered greater resistance compared to nonresident strains, consistent with maladaptation of the resident bacterial population. We weigh the plausibility of two explanations: general maladaptation of pathogen strains and a more novel hypothesis whereby community level epidemiological dynamics result in adaptive dynamics favoring ephemeral hosts like A. thaliana.