Highly effective mlo-based powdery mildew resistance in hexaploid wheat without pleiotropic effects.

Application of the mlo-based resistance in barley against powdery mildew attacks is a major success in crop breeding, since it confers durable disease resistance. Resistance caused by mutations in the Mlo gene seems to be ubiquitous across a range of species. This work addresses the introduction of mlo-based resistance into hexaploid wheat, which is complicated by the occurrence of three homoeologous genes: Mlo-A1, Mlo-B1 and Mlo-D1. EMS-generated mutant plants were screened for mutations in the three homoeologues. We selected and combined 6, 8, and 4 mutations, respectively, to obtain triple homozygous mlo mutant lines. Twenty-four mutant lines showed highly effective resistance towards attack by the powdery mildew pathogen under field conditions. All 18 mutations appeared to contribute to resistance; however, they had different effects on the occurrence of symptoms such as chlorotic and necrotic spots, which are pleiotropic to the mlo-based powdery mildew resistance. We conclude that to obtain highly effective powdery mildew resistance in wheat and to avoid detrimental pleiotropic effects, all three Mlo homoeologues should be mutated; however, at least one of the mutations should be of the weaker type in order to alleviate strong pleiotropic effects from the other mutations.

Genomic prediction of yield and root development in wheat under changing water availability.

BACKGROUND: Deeper roots help plants take up available resources in deep soil ensuring better growth and higher yields under conditions of drought. A large-scale semi-field root phenotyping facility was developed to allow a water availability gradient and detect potential interaction of genotype by water availability gradient. Genotyped winter wheat lines were grown as rows in four beds of this facility, where indirect genetic effects from neighbors could be important to trait variation. The objective was to explore the possibility of genomic prediction for grain-related traits and deep root traits collected via images taken in a minirhizotron tube under each row of winter wheat measured. RESULTS: The analysis comprised four grain-related traits: grain yield, thousand-kernel weight, protein concentration, and total nitrogen content measured on each half row that were harvested separately. Two root traits, total root length between 1.2 and 2 m depth and root length in four intervals on each tube were also analyzed. Two sets of models with or without the effects of neighbors from both sides of each row were applied. No interaction between genotypes and changing water availability were detected for any trait. Estimated genomic heritabilities ranged from 0.263 to 0.680 for grain-related traits and from 0.030 to 0.055 for root traits. The coefficients of genetic variation were similar for grain-related and root traits. The prediction accuracy of breeding values ranged from 0.440 to 0.598 for grain-related traits and from 0.264 to 0.334 for root traits. Including neighbor effects in the model generally increased the estimated genomic heritabilities and accuracy of predicted breeding values for grain yield and nitrogen content. CONCLUSIONS: Similar relative amounts of additive genetic variance were found for both yield traits and root traits but no interaction between genotypes and water availability were detected. It is possible to obtain accurate genomic prediction of breeding values for grain-related traits and reasonably accurate predicted breeding values for deep root traits using records from the semi-field facility. Including neighbor effects increased the estimated additive genetic variance of grain-related traits and accuracy of predicting breeding values. High prediction accuracy can be obtained although heritability is low.

Differential regulation of the Epr3 receptor coordinates membrane-restricted rhizobial colonization of root nodule primordia.

In Lotus japonicus, a LysM receptor kinase, EPR3, distinguishes compatible and incompatible rhizobial exopolysaccharides at the epidermis. However, the role of this recognition system in bacterial colonization of the root interior is unknown. Here we show that EPR3 advances the intracellular infection mechanism that mediates infection thread invasion of the root cortex and nodule primordia. At the cellular level, Epr3 expression delineates progression of infection threads into nodule primordia and cortical infection thread formation is impaired in epr3 mutants. Genetic dissection of this developmental coordination showed that Epr3 is integrated into the symbiosis signal transduction pathways. Further analysis showed differential expression of Epr3 in the epidermis and cortical primordia and identified key transcription factors controlling this tissue specificity. These results suggest that exopolysaccharide recognition is reiterated during the progressing infection and that EPR3 perception of compatible exopolysaccharide promotes an intracellular cortical infection mechanism maintaining bacteria enclosed in plant membranes.

The effect of heterogeneity on invasion in spatial epidemics: from theory to experimental evidence in a model system.

Heterogeneity in host populations is an important factor affecting the ability of a pathogen to invade, yet the quantitative investigation of its effects on epidemic spread is still an open problem. In this paper, we test recent theoretical results, which extend the established "percolation paradigm" to the spread of a pathogen in discrete heterogeneous host populations. In particular, we test the hypothesis that the probability of epidemic invasion decreases when host heterogeneity is increased. We use replicated experimental microcosms, in which the ubiquitous pathogenic fungus Rhizoctonia solani grows through a population of discrete nutrient sites on a lattice, with nutrient sites representing hosts. The degree of host heterogeneity within different populations is adjusted by changing the proportion and the nutrient concentration of nutrient sites. The experimental data are analysed via Bayesian inference methods, estimating pathogen transmission parameters for each individual population. We find a significant, negative correlation between heterogeneity and the probability of pathogen invasion, thereby validating the theory. The value of the correlation is also in remarkably good agreement with the theoretical predictions. We briefly discuss how our results can be exploited in the design and implementation of disease control strategies.