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From cultivar mixtures to allelic mixtures: opposite effects of allelic richness between genotypes and genotype richness in wheat.

ABSTRACT: Agroecosystem diversification through increased crop genetic diversity could provide multiple services such as improved disease control or increased productivity. However, we still poorly understand how genetic diversity affects agronomic performance. We grew 179 inbred lines of durum wheat in pure stands and in 202 binary mixtures in field conditions. We then tested the effect of allelic richness between genotypes and genotype richness on grain yield and Septoria tritici blotch disease. Allelic richness was tested at 19K single nucleotide polymorphisms distributed along the durum wheat genome. Both genotype richness and allelic richness could be equal to 1 or 2. Mixtures were overall more productive and less diseased than their pure stand components. Yet, we identified one locus at which allelic richness between genotypes was associated with increased disease severity and decreased grain yield. The effect of allelic richness at this locus was stronger than the effect of genotype richness on grain yield (-7.6% vs +5.7%). Our results suggest that positive effects of crop diversity can be reversed by unfavourable allelic associations. This highlights the need to integrate genomic data into crop diversification strategies. More generally, investigating plant-plant interactions at the genomic level is promising to better understand biodiversity-ecosystem functioning relationships.

SUBMITTER: Montazeaud G

PROVIDER: S-EPMC9306887 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:Increasing the cultivated diversity has been identified as a major leverage for the agroecological transition as it can help improve the resilience of low input cropping systems. For wheat, which is the most cultivated crop worldwide in terms of harvested area, the use of cultivar mixtures is spreading in several countries, but studies have seldom focused on establishing mixing rules based on plant architecture. Yet, the aerial architecture of plants and the overall canopy structure are critical for field performance as they greatly influence light interception, plant interactions and yield. The very high number of trait combinations in wheat mixtures makes it difficult to conduct experimentations on this issue, which is why a modeling approach appears to be an appropriate solution. In this study, we used WALTer, a functional structural plant model (FSPM), to simulate wheat cultivar mixtures and try to better understand how differences between cultivars in key traits of the aerial architecture influence mixture performance. We simulated balanced binary mixtures of cultivars differing for different critical plant traits: final height, leaf dimensions, leaf insertion angle and tillering capability. Our study highlights the impact of the leaf dimensions and the tillering capability on the performance of the simulated mixtures, which suggests that traits impacting the plants' leaf area index (LAI) have more influence on the performance of the stand than traits impacting the arrangement of the leaves. Our results show that the performance of mixtures is very variable depending on the values of the explored architectural traits. In particular, the best performances were achieved by mixing cultivars with different leaf dimensions and different tillering capability, which is in agreement with numerous studies linking the diversity of functional traits in plant communities to their productivity. However, some of the worst performances were also achieved by mixing varieties differing in their aerial architecture, which suggests that diversity is not a sufficient criterion to design efficient mixtures. Overall, these results highlight the importance of simulation-based explorations for establishing assembly rules to design efficient mixtures.

Project description:Cultivar mixtures can be used to improve the sustainability of disease management within farming systems by growing cultivars that differ in their disease resistance level in the same field. The impact of canopy aerial architecture on rain-splash dispersal could amplify disease reduction within mixtures. We designed a controlled conditions experiment to study single splash-dispersal events and their consequences for disease. We quantified this impact through the spore interception capacities of the component cultivars of a mixture. Two wheat cultivars, differing in their aerial architecture (mainly leaf area density) and resistance to Septoria tritici blotch, were used to constitute pure stands and mixtures with 75% of resistant plants that accounted for 80% of the canopy leaf area. Canopies composed of 3 rows of plants were exposed to standardized spore fluxes produced by splashing calibrated rain drops on a linear source of inoculum. Disease propagation was measured through spore fluxes and several disease indicators. Leaf susceptibility was higher for upper than for lower leaves. Dense canopies intercepted more spores and mainly limited horizontal spore transfer to the first two rows. The presence of the resistant and dense cultivar made the mixed canopy denser than the susceptible pure stand. No disease symptoms were observed on susceptible plants of the second and third rows in the cultivar mixture, suggesting that the number of spores intercepted by these plants was too low to cause disease symptoms. Both lesion area and disease conditional severity were significantly reduced on susceptible plants within mixtures on the first row beside the inoculum source. Those reductions on one single-splash dispersal event, should be amplified after several cycle over the full epidemic season. Control of splash-dispersed diseases within mixtures could therefore be improved by a careful choice of cultivars taking into consideration both resistance and architecture.

Project description:Background and aimsPredicting light partitioning in crop mixtures is a critical step in improving the productivity of such complex systems, and light interception has been shown to be closely linked to plant architecture. The aim of the present work was to analyse the relationships between plant architecture and light partitioning within wheat-pea (Triticum aestivum-Pisum sativum) mixtures. An existing model for wheat was utilized and a new model for pea morphogenesis was developed. Both models were then used to assess the effects of architectural variations in light partitioning.MethodsFirst, a deterministic model (L-Pea) was developed in order to obtain dynamic reconstructions of pea architecture. The L-Pea model is based on L-systems formalism and consists of modules for 'vegetative development' and 'organ extension'. A tripartite simulator was then built up from pea and wheat models interfaced with a radiative transfer model. Architectural parameters from both plant models, selected on the basis of their contribution to leaf area index (LAI), height and leaf geometry, were then modified in order to generate contrasting architectures of wheat and pea.Key resultsBy scaling down the analysis to the organ level, it could be shown that the number of branches/tillers and length of internodes significantly determined the partitioning of light within mixtures. Temporal relationships between light partitioning and the LAI and height of the different species showed that light capture was mainly related to the architectural traits involved in plant LAI during the early stages of development, and in plant height during the onset of interspecific competition.ConclusionsIn silico experiments enabled the study of the intrinsic effects of architectural parameters on the partitioning of light in crop mixtures of wheat and pea. The findings show that plant architecture is an important criterion for the identification/breeding of plant ideotypes, particularly with respect to light partitioning.

Project description:BackgroundSoybean (Glycine max) and other legumes are key crops grown around the world, providing protein and nutrients to a growing population, in a way that is more sustainable than most other cropping systems. Diazotrophs inhabiting root nodules provide soybean with nitrogen required for growth. Despite the knowledge of culturable Bradyrhizobium spp. and how they can differ across cultivars, less is known about the overall bacterial community (bacteriome) diversity within nodules, in situ. This variability could have large functional ramifications for the long-standing scientific dogma related to the plant-bacteriome interaction. Water availability also impacts soybean, in part, as a result of water-deficit sensitive nodule diazotrophs. There is a dearth of information on the effects of cultivar and water status on in situ rhizobia and non-rhizobia populations of nodule microbiomes. Therefore, soybean nodule microbiomes, using 16S rRNA and nifH genes, were sampled from nine cultivars treated with different field water regimes. It was hypothesized that the nodule bacteriome, composition, and function among rhizobia and non-rhizobia would differ in response to cultivar and soil water status.Results16S rRNA and nifH showed dominance by Bradyrhizobiaceae, but a large diversity was observed across phylogenetic groups with < 1% and up to 45% relative abundance in cultivars. Other groups primarily included Pseudomonadaceae and Enterobacteriaceae. Thus, nodule bacteriomes were not only dominated by rhizobia, but also described by high variability and partly dependent on cultivar and water status. Consequently, the function of the nodule bacteriomes differed, especially due to cultivar. Amino acid profiling within nodules, for example, described functional changes due to both cultivar and water status.ConclusionsOverall, these results reveal previously undescribed richness and functional changes in Bradyrhizobiaceae and non-rhizobia within the soybean nodule microbiome. Though the exact role of these atypical bacteria and relative variations in Bradyrhizobium spp. is not clear, there is potential for exploitation of these novel findings of microbiome diversity and function. This diversity needs consideration as part of bacterial-inclusive breeding of soybean to improve traits, such as yield and seed quality, and environmental resilience.

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From cultivar mixtures to allelic mixtures: opposite effects of allelic richness between genotypes and genotype richness in wheat.

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