Biology subjects

Enjalbert, J.

Publications and source records attributed to Enjalbert, J..

5 recordsLinked to original sources

bioRxiv2026

Joint modeling of social genetic effects in mono- and pluri-specific groups: case study in intercrops

The genetics of interspecific groups remains largely unexplored, despite the central role of social (or indirect) genetic effects in shaping phenotypic expression within communities. Intercropping, i.e. the simultaneous cultivation of multiple crop species in the same field, offers a powerful model to harness these interspecific social effects. Such species mixtures provide well-documented agricultural benefits, yet few breeding frameworks have integrated the genetics of social interactions. Here, we address this gap by extending quantitative genetic theory to interspecific groups, with intercropping as a concrete and applied model case. We propose a quantitative genetic model that jointly analyzes intra and interspecific interactions within a unifying framework. Breeding values are decomposed into a direct component, shared in mono and mixed-crops, an interspecific social component corresponding to the effect of one species on another, and an intraspecific component that captures the social effects within a mono-genotypic stand of cloned plants. Statistically, this consists in simultaneously fitting several linear mixed models, one per stand type, all having direct breeding values in common. As no open-source software can fit such a complex mixed model, we provide such an implementation in C++ available in the R package plantmix. Simulations across various genetic (co)variance structures and sparse experimental designs showed accurate estimation of all genetic (co)variances and breeding values. With an incomplete, yet balanced design combining sole crops and intercrops, genetic gains in both systems were achievable simultaneously, enabling breeding strategies that progressively integrate intercropping into existing, sole-crop-only schemes. More broadly, this framework allows dissecting direct and social genetic effects when genotypes are observed in mono- and mixed-species situations, cultivated or not. Article summaryThe genetics of interspecific groups remains largely unexplored, despite the central role of social genetic effects in shaping phenotypic expression within communities. We address this gap by extending quantitative genetic theory to interspecific groups, with intercropping as an example. We propose a quantitative genetic model that jointly analyzes intra- and interspecific interactions within a unifying framework. Simulations showed accurate estimation of genetic (co)variances and breeding values. This framework supports breeding strategies where breeders want to gradually integrate pluri-specific trials in their mono-specific platforms, and allows dissecting direct and social genetic effects when genotypes are observed in mono- and mixed-species situations.

genetics↗

bioRxiv2024

Diversification, loss, and virulence gains of the major effector AvrStb6 during continental spread of the wheat pathogen Zymoseptoria tritici

Interactions between plant pathogens and their hosts are highly dynamic and mainly driven by pathogen effectors and plant receptors. Host-pathogen co-evolution can cause rapid diversification or loss of pathogen genes encoding host-exposed proteins. The molecular mechanisms that underpin such sequence dynamics remains poorly investigated at the scale of entire pathogen species. Here, we focus on AvrStb6, a major effector of the global wheat pathogen Zymoseptoria tritici, evolving in response to the cognate receptor Stb6, a resistance widely deployed in wheat. We comprehensively captured effector gene evolution by analyzing a global thousand-genome panel using reference-free sequence analyses. We found that AvrStb6 has diversified into 59 protein isoforms with a strong association to the pathogen spreading to new continents. Across Europe, we found the strongest differentiation of the effector consistent with high rates of Stb6 deployment. The AvrStb6 locus showed also a remarkable diversification in transposable element content with specific expansion patterns across the globe. We detected the AvrStb6 gene losses and evidence for transposable element-mediated disruptions. We used genome-wide association mapping data to predict virulence emergence and found marked increases in Europe, followed by spread to subsequently colonized continents. Finally, we genotyped French bread wheat cultivars for Stb6 and monitored resistant cultivar deployment concomitant with AvrStb6 evolution. Taken together, our data provides a comprehensive view of how a rapidly diversifying effector locus can undergo large-scale sequence changes concomitant with gains in virulence on resistant cultivars. The analyses highlight also the need for large-scale pathogen sequencing panels to assess the durability of resistance genes and improve the sustainability of deployment strategies. Author summaryInteractions between plants and their specialized pathogens are often mediated by a sophisticated molecular dialogue. Effectors produced by pathogens serve to manipulate the host but may also be used by the host to trigger defence mechanisms upon recognition. Deploying plants carrying a resistance gene against a specific effector could lead to rapid adaptation in the pathogen. Here, we unraveled such dynamics at the scale of the global distribution range of the fungal wheat pathogen Zymoseptoria tritici. The effector is encoded by the gene AvrStb6 located in a polymorphic region of a chromosome near the telomere. We find selfish elements (i.e. transposable elements) repeatedly inserted nearby the gene, which has likely facilitated the rapid sequence evolution. The effector diversified among continents, and we could predict that the sequence changes likely helped escape recognition by the host receptor. Our study provides one of the most comprehensive views how a crop pathogen diversified a major effector in response to host resistance factors. Such studies facilitate devising more durable deployment strategies of host resistance in order to maintain crop yield.

genomics↗

bioRxiv2024

A multidisciplinary on-farm survey of maize-bean intercropping shows that revival of traditionalagricultural systems requires careful consideration of partner varieties and agronomic practices.

O_LICereal-legume intercropping is a promising strategy for sustainable agroecosystems. The traditional intercropping of maize and bean is experiencing a revival in some modern agricultural settings, such as in southwestern France, where maize hybrids are intercropped with the commercialized Tarbais bean. We conducted on-farm surveys and a field assay to address the following questions: How does the cropping system impact yield, nutrient uptake, and rhizosphere bacterial assemblages? Do positive or negative interactions between maize and beans dominate in intercropping? What is the effect of intercropping on plant transcriptomics? C_LIO_LIWe recorded farming practices, conducted yield and nutrient measurements, and characterized soil bacterial assemblages to compare sole-cropped maize and beans with intercropped plants. A controlled field assay was also established to extend this comparison to plant gene expression differences. C_LIO_LIIntercropping was associated with a trend towards increased bacterial diversity. The cropping system significantly influenced agronomic traits, with frequent farm-by-cropping system interactions underscoring the critical role of farming practices. Competition dominated maize-bean intercropping, with 34 negative correlations among the 47 significant ones between maize and bean traits. This competition affected yield and nutrition, but primarily impacted beans, which produced fewer but bigger/heavier seeds. Transcriptomic results concurred with these findings, revealing no differentially expressed genes in maize but 5,070 in beans under competition. C_LIO_LIOverall, our findings suggest that beneficial interactions between the two crops are hindered under current field conditions, underscoring the importance of carefully considering partner varieties and farming practices to revive traditional agricultural systems. C_LI Societal Impact StatementCereal-legume intercropping is a promising strategy for sustainable agroecosystems that leverages the biological complementarities between plant species, reducing the need for chemical inputs while enhancing field biodiversity. Here, we focused on maize-bean intercropping, which is experiencing a revival in modern conventional agricultural settings. We found a trend towards an increased soil bacterial diversity in intercropping. However, competition between the two crops dominated and primarily impacted yield and gene expression in beans. Despite lower yield, bean seeds exhibited greater size. Our study indicates that implementing variety selection of both species and adapting farming practices is essential to fully harness the potential of intercropping.

plant biology↗

bioRxiv2022

Contrasted phenotypic plasticities of life-history traits in interacting plants: case of pure vs mixed stands of wheat

ContextMixing cultivars is an agroecological practice of crop diversification, increasingly used for cereals. The yield of such cereal mixtures is higher on average than the mean yield of their components in pure stands, but with a large variance. The drivers of this variance are plant- plant interactions leading to different plant phenotypes in pure and mixed stands, i.e phenotypic plasticity. ObjectivesThe objectives were (i) to quantify the magnitude of phenotypic plasticity for yield in pure versus mixed stands, (ii) to identify the yield components that contribute the most to yield plasticity, and (iii) to link such plasticities to differences in functional traits, i.e. plant height and flowering earliness. MethodsA new experimental design based on a precision sowing allowed phenotyping each cultivar in mixture, at the level of individual plants, for above-ground traits throughout growth. Eight commercial cultivars of Triticum aestivum L. were grown in pure and mixed stands in field plots repeated for two years (2019-2020, 2020-2021) with contrasted climatic conditions and with nitrogen fertilization, fungicide and weed removal management strategies. Two quaternary mixtures were assembled with cultivars contrasted either for height or earliness. ResultsCompared to the average of cultivars in pure stands, the height mixture strongly underyielded over both years (-29%) while the earliness mixture overyielded the second year (+11%) and underyielded the first year (-8%). The second year, the magnitude of cultivars grain weight plasticity, measured as the difference between pure and mixed stands, was significantly and positively associated with their relative yield differences in pure stands (R2=0.51). When grain weight plasticity, measured as the log ratio of pure over mixed stands, was partitioned as the sum of plasticities in each yield component, its strongest contributor was the plasticity in spike number per plant ([~]56% of the sum), driven by even stronger but opposed underlying plasticities in both tiller emission and regression. For both years, the plasticity in tiller emission was significantly, positively associated with the height differentials between cultivars in mixture (R2=0.43 in 2019-2020 and 0.17 in 2020-2021). ConclusionsPlasticity in the early recognition of potential resource competitors is a major component of cultivar strategies in mixtures, as shown here for tillering dynamics. Our results also highlighted a link between plasticity in tiller emission and height differential in mixture. Both height and tillering dynamics displayed plasticities typical of the shade avoidance syndrome. ImplicationsBoth the new experimental design and decomposition of plasticities developed in this study open avenues to better study plant-plant interactions in agronomically-realistic conditions. This study also contributed a unique, plant-level data set allowing the calibration of process-based plant models to explore the space of all possible mixtures.

plant biology↗

bioRxiv2021

Automatic calibration of a functional-structural wheat model using an adaptive design and a metamodelling approach

O_LIBackground and Aims Functional-structural plant models are increasingly being used by plant scientists to address a wide variety of questions. However, the calibration of these complex models is often challenging, mainly because of their high computational cost. In this paper, we applied an automatic method to the calibration of WALTer: a functional-structural wheat model that simulates the plasticity of tillering in response to competition for light. C_LIO_LIMethods We used a Bayesian calibration method to estimate the values of 5 parameters of the WALTer model by fitting the model outputs to tillering dynamics data. The method presented in this paper is based on the Efficient Global Optimisation algorithm. It involves the use of Gaussian process metamodels to generate fast approximations of the model outputs. To account for the uncertainty associated with the metamodels approximations, an adaptive design was used. The efficacy of the method was first assessed using simulated data. The calibration was then applied to experimental data. C_LIO_LIKey Results The method presented here performed well on both simulated and experimental data. In particular, the use of an adaptive design proved to be a very efficient method to improve the quality of the metamodels predictions, especially by reducing the uncertainty in areas of the parameter space that were of interest for the fitting. Moreover, we showed the necessity to have a diversity of field data in order to be able to calibrate the parameters. C_LIO_LIConclusions The method presented in this paper, based on an adaptive design and Gaussian process metamodels, is an efficient approach for the calibration of WALTer and could be of interest for the calibration of other functional-structural plant models. C_LI

bioinformatics↗