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LabEx BASC

Maïs: cycles de vie, sélection, adaptations, insectes nuisibles

Itemaize
En utilisant le maïs comme culture modèle, le projet visait à (i) mieux comprendre l'impact de l'environnement sur les cycles de vie des plantes et leur interaction avec les insectes nuisibles ; (ii) prévoir le potentiel d'adaptations (épi)génétiques et (iii) définir des critères de sélection pour les changements de cycle de vie des cultures.

Intitulé et acronyme du projet: Approches intégratives des variations de la floraison chez le maïs (Itemaize)

Porteurs du projet : Christine DILLMANN (GQE-Le Moulon: Génétique quantitative et évolution), Bruno ANDRIEU (ECOSYS: Ecologie fonctionnelle et écotoxicologie des agroécosystèmes), Arnaud LE ROUZIC (EGCE: Evolution, génomes, comportement, écologie)

Autres unités partenaires dans BASC : ESE (Ecologie, systématique, évolution)

Partenaires académiques hors BASC : IJPB (Institut Jean-Pierre Bourgin: biologie des plantes), MaIAGE (Mathématiques et informatique appliquées du génome à l'environnement)

Using maize as a model crop, and building upon complementarities between project partners, Itemaize will help to (i) better understand how environment impacts plant life-cycles and their interaction with insect pests; (ii) predict the potential for (epi)genetic adaptations and (iii) define selection criteria for crop life-cycle shifts. The project will also sustain methodological developments on phenotyping, data analyses and modelling.

Bringing partners from different disciplines, the project relies on a unique plant material resulting from 20 years of divergent selection for flowering time performed in the Plateau de Saclay. Selecting each year for early and late flowering from a narrow genetic diversity (two inbred lines), we created an evolved plant material likely to be enriched in (epi)genetic differences related to flowering time, while preserving the original characteristics of the initial inbred lines. Comparisons among generations allow investigating the dynamics of the response to selection in a changing environment. Comparisons between Early and Late families allow investigating the genotype-phenotype map.

Early and Late progenitors from generation G18 will be used to perform in-depth characterization of plants growth and development (Task 1). Integration of different scales (from the genetic level to the whole plant growth dynamics) will make use of both partner's expertise and strong investment in statistical modelling.

Data will serve to calibrate a plant growth model that couples development, phenology and metabolism (Task 2) to better understand how the environment can modulate maize life-cycle, as well as to decipher between genetic and plastic bases for life-cycle shifts. An evaluation trial of all plant material of the selection experiment will help to monitor and modelize genetic and phenotypic changes that occurred during the response to selection, and to better understand genotype-phenotype relationships. Again, the project will benefit from both practical (phenotyping) and theoretical (quantitative and population genetics) advances from the partners, as well as from a strong input from mathematics.

Plant-insects: Life-cycle matters_Itemaize

Finally we will use climatic data from the last 20 years, along with the observed response to selection, to describe links between environment and the dynamics of adaptation. Using Lepidoptera stem borers as a model system, we will also analyse how plant phenology shifts interfere with pathogen life-cycles.

Schéma Itemaize

===> La porteuse vous explique le projet et ses RESULTATS en VIDEO (journées scientifiques du LabEx, janvier 2021)

Publications

> Vidal, T., Aissaoui, H., Rehali, S., and Andrieu, B. (2021). Two maize cultivars of contrasting leaf size show different leaf elongation rates with identical patterns of extension dynamics and coordination. Aob Plants https://doi.org/10.1093/aobpla/plaa072Résumé: "Simulating leaf development from initiation to maturity opens new possibilities to model plant–environment interactions and the plasticity of plant architecture. This study analyses the dynamics of leaf production and extension along a maize (Zea mays) shoot to assess important modelling choices. Maize plants from two cultivars originating from the same inbred line, yet differing in the length of mature leaves were used in this study. We characterized the dynamics of the blade and sheath lengths of all phytomers by dissecting plants every 2–3 days. We analysed how differences in leaf size were built up and we examined the coordination between the emergence of organs and phases of their extension. Leaf extension rates were higher in the cultivar with longer leaves than in the cultivar with shorter leaves; no differences were found in other aspects. We found that (i) first post-embryonic leaves were initiated at a markedly higher rate than upper leaves; (ii) below ear position, sheaths were initiated at a time intermediate between tip emergence and appearance, while above the ear position, sheaths were initiated at a high rate, such that the time interval between the blade and sheath initiations decreased for these leaves; and (iii) ear position also marked a change in the correlation in size between successive phytomers with little correlation of size between upper and lower leaves. Our results identified leaf extension rate as the reason for the difference in size between the two cultivars. The two cultivars shared the same pattern for the timing of initiation events, which was more complex than previously thought. The differences described here may explain some inaccuracies reported in functional–structural plant models. We speculate that genotypic variation in behaviour for leaf and sheath initiation exists, which has been little documented in former studies."

Two maize cultivars of contrasting leaf size show different leaf elongation rates with identical patterns of extension dynamics and coordination

(Une figure de l'article susmentionné)

> Desbiez-Piat A., Le Rouzic A., Tenaillon M.I., Dillmann C. (2020) Interplay between high-drift and high-selection limits the genetic load in small selfing maize populations. bioRxiv: https://doi.org/10.1101/2020.12.22.423930  

> I. Sanané, J. Legrand, C. Dillmann, F. Marion-Poll (2020) A semi-automated design for high-throughput Lepidoptera larvae feeding bioassays. https://doi.org/10.1101/2020.08.02.232256

> Tenaillon M.I., Sedikki K., Mollion M., Le Guilloux M., Marchadier, E., Ressayre A., Dillmann C. (2019). Transcriptomic response to divergent selection for flowering time in maize reveals convergence and key players of the underlying gene regulatory network. BioRxiv, 461947, ver. 5. Peer-reviewed and recommended by PCI Evolutionary Biology (Tanja Pyhäjärvi (2019) Early and late flowering gene expression patterns in maize. Peer Community in Evolutionary Biology, 100071. 10.24072/pci.evolbiol.100071) https://doi.org/10.1101/461947Résumé: "Artificial selection experiments are designed to investigate phenotypic evolution of complex traits and its genetic basis. Herewe focused on flowering time, a trait of key importance for plant adaptation and life-cycle shifts. We undertook divergent selection experiments from two maize inbred lines. After 13 generations of selection, we obtained a time-lag of roughly two weeks between Early- and Late-populations. We used this material to characterize the genome-wide transcriptomic response to selection in the shoot apical meristem before, during and after floral transition in field conditions during two consecutive years. We validated the reliability of performing RNA-sequencing in uncontrolled conditions. We found that roughly half of maize genes were expressed in the shoot apical meristem, 59.3% of which were differentially expressed. We detected a majority of genes with differential expression between inbreds and across meristem status, and retrieved a subset of 2,451 genes involved in the response to selection. Among these, we found a significant enrichment for genes with known function in maize flowering time. Furthermore, they were more often shared between inbreds than expected by chance, suggesting convergence of gene expression. We discuss new insights into the expression pattern of key players of the underlying gene regulatory network including the Zea mays genes CENTRORADIALIS (ZCN8), RELATED TO AP2.7(RAP2.7), MADS4 (ZMM4), KNOTTED1 (KN1), GIBBERELLIN2-OXIDASE1 (GA2ox1), as well as alternative scenarios for genetic convergence."

Publi Itemaize - Contrasting phenotypes emerging from stable rules: A model based on self-regulated control loops captures the dynamics of shoot ex...

> Vidal T, Andrieu B., 2019. Contrasting phenotypes emerging from stable rules: A model based on self-regulated control loops captures the dynamics of shoot extension in contrasting maize phenotypes. Ann Bot. 2019 Oct 19. pii: mcz168. https://doi.org/10.1093/aob/mcz168Résumé: "Background and Aims: The dynamics of plant architecture is a central aspect of plant and crop models. Most models assume that whole shoot development is orchestrated by the leaf appearance rate, which follows a thermal time schedule. However, leaf appearance actually results from leaf extension and taking it as an input hampers our ability to understand shoot construction. The objective of the present study was to assess a modelling framework for grasses, in which the emergence of leaves and other organs is explicitly calculated as a result of their extension. Methods: The approach builds on a previous model, which uses a set of rules co-ordinating the timing of development within and between phytomers. We first assessed rule validity for four experimental datasets, including different cultivars, planting densities and environments, and accordingly revised the equations driving the extension of the upper leaves and of internodes. We then fitted model parameters for each dataset and evaluated the ability to simulate the measured phenotypes across time. Finally, we carried out a sensitivity analysis to identify the parameters that had the greatest impact and to investigate model behaviour. Key Results: The modified version of the model simulated correctly the contrasting maize phenotypes. Co-ordination rules accounted for the observations in all studied cultivars. Factors with major impact on model output included extension rates, the time of tassel initiation and initial conditions. A large diversity of phenotypes could be simulated. Conclusions: This work provides direct experimental evidence for co-ordination rules and illustrates the capacity of the model to represent contrasting phenotypes. These rules play an important role in patterning shoot architecture and some of them need to be assessed further, considering contrasting growth conditions. To make the model more predictive, several parameters could be considered in the future as internal variables driven by plant status."        Illustration: "Visual representation of phytomer extension"

> Vidal, T., Dillmann, C., Andrieu, B., 2018. A coordination model captures the dynamics of organ extension in contrasted maize phenotypes, in: 2018 6th International Symposium on Plant Growth Modeling, Simulation, Visualization and Applications (PMA). IEEE, pp. 126–133. https://doi.org/10.1109/PMA.2018.8611569