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ADAAPT project overview with the organization in five WPs (WorkPackage). Biorender (www.biorender.com) agreement UH26T0RHN9

Résumé

Agroecological transitions of the current agrifood systems unfold against a backdrop of mounting pressure from climate change (encompassing heatwaves, droughts, emergence of new pathogens, …). To improve the sustainability of our agricultural systems in the context of climate change, it is essential to understand how individuals can adapt to environmental changes. In recent decades, genetic selection has significantly boosted the production capabilities of agricultural systems. However, genetics only account for a portion of phenotypic variation, and prevailing models assume that the ranking of individuals remains unaffected by environmental conditions. Across various species, it has been demonstrated that environmental disruptions - ranging from nutrition and stress to diseases and climatic fluctuations - can influence organisms’ epigenome and phenotypic traits. This impact can be particularly significant in some animal species where production careers are extended. Another example is plants’ stress memory-coordinated changes (crop priming) that prepare plants to be more responsive to recurrent stress within or across generations. Likewise, in animals, development is a period of high sensitivity to environmental factors, and the long-term phenotype can be programmed by the conditions encountered during early life. In addition to genetics and epigenetics, it is also crucial to study the role of the microbiota in explaining phenotypic variability. We thus have to consider the holobiont, i.e. the host organism (animal or plant) and various microorganisms (e.g. bacteria, viruses, protozoa and fungi) that live within and on the host organism. Faced with these challenges, which apply to both cultivated plant species and farm animals, new phenotyping tools must be developed to monitor the suitability of the individual (plant or animal) and its environment (exposome). Epigenetic modifications, such as DNA methylation, are molecular marks impacting organisms' phenotypic diversity from the preconception stage throughout their lives, intertwined with their exposome. The project's scientific challenge is to use machine learning-type digital technologies to exploit epigenetic data to optimize the use of animal and plant genetic resources, including their microbiota (holobiont), in agroecology. It will also enable us to model the phenotypic trajectories of livestock or crop plants in agroecological itineraries characterized in particular by a reduction in inputs such as water, in a global context of global warming. The ADAAPT project proposes to tackle these challenges by merging skills in farm animals, crops, their microbiota, physiology, genetics, epigenetics, epigenomics and digital technologies for agriculture, from 13 different INRAE laboratories, two teams from Institut Agro, one team from Orléans University and one team from INRIA. Such a consortium allows to gather biologists with strong expertise in various fields (geneticists, physiologists, microbiologists) and numericians (statisticians and bioinformaticians). Specifically, its objectives include (i) characterizing the epigenetic profiles of genetic resources conserved in France across diverse exposomes linked to agroecological transition; (ii) demonstrating the practical value of epigenetic biomarkers (epimarkers) for agricultural modelling through numerical methods; (iii) investigating epigenetic variability and its implications for adaptive capacities at the holobiont level, both in natural environments and in response to significant environmental shifts, such as thermal stress and (iv) investigating whether an epigenetic clock can accurately predict phenotypes and be a good biomarker of past expositions. The methylation data generated during the project will contribute to developing a high-throughput epigenotyping tool that could be used in the mid-term by breeders to integrate genetic and epigenetic information, thereby enhancing the accuracy of phenotype predictions.

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Dates et versions

hal-04572622 , version 1 (13-05-2024)

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  • HAL Id : hal-04572622 , version 1

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Laurence Drouilhet, Stéphane Maury. ADAAPT project overview with the organization in five WPs (WorkPackage). Biorender (www.biorender.com) agreement UH26T0RHN9. France. 2024. ⟨hal-04572622⟩

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