DÉveloppement de MÉthodes et ouTils pour décoder l’ÉpiTranscriptome

Context and key challenges

Faced with the current intensification of abiotic stresses associated with climate change, it is essential to improve our understanding of the molecular mechanisms that enable plants to detect these stresses and adapt quickly to their environments. While the role of epigenetics in these responses is well-documented, that of the epitranscriptome – the set of reversible chemical changes affecting RNA – continues to be under-investigated, even for species of agronomic interest.

The DEMETER project has elected to explore this new level of regulatory mechanisms in the sunflower, a crop that is naturally tolerant of drought and adapts well to environments with low agricultural inputs.

For its investigation, the project intends to make use of direct RNA sequencing using nanopore technology. This innovative approach enables the detection of changes in RNA without having to resort to amplification or reverse transcription. Despite these advantages, the analysis of the raw signals generated by this technology, which are both complex and noisy, poses fresh scientific challenges that themselves call for the development of innovative techniques and a strongly interdisciplinary approach. Positioned at the interface between molecular biology, bioinformatics, and data science, DEMETER has been designed to address these challenges, seeking to increase our understanding of the mechanisms in plants that help them to adapt to environmental stresses, and to improve the tools used to detect changes to RNA.

Goals and methodology

For this approach to succeed, a high degree of interdisciplinarity must be achieved, which is being fostered through jointly supervised internships and through workshops and actions that enable mutual knowledge sharing between partners. The goal is to develop a shared skills base that makes it possible to link electrical signals derived from direct RNA sequencing to specific epitranscriptomic signatures and to interpret their functional consequences in biological contexts, such as the response to thermal stress.

To meet the challenge, DEMETER will develop new dedicated AI approaches based on nanopore sequencing data to the detection of changes in RNA.

After carrying out a comparative assessment of existing tools using synthetic and real data from sunflower and Arabidopsis, new Deep Learning models will be devised to improve the exploitation of raw electrical signals and to take into account the uncertainties inherent to biological data. The techniques developed will then be applied to the study of the epitranscriptomes of contrasting sunflower lines under stress in order to identify the changes in RNA that contribute to adaptation mechanisms.

The DEMETER project will thus add to knowledge of the role of RNA changes in the adaptation of plants to environmental stresses, while developing reproducible generic techniques and tools that are transferrable to other species.

Ultimately, these advances will open new pathways for the characterization and selection of agricultural varieties with greater resilience to environmental changes.

Contact - coordination

Participating INRAE units and external partners

INRAE units

Partenaires extérieurs