Epigenetics for Plant Improvement: Current Knowledge and Modeling Avenues. (July 2017)

• Record Type: Journal Article
• Authors: Gallusci, Philippe; Dai, Zhanwu; Génard, Michel; Gauffretau, Arnaud; Leblanc-Fournier, Nathalie; Richard-Molard, Céline; Vile, Denis; Brunel-Muguet, Sophie
• Is Part Of: Trends in plant science. Volume 22:Number 7(2017)
• Page Start: 610
• Page End: 623
• Publication Date: 2017-07
• Subjects: epigenetics -- modeling -- plant breeding -- adaptation -- environment -- development; Botany -- Periodicals; Botanique -- Périodiques; Botany; Periodicals; 580.5
• DOI: 10.1016/j.tplants.2017.04.009
• Languages: English
• ISSNs: 1360-1385

Abstract

Abstract : Epigenetic variations are involved in the control of plant developmental processes and participate in shaping phenotypic plasticity to the environment. Intense breeding has eroded genetic diversity, and epigenetic diversity now emerge as a new source of phenotypic variations to improve adaptation to changing environments and ensure the yield and quality of crops. Here, we review how the characterization of the stability and heritability of epigenetic variations is required to drive breeding strategies, which can be assisted by process-based models. We propose future directions to hasten the elucidation of complex epigenetic regulatory networks that should help crop modelers to take epigenetic modifications into account and assist breeding strategies for specific agronomical traits. Trends: Broadening crop phenotypic diversity is a key issue facing the challenge of sustainable food security and crop adaptation to ongoing climate changes. Chromatin marks and epigenetic regulatory mechanisms are essential to the control of plant developmental processes and in shaping plant phenotypic plasticity, including adaptive responses to environmental stresses. Stability and heritability features of epigenetic marks and knowledge of epigenetic regulatory mechanisms are crucial for breeding applications. Modeling epigenetic variations requires understanding epigenetic regulatory mechanisms to further predict their impact on plant performances. Modeling epigenetic variations with a process-based approach could help to assess and quantify their impacts on plant performances and then to guide the decision to either induce or repress them. This modeling feedback is central to model-driven breeding strategies. Crop modelers are urged to take epigenetic variations into account to assist breeding strategies.