Gaining insights into epigenetic memories through artificial intelligence and omics science in plants.

Journal: Journal of integrative plant biology
Published Date:

Abstract

Plants exhibit remarkable abilities to learn, communicate, memorize, and develop stimulus-dependent decision-making circuits. Unlike animals, plant memory is uniquely rooted in cellular, molecular, and biochemical networks, lacking specialized organs for these functions. Consequently, plants can effectively learn and respond to diverse challenges, becoming used to recurring signals. Artificial intelligence (AI) and machine learning (ML) represent the new frontiers of biological sciences, offering the potential to predict crop behavior under environmental stresses associated with climate change. Epigenetic mechanisms, serving as the foundational blueprints of plant memory, are crucial in regulating plant adaptation to environmental stimuli. They achieve this adaptation by modulating chromatin structure and accessibility, which contribute to gene expression regulation and allow plants to adapt dynamically to changing environmental conditions. In this review, we describe novel methods and approaches in AI and ML to elucidate how plant memory occurs in response to environmental stimuli and priming mechanisms. Furthermore, we explore innovative strategies exploiting transgenerational memory for plant breeding to develop crops resilient to multiple stresses. In this context, AI and ML can aid in integrating and analyzing epigenetic data of plant stress responses to optimize the training of the parental plants.

Authors

  • Judit Dobránszki
    Centre for Agricultural Genomics and Biotechnology, University of Debrecen, PO Box 12., Nyíregyháza 4400, Hungary.
  • Valya Vassileva
    Department of Molecular Biology and Genetics, Institute of Plant Physiology and Genetics, Bulgarian Academy of Sciences, Sofia 1113, Bulgaria.
  • Dolores R Agius
    Department of Biology, Ġ.F. Abela Junior College, Ġuzè Debono Square, Msida MSD 1252, Malta.
  • Panagiotis Nikolaou Moschou
    Department of Molecular Sciences, Uppsala BioCenter, Swedish University of Agricultural Sciences and Linnean Center for Plant Biology, Uppsala, Sweden.
  • Philippe Gallusci
    UMR Ecophysiologie et Génomique Fonctionnelle de la Vigne (EGFV), University of Bordeaux, Bordeaux Sciences Agro, Institut National de la Recherche pour l'Agriculture, l'Alimentation et l'Environnement (INRAE), Institut des Sciences de la Vigne et du Vin (ISVV), Villenave d'Ornon, 33882, France.
  • Margot M J Berger
    UMR Ecophysiologie et Génomique Fonctionnelle de la Vigne (EGFV), University of Bordeaux, Bordeaux Sciences Agro, Institut National de la Recherche pour l'Agriculture, l'Alimentation et l'Environnement (INRAE), Institut des Sciences de la Vigne et du Vin (ISVV), Villenave d'Ornon, 33882, France.
  • Dóra Farkas
    Department of Pharmaceutics, Semmelweis University, 9 Hőgyes Endre Street, Budapest H-1092, Hungary.
  • Marcos Fernando Basso
    Department of Biology, University of Florence, Firenze, 50019, Italy.
  • Federico Martinelli
    Department of Biology, University of Florence, Firenze, 50019, Italy.

Keywords

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