AI Models in Studying Plant Epigenetics

Abstract

This chapter explores the profound and rapidly evolving intersection of plant epigenetics and artificial intelligence (AI). We embark on a chronological journey, tracing the evolution from classical bioinformatics to the transformative impact of deep learning (DL) and large language models (LLMs) in deciphering the intricate epigenetic language of plants. We will highlight key AI models, present landmark case studies across diverse plant species, and discuss cutting-edge applications, including the prediction of DNA methylation, histone modifications, and the integration of multi-omics data. Special attention is given to the role of AI in understanding plants’ epigenetic responses to stress and its potential for precision agriculture and enhancing climate resilience. We also critically examine current limitations, such as data scarcity and model interpretability, before casting a forward gaze toward exciting prospects like AI-augmented epigenome editing and the democratization of AI tools in plant science.