Deciphering plant stress resilience in different millet crops: from multi-omics discoveries to predictive breeding for climate-resilient crop enhancement

Abstract

Global climatic and abiotic stresses severely affect agricultural production, while millets are stress-tolerant and nutritious cereal crops adapted to diverse environments. Although single-omics technologies, including genomics, transcriptomics, proteomics, metabolomics, epigenomics, ionomics, and phenomics, have substantially advanced our understanding of individual components of plant stress responses, each approach captures only one molecular layer and therefore cannot fully resolve the interconnected regulatory networks that govern complex stress adaption. The challenge now is to bring together these widely varied molecular data to make them biologically meaningful and to be able to predict genotype-phenotype relationships under varying field conditions. This review critically covers recent developments in multi-omics technologies that have been used to uncover abiotic stress tolerance mechanisms, and how they can be complementary to identify stress-responsive genes, regulatory pathways, stress markers, and adaptive metabolic processes. Additionally, the review covers recent developments in AI and ML integration with multi-omics data, predictive modeling, and precision breeding to enhance the identification of better genotypes and breeding decisions. Finally, future prospects for the integration of multi-omics, AI analytics, digital phenotyping and breeding pipelines for next-generation cultivars of millets for future climate change are outlined, which will enable the improvement of current cultivars with higher resilience, yield and nutritional value, while simultaneously supporting sustainable agriculture.