Precision breeding for climate-resilient rice: Integrating CRISPR, prime editing, artificial intelligence, and microbiome engineering

Rice ( Oryza sativa L.) serves as a primary food source for over half of the world’s population. However, its production is increasingly threatened by climate change-induced biotic and abiotic stresses. Yield losses of approximately 20–40% caused by pests and pathogens, along with rising temperature extremes that reduce productivity by 6–10% for every 1°C above optimal flowering conditions, highlight the urgent need for innovations that go beyond traditional breeding methods. In recent years, the integration of genome-editing technologies, artificial intelligence (AI), high-throughput phenotyping (HTP), and advances in microbiome engineering has significantly reshaped rice improvement strategies. This review provides a comprehensive synthesis of these integrated approaches, with a particular focus on the transition from first-generation CRISPR/Cas9 systems to advanced prime editing (PE) technologies. It examines the molecular basis of stress tolerance, reviews successful CRISPR/Cas9 applications for enhancing resistance to biotic and abiotic stresses as well as yield traits, and discusses the functional advantages of PE platforms (ranging from PE1 to PEmax and newer variants), which allow precise nucleotide substitutions, insertions, and deletions without introducing double-strand breaks or requiring donor DNA templates. The role of AI and HTP in accelerating breeding pipelines is also discussed, particularly in improving guide RNA design, enhancing genomic prediction accuracy, and enabling early disease detection, which together contribute to improved efficiency in modern breeding workflows. Rather than fixed breeding timelines, these approaches are presented as components of integrated breeding pipelines that can substantially accelerate selection and development processes under optimized conditions. The review also highlights emerging technologies such as microbiome engineering, nanotechnology-based transgene-free delivery systems, synthetic biology, and quantum computing as promising tools for achieving long-term resilience. Despite these advances, several limitations persist, including low transformation efficiencies in elite cultivars, unintended off-target modifications, inconsistencies in global regulatory frameworks, and discrepancies between controlled-environment success and field-level performance. Finally, a strategic framework for “Breeding 4.0” is proposed, integrating multiplex prime editing, genomic selection, speed breeding, and AI-driven predictive tools to develop high-yielding, climate-resilient, and nutritionally improved rice varieties capable of supporting global food security through 2050 and beyond.