Programmable Domestication: CRISPR, Pan‐Genomics and System Level Engineering for Next‐Generation Crops
Abstract
ABSTRACT Global agriculture is increasingly challenged by climate instability, genetic erosion, emerging pathogens and rising food demands, exposing the limitations of conventional breeding and traditional domestication strategies. Recent advances in CRISPR‐based genome editing, pangenomic, synthetic biology, artificial intelligence (AI)‐assisted breeding and predictive phenomics are transforming de novo domestication from a slow evolutionary process into a programmable framework for rational crop redesign. This review synthesises recent advances in programmable de novo domestication and highlights how crop wild relatives and underutilised germplasm can be harnessed to develop resilient, climate‐adaptive and sustainable crop systems. The integration of multiplex genome editing, pan‐genomic variation discovery, AI‐driven genomic prediction and predictive breeding enables precise engineering of key domestication traits governing plant architecture, yield potential, stress resilience and nutritional quality. Furthermore, we propose a trajectory‐based framework for programmable domestication comprising Adaptive Rescue, Agronomic Refinement and Novel Chassis Engineering, which illustrates distinct evolutionary pathways, engineering complexity and crop redesign objectives. We also examine the major system level challenges that constrain programmable domestication, including cryptic genetic variation, epistasis, gene regulatory network complexity, genotype phenotype predictability, biodiversity conservation and regulatory considerations. Collectively, programmable domestication represents a transformative shift from conventional crop improvement towards system‐level engineering of next‐generation crops, providing a strategic foundation for enhancing global food security, agricultural sustainability and environmental resilience in the face of accelerating climate change.
