Next-generation translational genomics for developing future crops

Abstract

Advancements in translational genomics have revolutionized crop breeding, driving us from traditional breeding methods towards next-generation strategies that integrate genomic, transcriptomic, and phenotypic data to expedite crop improvement. There has been a shift from single genomes to pan-genomes, which better capture intraspecific diversity, and from bulk transcriptome analyses to single-cell transcriptomics, enabling cell-specific insights into gene regulation and functional genomics. Both high throughput genopyting and phenotyping approaches are now possible due to rapid technological advancement in the field of translational genomics. Large-scale phenotyping data from multi-environment field trials is now possible due to AI-enabled digital and drone-based scanning. In the era of artificial intelligence and machine learning we have developed flexible models to handle complex genetic architecture of trait regulation using various tools and approaches. These genetic and genomic resources are the foundation for generating novel, adaptable, and high-yielding varieties, accelerating trait discovery and mapping. This review explores the comprehensive landscape of modern translational genomics, highlighting key shifts and innovations that enhance our capacity to address agricultural challenges. Integrative pipelines that unify these next-generation approaches could facilitate faster, more precise, and sustainable crop improvement, ultimately meeting the growing demands for future-ready crops.