Multi-Omics Insights into Climate-Driven Abiotic Stress Responses and Tolerance Mechanisms in Fruit Crops

Abstract

Climate change is intensifying drought, salinity, heat, chilling, flooding, and heavy-metal stresses across major fruit-producing regions, threatening yield stability and fruit quality in economically vital, perennial crops such as apple, grapevine, citrus, banana, strawberry, and peach. Because these species are long-lived, highly heterozygous, and polyploid, conventional breeding for climate resilience remains slow and often inadequate, necessitating molecular strategies informed by systems-level understanding. This review synthesizes recent advances in multi-omics research spanning genomics, transcriptomics, proteomics, metabolomics, epigenomics, ionomics, and phenomics that have collectively decoded the regulatory architecture underlying abiotic stress perception, signaling, and tolerance in fruit crops. Hormonal networks, particularly abscisic acid (ABA) crosstalk with jasmonate, salicylic acid, ethylene, and brassinosteroids, emerge as central integrators of stress responses, coordinating stomatal regulation, osmolyte accumulation, antioxidant defense, and secondary metabolite biosynthesis. Genomic and pangenomic approaches have identified stress-associated loci and cultivar-specific structural variants, while transcriptomic and proteomic studies reveal transcription factor networks (MdERF38–MdMYB1, MaMYB4–MaHDA2, VvDREB1, CsNAC29) and post-translational regulatory switches governing tolerance mechanisms across drought, cold, salinity, and flooding stress. Metabolomic and ionomic profiling link biochemical reprogramming to fruit quality traits, whereas epigenomic mechanisms including DNA methylation, histone modifications, and small RNA regulation provide a chromatin-level layer mediating stress memory across growing seasons. Integration of these omics layers through systems biology, machine learning, and high-throughput phenomics is enabling functional validation via CRISPR-Cas9 and marker-assisted selection, translating correlative associations into causally validated breeding targets. Despite this progress, challenges including batch effects, tissue heterogeneity, and methodological inconsistencies in data integration continue to constrain translational applications. This highlights convergent regulatory hubs across stress types and species, underscoring multi-omics-guided precision breeding as the most promising pathway toward developing climate-resilient, high-quality fruit crop cultivars for sustainable global production.