Multi-omics-guided engineering of safflower for abiotic stress resilience and metabolic improvement

Safflower ( Carthamus tinctorius L.) is a drought adapted oilseed and medicinal crop valued for its unsaturated seed oil and specialized floral metabolites particularly hydroxysafflor yellow A (HSYA) making it an attractive but underexploited target for trait engineering. Chromosome-scale genomes, population resequencing, and expanding multi-omics datasets have transformed safflower's molecular toolkit, but progress toward causal validation remains uneven across trait areas. Here we assess that gap across three principal trait areas. Seed-oil biosynthesis is well mapped but functionally validated at only one locus, FAD2–1 . Drought-response datasets are extensive yet largely correlative. HSYA biosynthesis stands apart as the most mechanistically resolved pathway in the species, anchored by validated enzymatic steps. Across all three areas, we find fragmented multi-omics integration, sparse proteomic and metabolomic coverage, genotype-dependent transformation, and a complete absence of genome-scale metabolic models, standardized genetic parts, and/or design-build-test-learn infrastructure (DBTL). We presented a roadmap for closing these gaps, arguing that the existing genomic wealth of safflower can be redirected toward systematic functional validation and iterative engineering, repositioning it as a tractable model for climate-resilient, high-value crop design.