Temporal DIA-MS Proteomics Reveals Coordinated Metabolic Reprogramming Associated with Oil Accumulation in Oil Palm Mesocarp

Oil palm ( Elaeis guineensis Jacq.) is the most productive oil-bearing crop globally, yet the molecular basis of mesocarp development and lipid accumulation remains poorly understood. Ultra-deep data-independent acquisition mass spectrometry (DIA-MS) was applied to characterize proteome dynamics in two contrasting genotypes, seedless (KS) and thin-shelled (TS), across five developmental stages (P1–P5) spanning fruit development to mature oil accumulation. Phenotypic analysis revealed higher mesocarp proportion and oil content in KS during late maturation. A total of 137,615 peptides corresponding to 12,163 protein groups were identified, providing a temporal proteomic landscape of mesocarp development. Multivariate analysis indicated that developmental progression was the primary contributor to proteomic variation, whereas genotype-associated differences increased during lipid accumulation. Differentially abundant proteins were mainly associated with carbohydrate metabolism, photosynthesis, proteolysis, antioxidant responses, and lipid biosynthesis. Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and KOG analyses suggested extensive remodeling of metabolic networks, including developmental changes in photosynthesis-associated proteins and increased representation of lipid-associated pathways during maturation. Weighted protein co-expression network analysis identified 17 modules associated with developmental progression and lipid accumulation, highlighting candidate proteins involved in carbon metabolism, energy production, and cellular protection. Genes encoding selected hub protein candidates were further examined by RT-qPCR. Biochemical analyses supported these proteomic patterns, showing increased acetyl-CoA availability, enhanced antioxidant enzyme activities (SOD, CAT, APX, and GR), improved GSH/GSSG balance, and reduced oxidative damage in KS. Together, these findings provide a temporal proteomic and biochemical framework for understanding genotype-associated differences in oil accumulation and identify candidate metabolic networks for functional studies.