Phosphorus modulates starch granule development and metabolic partitioning in wheat grain: Insights from SGAP proteomics and nutrition and processing quality.

Abstract

This study investigates how phosphorus (P) levels are associated with carbon-nitrogen metabolism in wheat grains. Optimal P application (105 kg P₂O₅ ha⁻¹) was associated with enhanced pericarp-endosperm coordination, increased carbon allocation to the endosperm, and early B‑type starch granule formation. Starch granule‑associated protein (SGAP) proteomics showed that optimal P upregulated cytoskeletal and starch‑synthesis proteins bound to starch granules in the endosperm, while reducing storage protein degradation‑related SGAPs in the pericarp. These metabolic adjustments were correlated with increased grain‑filling intensity and duration, and were associated with the highest theoretical grain weight (50.70 mg). Furthermore, optimal P was associated with enrichment of amino acid biosynthesis pathways and with higher levels of essential amino acids (e.g., lysine and threonine by 17.0--26.8%) and an improved essential amino acid profile without altering total protein content. In contrast, excessive P (210 kg P₂O₅ ha⁻¹) was associated with disrupted inter‑tissue coordination but did not simply impair grain filling; instead, HP corresponded to a unique developmental program: it was linked to an early burst of C‑type starch granules (0∼5 µm) at 7 DPA, yet by maturity achieved the highest proportion of large A‑type granules (56.8%) and the highest total starch content (63.5%), together with elevated endosperm phosphorus at 14 DPA and enrichment of spliceosome‑related pathways. HP also showed higher levels of several functional amino acids (glutamate, cysteine, histidine, proline) compared to P0. However, HP was associated with a higher gliadin/globulin ratio and did not improve grain yield. These findings suggest that phosphorus supply is associated with grain quality through tissue‑specific metabolic reprogramming, and that precision management-rather than maximized application-warrants consideration for optimizing both yield and processing quality.