Metagenomic Insights into the Root‒Soil Response Mechanisms of Indica and Japonica Rice Under Nitrogen Deficiency and High-Efficiency Nitrogen Compensation.

Abstract

Nitrogen (N) dynamics critically regulate rice productivity through root-mediated absorption and assimilation processes. This study investigates the differential responses of japonica (Suxiu 867) and indica (Yangxianyou 918) rice to N deficiency and subsequent high-efficiency compensation, integrating metagenomic analysis with physiological assessments of N metabolism. Building on an established high-efficiency N compensation period (18 days after tillering for japonica and 12 days for indica), we demonstrate that optimized N compensation significantly enhances dry matter accumulation and yield in both subspecies through distinct biological mechanisms. Compensation treatment elevated key metabolic indicators including soluble protein content (Cpr), glutamine synthetase (GDH) activity, soil urease (S-UE) activity, glutamate synthase (GOGAT) activity, and glutamine synthetase (GS) activity, collectively enhancing N assimilation efficiency. Rhizosphere microbiome restructuring showed subspecies-specific patterns, with Chloroflexi and Betaproteobacteria abundance positively correlating with N metabolic enzymes in indica, versus Actinomycetia, Deltaproteobacteria associations in japonica. Functional microbial analysis revealed divergent keystone taxa, with Noviherbaspirillum (indica) and Bacillus (japonica) driving N conversion efficiencies through niche-specific community synergies. Notably, indica rice presented a relatively high N absorption capacity and conversion efficiency, while japonica rice presented relatively stable N absorption and distribution mechanisms, and relatively high N fertilizer application significantly increased the abundance of specific microbial communities in japonica rice. These findings elucidate how subspecies-specific root physiology coordinates with rhizosphere microbial ecology to optimize N utilization, providing actionable insights for precision N management strategies tailored to rice genetic types.