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Published on: September 6, 2018
Source-sink nitrogen dynamics and their response to variable nitrogen levels during rice grain filling
Xiao-Li Huang1,2,3, Yan Peng1,2,3, Zhi-Jun Xu1,2,3
1Hunan Provincial Key Laboratory of Rice Stress Biology, Hunan Agricultural University, Changsha, 410128, China.
Background:
Rice grains largely depend on nitrogen (N) remobilization from leaves. However, the dynamics of N species in source (leaf) and sink (grain) tissues and the effects of the external N supply remain unclear.
Results:
This study investigated the dynamic changes and metabolic characteristics of major N fractions in flag leaves and grains under high-nitrogen (HN) and low-nitrogen (LN) treatments during grain filling. The concentrations of grain nitrate-N (NO₃⁻-N) and amino acid-N (AAs-N) decreased, whereas ammonium-N (NH₄⁺-N) showed dynamic changes, leading to an increased proportion of inorganic N (IN). The total N (TN) in the grain was negatively correlated with NO₃⁻-N but positively correlated with NH₄⁺-N (LN: r = 0.75; HN: r = 0.92). In flag leaves, only NO₃⁻-N increased. Despite similar overall trends, the magnitudes of these changes varied among the N treatments. The grain TN was predominantly supported by AAs-N: under HN, AAs-N accounted for 74.1-50.0%, which consistently exceeded IN (25.9-49.9%); in contrast, under LN at the middle-to-late stages, IN (50.2-69.7%) exceeded AAs-N (49.8-30.3%). HN strengthened the positive correlation between grain NH₄⁺-N and TN, whereas LN intensified the correlations among the leaf N fractions. LN accelerated TN and AAs-N degradation and promoted NO₃⁻-N accumulation and N remobilization in leaves. Furthermore, LN upregulated grain N-assimilating enzymes and leaf NiR, whereas HN maintained relatively high leaf NR and GS. Transcriptomic analysis revealed that hormone signals were involved in regulating rice N metabolism.
Conclusions:
During rice grain filling, NO₃⁻-N, NH₄⁺-N, and AAs-N in grains and leaves dynamically changed and were differentially regulated by enzyme activity and gene expression, ultimately clarifying source‒sink nitrogen dynamics for optimized nitrogen management.
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