Integrated physiological, transcriptomic and metabolomic analyses characterize treatment-associated autumn shoot self-pruning and maturation in Wogan mandarin
Abstract
Autumn shoot maturation is important for citrus canopy management and subsequent reproductive development. We compared five foliar treatments but interpret their effects as treatment-specific because the salts were not equimolar and KH₂PO₄ supplied both K and P. Water (CK), 0.3% (w/v) KNO₃, 0.3% KH₂PO₄, 0.3% K₂SO₄ and a seaweed-polysaccharide product were applied twice to 15 three-year-old Wogan mandarin trees (three trees per treatment). Under an exploratory equal-weight framework, KH₂PO₄ had the highest integrated score (0.858) and remained first in all 11 leave-one-indicator-out analyses. Longitudinal mixed models detected treatment-by-linear-time interactions for shoot length, shoot diameter, internode length, leaf number, leaf width and leaf thickness, but not for self-pruning rate or SPAD. RNA-seq and untargeted LC-MS profiling of CK and KH₂PO₄ leaves and stems showed tissue- and stage-dependent responses. The broad VIP > 1 and P < 0.05 metabolite set was largest at 3 d (554 leaf and 357 stem features), whereas only 31 leaf and one stem feature at 3 d met VIP > 1 and BH q < 0.05; the remaining six comparisons had none. Co-expression, putative PPI and pathway analyses prioritized lignin-, hormone- and redox-related candidates. qRT-PCR of nine genes detected 19 FDR-significant tissue–time responses and supported several key RNA-seq expression patterns. Foliar KH₂PO₄ was associated with high leaf K, low Na, carbon–osmotic adjustment, redox stabilization and lignin-related transcription. These data identify treatment-associated candidate pathways and genes rather than a K-specific, P-specific or causal mechanism.
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Authors: Guoguo Li, Qiuyou Chen, Xuejun Bei, Yin Luo, Xiangling Chen, Yijie Li, Xiaolin Cai, Hongtao Zhao, Qichun Huang, 陆振, Yongzhong Liu
Institutions: Huazhong Agricultural University, Yulin Normal University, Guangxi Academy of Agricultural Science