Tong Haiyang, Wang Chao, Han Xiaoqian, Sun Qihao, Luo Enxi, Yang Chao, Xu Guo, Ou Xumin, Li Shixuan, Zhang Jianing, Yang Jun
National Key Laboratory for Tropical Crop Breeding, School of Breeding and Multiplication (Sanya Institute of Breeding and Multiplication), Hainan University, Sanya Hainan, 572025, China.
National Key Laboratory for Tropical Crop Breeding, College of Tropical Agriculture and Forestry, Hainan University, Sanya Hainan, 572025, China.
Rice (N Y). 2025 Jun 13;18(1):50. doi: 10.1186/s12284-025-00811-6.
Rice (Oryza sativa L.), one of the most vital staple crops globally, suffers severe yield losses due to metabolic dysregulation under salt stress. However, the systemic mechanisms by which non-coding RNAs (ncRNAs) coordinately regulate metabolic reprogramming remain elusive, and the genotype-specific regulatory networks in salt-tolerant cultivars are poorly characterized. To address this, we performed metabolomic analysis using ultra-high-performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS) across different rice varieties under salt stress, identifying 327 metabolites, with the most notable fluctuations observed in lipids, polyamines, and phenolamides. The salt-tolerant variety Pokkali exhibited 51.96% and 31.37% fewer differentially accumulated metabolites (DAMs) in the shoots and roots respectively, compared to the salt-sensitive variety Nipponbare (NIP), which explains its superior salt-tolerant phenotype from a metabolic homeostasis perspective. Transcriptome profiling revealed 18,597 differentially expressed genes (DEGs), with 70.8% showing genotype-specific expression patterns. Pokkali-specific DEGs were markedly enriched in salt-responsive pathways, including reactive nitrogen species scavenging and ion compartmentalization. By integrating long non-coding RNA (lncRNA) and microRNA (miRNA) sequencing data, we constructed a four-tiered regulatory network comprising 6,201 DEGs, 458 miRNAs, 970 DElncRNAs, and 177 metabolites. In the regulatory network, Osa-miR408-3p was identified as a negative regulator of Os03 g0709300 expression. Network analysis revealed that 21 polyamine and phenolamides biosynthesis-related genes were co-regulated by eight miRNAs, each forming a feedback loop with 2-11 lncRNAs. This study constructed a four-way cascade of "lncRNA-miRNA-mRNA-metabolite", and proposed a new concept of ncRNA-mediated "network regulation instead of single-gene effect".
水稻（Oryza sativa L.）是全球最重要的主食作物之一，在盐胁迫下由于代谢失调而遭受严重的产量损失。然而，非编码RNA（ncRNA）协调调节代谢重编程的系统机制仍不清楚，耐盐品种中的基因型特异性调控网络也鲜有特征描述。为了解决这个问题，我们使用超高效液相色谱-串联质谱（UPLC-MS/MS）对盐胁迫下的不同水稻品种进行了代谢组学分析，鉴定出327种代谢物，其中脂质、多胺和酚酰胺的波动最为显著。与盐敏感品种日本晴（NIP）相比，耐盐品种Pokkali在地上部和根部的差异积累代谢物（DAM）分别减少了51.96%和31.37%，这从代谢稳态的角度解释了其优异的耐盐表型。转录组分析揭示了18597个差异表达基因（DEG），其中70.8%表现出基因型特异性表达模式。Pokkali特异性DEG在盐响应途径中显著富集，包括活性氮清除和离子区室化。通过整合长链非编码RNA（lncRNA）和微小RNA（miRNA）测序数据，我们构建了一个由6201个DEG、458个miRNA、970个DElncRNA和177个代谢物组成的四层调控网络。在调控网络中，Osa-miR408-3p被鉴定为Os03 g0709300表达的负调控因子。网络分析表明，21个多胺和酚酰胺生物合成相关基因由8个miRNA共同调控，每个基因与2-11个lncRNA形成一个反馈环。本研究构建了“lncRNA-miRNA-mRNA-代谢物”的四路级联，并提出了ncRNA介导的“网络调控而非单基因效应”的新概念。
