Key message: RNAi-based genetically modified maize resistant to Monolepta hieroglyphica (Motschulsky) was demonstrated with negligible transcriptome and metabolome alterations compared to its unmodified equivalent. As one of the most prevalent insect pests afflicting various crops, Monolepta hieroglyphica (Motschulsky) causes severe loss of agricultural and economic productivity for many years in China. In an effort to reduce damages, in this study, an RNA interference (RNAi)-based genetically modified (GM) maize was developed. It was engineered to produce MhSnf7 double-stranded RNAs (dsRNAs), which can suppress the Snf7 gene expression and then lead M. hieroglyphica to death. Field trail analysis confirmed the robustly insecticidal ability of the MhSnf7 GM maize to resist damages by M. hieroglyphica. RNA sequencing analysis identified that only one gene was differentially expressed in the MhSnf7 GM maize compared to non-GM maize, indicating that the transcriptome in MhSnf7 GM maize is principally unaffected by the introduction of the MhSnf7 dsRNA expression vector. Likewise, metabolomics analysis identified that only 8 out of 5787 metabolites were significantly changed. Hence, the integration of transcriptomics and metabolomics demonstrates that there are negligible differences between MhSnf7 GM maize and its unmodified equivalent. This study not only presents a comprehensive assessment of cellular alteration in terms of gene transcription and metabolite abundance in RNAi-based GM maize, but also could be used as a reference for evaluating the unintended effect of GM crops.

Rice consumption and demand for premium rice are increasing worldwide. However, the characterizations and how to identify the premium rice are still unclear. Small molecular metabolites have a great advantage in distinguishing subtle differences among similar agricultural products. So, we hypothesized that the metabolites would be the key to identifying the tiny differences in premium rice among similar varieties. In this study, we performed metabolomic and transcriptomic profiles to comprehensively elucidate key metabolites, genes, and formation mechanisms of premium rice. As a result, eight compounds belong to four categories, and 49 different expressional genes were identified in premium rice varieties after comparing with the second-best varieties. Moreover, the integrated analysis confirmed that the amino acid pathway, including 42 expression genes and 11 metabolites, was critical for the premium rice formation. Six genes and two metabolites had significant regulatory effects on the pathways. Furthermore, amino acid quantification confirmed the content of 12 kinds of hydrolytic amino acids, such as aspartic acid and arginine were different between premium and other varieties. These amino acids may serve as potential biomarkers for differentiating premium rice in Northeast China. Our results strongly support the possibility of differentiating premium rice and would provide essential data for premium rice identification and metabolomics-assisted breeding.

Lipids play a critical role in maintaining the quality of rice. However, lipidomic profiles of japonica rice cultivars from Northeast China under practical storage conditions remain poorly characterized. The japonica rice varieties were stored at 10°C and 25°C for up to 200 days. After the periodic assessment of key quality parameters of milled rice, lipidomics by liquid chromatography‐tandem mass spectrometry (LC‐MS/MS) was performed on samples stored at 25°C on Days 0 and 140, with additional varieties used for validation. Notable changes in rice quality emerged after a 140‐day storage. Lipidomics analysis identified 349 lipids, and the levels of 19 lipids from the glycerolipid (GL) and glycerophospholipid (GP) pathways significantly reduced. Correlation analyses revealed that pentadecanoic acid (C15:0) exhibited the strongest inverse correlation with eating quality (r = −0.861). This study presents a comprehensive lipidomic profile of milled japonica rice and identifies differentially expressed lipids associated with quality loss after storage. The observed lipid after storage suggested hydrolytic processes may be associated with a decline in quality. C15:0 may serve as a candidate biomarker of quality change during storage. These insights support improved storage strategies and quality monitoring protocols for high‐value rice products.

Residual gene editors are a concern associated with the widespread application of CRISPR/Cas9 technology. Here, we developed a CRISPR/Cas12a-based fluorescent aptasensor for the qualitative and quantitative detection of Cas9 protein. Secondary structure prediction and molecular docking were combined to identify potential binding sites of the Cas9-specific aptamer. A fluorescence aptasensor was constructed based on competitive binding: in the presence of Cas9, the aptamer binds to the target and releases complementary DNA (cDNA), which activates the trans-cleavage activity of Cas12a. Cas12a subsequently cleaves a single-stranded DNA (ssDNA) reporter labeled with a fluorophore and a quencher, generating a fluorescence signal, expressed in relative fluorescence units (RFU), that increases with Cas9 concentration. The optimized conditions comprised a trans-cleavage reaction time of 20 min, a Cas12a:CRISPR RNA (crRNA) molar ratio of 1:1, a final aptamer concentration of 180 nM, and a combination of low- and high-salt buffers to balance molecular recognition and protein stability. The proposed assay enabled Cas9 protein detection in buffer and Cas9-spiked soybean milk and cereal matrices. These results represent a proof-of-concept evaluation in complex food matrices rather than validation of authentic residual Cas9 detection. Further studies using unspiked gene-edited samples with independently verified Cas9 residues and an orthogonal reference method are required.