The perilla anthocyanins have important medicinal and ornamental value, and their contents are significantly affected by light intensity. In view of their molecular mechanisms were not well understood, we integrated the metabolomic and transcriptomic analyses of the light-sensitive perilla variety under different light intensity. The perilla leave color were obviously affected under different treatments. Totally 140 flavonoid metabolites and 2461 genes showed steady change, among which 60 flavonoid metabolites were increased accumulation and 983 genes were upregulated expression under elevated light intensity treatment. Light treatment prominently affected the expression of genes involved in the main anthocyanin metabolites accumulation in perilla leaves. Using WGCNA analysis, we identified 4 key genes in anthocyanin biosynthesis pathway (CHI, DFR, and ANS) and 147 transcription factors (MYB, bHLH, bZIP, ERF, and NAC) involved in malonylshisonin biosynthesis. Among them, 6 MYBs and 4 bZIPs were predicted to play important roles in light regulation of malonylshisonin biosynthesis based on phylogenetic construction, correlation analysis, cis-acting element identification and qPCR verification. The identified key genes and regulatory factors will help us to understand the potential mechanism of photo-regulated anthocyanin accumulation in perilla.

Perilla frutescens (Perilla) has great potential for utilization in food and medicine due to the abundance of secondary metabolites, especially phenolic compounds. However, the molecular mechanism underlying phenolic compound synthesis in perilla remains poorly understood. By targeted metabolome analysis, we found nine differentially accumulated metabolites among QS2, QS6, and QO7 leaves and nine unique metabolites which only exist in QS6. Furthermore, transcriptome analysis showed the differential expression genes (DEGs) were significantly enriched into phenylpropanoid- and flavonoid-related pathways. Moreover, the integrated transcriptome and metabolome analyses indicated 14 candidates highly correlated with phenolic compound biosynthesis. In addition, phenylpropanoid- and flavonoid-biosynthesis-related DEGs, including one PAL, one CYP73A, one 4CL, two CHI, two F3H, one FLS, three CHS, two CYP75B1, one ANS, and two DFR, were isolated. The results in this study provide useful information for the metabolic regulation of phenolic compounds and serve as essential gene resources for future breeding programs.

Rosmarinic acid (RA) is an important medicinal metabolite and a potent food antioxidant. We discovered that exposure to high light intensifies the accumulation of RA in the leaves of perilla (Perilla frutescens (L.) Britt). However, the molecular mechanism underlying RA synthesis in response to high light stress remains poorly understood. To address this knowledge gap, we conducted a comprehensive analysis employing transcriptomic sequencing, transcriptional activation, and genetic transformation techniques. High light treatment for 1 and 48 h resulted in the upregulation of 592 and 1,060 genes, respectively. Among these genes, three structural genes and 93 transcription factors exhibited co-expression. Notably, NAC family member PfNAC2, GBF family member PfGBF3, and cinnamate-4-hydroxylase gene PfC4H demonstrated significant co-expression and upregulation under high light stress. Transcriptional activation analysis revealed that PfGBF3 binds to and activates the PfNAC2 promoter. Additionally, both PfNAC2 and PfGBF3 bind to the PfC4H promoter, thereby positively regulating PfC4H expression. Transient overexpression of PfNAC2, PfGBF3, and PfC4H, as well as stable transgenic expression of PfNAC2, led to a substantial increase in RA accumulation in perilla. Consequently, PfGBF3 acts as a photosensitive factor that positively regulates PfNAC2 and PfC4H, while PfNAC2 also regulates PfC4H to promote RA accumulation under high light stress. The elucidation of the regulatory mechanism governing RA accumulation in perilla under high light conditions provides a foundation for developing a high-yield RA system and a model to understand light-induced metabolic accumulation.

Recently, alterations in the expression pattern of PPP2R5C associated with malignant transformation have been characterized, and PPP2R5C overexpression was demonstrated in leukemias. To confirm the role of PPP2R5C in proliferation and its molecular mechanism, three PPP2R5C-siRNAs and a scrambled nonsilencing siRNA control were used to treat Molt-4 and Jurkat T cells. After nucleofection, PPP2R5C expression and biological consequences based on a highly efficient and specific PPP2R5C-siRNA were demonstrated by qRT-PCR, CCK-8 assay, Annexin V/PI, and flow cytometry. The global gene expression profile of PPP2R5C-siRNA-treated Jurkat T cells was established. A significant reduction in the PPP2R5C mRNA level was observed at 24 to 72 h in Molt-4 and Jurkat T cells with all of the PPP2R5C-siRNAs. The proliferation rate of Molt-4 and Jurkat T cells transfected with different PPP2R5C-siRNAs was significantly decreased at 72 h compared with the control (p<0.05). However, the transfected cells did not show a significant increase in Annexin V/PI-positive cells (apoptosis). The highly efficient PPP2R5C-siRNA2 was used to treat Jurkat T cells for gene expression profile analysis. In total, 439 genes were upregulated, and 524 genes were downregulated at least twofold in PPP2R5C-siRNA-treated Jurkat T cells. Changes in signaling pathway genes closely related to the TCR, Wnt, calcium, MAPK, and p53 signaling pathways were observed. In conclusion, the suppression of PPP2R5C by RNA interference could effectively inhibit the proliferation of leukemic T cells, the PPP2R5C-siRNA treatment altered gene expression profiles, and the differential expression of the glycogen synthase kinase 3 beta (GSK-3β), ataxia telangiectasia mutated (ATM), and Mdm2 p53 binding protein homolog (MDM2) genes may play an important role in the effects of PPP2R5C knockdown in Jurkat T cells. Knocking down PPP2R5C using siRNA altered downstream gene expression, and was associated with decreased proliferation of Jurkat cells. Among the differentially expressed genes are GSK-3β, ATM, and Mdm2 p53 binding protein homolog.