Medicinal Plant Research 2025, Vol.15, No.6, 264-273 http://hortherbpublisher.com/index.php/mpr 268 in A. sinensis (Wu et al., 2024). Other TFs involved in the coordinated regulation of phenylpropanoid metabolism include bHLH and WRKY as identified by Du et al. (2022). 4.3 Epigenetic regulation Epigenetic mechanisms, especially DNA methylation, are important to phenylpropanoid biosynthesis in A. sinensis. Genome-wide methylation studies reveal that CHH-type methylation in promoter regions is related to the regulation of such key genes as AsCOMT1 participating in ferulic acid and lignin synthesis. Higher DNA methylation degree corresponds with high gene expression and secondary metabolite accumulation-a fact emphasizing its regulatory significance (Yuan et al., 2024). Histone modifications, though less characterized in A. sinensis, are also involved in the regulation of genes of phenylpropanoid metabolism in other plants. 4.4 Regulatory networks: Metabolic pathways and TF-structural gene coordination In A. sinensis, the complex interactions between metabolic pathways and structural gene coordination by TFs take place within regulatory networks (Xu et al., 2019; Wu et al., 2024). Weighted gene co-expression network analysis has identified modules of co-expressed genes with TFs that control the spatial and temporal expression of the genes responsible for phenylpropanoid biosynthesis. Such networks ensure that bioactive compound biosynthesis is coordinated-with TFs such as MYB, bHLH, and WRKY integrating developmental and environmental signals to modulate pathway flux (Du et al., 2022). 4.5 Gene family expansion andA. sinensis-specific evolutionary adaptations A. sinensis has considerable expansions of the phenylpropanoid biosynthesis gene families, including but not limited to PTs, CYPs, and other pathway enzymes. These are evident through whole-genome duplication and tandem duplication events, which have enabled metabolic diversification and adaptation. By comparative genomics, such expansions into CYPs would seem unique to A. sinensis and its close Apiaceae relatives, thereby underpinning the evolution of unique coumarin and polyphenol profiles (Han et al., 2022; Li et al., 2023). Such adaptations underpin the medicinal properties and ecological success of this plant. 5 Multi-omics Insights into the Regulation of Phenylpropanoid Biosynthesis inA. sinensis 5.1 Transcriptomic analysis of pathway gene expression patterns Transcriptomic studies have shown that the main phenylpropanoid biosynthesis genes display tissue- and stage-specific expressions, such as PAL, C3H, CQT, COMT, and 4CL. For instance, high expressions of PAL, C3H, and CQT transcripts in the root tail are coincident with higher ferulic acid contents, and thousands of unigenes exhibit specific expression patterns in heads, bodies, and tails (Xu et al., 2019; Yang et al., 2020). The differential expression of genes also explains the flavonoid and anthocyanin accumulation in cultivar specificity. 5.2 Proteomic and phosphoproteomic insights into enzyme activity regulation Though few direct proteomic and phosphoproteomic studies have been conducted in A. sinensis, multi-omics integrations have pinpointed candidate enzymes and isoforms that participate in the biosynthesis of phenylpropanoids and phthalides. Enzyme activities are usually inferred from transcript abundance and metabolite accumulation. Validation through heterologous expressions and enzyme assays has been performed for a number of key steps (Feng et al., 2022; Li et al., 2023). These approaches contribute to the linking of gene expression with functional enzyme activity and metabolite profiles. 5.3 Metabolomic correlations across developmental stages and plant tissues Metabolomic profiling reveals that the phenylpropanoid compounds, including ferulic acid and flavonoids, are distributed variably among root parts and cultivars. The highest levels of ferulic and caffeic acid have been detected in the root tail, coinciding with the expression of biosynthetic genes (Yang et al., 2020). Metabolomic variation also reflects developmental and environmental influences, such as light exposure, influencing the accumulation of metabolites and gene expression alike (Su et al., 2024).
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