Editorial: In-Depth Interpretation of Critical Genomic Information Related to the Biosynthesis of Key Specialized (Secondary) Metabolism in Medicinal Plants

Mingcheng Wang^1*Xinyi Guo²Zefu Wang³

• ¹Chengdu University, Chengdu, China
• ²Masarykova univerzita, Brno, Czechia
• ³Nanjing Forestry University, Nanjing, China

Since the first plant genome was decoded just over two decades ago, research on specialized 2 metabolites has evolved from labor-intensive phytochemistry into a data-rich, multi-omics 3 enterprise. The 13 articles in this Research Topic illustrate both the impressive advances and the 4 persistent challenges in applying genomics, transcriptomics, metabolomics, and synthetic biology 5 to medicinal plants. Collectively, they investigate 11 species spanning several major metabolite 6 classes, employing strategies from telomere-to-telomere (T2T) genome assemblies to optimized 7 tissue-culture platforms. Above all, these studies demonstrate that modern natural-product science 8 is inherently integrative: pathway genes cannot be fully understood without their regulatory 9 networks, and metabolite accumulation must be interpreted in its ecological and developmental 10 contexts. 11 The first cluster of papers demonstrates how chromosome-level (including T2T) genomes unlock 13 complete mechanistic views of specialized metabolic pathways. The T2T assembly of Hedyotis 14 diffusa revealed a recent whole-genome duplication that expanded key enzyme families. Through 15 transcriptome analysis, one loganic-acid O-methyltransferase and two cytochrome P450 genes 16 were identified as late-stage iridoid tailoring enzymes, closing a critical gap in the biosynthetic 17 map (Chen et al., 2025). Mapping jasmonate-elicited RNA-seq and small RNAs to the Taxus 18 chinensis chromosome-level genome identified 990 transcription factors, 460 miRNAs and 160 19 phasiRNAs linked to paclitaxel biosynthesis. Enzyme genes were most highly expressed in cones 20 and roots, methyl jasmonate failed to induce GGPPS or CoA-ligase, and the resulting 21 miRNA-phasiRNA network buffers paclitaxel output while suggesting precise engineering targets 22 (Sun et al., 2025). In Quercus variabilis, a chromosome-level genome enabled the identification of 23 22 TCP transcription factors and revealed that TCP3 is tightly co-expressed with the 24 hydrolysable-tannin glycosyltransferase UGT84A13 in the cupule. Dual-luciferase assays 25 confirmed that TCP3 binds and activates the UGT84A13 promoter, demonstrating how 26 lineage-specific expansion of TCPs governs tissue-specific tannin accumulation (Wang et al., 27 2024a). Combined metabolomic and transcriptomic profiling of Pogostemon cablin tissues 28 showed that pogostone accumulates primarily in the roots. Mapping RNA-seq reads to the 29 reference genome, together with expression-metabolite correlation and HXXXD motif screening, 30 highlighted BAHD-DCR acyltransferases as candidate terminal enzymes for pathway engineering 31 (Wang et al., 2025a). Twenty-one 2,3-oxidosqualene cyclase (OSC) genes were identified from the 32 Panax japonicus genome, and several were found to be root-enriched and localized to the nucleus, 33 suggesting specialized roles in tissue-specific triterpenoid biosynthesis (Yang et al., 2025). Finally, 34 analysis of the Musella lasiocarpa genome identified 158 WRKY transcription factors distributed across nine chromosomes. Integrating organ-specific RNA-seq and qRT-PCR data, MlWRKY15, 36 MlWRKY111, and MlWRKY122 were co-expressed with two O-methyltransferase genes, 37 implicating these WRKYs in organ-specific regulation of phenylphenalenone biosynthesis (Huang 38 et al., 2025). Together, these studies combine high-quality genomes and integrative multi-omics to 39 dissect medicinal plant specialized metabolic pathways with unprecedented resolution, thereby 40 closing critical mechanistic gaps. 41The second group of studies showcases what can be achieved when reference genomes are 42 absent. Through integrated transcriptomic and metabolomic profiling, Wu et al. ( 2024) identified 43 seven key enzyme genes and thirteen co-expressed transcription factors central to Huperzine A 44 biosynthesis in Huperzia serrata. They further showed that phenylpropanoid and flavonoid 45 pathways were up-regulated in cultured thalli, a shift that correlated with heightened antioxidant strategies. In Taxus, the small-RNA network suggests deploying miRNA sponges or CRISPR 71 knock-outs to derepress taxoid P450s (Sun et al., 2025). Overexpressing TCP3 in Quercus could 72 enhance cupule tannin levels (Wang et al., 2024a), while tuning specific WRKY factors in Musella 73 could increase phenylphenalenone production (Huang et al., 2025). In Pogostemon, several 74 BAHD acyltransferases emerge as prime targets for enhancing pogostone (Wang et al., 2025a), 75 and in Peucedanum, upregulating the C2′H hydroxylase could elevate coumarin content (Liu et al., 76 2025). These actionable targets thus provide a roadmap for future integration with efficient 77 tissue-culture and cell-factory technologies, laying the groundwork for predictable, high-yield 78 production pipelines. 79The two review articles place these empirical advances in a broader methodological and 80 translational context. One integrates genomics, transcriptomics, proteomics and metabolomics to 81 reveal how multi-omics dissects biosynthetic gene clusters, pathway reconstruction and 82 stress-response mechanisms in medicinal plants. It also profiles bioinformatics platforms, 83 highlights single-cell and spatial transcriptomics alongside CRISPR/Cas editing, and identifies 84 challenges in data integration, standardization and dynamic pathway mapping for scalable 85 metabolite production (Wang et al., 2024b). The second review synthesizes current knowledge on 86 benzylisoquinoline alkaloid (BIA) biosynthesis by cataloguing key enzymatic steps from 87 norcoclaurine synthase to P450 monooxygenases and integrating multi-omics findings to close 88 pathway gaps. It evaluates synthetic biology strategies such as modular reconstruction in 89 microbial and plant hosts and dynamic flux control for scalable BIA production (Zhao et al., 90 2025). 91 This collection highlights two complementary paradigms for dissecting medicinal plant 93 metabolism. Genome-enabled studies exploit chromosome-level and T2T assemblies to uncover 94 duplications, gene family expansions and regulatory networks, identifying enzymes and 95 transcription factors that drive tissue-and stress-specific metabolite accumulation. Parallel efforts 96 using de novo transcriptomes, metabolite profiling and genetic markers chart biosynthetic modules 97 and post-transcriptional controls even in species lacking reference assemblies. Together, they 98 deliver a coherent set of strategies for identifying bottlenecks and engineering targets across 99 diverse metabolite classes. 100Looking forward, realizing the full complexity of plant specialized metabolism will require 101 integrating single-cell methods to resolve cell-type pathways, spatial-omics to trace metabolite 102 flux in situ and artificial intelligence-powered models to predict enzyme function and network 103 dynamics. Coupling these innovations with high-quality genomes and biochemical validation will 104 transform pathway elucidation from retrospective description to forward-looking design. Such