Transcriptome alterations overview
Transcriptome sequencing was conducted on S. tonkinensis roots, stems, leaves, and seeds (Fig. 1) to determine the molecular regulation in different tissues. The acquired raw reads ranged from 45.71 to 51.09 million, with respective Q20 and Q30 values exceeding 97% and 93% (Table S1), suggesting the acquisition of high-throughput and high-quality RNA-Seq data. Following the removal of low-quality reads, a further analysis was performed on 44.36 to 49.33 million clean reads. Out of all the clean reads, between 69.19% and 92.05% were found to map to the genome of S. tonkinensis. The RNA-Seq dataset with the accession number PRJNA1052132 is archived in the NCBI SRA database. Additionally, the number of DEGs across various S. tonkinensis tissues was observed (Fig. 2A). In all comparison groups, a comprehensive set of 2,727 DEGs were screened (Fig. 2B and Table S2). Of these, 543 DEGs were commonly expressed in all groups, accounting for 3.55%. The remaining six groups showed specific genes for each comparison group (Fig. 2B), indicating that the expression of these genes was activated by S. tonkinensis in response to various tissue functional structures. To ascertain if the RNA-Seq data were reliable, we selected 12 DEGs, including two related to alkaloid biosynthesis, two related to flavonoid biosynthesis, two related to transcription factors, two related to photosynthesis, and four randomly selected DEGs. Their expression levels were assessed using qPCR, revealing a positive correlation between the expression profiles detected by qPCR and the RNA-Seq results (Fig. 3).
DEGs involved in the alkaloid biosynthesis and flavonoid biosynthesis pathways
Thirty-five DEGs involved in alkaloid biosynthesis were identified to further understand the differential expression genes associated with the biosynthetic pathways of flavonoids and alkaloids in distinct S. tonkinensis tissues (Fig. 4A). These 35 DEGs encompass ten tropinone reductases (TRs), eight copper amine oxidases (CAOs), seven polyphenol oxidases (PPOs), three tyrosine aminotransferases (TATs), two dependent decarboxylase conserves (DDCs), two histidinol-phosphate aminotransferases (HisCs), one aspartate aminotransferase (ASP5), one aspartate aminotransferase (GOT2), and one lysine decarboxylase (LDC).
Furthermore, 48 DEGs involved in flavonoid biosynthesis were identified (Fig. 4B), including 11 chalcone synthases (CHSs), seven hydroxycinnamoyl transferases (HCTs), six chalcone isomerases (CHIs), three flavonol synthases (FLSs), three spermidine hydroxycinnamoyl transferases (SHTs), two caffeoyl-CoA O-methyltransferases (CCoAOMTs), two cinnamate 4-hydroxylases (CYP73As), two flavonoid 3',5'-hydroxylases (CYP75As), two dihydroflavonol reductases (DFRs), two flavonoid 3',5'-methyltransferases (FAOMTs), one anthocyanidin reductase (ANR), one cinnamoyl-CoA O-methyltransferase (CCOMT), one flavonoid 3'-monooxygenase (CYP75B1), one coumaroylquinate (coumaroylshikimate) 3'-monooxygenase (CYP98A), one omega-hydroxypalmitate O-feruloyl transferase (HHT1), one leucoanthocyanidin dioxygenase (LDOX), one NAD(P)H-dependent 6'-deoxychalcone synthase (NADH), and one phloretin 2'-O-glucosyltransferas (PGT1).
By examining the expression levels, we found that StCAO (evm.model.3.924) in the alkaloid biosynthesis pathway exhibited significantly enhanced expression in the roots, stems, leaves, and seeds, particularly in the seeds where its expression surpasses that of other genes significantly. Additionally, the expression level of StCHI (evm.model.3.2047) was significantly higher in the root, stem, leaf, and seed in the flavonoid biosynthetic pathway. Among them, the expression level in the seed was 1.76, 1.98, and 3.07 times greater than that in the root, stem, and leaf, respectively. In the seed, StCHI (evm.model.3.2047) expression was significantly upregulated relative to that of other genes.
Alkaloid and flavonoid content in different S. tonkinensis tissues
As shown in Fig. 5, the concentrations of total alkaloids, matrine, and oxymatrine in seeds were significantly elevated relative to those in other tissues (P<0.05), registering values of 19.88 mg/g, 169.48 μg/g, and 9.43 mg/g, respectively. Similarly, the concentrations of total flavonoids and genistin in seeds were significantly elevated in comparison to other tissues (P<0.05), measuring 14.02 mg/g and 27.13 μg/g, respectively. The concentration of genistein in leaves reached 15.05 μg/g, which was significantly elevated relative to those in other tissues (P<0.05). These results highlight the variations in alkaloid and flavonoid contents across different S. tonkinensis tissues.
Overview of the metabolome changes
The results of metabolic compound detection in these samples have undergone quality control (QC) analysis. The QC sample relative standard deviation (RSD) evaluation plot is shown in Fig. S1. The overall data is considered qualified and reliable for subsequent analysis when the RSD is 0.3, with a cumulative proportion of ion peaks reaching 82.01%. PCA revealed that the proportion of total variance explained by the first principal component (PC1) was 43.90 %, distinguishing samples based on different tissues of S. tonkinensis. Conversely, 31.50 % of the total variance was attributed to the second principle component (PC2) (Fig. 6A). Samples from the same tissue cluster closely together, indicating good data condition. The roots and stems exhibit closer proximity, indicating higher similarity in chemical composition. In contrast, leaves and seeds are more distant from each other and the roots and stems, indicating lower chemical composition similarity and unique metabolic characteristics. The PCA results underscore differences in the metabolic products of different S. tonkinensis tissues.
The Pearson correlation coefficient analysis revealed consistent cumulative metabolite values among the six biological replicates in 24 S. tonkinensis samples (Fig. 6B). Additionally, the correlation coefficient within group samples surpasses that between inter-group samples, affirming the reliability of the obtained differential metabolites. These findings underscore the robust correlation and reliability of experimental results across different tissues of S. tonkinensis.
In total, 4,138 metabolites were identified from four tissues, with 2,282 in positive and 1,856 in negative ion modes (Table S3). Employing PLS-DA model analysis, differentially expressed metabolites (DEMs) were screened using significance criteria of P<0.05 and VIP value >1. The results revealed 1,553 DEMs between roots and stems (432 upregulated and 1,121 downregulated), 1,658 DEMs between roots and leaves (584 upregulated and 1,074 downregulated), 1,761 DEMs between roots and seeds (4 upregulated and 867 downregulated), 1,634 DEMs between stems and leaves (861 upregulated and 773 downregulated), 1,831 DEMs between stems and seeds (1,173 upregulated and 658 downregulated), and 1,846 DEMs between leaves and seeds (1,149 upregulated and 697 downregulated (Fig. 6C). These results highlight the diverse metabolic composition across different tissues of S. tonkinensis. Further analysis of DEMs among roots, stems, leaves, and seeds identified 18 major DEMs (Fig. 6D), including sparteine, homoferreirin, O-desmethyltramadol, dihydrofolic acid, deoxypyridinoline, artocarpesin, ID14326, 12,20-dioxo-leukotriene B4, CDP-ethanolamine, lucuminoside, 4-hydroxyandrostenedione glucuronide, 6-Epi-7-isocucurbic acid glucoside, isopropyl beta-D-glucoside, ribostamycin, (3S,7E,9R)-4,7-megastigmadiene-3,9-diol 9-[apiosyl-(1->6)-glucoside], kuwanon B, wyerone, isovitexin 2''-(6'''-feruloylglucoside) 4'-glucoside. Among them, sparteine is associated with alkaloid biosynthesis.
Integrated transcriptome and metabolome analysis
The histogram illustrates KEGG pathway enrichments of DEGs and DEMs. In root_vs_stem involving 126 DEGs and 79 DEMs, 20 metabolic pathways were enriched, with significant enrichment (P<0.01) observed in phenylpropanoid biosynthesis and flavonoid biosynthesis pathways (Fig. 7A). For leaf_vs_root involving 130 DEGs and 84 DEMs, 21 metabolic pathways were enriched, with significant enrichment (P<0.01) in the pathways related to the biosynthesis of isoflavonoids, phenylpropanoids, flavonoids, and betalains (Fig. 7B). Root_vs_seed, with 129 DEGs and 84 DEMs, exhibited enrichment in 20 metabolic pathways, showing significant enrichment (P<0.01) in pathways related to the biosynthesis of phenylpropanoids, flavonoids, and isoflavonoids (Fig. 7C). Leaf_vs_stem, featuring 129 DEGs and 82 DEMs, showed enrichment in 21 metabolic pathways, with significant enrichment (P<0.01) in flavonoid biosynthesis, phenylpropanoid biosynthesis, tryptophan metabolism, isoflavonoid biosynthesis, and alanine, aspartate and glutamate metabolism pathways (Fig. 7D). In leaf_vs_seed, encompassing 132 DEGs and 69 DEMs, 21 metabolic pathways were enriched, with significant enrichment (P<0.01) in isoflavonoid biosynthesis, phenylpropanoid biosynthesis, and flavonoid biosynthesis pathways (Fig. 7E). Seed_vs_stem, with 125 DEGs and 79 DEMs, showed enrichment in 20 metabolic pathways, exhibiting significant enrichment (P<0.01) in flavonoid biosynthesis, phenylpropanoid biosynthesis, tryptophan metabolism, isoflavonoid biosynthesis, and alanine, aspartate and glutamate metabolism pathways (Fig. 7F). The findings of this study emphasize the critical metabolic pathways that are implicated in the biosynthesis of phenylpropanoid, flavonoid, and isoflavonoid in S. tonkinensis.
Co-expression network analysis
Using RNA-seq and content data, we employed weighted gene co-expression network analysis (WGCNA) to examine genes related to the biosynthesis and metabolism of various flavonoids and alkaloids. The dendrogram illustrates the fifteen identified distinct modules (Fig. 8A). These modules, represented by distinct colors, revealed significant associations with the content of alkaloids, flavonoids, matrine, oxymatrine, genistein, and genistin, notably the “magenta,” “tan,” “salmon,” “magenta,” “tan,” and “green-yellow” modules (r>0.7, P<0.05) (Fig. 8B).
Based on eigengene connectivity (kME) values in the co-expression network, co-expression subnetworks were generated using the top 30 node genes from the "magenta," "tan," and "green-yellow" modules. In the “magenta” module, evm.model.8.1855 (no functional annotation information) exhibited the highest kME value, followed by copper amine oxidase (StCAO, evm.model.3.924). Additionally, tyrosine aminotransferase (StTAT, evm.model.2.3509), involved in alkaloid biosynthesis, was located in this network (Fig. 8C). In the “tan” module, squalene monooxygenase (StSQLE, evm.model.5.860) had the highest kME value. Additionally, chalcone isomerase (StCHI, evm.model.1.2104 and evm.model.1.2101), contributing to flavonoid synthesis, occupied a central role in this network (Fig. 8D). In the “green-yellow” module, chlorophyll a-b binding protein (StCAP10A,evm.model.1.2462) exhibited the highest kME value and displayed robust correlations with other node genes. Every node in this network was associated with photosynthesis, suggesting its crucial role in the network (Fig. 8E). These findings indicate that StCAO, StTAT, StCHI, and StCAP10A are involved in regulating alkaloid and flavonoid compound metabolism in different tissues of S. tonkinensis.