Growth Year and Chemotype Synergistically Regulate Coumarin Accumulation and the Associated Transcriptional Profiles in Peucedanum praeruptorum Dunn

Abstract

Peucedanum praeruptorum is increasingly cultivated as wild resources are depleted. However, cultivated plants often contain lower levels of coumarins than wild individuals and may not meet the standards of the Chinese Pharmacopoeia. To clarify whether growth year could influence coumarin accumulation, we analyzed P. praeruptorum populations cultivated for 1–3 years using a newly developed 17-coumarin quantification method and conducted transcriptomics to characterize gene expression across growth years. The results suggest that total coumarins and major pyranocoumarins (notably praeruptorin B) increased steadily with growth years, while furanocoumarins and simple coumarins increased initially then declined. Notably, despite substantial intra-population variation in coumarin content, cultivated plants could be classified into two distinct chemotypes: chemotype A (higher praeruptorin A and praeruptorin E, lower praeruptorin B) and chemotype B (lower praeruptorin A and praeruptorin E, higher praeruptorin B, pteryxin, and qianhucoumarin D than chemotype A). Both chemotypes coexisted across all examined populations, with the proportion of chemotype B increasing with growth years. Transcriptomic profiling revealed that 3-year-old plants showed higher expression of pyranocoumarin biosynthetic genes and lower expression of genes associated with simple coumarin and furanocoumarin biosynthesis compared with 1-year-old plants. Differential expression analysis further identified key candidate genes associated with growth years and chemotypes. Together, these results demonstrate that growth year and chemotype synergistically regulate coumarin accumulation in cultivated P. praeruptorum, providing a two-dimensional framework for improving the quality of cultivated medicinal materials.

1. Introduction

Peucedanum praeruptorum Dunn, a perennial medicinal plant belonging to the Apiaceae family, is one of the most widely used traditional Chinese herbal medicines, with a therapeutic history exceeding 1500 years [1]. The desiccated root of P. praeruptorum has a broad spectrum of pharmacological activities and usages, including the treatment of respiratory diseases [2], cardiovascular protection [3], antioxidant and antitumor effects [4]. The phytochemical profile of P. praeruptorum is highly complex and diverse and comprises bioactive compounds such as coumarins, flavonoids, organic acids, sterols, and volatile oils [5]. Among them, coumarin derivatives are recognized as both the primary bioactive constituents and the major phytochemical components [6]. Coumarins can be systematically categorized into five structural classes: simple coumarins, linear/angular furanocoumarins, and linear/angular pyranocoumarins. Pyranocoumarins represent the most abundant and characteristic compounds in P. praeruptorum [7]. Notably, multiple studies on praeruptorin A [8,9,10] and praeruptorin B [11,12] have demonstrated that they were the key bioactive constituents underlying the pharmacological efficacy of P. praeruptorum. These two compounds are also designated as marker compounds for quality assessment of P. praeruptorum in the Pharmacopoeia of the People’s Republic of China (hereafter termed the Chinese Pharmacopoeia).

In recent years, the demand for P. praeruptorum has been steadily increasing, leading to the rapid depletion of its wild resources, which can no longer meet market needs. As a result, cultivated P. praeruptorum has become the primary source of supply. However, the quality of cultivated P. praeruptorum, as reflected by the contents of praeruptorin A and praeruptorin B, is markedly lower than that of wild populations [13]. Surveys indicated that only about 30% of cultivated P. praeruptorum met the standards outlined in the Chinese Pharmacopoeia [14]. This quality decline not only compromises the clinical efficacy of cultivated medicinal materials but has also become a key bottleneck limiting the development of the P. praeruptorum industry. Therefore, enhancing the contents of praeruptorin A and praeruptorin B in cultivated P. praeruptorum represents a critical scientific challenge that must be addressed to achieve sustainable and high-efficiency development of this medicinal plant.

Currently, it is widely hypothesized that insufficient growth duration of P. praeruptorum is a major factor leading to the inferior quality of cultivated materials. P. praeruptorum is a monocarpic perennial plant. Each plant bolts and flowers only once before dying. Cultivated P. praeruptorum generally exhibits a two-year cycle, with vegetative growth in the first year and bolting/flowering in the second year, which is often accompanied by root lignification and reduced medicinal value [10,15,16]. Consequently, cultivated P. praeruptorum is usually harvested after only one year of growth. In contrast, wild populations generally undergo vegetative growth for two years or more. Previous studies have shown that growth duration can significantly impact the quality of medicinal plants such as Saposhnikovia divaricata [17] and Tripterygium wilfordii [18]. However, reliable methods for determining the age of wild P. praeruptorum are currently lacking. In addition, cultivated plants usually bolt and flower in the second year, so samples with more than two years of vegetative growth are difficult to obtain. As a result, direct evidence linking growth years to the quality of cultivated P. praeruptorum remains limited.

While coumarin biosynthetic pathways have been partially characterized in recent studies, key downstream steps remain unresolved. Phenylalanine ammonia-lyase (PAL), cinnamate 4-hydroxylase (C4H) and 4-Coumarate-CoA ligase (4CL) are common enzyme genes in the phenylpropanoid metabolic pathway, which provides precursors for coumarin synthesis [19]. Cinnamoyl ester 3′ hydroxylase (C3′H), hydroxycinnamoyl-CoA shikimate/quinate hydroxycinnamoyl transferase (HCT/HQT), caffeoyl-CoA O-methyltransferase (CCoAOMT), feruloyl-CoA 6′-hydroxylase (F6′H), and coumarin synthase (COSY) are involved in the synthesis of simple coumarins such as scopoletin [20]. For the biosynthesis of furanocoumarins and pyranocoumarins, key enzymes include p-coumaroyl-CoA 2′-hydroxylase (C2′H) [21], psoralen synthase (PS), bergaptol O-methyltransferase (BMT), xanthotoxiol O-methyltransferase (XMT), angelicin synthase (AS) [15,16,20], prenyltransferases (PpPT1-3), and CYP450 cyclases (PpDC and PpOC) [22]. It has been hypothesized that hydroxylases and acyltransferases may contribute to the formation of complex angular pyranocoumarins (e.g., praeruptorin A and praeruptorin B) through the modification of lomatin-derived intermediates in the pyranocoumarin pathway [23]. However, specific candidate genes have not yet been identified, warranting further investigation.

In this study, based on four consecutive years of field observations, we successfully obtained rare cultivated populations growing for 2 and 3 years. These samples provide an opportunity to investigate whether growth years could affect the accumulation of coumarin compounds and provide insights to elucidate the underlying regulatory mechanisms in cultivated P. praeruptorum. To address these knowledge gaps, this study aimed to: (1) establish a UPLC-based method for the simultaneous quantification of seventeen coumarin compounds in P. praeruptorum, covering simple coumarins, furanocoumarins, and pyranocoumarins; (2) compare and analyze the coumarin content profiles of P. praeruptorum populations cultivated for 1, 2, and 3 years using this validated method; (3) integrate transcriptomic data with coumarin content analysis of samples cultivated for 1 year and 3 years to identify candidate genes associated with coumarin biosynthesis and flowering time regulation; and (4) elucidate the potential molecular mechanisms underlying growth year-dependent variations in coumarin accumulation. By achieving these objectives, this study provides a scientific basis for the high-quality cultivation and molecular breeding of P. praeruptorum, directly addressing the critical needs to improve the quality of cultivated medicinal materials in the industry.

2. Results

2.1. Development and Validation of a UPLC Method for the Quantitative Analysis of Seventeen Coumarins

A quantitative method was developed to quantify seventeen coumarin compounds in P. praeruptorum simultaneously, which contributes to most of the higher content of coumarin compounds in P. praeruptorum [24]. The liquid chromatograms of the reference substance and sample are shown in Figure 1. The structures of seventeen coumarin compounds were shown in Figure S1. The established method for quantitative analysis was validated for linearity, linear range, limit of detection (LOD), limit of quantification (LOQ), precision, repeatability, stability, and recovery rate (Table 1). All the calibration curves in 2023 and 2024 of seventeen target coumarin compounds demonstrated good linearity (R² ≥ 0.9997) within the test ranges. The LODs and LOQs were in the range of 0.00101–0.0289 μg/mL and 0.0018–0.0459 μg/mL, respectively. The RSD values of precision, repeatability and stability of seventeen analytes were not more than 2.870%. The overall recovery ranged from 90.983 to 101.222% with the RSDs less than 2.689%. All these results clearly demonstrated that the developed quantitative method was accurate and reliable for the simultaneous determination of seventeen coumarin compounds.

Figure 1.

The UPLC chromatogram of the method for simultaneous quantification of seventeen coumarin compounds. (A) The UPLC chromatogram of reference substance; (B) The UPLC chromatogram of P. praeruptorum sample. 1: umbelliferone; 2: isofraxidin; 3: marmesin; 4: psoralen; 5: xanthotoxin; 6: bergapten; 7: ostenol; 8: oxypeucedanin; 9: qianhucoumarin D; 10: qianhucoumarin A; 11: imperatorin; 12: decursin; 13: peucedanocoumarin II; 14: pteryxin; 15: praeruptorin A; 16: praeruptorin B; 17: praeruptorin E.

Table 1.

Calibration curves, linear range, LOD, LOQ, precision, repeatability, stability and recovery rate data of seventeen coumarin compounds.

Analytes	Coumarin Type *	Calibration Curves	R2	Linear Range (μg/mL)	LOD (μg/mL)	LOQ (μg/mL)	Precision (RSD/%, n = 6)	Repeatability (RSD/%, n = 6)	Stability (0–24 h, RSD/%)	Recovery Rate (%, n = 6)	Recovery Rate (RSD/%, n = 6)
Umbelliferone	SC	y = 26,153x − 158.34	0.9998	0.0123–6.32	0.00515	0.00932	0.992	1.605	2.245	91.212	1.799
Isofraxidin	SC	y = 10,184x − 69.974	0.9998	0.030–7.68	0.00700	0.0248	0.892	1.509	2.799	93.859	1.966
Marmesin	Linear FC	y = 15,295x − 343.66	0.9998	0.0273–28.0	0.00467	0.0153	0.693	0.825	2.418	93.712	1.324
Psoralen	Linear FC	y = 10,078x − 252.72	0.9997	0.0244–18.72	0.00825	0.0244	0.792	1.375	2.626	90.983	1.079
Xanthotoxin	Linear FC	y = 9110.1x − 401.33	0.9999	0.0593–45.54	0.00825	0.0267	0.887	0.689	2.078	94.078	2.143
Bergapten	Linear FC	y = 9943x − 312.57	0.9999	0.0385–29.55	0.0125	0.0302	0.783	0.708	2.003	100.381	0.992
Ostenol	SC	y = 15,942x − 531.15	0.9999	0.0176–13.5	0.00848	0.0176	1.012	0.902	1.875	97.300	2.689
Oxypeucedanin	Linear FC	y = 10,662x + 129.79	1.0000	0.0336–25.785	0.0127	0.0336	0.893	0.923	2.870	98.082	1.261
Qianhucoumarin D	Angular PC	y = 13,105x + 110.64	1.0000	0.0352–144	0.00954	0.0253	0.842	0.968	1.938	100.716	0.885
Qianhucoumarin A	Angular PC	y = 10,191x − 123.06	0.9999	0.0525–13.44	0.0131	0.0263	0.959	1.602	1.857	98.296	1.955
Imperatorin	Linear FC	y = 7293.6x − 27.278	1.0000	0.0430–44.0	0.0211	0.0430	0.943	1.646	2.723	99.002	2.563
Decursin	Linear PC	y = 15,564x − 981.08	0.9999	0.0167–68.32	0.00313	0.00834	1.103	2.602	1.473	97.319	1.494
Peucedanocoumarin II	Angular PC	y = 4506.9x − 2820.8	0.9998	0.0644–660	0.0134	0.0292	0.792	1.001	1.766	96.561	1.285
Pteryxin	Angular PC	y = 9830.5x + 336.09	1.0000	0.0355–727.2	0.00812	0.0284	0.664	1.428	1.601	97.304	1.376
Praeruptorin A	Angular PC	y = 12,638x − 8687.2	0.9997	0.0685–701.4	0.00101	0.00180	0.673	1.423	1.707	97.355	1.367
Praeruptorin B	Angular PC	y = 7412.1x − 5362.7	0.9999	0.0459–940.68	0.0289	0.0459	0.683	1.091	1.715	100.519	0.851
Praeruptorin E	Angular PC	y = 7780.4x − 8023.9	0.9997	0.0683–465.96	0.0218	0.0459	0.695	1.469	1.680	101.222	0.715

* Coumarin type: simple coumarin (SC); furanocoumarins (FC); pyranocoumarins (PC).

2.2. Analysis of Coumarin Content Variations Across Populations of Different Growth Years

The developed method was subsequently applied to simultaneously analyze 357 individual P. praeruptorum plants from populations of three different cultivation years (1 year: Pp1y, 2 years: Pp2y, and 3 years: Pp3y). To ensure the reliability, the plants were growing at six experimental plots from two provinces: AnHui (AH) and SiChuan (SC). First, samples from replicate plots with identical growth years were treated as biological replicates to compare coumarin content differences among Pp1y, Pp2y, and Pp3y populations. The mean content ranges were 0.004–7.439 mg/g (AH) and 0.004–8.903 mg/g (SC), with the top seven compounds (praeruptorin A > praeruptorin B > praeruptorin E > pteryxin > qianhucoumarin D > peucedanocoumarin II > decursin) all being pyranocoumarins (Table S2, Figure 2A). The six most abundant compounds each exceeded 0.1 mg/g, confirming pyranocoumarins as both the dominant coumarin class and primary bioactive components in P. praeruptorum [25]. When analyzed by coumarin subtype (Figure 2B), both total coumarins and total pyranocoumarins showed progressive increases from Pp1y to Pp3y, with highly significant differences between groups (p < 0.01 or p < 0.001). This trend was consistent across both experimental sites. In contrast, total furanocoumarins and total simple coumarins exhibited an initial increase followed by a decrease, with AH samples showing particularly significant variation (p < 0.001).

Figure 2.

Quantitative analysis of coumarin compounds of cultivated P. praeruptorum grown in AH or SC province after 1–3 years (Pp1y, Pp2y, and Pp3y) (mg/g). (A) Vertical stack bar for the content of seventeen coumarin compounds in Pp1y, Pp2y, and Pp3y populations from AH or SC experimental sites; (B) Differences in the total content of seventeen coumarin compounds, eight pyranocoumarins, six furanocoumarins and three simple coumarins; (C) Differences in the content of each coumarin compound, (a): umbelliferone, (b): isofraxidin, (c): ostenol, (d): marmesin, (e): psoralen, (f): xanthotoxin, (g): bergapten, (h): oxypeucedanin; (i): qianhucoumarin D, (j): qianhucoumarin A, (k): imperatorin, (l): decursin, (m): peucedanocoumarin II, (n): pteryxin, (o): praeruptorin A, (p): praeruptorin B, (q): praeruptorin E. Statistical significance was denoted as * p < 0.05, ** p < 0.01, *** p < 0.001, and ns = not significant.

Analysis of the seventeen coumarin compounds across different growth years is presented in Figure 2C and Table S2. Praeruptorin A and praeruptorin B serve as both primary bioactive components and key quality control markers in commercial products [25]. Both compounds showed progressive increases from Pp1y to Pp3y; praeruptorin A exhibited no statistically significant changes, whereas praeruptorin B demonstrated significant accumulation (Figure 2C(p,q)). Notably, praeruptorin B content of Pp2y samples showed 66.53% (AH) and 96.64% (SC) increases over Pp1y; Pp3y samples showed 204.02% (AH) and 279.019% (SC) increases over Pp1y, with consistent trends between the two experimental sites (Figure 2C(q), Table S2). Among the remaining fifteen coumarin compounds, in Pp2y relative to Pp1y, thirteen compounds (pteryxin, qianhucoumarin D, peucedanocoumarin II, decursin, imperatorin, oxypeucedanin, umbelliferone, bergapten, isofraxidin, ostenol, qianhucoumarin A, marmesin, and psoralen) increased (Figure 2C(a–e) or Figure 2C(g–n)), with only praeruptorin E (Figure 2C(o)) and xanthotoxin (Figure 2C(f)) showing declines. In Pp3y relative to Pp1y, the content of praeruptorin E, qianhucoumarin D, peucedanocoumarin II, and decursin exhibited significant increases (p < 0.01), while pteryxin and qianhucoumarin A remained stable. However, six furanocoumarins (imperatorin, oxypeucedanin, bergapten, marmesin, xanthotoxin and psoralen) and three simple coumarins (umbelliferone, isofraxidin and ostenol) showed either significant decreases or non-significant changes (except for SC’s marmesin, psoralen, xanthotoxin, and bergapten, p < 0.05). The overall trends were consistent between sites, with minor statistical variations likely attributable to germplasm and environmental factors. In summary, compared to Pp1y, the seven most abundant pyranocoumarins demonstrated growth year-dependent accumulation, with praeruptorin B showing the most pronounced increase. Conversely, the six lower-abundance furanocoumarins and three simple coumarins generally followed an initial rise followed by a decline. This indicated that an insufficient growth year is one reason for the low content of coumarin compounds in cultivated P. praeruptorum. Therefore, it is recommended to harvest cultivated P. praeruptorum after at least two years of growth.

Additional analysis of Figure 2C and Table S1 revealed substantial variability in coumarin content among individual plants across growth years. The coefficient of variation (CV) for all seventeen coumarin compounds ranged from 25.52% to 310.29% in the AH experimental site and 29.94% to 217.66% in SC, demonstrating strong inter-individual variation within populations at different growth years.

2.3. Characteristics of Coumarin Contents in Individual Plants Within Pp1y, Pp2y and Pp3y Populations

2.3.1. Cultivated P. praeruptorum Exhibited Significant Intra-Population Variation in Coumarin Contents

Section 2.2 revealed significant differences in coumarin compounds among individual plants from cultivated populations of different growth years. To further determine whether these variations were influenced by different experimental plots or inherent genetic factors, we analyzed the coumarin content of individual plants from each plot. The results (Figure 3, Table S3) showed that even within the same plot, where growth conditions and cultivation practices were consistent, there were significant differences in coumarin content among individual plants. The coefficient of variation (CV) for the seventeen coumarin compounds ranged from 19.50% to 569.69%. For the six major coumarins in P. praeruptorum roots—praeruptorin A, praeruptorin B, praeruptorin E, pteryxin, qianhucoumarin D, and peucedanocoumarin II, the CV ranges were 34.00–62.92%, 40.24–127.35%, 63.10–39.00%, 53.72–249.70%, 64.95–205.35%, and 28.04–154.64%, respectively. Data from all six experimental plots demonstrated significant intraspecific heterogeneity in coumarin content among individuals under homogeneous conditions, a pattern observed across Pp1y, Pp2y and Pp3y populations. This variation among different strains within the same microenvironment is likely driven primarily by genetic factors, indicating genetic diversity within cultivated P. praeruptorum populations, which provides a foundation for elite cultivar selection [26].

Figure 3.

Vertical stack bar for the content of seventeen coumarin compounds in individual samples from six plots (AH1, AH2, AH3, AH4, SC1and SC2) of two experimental sites (AH and SC) after 1–3 years’ cultivation.

Interestingly, the CV ranges for the total content of all seventeen coumarins and the total content of eight pyranocoumarins across the six plots were much lower (13.98–29.32% and 13.89–29.34%, respectively) compared to the CVs of individual coumarins within the same plot. Analysis of individual coumarin profiles (Figure 3) revealed correlations among pyranocoumarin levels: praeruptorin A showed a positive correlation with praeruptorin E but negative correlations with praeruptorin B, pteryxin, and qianhucoumarin D.

By analyzing 357 individual samples from six plots across two experimental sites, we further demonstrated that the total coumarin and total pyranocoumarin content in P. praeruptorum exhibit a sustained increasing trend with prolonged growth years (Table S3). Notably, the content of praeruptorin B, a key bioactive compound, also consistently increased over time. This suggests that insufficient growth duration is one reason why cultivated P. praeruptorum contains lower praeruptorin B levels than wild P. praeruptorum.

2.3.2. Cluster Analysis of Individual Plants Within Pp1y, Pp2y and Pp3y Populations Two Chemotypes Identified in All Pp1y, Pp2y, and Pp3y Populations by Clustering of Coumarin Content

Based on the content of coumarin compounds, cluster analysis was performed on 357 individual samples of different growth years (Figure 4A), revealing that the samples were divided into two chemotypes. One chemotype exhibited high levels of praeruptorin A and praeruptorin E, with relatively lower praeruptorin B, while the contents of pteryxin and qianhucoumarin D were nearly 0 mg/g, designated as “chemotype A” in this study. The other chemotype showed higher levels of praeruptorin B, pteryxin, and qianhucoumarin D, while the contents of praeruptorin A and praeruptorin E were lower than those in “chemotype A”, designated as “chemotype B”. In both the AH and SC experimental sites, populations of different growth years (Pp1y, Pp2y, and Pp3y) contained both chemotype A and chemotype B, with varying proportions across growth years. Specifically: in the Pp1y-AH, Pp2y-AH, and Pp3y-AH populations, the proportions of chemotype B individuals were 24.24% (16/66), 41.18% (42/102), and 42.86% (3/7), respectively; in the Pp1y-SC, Pp2y-SC, and Pp3y-SC populations, the proportions of chemotype B individuals were 12.77% (6/47), 31.25% (40/128), and 42.86% (3/7), respectively (Figure 4A, Supplementary Table S2). Overall, the proportion of chemotype B individuals in the populations increased with growth years: Pp1y (19.47%) < Pp2y (35.65%) < Pp3y (42.86%) (Table S4). This suggests that the proportion of individuals with chemotype B gradually rises as the growth years extend, which may be one reason why older populations exhibit higher praeruptorin B content.

Figure 4.

Cluster analysis of individual plants within Pp1y, Pp2y and Pp3y populations. (A) Clustered bar chart of individual plants within Pp1y, Pp2y and Pp3y populations from AH and SC experimental sites; (B) Vertical stack bar for the contents of seventeen coumarin compounds of chemotype A and chemotype B samples in Pp1y, Pp2y, and Pp3y populations from AH and SC experimental sites.

According to the cluster analysis, populations of different growth years were classified into two chemotypes: chemotype A and chemotype B. A comparison of coumarin compound content in Pp1y, Pp2y, and Pp3y populations between chemotype A and chemotype B samples (Figure 4B) revealed the following trends with increasing growth years: (i) in chemotype A samples, the levels of praeruptorin A, praeruptorin B, praeruptorin E, and total coumarins showed a gradual increasing trend; (ii) in chemotype B samples, the praeruptorin A, praeruptorin B and total coumarins, also exhibited a steady increase. However, praeruptorin E and peucedanocoumarin II first decreased and then increased, while pteryxin initially rose before declining.

These results indicate that, regardless of chemotype, the total coumarin content and the levels of key marker compounds (praeruptorin A and praeruptorin B) in P. praeruptorum consistently increased with growth year. This suggests that the coumarin content in P. praeruptorum is influenced by both the proportion of chemotypes within the population and the growth year.

2.4. Profiling of Coumarin Compounds in Two Chemotypes of P. praeruptorum Cultivated for 1 and 3 Years

We classified the P. praeruptorum samples cultivated for 1 year (designated as 1y) into two groups based on chemotype: chemotype A (1yA) and chemotype B (1yB); similarly, categorized P. praeruptorum samples cultivated for 3 years (3y) into chemotype A (3yA) and chemotype B (3yB). Among these groups, the 3yA group contained four biological replicates, whereas the other three groups (1yA, 1yB, and 3yB) each had three biological replicates.

Analysis of the seventeen coumarin compounds in the P. praeruptorum samples cultivated for 1 and 3 years (1yA vs. 3yA and 1yB vs. 3yB) revealed that the contents of three simple coumarins (umbelliferone, isofraxidin, and ostenol) and six linear furanocoumarins (marmesin, psoralen, xanthotoxin, bergapten, oxypeucedanin, and imperatorin) in the samples cultivated for 3 years were lower than those in the samples cultivated for 1 year, and among them, the contents of umbelliferone, ostenol, marmesin, xanthotoxin, and oxypeucedanin decreased significantly (p < 0.05) (Figure 5A). The variation in the content of simple coumarins and linear furanocoumarins with P. praeruptorum samples cultivated for 1 and 3 years was consistent with the trends observed in the Pp1y and Pp3y samples mentioned in Section 2.2. In the comparisons between the chemotype A and chemotype B (1yA vs. 1yB and 3yA vs. 3yB), significant differences were found only in four angular pyranocoumarins: praeruptorin A, praeruptorin B, pteryxin and qianhucoumarin D. The praeruptorin A content in chemotype A samples was significantly greater than that in chemotype B samples (p < 0.01), whereas the content of praeruptorin B (p < 0.001), pteryxin (p < 0.001) and qianhucoumarin D (p < 0.05) in chemotype A samples were significantly lower than those in chemotype B samples. However, no significant differences were found in the contents of the other thirteen coumarin compounds between chemotypes A and B.

Figure 5.

Profiling of coumarin compounds in two chemotypes of P. praeruptorum cultivated for 1 and 3 years. 1yA/1yB: chemotype A/chemotype B of P. praeruptorum samples cultivated for 1 year, 3yA/3yB: chemotype A/chemotype B of P. praeruptorum samples cultivated for 3 years. (A) The contents of seventeen coumarin compounds. Different letters indicate significant differences among P. praeruptorum samples cultivated for 1 year and 3 years; (B) Pearson’s correlation analysis of the contents of seventeen coumarin compounds in P. praeruptorum. The orange and blue colors indicate positive and negative correlations, respectively, and the number refers to the correlation coefficient (r), which ranges from –1 to +1; (C) PCA of the detected coumarin compounds in P. praeruptorum roots. The axes (PC1 and PC2) are centered at the origin, which represents the mean of the principal component scores. Percentages in parentheses indicate the variance explained by each principal component.

Analysis of the correlations among the contents of the seventeen coumarin compounds in the 1yA, 1yB, 3yA, and 3yB groups revealed that praeruptorin A, praeruptorin E and decursin were negatively correlated with the content of praeruptorin B, pteryxin and qianhucoumarin D. The praeruptorin B content was strongly negatively correlated with the praeruptorin A content (r = −0.81) and strongly positively correlated with the pteryxin content (r = 0.94). Additionally, six linear furanocoumarins (marmesin, psoralen, xanthotoxin, bergapten, oxypeucedanin, and imperatorin) generally presented positive correlations with each other (Figure 5B). PCA results of the seventeen coumarin compounds revealed that the samples could be categorized into four groups (Figure 5C), indicating differential metabolic patterns between plants of different growth years (1 year vs. 3 years) and chemotypes (chemotypes A vs. B).

2.5. Transcriptomic Analysis of the Two Chemotypes of P. praeruptorum Cultivated for 1 and 3 Years

2.5.1. Differential Gene Expression Analysis

To investigate the effects of growth year and chemotype on the effect of gene expression on coumarin accumulation in P. praeruptorum roots, RNA-seq and comparative transcriptomics analyses were conducted. The average clean data yielded over 5.85 Gb per sample, with a Q30 of 93.86%. The FPKM values were calculated to normalize the expression for each sample. PCA results demonstrated clustering within groups and clear dispersion between groups, with 3yA and 3yB positioned in the left half of the PCA plot, while 1yA and 1yB were located in the right half (Figure S2). The greatest number of different expressed genes (DEGs) (6176) was found between 1yA and 3yA, while the lowest number of DEGs (1183) was found between 1yA and 1yB. The number of DEGs both in 1yA vs. 3yA and 1yB vs. 3yB was 2935. However, the number of DEGs in the 1yA vs. 1yB and the 3yA vs. 3yB comparisons was only 124 (Figure 6A and Figure S3). These findings indicated that the differences in transcription between samples from different growth years were more pronounced, whereas the differences between chemotypes A and B were relatively minor.

Figure 6.

Differential gene expression analysis of the two chemotypes of P. praeruptorum cultivated for 1 and 3 years (1yA, 1yB, 3yA, and 3yB). (A) Venn diagrams showing the number of DEGs; (B–E) KEGG enrichment analysis of the DEGs in 1yA vs. 3yA, 1yB vs. 3yB, 1yA vs. 1yB, and 3yA vs. 3yB.

The results of the KEGG analysis revealed that these DEGs were enriched in pathways related to various metabolic pathways, plant hormone signal transduction pathways, and plant-pathogen interactions. Additionally, across all pairwise comparison groups, the KEGG enrichment analysis revealed that the greatest number of DEGs related to metabolic pathways were associated with starch and sucrose metabolism, followed by phenylpropanoid biosynthesis (Figure S4), indicating significant differences in the synthesis and accumulation of primary metabolites (e.g., starch and sucrose) and secondary metabolites (e.g., coumarins) between the roots of P. praeruptorum plants of different growth years and chemotypes. In addition, among 1yA vs. 3yA, 1yB vs. 3yB, 1yA vs. 1yB and 3yA vs. 3yB, the enrichment dot bubble plot showed that DEGs were more prominently enriched in the phenylpropanoid biosynthesis pathway (Figure 6B–E).

2.5.2. Candidate Genes Involved in Coumarin Biosynthesis

Across the four sample groups (1yA, 1yB, 3yA, and 3yB), we identified 30 differentially expressed genes (DEGs) encoding enzymes putatively involved in coumarin biosynthesis (Table S5), including 25 DEGs mapped to the confirmed biosynthetic steps (solid arrows in Figure 7A). Expression heatmaps across 13 samples showed good consistency among biological replicates (Figure 7A and Figure S5). Comparisons between cultivation years yielded 27 coumarin-pathway DEGs (1yA vs. 3yA and 1yB vs. 3yB), whereas chemotype comparisons yielded 10 DEGs (1yA vs. 1yB and 3yA vs. 3yB) (Figure S5). Seven genes (PpC2′H1, PpC2′H2, PpF6′H, PpHCT1, PpPS1, PpAT2, and PpAT4) were shared across both year- and chemotype-based comparisons.

Figure 7.

Metabolic pathway analysis of candidate genes related to coumarin biosynthesis in P. praeruptorum. (A) Pathway diagram of DEGs in the coumarin biosynthetic pathway in two chemotypes of P. praeruptorum across four groups (1yA, 1yB, 3yA, and 3yB). Orange indicates higher transcript expression levels, whereas blue indicates lower expression. PpAT1–PpAT5 are candidate acyltransferase genes; (B) Spearman correlation analysis between genes in the coumarin biosynthetic pathway and the content of coumarin compounds. Statistical significance was denoted as * p < 0.05, ** p < 0.01, *** p < 0.001. PAL, phenylalanine ammonia-lyase; C4H, cinnamate 4-hydroxylase; 4CL, 4-Coumarate-CoA ligase; C3′H, cinnamoyl ester 3′ hydroxylase; HCT/HQT, hydroxycinnamoyl-CoA shikimate/quinate hy-droxycinnamoyl transferase; CCoAOMT, caffeoyl-CoA O-methyltransferase; F6′H, feruloyl-CoA 6′-hydroxylase; COSY, coumarin synthase; C2′H, p-coumaroyl-CoA 2′-hydroxylase; PS, psoralen synthase; BMT, bergaptol O-methyltransferase; XMT, xanthotoxiol O-methyltransferase; AS, angelicin synthase; PT, prenyltransferases; DC, demelthyisuberosin cyclase; OC, ostenol cyclase; AT, acetyltransferase. The corresponding EC numbers for these enzymes are provided in Table S5.

To identify genes associated with angular pyranocoumarin accumulation (e.g., praeruptorin A and praeruptorin B), we compared chemotypes A and B, which differ markedly in angular pyranocoumarin content. Given the proposed involvement of acyltransferases in pyranocoumarin biosynthesis [23], we identified five BAHD acyltransferase DEGs (PpAT1–PpAT5). Spearman correlation analysis (r > 0.50, p < 0.05) between the 30 DEGs and 17 coumarin metabolites showed that each DEG was significantly correlated with at least one metabolite (Figure 7B). Notably, PpAT1–PpAT4 were upregulated in chemotype B and were positively correlated with praeruptorin B, qianhucoumarin D, and pteryxin, but negatively correlated with praeruptorin A, praeruptorin E, and decursin. In contrast, PpAT5 was upregulated in chemotype A and positively correlated with praeruptorin A and decursin. BAHD acyltransferases catalyze the acylation of plant secondary metabolites [27,28,29]. These correlations support the candidacy of PpAT1–PpAT5 as putative acyltransferase genes associated with angular pyranocoumarin variation, while functional validation is required to establish their biochemical roles.

Regarding growth year effects, upstream genes involved in p-coumaric acid formation (three PpPALs, two PpC4Hs, and two Pp4CLs) were more highly expressed in 1-year plants than in 3-year plants. Umbelliferone, a key precursor of both furanocoumarins and pyranocoumarins, is synthesized from p-coumaric acid under the regulation of C2′H, which may compete for substrates with scopoletin-branch enzymes such as F6′H [30]. Consistent with metabolite profiling (Figure 2 and Figure 6A), 3-year plants showed lower expression of genes involved in downstream steps of simple coumarin and linear furanocoumarin biosynthesis (e.g., PpPS, PpBMT, PpXMT, PpC3′H, PpHCT, PpCoAOMT, PpF6′H, and PpCOSY), but higher expression of pyranocoumarin-related genes (e.g., PpPT, PpDC, and PpAT) (Figure 7A). Reduced competition for shared intermediates may therefore favor pyranocoumarin biosynthesis and accumulation in 3-year plants. Other studies have shown that linear furanocoumarins exhibit high efficacy in antitumor therapies, photodynamic treatments, and plant defense mechanisms [31,32], whereas pyranocoumarins show significant pharmacological effects, including anti-inflammatory, antimicrobial, anticancer, and neuroprotective effects [33,34,35,36,37]. Accordingly, prolonged cultivation may enhance the therapeutic potential of P. praeruptorum via the progressive enrichment of bioactive coumarins.

2.5.3. Analysis of Candidate Genes Involved in Flowering Regulation

Analysis of gene expression levels in P. praeruptorum samples cultivated for 1 and 3 years (1yA, 1yB, 3yA, and 3yB) identified 126 DEGs potentially involved in flowering regulation (Figure 8). This indicates that a large number of flowering-related genes are differentially expressed in the early bolting stages of P. praeruptorum cultivated for 1 and 3 years. Among these DEGs, some are regulatory genes that delay flowering, while others promote flowering. For example, CIRCADIAN CLOCK ASSOCIATED 1 (CCA1) [38], LHY-CCA1-LIKE5 (LCL5) [39], SAP30 FUNCTION-RELATED 2 (AFR2) [40], CYCLING DOF FACTOR 2 (CDF2) [41], and B-BOX DOMAIN PROTEIN 30 (BBX30) [42] negatively regulate flowering time. Their homologous genes in P. praeruptorum (Ppr01G024560, Ppr02G023620, Ppr01G012170, Ppr02G007880, and Ppr04G000850) showed significantly lower expression in samples cultivated for 1 year than for 3 years. In contrast, CONSTANS-LIKE 5 (COL5) [43], COLD-REGULATED GENE 27 (COR27) [44], and GA REQUIRING 2 (GA2) [45] positively regulate flowering time. Their homologous genes in P. praeruptorum (Ppr02G034270, Ppr04G006140, and Ppr10G032960) exhibited significantly higher expression in samples cultivated for 1 year than for 3 years. Additionally, genes associated with the transition between annual and perennial life history strategies were identified, such as the homolog of MADS AFFECTING FLOWERING (MAF) [46]—Ppr01G024240, and the homolog of PERPETUAL FLOWERING 1 (PEP1) [47]—Ppr08G011350, both of which showed significantly lower expression in samples cultivated for 1 year than 3 years. These candidate genes may provide valuable insights for molecular breeding aimed at extending the growth duration of P. praeruptorum.

Figure 8.

Heatmap of candidate genes related to flowering regulation in P. praeruptorum cultivated for 1 and 3 years. 1yA/1yB: chemotype A/chemotype B of P. praeruptorum samples cultivated for 1 year, 3yA/3yB: chemotype A/chemotype B of P. praeruptorum samples cultivated for 3 years.

3. Discussion

The content of medicinal plant metabolites is closely related to growth years, as demonstrated in Astragali radix [48,49], Bupleurum scorzonerifolium [50], Panax ginseng [51], Codonopsis radix [52], and Dendrobium huoshanense [53]. Currently, there is limited research on the mechanisms by which growth years affect secondary metabolites. Temporal gene expression plays a regulatory role in the accumulation of plant secondary metabolites [54], including coumarins [55]. This study analyzed the trends in pyranocoumarins, furanocoumarins, and simple coumarins across different growth years. In addition, by integrating transcriptome data with coumarin content analysis, we found that growth years influence the accumulation of different types of coumarins by regulating the gene expression in the coumarin biosynthesis pathway, revealing that temporal shifts in gene expression contribute to the variation in coumarin levels between P. praeruptorum with different growth years. Transcriptome analysis also revealed that, compared to P. praeruptorum samples cultivated for 1 year, samples cultivated for 3 years exhibited enhanced pathogen interactions and plant hormone signal transduction. This suggests that interactions with microbial communities and the activation of plant defense mechanisms by hormones such as salicylic acid (SA) [56] may redirect secondary metabolic resources toward defense-related compounds like coumarins [57,58]. This study enriches research on the influence of growth years on plant secondary metabolite content, particularly pyranocoumarins. It also provides a molecular-level explanation for understanding the “growth years–quality” association in medicinal plants.

Notably, this study found that P. praeruptorum exhibited significant inter-individual variation in coumarin content —even when grown in the same habitat, under identical cultivation management, and harvested at the same time. This phenomenon has also been observed in other studies on P. praeruptorum [59] and Stephania tetrandra [60]. We identified two distinct chemotypes among individuals with marked differences in coumarin content. These two chemotypes were present across all six experimental plots and in populations of different growth years, suggesting that genetic factors primarily drive the chemotypic variation. Transcriptome analysis further confirmed that the differences in coumarin content between the two chemotypes are genetically regulated, indicating that cultivated P. praeruptorum populations possess germplasm diversity, which provides a valuable resource for the breeding of high-value varieties. More importantly, the proportion of individuals belonging to chemotype B (with a higher proportion of praeruptorin B content) significantly increased with growth years. This finding not only explains why older populations exhibit higher overall coumarin content but also reveals the synergistic regulatory effect of growth years and chemotype on coumarin accumulation.

Furthermore, based on the chemical profiles of chemotypes A and chemotypes B, a clear negative relationship was identified between the praeruptorin A/praeruptorin E branch and the praeruptorin B/pteryxin/qianhucoumarin D branch, whereas strong positive correlations existed within each group. Because the chemical structures of components in each group are comparatively similar, this pattern suggests a metabolic bifurcation with a common precursor in the biosynthesis of angular pyranocoumarins. And the two branches might be regulated by branch-specific enzymes (e.g., acyltransferases or hydroxylases). Thus, the content of components in one branch could be influenced at the same time. Substrate Competition between the two branches may explain their negative correlation.

Based on the research findings, improving the quality of cultivated P. praeruptorum requires a “dual-dimensional strategy”: on one hand, extending the cultivation period to two years or more to leverage the cumulative effect of growth years on pyranocoumarin accumulation; on the other hand, directional breeding of specific chemotype germplasm resources to amplify the advantages of core bioactive components through genetic improvement. This strategy, which combines genetic screening with cultivation management, holds greater value for industrial applications. For P. praeruptorum, a monocarpic perennial plant, extending the cultivation period can be achieved through two pathways: first, multi-generational selective breeding to develop stable germplasm with delayed bolting using seeds from 3-year-old plants. This aligns with the pattern observed in other Apiaceae plants such as carrots [61] and Angelica sinensis [62], where “seeds from triennial maternal plants tend to produce offspring with delayed bolting and flowering.” Second, molecular breeding based on the 126 flowering-related candidate genes identified in this study, using gene editing technologies [63,64] to regulate bolting time, thereby accelerating the breeding process.

This study also has certain limitations: The five BAHD acyltransferases (PpAT1–PpAT5) were nominated as high-confidence candidates from transcriptomic–metabolomic associations, but direct functionally validated in vitro/in vivo is currently lacking; thus, their involvement in angular pyranocoumarin acylation remains hypothetical and requires biochemical and genetic validation. Moreover, the causal genetic variants underlying chemotypic divergence—and their implications for hybrid breeding—have yet to be resolved. Future studies should (i) establish enzymatic activities and substrate specificities of PpAT1–PpAT5, (ii) dissect the genetic architecture of chemotype differentiation, and (iii) evaluate the feasibility of combining desirable traits from both chemotypes via hybrid breeding. Together, these advances would enable more precise molecular-assisted improvement of cultivated P. praeruptorum.

4. Materials and Methods

4.1. Plant Materials, Chemicals and Reagents

4.1.1. Acquisition of Cultivated P. praeruptorum Materials with Distinct Growth Years

To verify whether P. praeruptorum could be cultivated for two years or longer, continuous observations were conducted on a large cultivated population from spring 2021 to spring 2024. The process of obtaining samples with confirmed growth years was as follows:

• (i)P. praeruptorum population cultivated for 1 year (Pp1y): In spring 2021, two cultivation sites—one in Hule Town, Ningguo City, Anhui Province (hereafter “AH”) and another in Qingchuan County, Guangyuan City, Sichuan Province (hereafter “SC”)—were established, each with a 1400 m² observation zone for monitoring growth years. Seeds from cultivated P. praeruptorum harvested at these sites were sown. The AH site included four replicate plots (AH1–AH4), while the SC site had two (SC1–SC2). Plants were managed using standard cultivation practices. In December 2021, 1-year-old plants were sampled from all six plots using an “S”-shaped sampling method.
• (ii)P. praeruptorum population cultivated for 2 and 3 years (Pp2y and Pp3y): After sampling one-year-old non-bolting plants, the remaining plants continued to grow under routine management (no additional fertilization), with bolting individuals removed. Despite over 98% of plants bolting between April and November of the second year, a sufficient cultivation area allowed both sites to yield non-bolting 2-year-old plants, which were harvested in late December 2022. Subsequent monitoring revealed an unexpected outcome: seven non-bolting 3-year-old plants were obtained from each site (AH and SC) and harvested as Pp3y samples in late December 2023.

The Pp1y, Pp2y, and Pp3y population samples were authenticated as P. praeruptorum by Professor Jianhe Wei. After gently rinsing root surfaces with clean water, the samples were dried in a constant-temperature oven at 40 °C for subsequent use. The number of individual plants analyzed from each experimental plot for Pp1y, Pp2y, and Pp3y populations, along with plot location information, is provided in Table S1. Due to the limited availability of 2- and 3-year-old plants within the plots, the number of samples analyzed per plot ranged from 5 to 32. A total of 375 individual plant samples from Pp1y, Pp2y, and Pp3y populations were ground into 50-mesh powders and stored under dry conditions at 4 °C prior to coumarin content analysis.

4.1.2. The P. praeruptorum Materials with Two Chemotypes of 1- and 3-Year-Old for Transcriptome Analysis

To investigate the molecular mechanisms underlying the effects of growth years and chemotypes on coumarin accumulation and flowering time in P. praeruptorum, while minimizing interference from non-target variables such as geographical environment, this study collected root samples from 1- and 3-year-old plants grown in the same standardized cultivation plot in late March 2024. The seeds of the plant materials originated from the AH experimental area. These samples were used for coumarin content analysis and transcriptomic profiling. Based on chemotype, the samples were divided into four comparative groups: 1-year-old chemotype A (1yA), 1-year-old chemotype B (1yB), 3-year-old chemotype A (3yA), and 3-year-old chemotype B (3yB). The 3yA group consisted of four biological replicates, while each of the other three groups contained three biological replicates. The variation in replicate numbers across groups was due to the limited availability of eligible plants with specific combinations of growth years and chemotype within the plot. Subsequent differential expression analysis of transcriptomic data employed statistical models suitable for unbalanced experimental designs (e.g., DESeq2) to ensure the reliability of the results.

In the field, no agronomic interventions other than routine weeding were performed prior to harvest. At the time of sampling, the P. praeruptorum plants had developed bolting stems approximately 10 cm in height. After collection, the roots were washed with purified water and dried with absorbent paper. The fresh root samples of P. praeruptorum were cut off and divided into two parts. One part was quickly frozen in liquid nitrogen and stored in a refrigerator (–80 °C) for transcriptomic analysis, and the other part was dried at 40 °C then ground into a powder (50 mesh), and stored at 4 °C for the content determination of seventeen coumarin compounds.

4.1.3. Chemicals and Reagents

The chemical standards of umbelliferone (B21854), isofraxidin (B21547), oxypeucedanin (B21471), praeruptorin A (B20035), praeruptorin B (B20037), and praeruptorin E (B20036) were purchased from YuanYe (Shanghai, China); ostenol (PCS1569), marmesin (PCS1166), psoralen (PCS0018), bergapten (PCS0397), xanthotoxin (PCS0023), imperatorin (PCS0073), and decursin (PCS1384) were purchased from HerbSubstance (Chengdu, China); pteryxin (PS0471) and qianhucoumarin D (PS3115) were purchased from BioPush (Chengdu, China). All 15 chemical standards listed above have a purity of >98%. Qianhucoumarin A (>95%, E18746) was purchased from OKA (Beijing, China), and peucedanocoumarin II (>95%, CFN92519) was purchased from ChemFaces (Wuhan, China). Pure water was distilled water provided by Watson’s Company (Hong Kong, China), and all other reagents were analytical grade.

4.2. Quantitative Analysis of Seventeen Coumarin Compounds in P. praeruptorum via UPLC

To systematically elucidate the differences in coumarin content among cultivated P. praeruptorum samples of varying growth years, and to facilitate analysis of accumulation patterns for different coumarin types along with their potential regulatory genes, we selected seventeen predominant compounds in P. praeruptorum roots as indicators and established a quantitative analytical method based on ultra-performance liquid chromatography (UPLC). The indicators include eight pyranocoumarins (qianhucoumarin D, qianhucoumarin A, peucedanocoumarin II, pteryxin, praeruptorin A, praeruptorin B, praeruptorin E and decursin), six furanocoumarins (marmesin, psoralen, xanthotoxin, bergapten, oxypeucedanin and imperatorin) and three simple coumarins (umbelliferone, isofraxidin and ostenol). Standard compounds as reference can be found in Section 4.1.3.

The quantitative method was validated for specificity, linearity, linear range, limit of detection (LOD), limit of quantification (LOQ), precision, repeatability, stability and recovery rate, which followed the method described in references [15,25]. As to sample measurement, the samples were accurately weighed to 0.2 g of dried powder, ultrasonically extracted (33 kHz, 250 W) with 25 mL of methanol at 30 °C for 30 min, and then filtered through a 0.22 μm nylon Millipore filter. UPLC was performed using a Waters Acquity UPLC H-Class (Waters Corp., Milford, MA, USA) with a CORTECS UPLC T3 column (2.1 mm × 150 mm, 1.6 μm) and an ACQUITY UPLC HSS T3 VanGuard precolumn (2.1 mm × 5 mm, 1.8 μm). The mobile phase, consisting of acetonitrile (A) and 0.1% formic acid in water (B), was run at a flow rate of 0.2 mL/min, and the injection volume was 2 μL. Using gradient elution, the program was as outlined below: 0–2 min, 12–20% A; 2–13.5 min, 20–40% A; 13.5–16 min, 40–63% A; 16–19 min, 63–64% A; 19–25 min, 64–66% A; 25–26.5 min, 66–70% A; 26.5–28 min, 70–76% A; and 28–31 min, 76–82% A. The column temperature was 30 °C, and the detection wavelength was 321 nm.

4.3. Transcriptome Sequencing and Differential Gene Expression Analysis

The total RNA was extracted from the roots of P. praeruptorum using the RNAprep Pure Plant Kit (Tiangen, Beijing, China; A0614A), and 1 μg of RNA per sample was used to construct the cDNA library, which was sequenced using the Illumina NovaSeq 6000 platform. The raw transcriptomic data were subsequently filtered by removing sequences containing adapters, more than 10% unknown nucleotides (N), and 50% low-quality bases (Q value ≤ 10) [65] to obtain clean reads for further analysis. Clean reads were aligned to the reference genome using Hisat2 (version 2.0.5). The reference genome used was a chromosome-level assembly of a wild P. praeruptorum genome generated by our research team, which has not yet been published. Gene expression levels were determined via fragments per kilobase of transcript per million fragments mapped (FPKM). The differentially expressed genes (DEGs) were analyzed using the DESeq2 software; only those genes that met the criteria of a fold change value > 2 and an FDR-corrected P-value < 0.05 were used for the analysis [66]. These DEGs were further annotated using the Kyoto Encyclopedia of Genes and Genomes (KEGG), NCBI nonredundant protein sequences (NR), COG, eggNOG, Swiss-Prot, KOG, Pfam, and GO databases [67].

4.4. Identification of Genes Involved in Coumarin Biosynthesis

The coumarin biosynthesis pathway involves key enzyme-encoding genes such as PAL, C4H, 4CL, C3′H, HCT/HQT, CCoAOMT, F6′H, COSY, C2′H, PS, AS, BMT, XMT, PT, DC, OC and AT. To identify candidate genes related to the coumarin biosynthesis pathways in P. praeruptorum, we selected protein sequences of genes in the coumarin biosynthesis pathways identified in Arabidopsis thaliana, P. praeruptorum, Angelica sinensis or Daucus carota, then tblastn v2.0 (E-value < 1 × 10⁻⁵) analysis was performed to identify orthologous genes in transcriptome data.

4.5. Identification of Candidate Flowering Genes in P. praeruptorum

Flowering pathway protein sequences from model plants (A. thaliana, Oryza sativa) and representative Apiaceae species (D. carota, Apium graveolens) were retrieved from the Database of Candidate Flowering Genes in Plants (https://yanglab.hzau.edu.cn/PlantCFG (accessed on 19 July 2025)) [68] to construct a reference flowering gene set. Using the Reciprocal BLAST module in TBtools software (v2.363) [69], we performed local alignment against the P. praeruptorum reference genome protein database with the following filtering parameters: E-value < 1 × 10⁻⁵, query coverage > 60%, and identity > 40%. Orthologous flowering-related genes were identified using the reciprocal best hit (RBH) criterion, where P. praeruptorum genes and reference flowering genes were mutually top BLAST hits.

4.6. Statistics Processing and Analysis

The data were analyzed by conducting one-way analysis of variance (ANOVA), or the Kruskal–Wallis test using SPSS Statistics 26.0 (IBM, Inc., Armonk, NY, USA). The normality of the data was assessed by conducting the Shapiro–Wilk test, and the homogeneity of variance was evaluated by conducting Levene’s test. Based on whether the data met the assumptions of normality and homoscedasticity, appropriate post hoc models were selected. If the data violated the assumptions of normality or homoscedasticity, square root or natural logarithmic transformations were first applied. For data that satisfied both normality and homoscedasticity, one-way ANOVA was performed. For data that met the assumptions of normality but not homoscedasticity, Tamhane’s T2 post hoc test was applied. If the assumptions of normality were not met, nonparametric tests (Kruskal–Wallis test) were performed for post hoc comparisons. The p < 0.05 was regarded as significantly different.

Heatmaps and histograms were plotted using TBtools (v2.363) [69] and GraphPad Prism 8.0.2 (GraphPad Software, Boston, MA, USA), respectively. Principal component analysis (PCA) of metabolic data, vertical stack bar, and Pearson correlation coefficient analysis were performed using an online platform (https://www.bioinformatics.com.cn (accessed on 24 July 2025)) for analyzing and visualizing the data [70]. A clustered bar chart was performed using the Metware Cloud (https://cloud.metware.cn (accessed on 26 July 2025)). All tests included three or more biological replicates.

5. Conclusions

Based on the UPLC method established in this study for determining the content of seventeen coumarin compounds, we analyzed the content characteristics of coumarin levels in 357 individual samples of P. praeruptorum with 1–3 years of cultivation (Pp1y, Pp2y, and Pp3y). Additionally, we explored the molecular mechanisms underlying the content variations among different growth years and chemotypes. In the Pp1y, Pp2y, and Pp3y populations, the content of total coumarin, total pyranocoumarin and seven pyranocoumarins with higher content all showed an upward trend as the growth years increased. In contrast, the six furanocoumarins and three simple coumarins with lower content generally displayed an initial increase followed by a decrease. Interestingly, we observed significant heterogeneity in coumarin content among intraspecific individuals of P. praeruptorum under homogeneous habitats, which could be classified into two chemotypes. And both chemotypes were present in populations of different growth years. These findings suggest that, in addition to growth years, genetic factors also significantly influence the coumarin content in cultivated P. praeruptorum. Transcriptome analysis of samples cultivated for 1 and 3 years revealed that temporal shifts in gene expression involved in pyranocoumarin, furanocoumarin, and simple coumarin biosynthesis contribute to the variation in coumarin levels among P. praeruptorum with different growth years. Furthermore, this study identified 27 growth-year-associated and 10 chemotype-associated DEGs putatively involved in coumarin biosynthesis, together with 126 candidate genes putatively implicated in flowering-time regulation. This study is the first to investigate the coumarin profiles and transcriptomic characteristics of cultivated P. praeruptorum across different growth years and chemotypes, and to explore the molecular mechanisms underlying content variations. It provides valuable insights for the breeding of high-quality cultivated P. praeruptorum varieties.

Supplementary Materials

The following supporting information can be downloaded at https://www.mdpi.com/article/10.3390/plants15040598/s1: Figure S1. Chemical structures of seventeen coumarin compounds; Figure S2. PCA plot of the two chemotypes of Peucedanum praeruptorum samples cultivated for 1 and 3 years; Figure S3. The number of significantly up- and down-regulated genes (p value < 0.05 and fold-change > 2) in 1yA vs. 1yB, 1yA vs. 3yA, 1yA vs. 3yB, 1yB vs. 3yA, 1yB vs. 3yB and 3yA vs. 3yB; Figure S4. The enrichment analysis of KEGG pathways based on DEGs among the two chemotypes of P. praeruptorum samples cultivated for 1 year (1yA and 1yB) and 3 years (3yA and 3yB). A. 1yA vs. 3yA; B. 1yB vs. 3yB; C. 1yA vs. 1yB; D. 3yA vs. 3yB; Figure S5. (A) Heatmap showing expression levels of the 27 DEGs in coumarin biosynthesis in a comparison between P. praeruptorum samples cultivated for 1 and 3 years (1yA vs. 3yA and 1yB vs. 3yB); (B) Heatmap showing expression levels of the 10 DEGs in coumarin biosynthesis in a comparison between chemotype A and chemotype B plants (1yA vs. 1yB and 3yA vs. 3yB); Table S1. The number of Peucedanum praeruptorum individual plants cultivated for 1–3 years (Pp1y, Pp2y, and Pp3y) collected from each experimental plot in the AH and SC trial sites, along with the geographical location information of the experimental plots; Table S2. Statistical data for the content of seventeen coumarin compounds of P. praeruptorum populations cultivated for 1–3 years (Pp1y, Pp2y, and Pp3y); Table S3. Statistical data for the content of seventeen coumarin compounds of P. praeruptorum samples from six plots (AH1, AH2, AH3, AH4, SC1and SC2) across two experimental sites (AH and SC) with 1–3 years of cultivation (Pp1y, Pp2y, and Pp3y); Table S4. Statistical data for the content of seventeen coumarin compounds of the two chemotypes of P. praeruptorum samples cultivated for 1–3 years (Pp1y, Pp2y, and Pp3y). Table S5. The enzyme names, EC numbers, and candidate gene numbers involved in coumarin biosynthesis in P. praeruptorum.

Author Contributions

J.J.: Methodology, formal analysis, investigation, data curation, writing—original draft and writing—review and editing. Y.L. and J.Y.: writing—review and editing, data curation. L.F., D.W., M.L. and Z.Z.: Visualization and investigation. Q.W.: Supervision, project administration and writing—review and editing. Z.G.: Supervision and writing—review and editing. J.W.: Conceptualization, supervision, funding acquisition, project administration and writing—review and editing. All authors have read and agreed to the published version of the manuscript.

Data Availability Statement

The raw sequence data reported in this paper have been deposited in the Genome Sequence Archive (Genomics, Proteomics & Bioinformatics 2025) in National Genomics Data Center (Nucleic Acids Res 2025), China National Center for Bioinformation/Beijing Institute of Genomics, Chinese Academy of Sciences (GSA: CRA036659) that are publicly accessible at https://ngdc.cncb.ac.cn/gsa (accessed on 10 February 2026).

Conflicts of Interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Funding Statement

This research was funded by the National Key Research and Development Program of China (2022YFC3501500); the National Traditional Chinese Medicine Industry Technology System (CARS-21); the CAMS Innovation Fund for Medical Sciences (CIFMS) (2021-I2M-1-032); and the State Administration of Traditional Chinese Medicine of the People′s Republic of China (GZY-KJS-2023-008).