Untargeted metabolomics and functional analyses reveal that the secondary metabolite quinic acid associates with 
As a primary source of medicine, medicinal plants contain an immense number of secondary metabolites, which are traditional active substances that possess medicine-like properties for human use . For the medicinal plants of the umbelliferous family, whose medicinal parts are roots, early flowering may lead to changes in the quality of the medicinal materials. Angelica sinensis (Oliv.) Diels, an herbaceous perennial species in the family Umbelliferae, is a type of habitat-oriented medicinal plant. Since the 1970s, more than 160 chemical constituents, including aromatic acids, phthalides, and phenylpropanoids, have been isolated or identified from the roots of A. sinensis . Most of these secondary metabolites are associated with biological activities and clinical applications . The synthesis and accumulation of plant secondary metabolites are influenced by many factors, including genetic factors, environmental conditions, biological stress and plant development stage, some secondary metabolites (such as flavonoids) can be used as cofactors to participate in auxin transport and distribution, thereby regulating plant growth and development . In the production districts of A. sinensis in China, the seeds of A. sinensis are sown in early summer for seedling cultivation. After indoor overwintering, the seedlings are planted in the field the following spring. The nonlignified roots are obtained in the fall of the second year. In May of the third lunar calendar year, A. sinensis begins to put forth blossoms, similar to small umbrellas, with dozens of small green‒white flowers. Seeds are then collected in midsummer. However, up to 40% ~ 50% of A. sinensis flowers early in the second year. All the roots in these early-flowering A. sinensis plants become lignified, and the accumulation of effective secondary metabolites, such as ferulic acid and ligustilide, decreases; thus, these early-flowering A. sinensis plants can no longer be used medicinally . Flowering is a significant reproductive process. The main genetic pathways involved in flowering include the photoperiod, vernalization, autonomous and gibberellin pathways . Gibberellins (GAs) are major phytohormones involved in floral transition in Arabidopsis . Several endogenous hormones interact to regulate the flowering process of plants . In addition to GAs, jasmonic acid (JA) has been found to be involved in the regulation of flower opening . The levels of the endogenous hormones GAs, JA, abscisic acid (ABA), and cytokinins (CKs) are significantly altered during early bolting in A. sinensis . Many hormones and other chemical signals come from secondary metabolic pathways, such as alpha-linolenic acid metabolism, that provide precursors for the phytohormone JA. Some hormones are key mediators of plant secondary metabolites; for example, GAs inhibit flavonoid biosynthesis in Medicago truncatula . It also influences the synthesis of monoterpenes and sesquiterpenes. Like those in other plants, plant hormones play important roles in the growth of A. sinensis . Genes associated with secondary metabolism, hormone signaling and floral development were found in the leaves and lateral roots of early-flowering A. sinensis . JA was first isolated from Cucurbita pepo in 1977 and was shown to be an important resistance hormone in the 1990s. There may also be hormone-like substances in the secondary metabolites of A. sinensis. Compared with traditional chromatographic separation methods, the advancement of metabolomics has assisted in the identification of novel primary and secondary metabolite biomarkers from minimal samples . Although this high-throughput technique provides a wide range of data on host metabolism, the specific metabolites must be functionally verified via classical plant molecular biological methods. In the present study, we investigated the multiparametric metabolic responses of A. sinensis leaves to genetic or environmental perturbations via a metabolomics method. By drawing metabolite profile patterns, a holistic signature of the physiological state of A. sinensis , together with important metabolites of specific biochemical processes, was generated. Field and aseptic seedling pot experiments in A. sinensis were then carried out to observe the key secondary metabolites involved in flowering. Furthermore, the model plant Arabidopsis thaliana and its mutants were used to elucidate the mechanisms of flowering regulation by key secondary metabolites. These experiments enabled us to discover new pro-flowering molecules from secondary metabolites that are required for A. sinensis growth and development, as well as a strategy for controlling early flowering in Umbelliferae family medicinal plants. 

Metabolomic sample preparation A. sinensis samples, including biennial unbolted, biennial flowering, biennial seeded and triennial seeded were collected from Min County, Dingxi city, Gansu Province, China (longitude of E 103.9°, latitude of N 34.5° and altitude of 2943 m) in August 2017 (Fig. ). The seedlings of A. sinensis were propagated by the same grower. Among them, the seedling of triennial seeded A. sinensis sample was transplanted into the field in April 2015 for experimental purposes, and the others was transplanted into the field in April 2016. Authentication by J. A. Duan confirmed that the plants were A. sinensis , and voucher specimens were deposited in the Herbarium of Nanjing University of Chinese Medicine, Nanjing, PR China. Leaves and roots were separated, with leaves snap-frozen in liquid nitrogen, 0.5 cm × 0.5 cm slices, and 0.5 g of leaf pieces added to a 10 mL centrifuge tube with 5 mL of ethyl acetate. Ultrasonication (40 kHz) for 10 min at room temperature, followed by filtration, constituted the initial extraction. A second extraction involved adding 5 mL of fresh ethyl acetate to the residue, followed by a 10-min ultrasonic extraction. The combined filtrate was centrifuged (16,000 × g for 10 min), and the resulting filtrate was concentrated via centrifugation to obtain the EAC fraction. The residue was then subjected to further extractions with methanol and methanol with 1% formic acid, resulting in MeOH and MeOH-FA fractions, respectively. Water was used to obtain the H 2 O fraction. All extraction samples were stored at 4 °C in airtight tubes, and before UHPLC-LTQ-Orbitrap/MS analysis, the samples were redissolved in 95% water/acetonitrile (including 0.1% formic acid, v/v). Six independent samples per group were used. UHPLC-LTQ-Orbitrap/MS and UPLC-QqQ/MS conditions for untargeted metabolism and quantitative determination of the principal markers Chromatographic and mass spectrometry conditions, as detailed in our published literature , were optimized. Separation was carried out for 20 min under the following conditions: 0–2.5 min, A: 95% ~ 65%; 2.5–4 min, A: 65% ~ 55%; 4–10 min, A: 55% ~ 35%; 10–11 min, A: 35% ~ 15%; 11–16 min, A: 15% ~ 10%; 16–18 min, A: 10 ~ 5%; 18–19.5 min, A: 5%; and 19.5–20 min, A: 5 − 95%. Untargeted metabolism data for A. sinensis leaves were collected via LTQ-Orbitrap/MS analysis. The data were normalized to the summed total ion intensity per chromatogram, and SIMICA-P 15.0 software was used for PCA and OPLS-DA. Variables from the UHPLC‒MS/MS datasets were UV-scaled to Pareto variance, and OPLS‒DA score plots were characterized by R2Y and Q2 values for total explained variation and model predictability, respectively. S-plot and VIP values (> 1) were used for marker selection . UPLC-QqQ/MS was used for quantitative determination of the principal markers in A. sinensis leaves. ESI‒MS spectra were acquired in multiple reaction monitoring (MRM) mode. The contents of the markers were calculated via the external standard method. The complete methodology can be found in Supplementary Text 1. Field experiment to observe A. sinensis flowering A field experiment was established at the A. sinensis Research Institute, Minxian County, Gansu Province (34.2895 N, 104.0420E; H 2524 m), in which the early bolting rate was monitored after exogenous spraying of the principal marker quinic acid in 2023. The planting density was 28 plants/m 2 . Blank water was used as the control, and the quinic acid concentrations of the groups from low to high were 33 mg/m 2 , 164 mg/m 2 , and 328 mg/m 2 , respectively. After transplanting, A. sinensis was sprayed once every 2 weeks for a total of 3 times. There were two main periods of early bolting of A. sinensis : a first outbreak from mid-June to mid-July and a second from mid-July to mid-August. Early bolting of A. sinensis occurred mainly during the first outbreak period, and a small portion occurred during the second outbreak period. We determined the early bolting rate of A. sinensis under the different groups on July 19 and August 15. Plant materials and growth conditions in the laboratory To further clarify the function of the principal marker, the seeds of A. sinensis were utilized to cultivate sterile seedlings (Supplementary Text 1) . The plants were cultivated in a growth chamber at 23 ± 1 °C under a 16-hour photoperiod and 2000 lx light intensity. In certain experiments, seedlings were transferred to a new medium with a principal marker (quinic acid, 100 µM), methyl jasmonate (JAM, 100 µM), gibberellin 3 (GA3, 100 µM), or plain MS medium when the cotyledons had flattened, when the true leaves had grown, and after 30 to 40 days after planting. After 14 days in the new medium, complete plantlets were extracted from the culture medium and gently washed with deionized water. The morphology was then observed and recorded. A. thaliana , a model for flowering plant research, has also been used for principal marker function validation and regulatory mechanism analysis. A. thaliana lines in the Columbia (Col) background and the mutants qdh1,qdh2 and qdh3 were utilized. Seeds of Col and the mutants were obtained from AraShare ( http://www.arashare.cn , Fujian, China). The mutants were analyzed via PCR (the primer sequences are listed in Supplementary Table S8). The seeds were first cultured on medium (Supplementary Text 1) . After being transferred to soil, they were subjected to cold imbibition for 3 days at 4 °C in complete darkness, followed by germination in a controlled culture room set at 21 °C with a relative humidity of 65% under 16 h/8 h light/dark periods under “LD” conditions. The plants were individually sprayed with quinic acid (QA, 100 µM), gibberellin 3 (GA3, 100 µM), or water (Con) over the 24 plants every week until all the plants had initiated flowering in Col At . Similarly, the At mutant plants were sprayed with quinic acid (QA, 100 µM), gibberellin 3 (GA3, 100 µM), water (Col), or water ( qdh1 -con/ qdh3 -con) for at least 24 plants in one treatment per week until flowering began. For the transcription and protein level analyses, the seedlings were transferred to new medium supplemented with quinic acid (QA, 100 µM), methyl jasmonate (JAM, 100 µM), gibberellin 3 (GA3, 100 µM), or plain ½ MS media (Con) 10 days after planting. On Days 1, 7, and 14 in the new medium, complete plantlets were extracted from the culture medium, washed with deionized water, and prepared for total RNA and protein extraction. Flowering time indicator measurements The bolting time was determined when the bolt reached approximately 1 cm in height. The flowering time was determined when the first visible flower appeared. The bolting and flowering times and the number of rosette, cauline, and total leaves, were recorded. For statistical analysis, values are reported as the means ± standard deviations, and unpaired nonparametric tests were conducted. A brief graphical illustration has been included in Supplementary Material Fig. . Quantitative real-time PCR (qRT‒PCR) method Complete sterile A. sinensis seedlings after 14 days of culture and complete A. thaliana plantlets after 1, 7, and 14 days of culture were collected from the culture medium. The samples were washed with deionized water and prepared for total RNA extraction. Total RNA was extracted with an RNA prep pure plant kit (polysaccharide polyphenolic-rich) (Tiangen, Beijing, China). After reverse transcription of 1.5 µg of total RNA, quantitative RT‒PCR was conducted on an ABI 7500 real-time PCR system (Supplementary Text 1). Relative expression levels were estimated via the housekeeping genes 18 S RNA (for A. sinensis ) and ACTIN2 (for At ) as references via the 2 −∆∆Ct method . The list of primers (Invitrogen, Shanghai, China) utilized for qRT‒PCR is included in Supplementary Table S7. All experiments were conducted in triplicate for both independent biological replicates and technical replicates. Gibberellins and jasmonic acid quantification To quantify GAs and JA contents, approximately 20 mg per sample of fresh complete sterile A. sinensis seedlings cultured for 14 days was extracted. These samples were homogenized in an extraction mixture with a sample-to-saline ratio of 1:9 for enzyme-linked immunosorbent assay (ELISA) . ELISA procedures were executed following the manufacturer’s instructions. Six independent samples per group were used. Extraction of total protein and Western blot analysis Complete A. thaliana plantlets cultured for 1, 7, and 14 days were used to prepare total proteins. Total proteins were extracted using RIPA (1% PMSF) buffer (Beyotime, Shanghai, China). The protein concentration was determined via BCA assay, and 20 µg of total protein was loaded for SDS‒PAGE. Proteins were identified by using the rabbit polyclonal antibodies against DELLA protein GAI (GAI, PhytoAB, USA), chloroplastic lipoxygenase (LOX2, PhytoAB, USA), gibberellin receptor GID1A, N-terminal (GID1A, PhytoAB, USA), and RbcL subunit of RuBisCO (RbcL, PhytoAB, USA) and secondary antibodies conjugated to horseradish peroxidase (goat anti-rabbit IgG, Abbkine, Wuhan, China). RbcL was used as an internal control. Three independent experiments were performed for each sample. The intensities of the immunoreactive bands were quantified using ImageJ software. Three independent samples per group were used. Statistical analysis The experimental data are expressed as the means ± standard errors of the means (SEMs). Statistical significance was assessed via ANOVA, and a normal distribution was tested via paired-sample t tests with SPSS v18.0 (SPSS, Inc., Chicago, IL, USA). A confidence level of 95% was set for all the experiments to determine the significance of the differences ( p < 0.05). With respect to biological and technical replicates, for untargeted metabolism, n = 6; for targeted metabolism, n = 94; for bolting time and flowering time of At,n = 50; for bolting time and flowering time of A. sinensis,n = 128; for qRT‒PCR and WB, n = 3; and for ELISA, n = 6. 

A. sinensis samples, including biennial unbolted, biennial flowering, biennial seeded and triennial seeded were collected from Min County, Dingxi city, Gansu Province, China (longitude of E 103.9°, latitude of N 34.5° and altitude of 2943 m) in August 2017 (Fig. ). The seedlings of A. sinensis were propagated by the same grower. Among them, the seedling of triennial seeded A. sinensis sample was transplanted into the field in April 2015 for experimental purposes, and the others was transplanted into the field in April 2016. Authentication by J. A. Duan confirmed that the plants were A. sinensis , and voucher specimens were deposited in the Herbarium of Nanjing University of Chinese Medicine, Nanjing, PR China. Leaves and roots were separated, with leaves snap-frozen in liquid nitrogen, 0.5 cm × 0.5 cm slices, and 0.5 g of leaf pieces added to a 10 mL centrifuge tube with 5 mL of ethyl acetate. Ultrasonication (40 kHz) for 10 min at room temperature, followed by filtration, constituted the initial extraction. A second extraction involved adding 5 mL of fresh ethyl acetate to the residue, followed by a 10-min ultrasonic extraction. The combined filtrate was centrifuged (16,000 × g for 10 min), and the resulting filtrate was concentrated via centrifugation to obtain the EAC fraction. The residue was then subjected to further extractions with methanol and methanol with 1% formic acid, resulting in MeOH and MeOH-FA fractions, respectively. Water was used to obtain the H 2 O fraction. All extraction samples were stored at 4 °C in airtight tubes, and before UHPLC-LTQ-Orbitrap/MS analysis, the samples were redissolved in 95% water/acetonitrile (including 0.1% formic acid, v/v). Six independent samples per group were used. 

Chromatographic and mass spectrometry conditions, as detailed in our published literature , were optimized. Separation was carried out for 20 min under the following conditions: 0–2.5 min, A: 95% ~ 65%; 2.5–4 min, A: 65% ~ 55%; 4–10 min, A: 55% ~ 35%; 10–11 min, A: 35% ~ 15%; 11–16 min, A: 15% ~ 10%; 16–18 min, A: 10 ~ 5%; 18–19.5 min, A: 5%; and 19.5–20 min, A: 5 − 95%. Untargeted metabolism data for A. sinensis leaves were collected via LTQ-Orbitrap/MS analysis. The data were normalized to the summed total ion intensity per chromatogram, and SIMICA-P 15.0 software was used for PCA and OPLS-DA. Variables from the UHPLC‒MS/MS datasets were UV-scaled to Pareto variance, and OPLS‒DA score plots were characterized by R2Y and Q2 values for total explained variation and model predictability, respectively. S-plot and VIP values (> 1) were used for marker selection . UPLC-QqQ/MS was used for quantitative determination of the principal markers in A. sinensis leaves. ESI‒MS spectra were acquired in multiple reaction monitoring (MRM) mode. The contents of the markers were calculated via the external standard method. The complete methodology can be found in Supplementary Text 1. 

A. sinensis flowering A field experiment was established at the A. sinensis Research Institute, Minxian County, Gansu Province (34.2895 N, 104.0420E; H 2524 m), in which the early bolting rate was monitored after exogenous spraying of the principal marker quinic acid in 2023. The planting density was 28 plants/m 2 . Blank water was used as the control, and the quinic acid concentrations of the groups from low to high were 33 mg/m 2 , 164 mg/m 2 , and 328 mg/m 2 , respectively. After transplanting, A. sinensis was sprayed once every 2 weeks for a total of 3 times. There were two main periods of early bolting of A. sinensis : a first outbreak from mid-June to mid-July and a second from mid-July to mid-August. Early bolting of A. sinensis occurred mainly during the first outbreak period, and a small portion occurred during the second outbreak period. We determined the early bolting rate of A. sinensis under the different groups on July 19 and August 15. 

To further clarify the function of the principal marker, the seeds of A. sinensis were utilized to cultivate sterile seedlings (Supplementary Text 1) . The plants were cultivated in a growth chamber at 23 ± 1 °C under a 16-hour photoperiod and 2000 lx light intensity. In certain experiments, seedlings were transferred to a new medium with a principal marker (quinic acid, 100 µM), methyl jasmonate (JAM, 100 µM), gibberellin 3 (GA3, 100 µM), or plain MS medium when the cotyledons had flattened, when the true leaves had grown, and after 30 to 40 days after planting. After 14 days in the new medium, complete plantlets were extracted from the culture medium and gently washed with deionized water. The morphology was then observed and recorded. A. thaliana , a model for flowering plant research, has also been used for principal marker function validation and regulatory mechanism analysis. A. thaliana lines in the Columbia (Col) background and the mutants qdh1,qdh2 and qdh3 were utilized. Seeds of Col and the mutants were obtained from AraShare ( http://www.arashare.cn , Fujian, China). The mutants were analyzed via PCR (the primer sequences are listed in Supplementary Table S8). The seeds were first cultured on medium (Supplementary Text 1) . After being transferred to soil, they were subjected to cold imbibition for 3 days at 4 °C in complete darkness, followed by germination in a controlled culture room set at 21 °C with a relative humidity of 65% under 16 h/8 h light/dark periods under “LD” conditions. The plants were individually sprayed with quinic acid (QA, 100 µM), gibberellin 3 (GA3, 100 µM), or water (Con) over the 24 plants every week until all the plants had initiated flowering in Col At . Similarly, the At mutant plants were sprayed with quinic acid (QA, 100 µM), gibberellin 3 (GA3, 100 µM), water (Col), or water ( qdh1 -con/ qdh3 -con) for at least 24 plants in one treatment per week until flowering began. For the transcription and protein level analyses, the seedlings were transferred to new medium supplemented with quinic acid (QA, 100 µM), methyl jasmonate (JAM, 100 µM), gibberellin 3 (GA3, 100 µM), or plain ½ MS media (Con) 10 days after planting. On Days 1, 7, and 14 in the new medium, complete plantlets were extracted from the culture medium, washed with deionized water, and prepared for total RNA and protein extraction. 

The bolting time was determined when the bolt reached approximately 1 cm in height. The flowering time was determined when the first visible flower appeared. The bolting and flowering times and the number of rosette, cauline, and total leaves, were recorded. For statistical analysis, values are reported as the means ± standard deviations, and unpaired nonparametric tests were conducted. A brief graphical illustration has been included in Supplementary Material Fig. . 

Complete sterile A. sinensis seedlings after 14 days of culture and complete A. thaliana plantlets after 1, 7, and 14 days of culture were collected from the culture medium. The samples were washed with deionized water and prepared for total RNA extraction. Total RNA was extracted with an RNA prep pure plant kit (polysaccharide polyphenolic-rich) (Tiangen, Beijing, China). After reverse transcription of 1.5 µg of total RNA, quantitative RT‒PCR was conducted on an ABI 7500 real-time PCR system (Supplementary Text 1). Relative expression levels were estimated via the housekeeping genes 18 S RNA (for A. sinensis ) and ACTIN2 (for At ) as references via the 2 −∆∆Ct method . The list of primers (Invitrogen, Shanghai, China) utilized for qRT‒PCR is included in Supplementary Table S7. All experiments were conducted in triplicate for both independent biological replicates and technical replicates. 

To quantify GAs and JA contents, approximately 20 mg per sample of fresh complete sterile A. sinensis seedlings cultured for 14 days was extracted. These samples were homogenized in an extraction mixture with a sample-to-saline ratio of 1:9 for enzyme-linked immunosorbent assay (ELISA) . ELISA procedures were executed following the manufacturer’s instructions. Six independent samples per group were used. 

Complete A. thaliana plantlets cultured for 1, 7, and 14 days were used to prepare total proteins. Total proteins were extracted using RIPA (1% PMSF) buffer (Beyotime, Shanghai, China). The protein concentration was determined via BCA assay, and 20 µg of total protein was loaded for SDS‒PAGE. Proteins were identified by using the rabbit polyclonal antibodies against DELLA protein GAI (GAI, PhytoAB, USA), chloroplastic lipoxygenase (LOX2, PhytoAB, USA), gibberellin receptor GID1A, N-terminal (GID1A, PhytoAB, USA), and RbcL subunit of RuBisCO (RbcL, PhytoAB, USA) and secondary antibodies conjugated to horseradish peroxidase (goat anti-rabbit IgG, Abbkine, Wuhan, China). RbcL was used as an internal control. Three independent experiments were performed for each sample. The intensities of the immunoreactive bands were quantified using ImageJ software. Three independent samples per group were used. 

The experimental data are expressed as the means ± standard errors of the means (SEMs). Statistical significance was assessed via ANOVA, and a normal distribution was tested via paired-sample t tests with SPSS v18.0 (SPSS, Inc., Chicago, IL, USA). A confidence level of 95% was set for all the experiments to determine the significance of the differences ( p < 0.05). With respect to biological and technical replicates, for untargeted metabolism, n = 6; for targeted metabolism, n = 94; for bolting time and flowering time of At,n = 50; for bolting time and flowering time of A. sinensis,n = 128; for qRT‒PCR and WB, n = 3; and for ELISA, n = 6. 

Metabolomics analysis of leaves suggests quinic acid as a potential marker for monitoring the early flowering phenomenon of A. sinensis To obtain enough chemical information, hierarchical extraction of A. sinensis leaves, including ethyl acetate extraction (EAC), methanol extraction (MeOH), methanol with 1% formic acid (v/v) extraction (MeOH-FA) and water extraction (H 2 O), was used for metabolomics analysis via UHPLC-LTQ-Orbitrap/MS. Owing to the limitations of this method, small polar compounds will not be characterized here. Representative spectra of the four fractions from each sample are shown in Supplementary Fig. S2. Clear clustering of the biennial unbolted samples, the biennial flowering and biennial seeded samples, and the triennial seeded samples, as shown in the PCA score plots (Fig. A-B and Supplementary Fig. S3A-B, S4A-B, S5A-B), demonstrated that early flowering of A. sinensis resulted in changes in metabolites. A supervised OPLS-DA model was built to explore potential markers for plant physiological changes. OPLS-DA distinguished the unbolted and flowering cohorts with 100% sensitivity and no less than 95% specificity via a leave-one-out algorithm. For negative ion mode, the R 2 Y values of this OPLS-DA model were 0.815 (EAC samples), 0.824 (MeOH samples), 0.862 (MeOH-FA samples) and 0.764 (H 2 O samples). The Q 2 values were determined to be 0.541 (EAC samples), 0.271 (MeOH samples), 0.633 (MeOH-FA samples) and 0.493 (H 2 O samples). For positive ion mode, the R 2 Y values of this OPLS-DA model were 0.954 (EAC samples), 0.957 (MeOH samples), 0.798 (MeOH-FA samples) and 0.848 (H 2 O samples). The values of Q 2 were 0.832 (EAC samples), 0.735 (MeOH samples), 0.598 (MeOH-FA samples) and 0.620 (H 2 O samples) (Fig. C-D and Supplementary Fig. S3C-D, S4C-D, S5C-D). A full external validation paradigm, with discriminatory sensitivity set at 100% and specificity > 90%, was used. Potential metabolites responsible for the separation in the biennial unbolted samples, the biennial flowering and biennial seeded samples, and the triennial seeded samples could be selected from the loading scatter plot and VIP value plot (Fig. E-H and Supplementary Fig. S3E-H, S4E-H, S5E-H). The variables with VIP values greater than 1 were selected as candidates. The measurement error was 10 mDa. The presumed molecular formula was searched in databases, including METLIN ( https://metlin.scripps.edu/ ), ChemSpider ( http://www.chemspider.com/Search.aspx ) and others. The identified markers were confirmed by reference compounds, MS/MS spectra and literature data. Consequently, 202 compounds were identified from the four different leaf extractions. The ratios of the peak area to the IS of 202 secondary metabolites in the biennial unbolted samples, biennial flowering samples, biennial seeded samples and triennial seeded samples were compared via ANOVA and paired-sample t tests. Metabolites with p > 0.05 were eliminated from all three paired samples. Thereafter, 151 secondary metabolites, including quinic acid and phytosphingosine, contributing to the separation of unbolted and flowering A. sinensis were further selected as markers (Supplementary Table ). MetaboAnalyst analysis  revealed that these identified metabolites were involved in four main pathways: flavone and flavonol biosynthesis, sphingolipid metabolism, glyoxylate and dicarboxylate metabolism and alpha‒linolenic acid metabolism (Supplementary Fig. S6). Pathway enrichment analysis revealed that flavone and flavonol biosynthesis contribute to the different growth phases of A. sinensis . This pathway involves the biosynthesis of secondary metabolites, which are derived from the shikimate pathway . Phenolic compounds produced by the plant shikimate pathway are known to play multiple roles in plants . The precursor of quinic acid, 3-dehydroquinic acid, is the first intermediate with a carbon ring in the shikimate pathway. Therefore, among the 151 secondary metabolites, quinic acid, which has significantly increased in early-flowering samples, was selected as the representative marker. To verify the authenticity of these compounds, 188 leaf samples, including biennial unbolted and flowering A. sinensis from the same area in Min County, were collected in August 2018. QqQ/MS was used for the quantification of quinic acid. The MRM transitions and parameters applied in the study are listed in Supplementary Table S2. The average concentration of quinic acid in the unbolted samples was determined to be 0.27 ± 0.07 µg/mg, whereas that in the flowering samples was 0.66 ± 0.08 µg/mg, with a p value of 0.00043. It increased significantly during the flowering of A. sinensis . Thus, we can confirm that quinic acid is a potential marker for monitoring the early flowering phenomenon of A. sinensis . Quinic acid treatment induces early flowering in A. sinensis and A. Thaliana In Apiaceae plants, flowering is an essential condition for reproductive success. The rates of first and second early bolting of the untreated A. sinensis plants were 17.58%, and those treated with 33 mg/m 2 and 164 mg/m 2 QA were 24.22% and 33.59%, respectively. The first early bolting rate of plants treated with 328 mg/m 2 QA was 15.63%, and the second bolting rate was 16.41% (Fig. A). The results showed that quinic acid has the potential to promote early bolting and flowering in plants. Apparently, a low dose (33-164mg/m 2 ) of quinic acid promoted the early flowering of A. sinensis , but a high dose(328 mg/m 2 ) had no significant effect on flowering. With increasing concentrations of quinic acid, the flowering time of At increased (Fig. B and Supplementary Fig. S7A). At 52.08 ± 2.60 days, the untreated Con plants bolted at approximately the 13.50 ± 0.93 rosette leaf stage. After exposure to increasing concentrations of quinic acid from 20 to 200 µM, a significant reduction in leaf number was observed, with the plants flowering on average one leaf earlier. Additionally, increased concentrations of quinic acid (500 µM, 1000 µM) had no effect on flowering time or flowering rosette leaf number compared with those of the untreated plants. The flowering of At is regulated by various pathways, with many hormones involved in the flowering induction process of plants, among which GAs has been demonstrated to be the dominant plant hormone involved in the transformation of At . We used water treatment as a blank control, 100 µM gibberellin 3 (GA3) as a positive control, and 100 µM quinic acid (QA) as the experimental group. GA3 and QA significantly accelerated the flowering process of At Col-0 to varying degrees. Compared with those in the water group, the flowering times in the GA3- and QA-treated groups were 5 and 3 days earlier, respectively (Fig. C, D, E, and Supplementary Fig. S7B, C). Late-flowering phenotypic characterization of Arabidopsis thaliana Qdh mutants Quinic acid is a carboxylated cyclohexanepolyol found in several plant sources. It is biosynthesized via the shikimic acid pathway from erythritose 4-phosphate (E4P) and phosphoenolpyruvate (PEP) condensation to form 3-deoxy-d-arabinoheptose-7-phosphate (DAHP) and then under the action of a series of enzymes to produce 3-dehydroquinic acid; then, under the action of quinate dehydrogenase (QDH), quinic acid is produced . Three At mutant strains (AT3G06350) were obtained from AraShare ( www.arashare.cn ) (Supplementary Table S3), and QDH homozygous Arabidopsis plants were identified and screened via PCR. qdh2 was mostly wild type or heterozygous, and qdh1 and qdh3 were homozygous mutant plants (Supplementary Fig. S8A). The transcript levels of QDH and the quinic acid content of qdh1 and qdh3 were markedly lower (Supplementary Fig. S8B). These lines presented a flowering phenotype that was delayed by approximately 3 days (Supplementary Table S4). Given that these phenotypes are caused by the observed lower quinic acid content, we supplied qdh1 and qdh3 seedlings with exogenous quinic acid at a concentration of 100 µM for 4 weeks. This treatment led to flowering occurring 2 days earlier. Exogenous GA3 was also added to the qdh1 and qdh3 mutant plants, and flowering occurred 3 days earlier (Fig. ). These data suggest that quinic acid is a positive regulator of flowering in At and is required at certain concentrations for normal development. Effect of quinic acid on the GA‒JA interaction pathway in Arabidopsis thaliana and its qdh1 mutant Flowering is a transition process from vegetative growth to reproductive growth, which is regulated by both endogenous and environmental signals. The gibberellin biosynthetic pathway is one of the six pathways that coordinate floral induction in At . Gibberellin signaling affects flowering through its interaction with well-known genes such as FLOWERING LOCUS T ( FT),LEAFY ( LFY ), and FLOWERING LOCUS C ( FLC ), as well as via crosstalk with other phytohormone signaling pathways, including the JA pathway . Moreover, with respect to the A. sinensis leaf metabolome pathway analysis results, it was especially interesting that alpha-linolenic acid metabolism impacted flowering. JA, a lipid-derived phytohormone, is derived mainly from the alpha-linolenic acid metabolism pathway . Therefore, to determine whether quinic acid participates in the GA‒JA interaction pathway, we examined the transcription factor expression of FT, SOC1 (SUPPRESSOR OF OVEREXPRESSION OF CONSTANS 1), LFY, FLC, FRI (FRIGIDA), CO (CONSTANS), MYC2, MYC3, MYC4, JAZ1, LOX2, GA20OX2, RGA, GAI, GID1A, GID1B and GID1C , etc., in wild-type At . At Col-0 plants were grown on medium for 10 days, then exogenously induced with 100 µM quinic acid, and whole plants were removed at 1, 7 and 14 days after treatment to analyze the transcription levels of key factors in the flowering pathway. The expression of FT was upregulated (4.95- and 5.67-fold compared with the untreated group, p < 0.05) after quinic acid induction for 1 and 7 days. LFY was upregulated (9.20- and 3.01-fold compared with the untreated group, p < 0.05) under quinic acid induction for 7 and 14 days. Quinic acid had no significant effect on the transcriptional regulation of SOC1 . Short-term treatment had no significant effect on the flowering repressor FLC , and FLC transcription was downregulated at 14 days (0.17-fold compared with the untreated group, p < 0.05). In addition, the main activator of FLC, FRI, had a significant regulatory effect only at the early stage of treatment, suggesting that the QA treatment had relatively little effect on FLC-mediated inhibition of flowering. The transcription of the main FT activator CO was upregulated (1.64-fold compared with the untreated group, p < 0.01) in the early stage of quinic acid treatment, but the regulatory effect of continuous treatment was not significant (0.86- and 1.07-fold compared with the untreated group, p > 0.05). The JA-activated transcription factors MYC2,MYC3 , and MYC4 redundantly regulate flowering under both LD and SD conditions. MYC2 and MYC3 suppress FT . We then tested whether quinic acid affects transcript levels in Col-0 At . qRT‒PCR analysis revealed that quinic acid treatment had little effect on the transcription of MYC4 but significantly downregulated the transcription of MYC2 and MYC3 (0.05 and 0.12, respectively, in the untreated group compared with the untreated group; p < 0.01). Therefore, we speculated that the regulation of FT transcription levels after quinic acid treatment is initially regulated by CO and then is regulated mainly by MYC2 and MYC3 under continuous treatment. The GA synthesis pathway is regulated mainly by the genes GA20OX, GA30OX , and GA2OX , and the signal transduction process is realized mainly by GA binding to the pocket structure of the receptor GIBBERELLIN INSENSITIVE DWARF1 ( GID1 ) and inducing changes in the Della domain. Della and MYC2 competitively bind JAZ1 proteins. At low GA levels, Della binds to JAZ1 and releases MYC2 to activate the downstream JA reaction. When the GA concentration increases, Della degradation is triggered, and JAZ1 is released. JAZ1 interacts with MYC2 , thus inhibiting the response of MYC2 to the JA pathway . Della can also participate in signaling processes by stabilizing MYC3 and interacting with JAZ . In this experiment, Col treated with 100 µM quinic acid for 1 day exhibited higher expression of GA20OX2 and GID1A (the receptor of GA) (1.70- and 1.99-fold compared with the untreated group, p < 0.05) and downregulation of GAI (GA response inhibitor, Della ) (0.39-fold compared with the untreated group, p < 0.01) (Fig. and Supplementary Table S5). In the qdh1 mutants, quinic acid induction was consistent with the trend in the wild type. The transcription levels of FT and LFY in the qdh1 At mutant were lower than those in Col-0 At . The low transcription level of FT in the mutant gradually removed with increasing plant growth, but the inhibition of LFY transcription in the mutant remained unchanged. After quinic acid treatment, the expression of FT and LFY was upregulated to promote flowering. For the key factors MYC2,MYC3,JAZ ( JAZ1),GID and Della ( GAI ), quinic acid also had compensatory effects, and the transcription levels were adjusted to those of the wild type At , thus alleviating the late flowering phenomenon of the qdh1 mutant plants (Supplementary Fig. S9 and Supplementary Table 6). Regulatory effects of quinic acid on the protein levels of key flowering factors in the wild type and the qdh1 mutant The proteins LOX2, GAI and GID1A, which affect flowering in At , were examined via WB. The expression of GAI was downregulated (0.50- and 0.70-fold compared with the untreated group, p < 0.05) under quinic acid induction for 7 and 14 days, whereas that of GID1A was upregulated (1.88- 1.40-fold compared with the untreated group, p < 0.05). LOX-2 was downregulated (0.45-fold compared with the untreated group, p < 0.01) under quinic acid induction for 7 days, but under quinic acid induction for 14 days, its expression level increased to 12.07-fold compared with the untreated group ( p < 0.01). Compared with that in the Col-0 control group, the expression of the LOX2 and GAI proteins in the qdh1 mutant At was upregulated, and the expression of the GID1A protein was reduced. The effect of the quinic acid treatment group on protein expression was the same as that of the wild-type control group. We also observed the effects of exogenous GA3 and methyl jasmonate on the expression of these proteins and found that the effect of quinic acid was similar to that of GA but not as strong as that of methyl jasmonate (Fig. , Supplementary Fig. S10). Effect of quinic acid on the GA‒JA interaction pathway in sterile A. sinensis seedlings The mRNA expression levels of 13-LOX, AOS, AOC, MYC2-1, MYC2-2, MYC2-3, MYC4, JAZ1-1, JAZ1-2, GA20OX, GA3OX and GA2OX in sterile seedlings of A. sinensis treated with quinic acid for 7 days were analyzed. Quinic acid treatment affected the expression of 13-LOX, GA20OX and MYC2 (1.41-, 2.55-, and 1.58-fold, respectively, compared with the untreated group; p < 0.05). Further dynamic point analysis revealed that quinic acid had a temporal effect on 13-LOX expression, but this trend was different from that of At . Quinic acid upregulated the expression of 13-LOX at the initial stage of treatment and downregulated the expression of 13-LOX with increasing duration of treatment. The expression of GA20OX in the GA pathway was upregulated, whereas that of MYC2 in the JA pathway was downregulated (Fig. ). The contents of JA and GA3 in sterile seedlings of A. sinensis subjected to different treatments were also calculated via ELISA. The values of JA in the untreated group, GA3-treated group, JA-treated group, and quinic acid-treated group were 1.91 ± 0.03, 1.94 ± 0.04, 2.00 ± 0.01, and 1.99 ± 0.09 ng/g, respectively. The treated groups did not exhibit significant differences from the control ( p > 0.05). The content of GA3 in the GA3-treated group was significantly lower (190.02 ng/g, p < 0.01) than that in the untreated group (202.99 ng/g); however, the levels in the JA-treated group and the quinic acid-treated group were significantly higher (231.35 and 210.87 ng/g, respectively; p < 0.05). These results indicated that intervention with exogenous GA and JA can affect the genes involved in the synthesis of both. Quinic acid treatment yielded similar gene regulation to GA treatment and promoted the accumulation of GA3. 

A. sinensis To obtain enough chemical information, hierarchical extraction of A. sinensis leaves, including ethyl acetate extraction (EAC), methanol extraction (MeOH), methanol with 1% formic acid (v/v) extraction (MeOH-FA) and water extraction (H 2 O), was used for metabolomics analysis via UHPLC-LTQ-Orbitrap/MS. Owing to the limitations of this method, small polar compounds will not be characterized here. Representative spectra of the four fractions from each sample are shown in Supplementary Fig. S2. Clear clustering of the biennial unbolted samples, the biennial flowering and biennial seeded samples, and the triennial seeded samples, as shown in the PCA score plots (Fig. A-B and Supplementary Fig. S3A-B, S4A-B, S5A-B), demonstrated that early flowering of A. sinensis resulted in changes in metabolites. A supervised OPLS-DA model was built to explore potential markers for plant physiological changes. OPLS-DA distinguished the unbolted and flowering cohorts with 100% sensitivity and no less than 95% specificity via a leave-one-out algorithm. For negative ion mode, the R 2 Y values of this OPLS-DA model were 0.815 (EAC samples), 0.824 (MeOH samples), 0.862 (MeOH-FA samples) and 0.764 (H 2 O samples). The Q 2 values were determined to be 0.541 (EAC samples), 0.271 (MeOH samples), 0.633 (MeOH-FA samples) and 0.493 (H 2 O samples). For positive ion mode, the R 2 Y values of this OPLS-DA model were 0.954 (EAC samples), 0.957 (MeOH samples), 0.798 (MeOH-FA samples) and 0.848 (H 2 O samples). The values of Q 2 were 0.832 (EAC samples), 0.735 (MeOH samples), 0.598 (MeOH-FA samples) and 0.620 (H 2 O samples) (Fig. C-D and Supplementary Fig. S3C-D, S4C-D, S5C-D). A full external validation paradigm, with discriminatory sensitivity set at 100% and specificity > 90%, was used. Potential metabolites responsible for the separation in the biennial unbolted samples, the biennial flowering and biennial seeded samples, and the triennial seeded samples could be selected from the loading scatter plot and VIP value plot (Fig. E-H and Supplementary Fig. S3E-H, S4E-H, S5E-H). The variables with VIP values greater than 1 were selected as candidates. The measurement error was 10 mDa. The presumed molecular formula was searched in databases, including METLIN ( https://metlin.scripps.edu/ ), ChemSpider ( http://www.chemspider.com/Search.aspx ) and others. The identified markers were confirmed by reference compounds, MS/MS spectra and literature data. Consequently, 202 compounds were identified from the four different leaf extractions. The ratios of the peak area to the IS of 202 secondary metabolites in the biennial unbolted samples, biennial flowering samples, biennial seeded samples and triennial seeded samples were compared via ANOVA and paired-sample t tests. Metabolites with p > 0.05 were eliminated from all three paired samples. Thereafter, 151 secondary metabolites, including quinic acid and phytosphingosine, contributing to the separation of unbolted and flowering A. sinensis were further selected as markers (Supplementary Table ). MetaboAnalyst analysis  revealed that these identified metabolites were involved in four main pathways: flavone and flavonol biosynthesis, sphingolipid metabolism, glyoxylate and dicarboxylate metabolism and alpha‒linolenic acid metabolism (Supplementary Fig. S6). Pathway enrichment analysis revealed that flavone and flavonol biosynthesis contribute to the different growth phases of A. sinensis . This pathway involves the biosynthesis of secondary metabolites, which are derived from the shikimate pathway . Phenolic compounds produced by the plant shikimate pathway are known to play multiple roles in plants . The precursor of quinic acid, 3-dehydroquinic acid, is the first intermediate with a carbon ring in the shikimate pathway. Therefore, among the 151 secondary metabolites, quinic acid, which has significantly increased in early-flowering samples, was selected as the representative marker. To verify the authenticity of these compounds, 188 leaf samples, including biennial unbolted and flowering A. sinensis from the same area in Min County, were collected in August 2018. QqQ/MS was used for the quantification of quinic acid. The MRM transitions and parameters applied in the study are listed in Supplementary Table S2. The average concentration of quinic acid in the unbolted samples was determined to be 0.27 ± 0.07 µg/mg, whereas that in the flowering samples was 0.66 ± 0.08 µg/mg, with a p value of 0.00043. It increased significantly during the flowering of A. sinensis . Thus, we can confirm that quinic acid is a potential marker for monitoring the early flowering phenomenon of A. sinensis . 

A. sinensis and A. Thaliana In Apiaceae plants, flowering is an essential condition for reproductive success. The rates of first and second early bolting of the untreated A. sinensis plants were 17.58%, and those treated with 33 mg/m 2 and 164 mg/m 2 QA were 24.22% and 33.59%, respectively. The first early bolting rate of plants treated with 328 mg/m 2 QA was 15.63%, and the second bolting rate was 16.41% (Fig. A). The results showed that quinic acid has the potential to promote early bolting and flowering in plants. Apparently, a low dose (33-164mg/m 2 ) of quinic acid promoted the early flowering of A. sinensis , but a high dose(328 mg/m 2 ) had no significant effect on flowering. With increasing concentrations of quinic acid, the flowering time of At increased (Fig. B and Supplementary Fig. S7A). At 52.08 ± 2.60 days, the untreated Con plants bolted at approximately the 13.50 ± 0.93 rosette leaf stage. After exposure to increasing concentrations of quinic acid from 20 to 200 µM, a significant reduction in leaf number was observed, with the plants flowering on average one leaf earlier. Additionally, increased concentrations of quinic acid (500 µM, 1000 µM) had no effect on flowering time or flowering rosette leaf number compared with those of the untreated plants. The flowering of At is regulated by various pathways, with many hormones involved in the flowering induction process of plants, among which GAs has been demonstrated to be the dominant plant hormone involved in the transformation of At . We used water treatment as a blank control, 100 µM gibberellin 3 (GA3) as a positive control, and 100 µM quinic acid (QA) as the experimental group. GA3 and QA significantly accelerated the flowering process of At Col-0 to varying degrees. Compared with those in the water group, the flowering times in the GA3- and QA-treated groups were 5 and 3 days earlier, respectively (Fig. C, D, E, and Supplementary Fig. S7B, C). 

Arabidopsis thaliana Qdh mutants Quinic acid is a carboxylated cyclohexanepolyol found in several plant sources. It is biosynthesized via the shikimic acid pathway from erythritose 4-phosphate (E4P) and phosphoenolpyruvate (PEP) condensation to form 3-deoxy-d-arabinoheptose-7-phosphate (DAHP) and then under the action of a series of enzymes to produce 3-dehydroquinic acid; then, under the action of quinate dehydrogenase (QDH), quinic acid is produced . Three At mutant strains (AT3G06350) were obtained from AraShare ( www.arashare.cn ) (Supplementary Table S3), and QDH homozygous Arabidopsis plants were identified and screened via PCR. qdh2 was mostly wild type or heterozygous, and qdh1 and qdh3 were homozygous mutant plants (Supplementary Fig. S8A). The transcript levels of QDH and the quinic acid content of qdh1 and qdh3 were markedly lower (Supplementary Fig. S8B). These lines presented a flowering phenotype that was delayed by approximately 3 days (Supplementary Table S4). Given that these phenotypes are caused by the observed lower quinic acid content, we supplied qdh1 and qdh3 seedlings with exogenous quinic acid at a concentration of 100 µM for 4 weeks. This treatment led to flowering occurring 2 days earlier. Exogenous GA3 was also added to the qdh1 and qdh3 mutant plants, and flowering occurred 3 days earlier (Fig. ). These data suggest that quinic acid is a positive regulator of flowering in At and is required at certain concentrations for normal development. 

Arabidopsis thaliana and its qdh1 mutant Flowering is a transition process from vegetative growth to reproductive growth, which is regulated by both endogenous and environmental signals. The gibberellin biosynthetic pathway is one of the six pathways that coordinate floral induction in At . Gibberellin signaling affects flowering through its interaction with well-known genes such as FLOWERING LOCUS T ( FT),LEAFY ( LFY ), and FLOWERING LOCUS C ( FLC ), as well as via crosstalk with other phytohormone signaling pathways, including the JA pathway . Moreover, with respect to the A. sinensis leaf metabolome pathway analysis results, it was especially interesting that alpha-linolenic acid metabolism impacted flowering. JA, a lipid-derived phytohormone, is derived mainly from the alpha-linolenic acid metabolism pathway . Therefore, to determine whether quinic acid participates in the GA‒JA interaction pathway, we examined the transcription factor expression of FT, SOC1 (SUPPRESSOR OF OVEREXPRESSION OF CONSTANS 1), LFY, FLC, FRI (FRIGIDA), CO (CONSTANS), MYC2, MYC3, MYC4, JAZ1, LOX2, GA20OX2, RGA, GAI, GID1A, GID1B and GID1C , etc., in wild-type At . At Col-0 plants were grown on medium for 10 days, then exogenously induced with 100 µM quinic acid, and whole plants were removed at 1, 7 and 14 days after treatment to analyze the transcription levels of key factors in the flowering pathway. The expression of FT was upregulated (4.95- and 5.67-fold compared with the untreated group, p < 0.05) after quinic acid induction for 1 and 7 days. LFY was upregulated (9.20- and 3.01-fold compared with the untreated group, p < 0.05) under quinic acid induction for 7 and 14 days. Quinic acid had no significant effect on the transcriptional regulation of SOC1 . Short-term treatment had no significant effect on the flowering repressor FLC , and FLC transcription was downregulated at 14 days (0.17-fold compared with the untreated group, p < 0.05). In addition, the main activator of FLC, FRI, had a significant regulatory effect only at the early stage of treatment, suggesting that the QA treatment had relatively little effect on FLC-mediated inhibition of flowering. The transcription of the main FT activator CO was upregulated (1.64-fold compared with the untreated group, p < 0.01) in the early stage of quinic acid treatment, but the regulatory effect of continuous treatment was not significant (0.86- and 1.07-fold compared with the untreated group, p > 0.05). The JA-activated transcription factors MYC2,MYC3 , and MYC4 redundantly regulate flowering under both LD and SD conditions. MYC2 and MYC3 suppress FT . We then tested whether quinic acid affects transcript levels in Col-0 At . qRT‒PCR analysis revealed that quinic acid treatment had little effect on the transcription of MYC4 but significantly downregulated the transcription of MYC2 and MYC3 (0.05 and 0.12, respectively, in the untreated group compared with the untreated group; p < 0.01). Therefore, we speculated that the regulation of FT transcription levels after quinic acid treatment is initially regulated by CO and then is regulated mainly by MYC2 and MYC3 under continuous treatment. The GA synthesis pathway is regulated mainly by the genes GA20OX, GA30OX , and GA2OX , and the signal transduction process is realized mainly by GA binding to the pocket structure of the receptor GIBBERELLIN INSENSITIVE DWARF1 ( GID1 ) and inducing changes in the Della domain. Della and MYC2 competitively bind JAZ1 proteins. At low GA levels, Della binds to JAZ1 and releases MYC2 to activate the downstream JA reaction. When the GA concentration increases, Della degradation is triggered, and JAZ1 is released. JAZ1 interacts with MYC2 , thus inhibiting the response of MYC2 to the JA pathway . Della can also participate in signaling processes by stabilizing MYC3 and interacting with JAZ . In this experiment, Col treated with 100 µM quinic acid for 1 day exhibited higher expression of GA20OX2 and GID1A (the receptor of GA) (1.70- and 1.99-fold compared with the untreated group, p < 0.05) and downregulation of GAI (GA response inhibitor, Della ) (0.39-fold compared with the untreated group, p < 0.01) (Fig. and Supplementary Table S5). In the qdh1 mutants, quinic acid induction was consistent with the trend in the wild type. The transcription levels of FT and LFY in the qdh1 At mutant were lower than those in Col-0 At . The low transcription level of FT in the mutant gradually removed with increasing plant growth, but the inhibition of LFY transcription in the mutant remained unchanged. After quinic acid treatment, the expression of FT and LFY was upregulated to promote flowering. For the key factors MYC2,MYC3,JAZ ( JAZ1),GID and Della ( GAI ), quinic acid also had compensatory effects, and the transcription levels were adjusted to those of the wild type At , thus alleviating the late flowering phenomenon of the qdh1 mutant plants (Supplementary Fig. S9 and Supplementary Table 6). 

qdh1 mutant The proteins LOX2, GAI and GID1A, which affect flowering in At , were examined via WB. The expression of GAI was downregulated (0.50- and 0.70-fold compared with the untreated group, p < 0.05) under quinic acid induction for 7 and 14 days, whereas that of GID1A was upregulated (1.88- 1.40-fold compared with the untreated group, p < 0.05). LOX-2 was downregulated (0.45-fold compared with the untreated group, p < 0.01) under quinic acid induction for 7 days, but under quinic acid induction for 14 days, its expression level increased to 12.07-fold compared with the untreated group ( p < 0.01). Compared with that in the Col-0 control group, the expression of the LOX2 and GAI proteins in the qdh1 mutant At was upregulated, and the expression of the GID1A protein was reduced. The effect of the quinic acid treatment group on protein expression was the same as that of the wild-type control group. We also observed the effects of exogenous GA3 and methyl jasmonate on the expression of these proteins and found that the effect of quinic acid was similar to that of GA but not as strong as that of methyl jasmonate (Fig. , Supplementary Fig. S10). 

A. sinensis seedlings The mRNA expression levels of 13-LOX, AOS, AOC, MYC2-1, MYC2-2, MYC2-3, MYC4, JAZ1-1, JAZ1-2, GA20OX, GA3OX and GA2OX in sterile seedlings of A. sinensis treated with quinic acid for 7 days were analyzed. Quinic acid treatment affected the expression of 13-LOX, GA20OX and MYC2 (1.41-, 2.55-, and 1.58-fold, respectively, compared with the untreated group; p < 0.05). Further dynamic point analysis revealed that quinic acid had a temporal effect on 13-LOX expression, but this trend was different from that of At . Quinic acid upregulated the expression of 13-LOX at the initial stage of treatment and downregulated the expression of 13-LOX with increasing duration of treatment. The expression of GA20OX in the GA pathway was upregulated, whereas that of MYC2 in the JA pathway was downregulated (Fig. ). The contents of JA and GA3 in sterile seedlings of A. sinensis subjected to different treatments were also calculated via ELISA. The values of JA in the untreated group, GA3-treated group, JA-treated group, and quinic acid-treated group were 1.91 ± 0.03, 1.94 ± 0.04, 2.00 ± 0.01, and 1.99 ± 0.09 ng/g, respectively. The treated groups did not exhibit significant differences from the control ( p > 0.05). The content of GA3 in the GA3-treated group was significantly lower (190.02 ng/g, p < 0.01) than that in the untreated group (202.99 ng/g); however, the levels in the JA-treated group and the quinic acid-treated group were significantly higher (231.35 and 210.87 ng/g, respectively; p < 0.05). These results indicated that intervention with exogenous GA and JA can affect the genes involved in the synthesis of both. Quinic acid treatment yielded similar gene regulation to GA treatment and promoted the accumulation of GA3. 

Early flowering is a phenomenon in which the vegetative body of a plant enters reproductive growth before it is fully grown. The early flowering phenomenon is known to reduce medicinal plant production and affect the active ingredients of medicinal materials, particularly Umbelliferae plants. The content of the characteristic active compound ligustilide decreased significantly in the roots of flowering A. sinensis (Supplementary Fig. S11). There have been several reports on control methods, including vernalization, LD conditions, intercropping, and chemical regulation, for preventing the early flowering of A. sinensis during cultivation . In production area of Gansu Province, brassinolide treatment was used before the A. sinensis seedlings were transplanted into the field. In Brassicaceae crop production, to prevent early bolting, exogenous hormones, such as cyanin (MH), B9, triiodobenzoic acid, nicotinic sulfate, CPPU and polybulobuzole (PP333), are sprayed at appropriate concentrations before bolting. This could weaken the sensitivity of plants to vernalization and bolting, thereby delaying reproductive growth. However, these hormones do not have a significant inhibitory effect on the early flowering of A. sinensis during production, and more evidence is needed to determine their potential toxicity and effects on the medicinal properties of A. sinensis roots. Thus, more effective growth regulators need to be identified. We attempted to use a metabolomics method based on liquid chromatography‒mass spectrometry (LC‒MS) to identify potential hormone-like substances from secondary metabolites in A. sinensis . During plant growth, the existence of various forms of endogenous hormones plays a key role in flowering, and leaves differentiation determine flowering time . The plant floral transition is mainly the transition from the leaf primordium to the flower primordium, and the leaf is the organ most easily disturbed by external factors. By performing leaf metabolic analysis in early-flowering A. sinensis , we found that the differentially abundant metabolites included many organic acids with low molecular weights. These compounds are enriched in two pathways: the alpha‒linolenic acid metabolism pathway and the flavone and flavonol biosynthesis pathway. The alpha-linolenic acid metabolism pathway leads to the synthesis of JA, which is a physiological molecule involved in a wide range of plant responses, from growth, flowering, and senescence to defense against abiotic and biotic stress . A study in tomato revealed that JA levels peak two days before flower opening . JA and its related derivatives are biosynthesized and act in different compartments of a plant cell. The first step occurs in plastids as α-linolenic acid, which forms cis--12-oxophytodienoic acid via 13-LOX, AOS and AOC. The right configuration of JA is exported by the JA transporter JAT1 on the plasma membrane and upon release into the cytosol . Most genes encoding the enzymes involved in JA biosynthesis are also inducible by JA . In our validation experiments on in vitro-grown A. sinensis , JA induced the expression of the genes encoding 13-LOX, AOS and AOC, suggesting the same feedforward regulation. Our previous study revealed several genes related to the GA signaling pathway with changes in expression during the early flowering of A. sinensis . We found that JA upregulated the expression of GA20ox and GA2ox, which are the rate-limiting enzymes in the GA biosynthesis pathway. This regulation, unlike exogenous GA3 treatment, upregulated the expression of GA2ox but downregulated that of GA20ox. It should be noted that studies of GA biosynthesis gene expression in At have shown that AtGA20ox1 and AtGA3ox1 expression is highly elevated in the context of GA deficiency, whereas these genes are downregulated after the application of bioactive GAs. In contrast, the expression of the GA-inactivated genes AtGA2ox1 and AtGA2ox2 is upregulated upon GA treatment . The GA biosynthesis gene expression trend in A. sinensis is consistent with that in Arabidopsis . Moreover, the content of GA3 increased in sterile seedlings of A. sinensis in response to exogenetic JA treatment. These data suggest that JA signaling crosstalk with GA signaling antagonizes each other in regulating flowering in A. sinensis . Flavone and flavonol biosynthesis pathways synthesize flavonoids, which are important secondary plant metabolites that confer resistance to biotic and abiotic stress . Among the biomarkers enriched in this pathway, we identified a compound with a similar structure and molecular weight to those of JA, namely, quinic acid. Quinic acid is one of the precursors for the synthesis of active phenolic compounds. It is a secondary metabolite that is widely distributed in plant tissues. The amount of quinic acid present in plants is not constant. The content of quinic acid in tea stems is higher than that in new shoots. In tomato, the utilization of quinic acid can suppress plant disease development . Quinic acid also protects eggplant from damage caused by western flower thrips . However, the mechanism of its action on plant growth has rarely been reported. Our findings showed that, within a certain concentration range, quinic acid promoted the flowering of the Umbelliferae plant A. sinensis , and the degree of the effect and the action process were similar to those of JA. Quinic acid can upregulate the expression of the gibberellin synthesis pathway gene GA20OX and the GID1 receptor, and downregulate the expression of the inhibitory factor DELLA, thus affecting the levels of the flowering integration factors FT and LFY and accelerating plant flowering. Moreover, some interactions occurred between the hormone networks. Quinic acid treatment also significantly altered the expression of the genes encoding LOX, JAZ1, and MYC family members (MYC2 and MYC3) in the JA pathway. The protein expression GID1, DELLA (GAI) and LOX2 was consistent with the expression of their corresponding transcripts. Therefore, quinic acid promotes plant flowering mainly by regulating the expression of key genes and proteins of the GA and JA pathways (Fig. ). Plant metabolism has evolved to maintain an intricate balance between growth and defense . Fungi represent an important component of the plant microbiome and can play important pathogenic or beneficial roles in plant growth and reproduction . In the early-flowering stage of A. sinensis , the Cladosporium fungus was significantly enriched and highly abundant. The abundance of this genus was significantly correlated with the plant secondary metabolite quinic acid (unpublished data). Therefore, in A. sinensis , quinic acid targets hormonal signaling networks not only for plant defense (JA) but also for growth (GA3). This manipulation can be performed directly by disrupting the balance of plant metabolism or indirectly by fungi that produce quinic acid with functions similar to those of plant hormones. The black arrows or linkers indicate positive or negative effects. The ellipse indicates the biosynthesis pathway, and the square indicates the transduction pathway. Red indicates upregulation after treatment with exogenous 100 µM quinic acid, and green indicates downregulation after treatment with exogenous 100 µM quinic acid. 

In summary, the early flowering phenomenon of A. sinensis is the result of metabolic disruption. The balance of metabolic pathways was perturbed, and the levels of the secondary metabolite quinic acid increased. Quinic acid mobilized the biosynthesis of the plant hormones JA and GAs by regulating related genes. With the accumulation of JA and GA3, downstream signaling pathways are activated, and plant growth accelerated, resulting in bolting and flowering. These findings highlight the potential application of quinic acid as a flowering-promoting molecule and expand our knowledge of early-flowering inhibitors to ensure the quality of Umbelliferae medicinal plants. 

Below is the link to the electronic supplementary material. Supplementary Material 1 

