Method for increasing content of volatile components in rosemary

Abstract

The invention belongs to the technical field of rosemary planting, and particularly relates to a method for increasing the content of volatile components of rosemary, and gibberellin is applied to the rosemary. According to the method, gibberellin is applied to rosemary, so that the content of volatile components in rosemary plants is increased, such as the content of any one of alpha-pinene, o-cymene, camphene, sabinene hydrate, linalool and camphor.

Description

Technical Field

[0001] The invention belongs to the field of plant planting, in particular to the technical field of rosemary planting, and particularly relates to a method for increasing the content of volatile components in rosemary. Background Art

[0002] Rosemary (Salvia rosmarinus Schleid.), also known as sea dew and tansy, is a shrub belonging to the dicotyledonous plant family, Lamiaceae. The plant's native distribution is primarily along the Mediterranean coast of North Africa. Its cultivation and use subsequently spread to Europe and the Americas, where it was often planted around churches and considered a tribute. It was introduced to China from the Western Regions, but initially used solely for its fragrance. Successful cultivation experiments in the 1980s marked the beginning of the domestic rosemary cultivation market. Rosemary was later categorized based on its agricultural characteristics into varieties such as upright white rosemary, needle-leaved rosemary, creeping rosemary, Australian rosemary, and variegated rosemary.

[0003] Rosemary is a shrub that can grow up to about 2 meters tall. Rosemary extract, primarily derived from its leaves, is a common herbal product. Fresh rosemary leaves are often used in Europe as a culinary flavor enhancer. Essential oils and other flavors are extracted from rosemary leaves and used as antioxidants and antibacterial agents in food processing and cosmetics. With technological advancements, rosemary's applications are becoming more widespread. In medical applications, rosemary extract has the potential to dilate blood vessels and serve as an adjunct to cancer chemotherapy.

[0004] Rosemary volatile components are the main components of rosemary essential oil, but the overall content of volatile components is relatively small. Summary of the Invention

[0005] The purpose of the present invention is to provide a method for increasing the content of volatile components of rosemary, so as to solve the problem of low content of volatile components of rosemary in the prior art.

[0006] The present invention adopts the following technical solutions:

[0007] A method for increasing the content of volatile components in rosemary, comprising applying gibberellins to the rosemary.

[0008] Preferably, the concentration of the gibberellin is 40-80 mg / L.

[0009] Preferably, gibberellins are applied to rosemary in March, April and May each year.

[0010] Preferably, the volatile component is any one or more of α-pinene, o-cymene, camphene, hydrated sabinene, linalool, and camphor.

[0011] Preferably, the volatile components are hydrated sabinene, o-cymene, linalool, and camphor, and the concentration of the gibberellin is 40 mg / L.

[0012] Preferably, the volatile component is α-pinene and the concentration of the gibberellin is 80 mg / L.

[0013] As a preference, spraying is performed once a month, and the amount of each spraying is based on the amount of water droplets falling from the leaves. By implementing the above technical solution, the present invention has the following beneficial effects:

[0014] The invention increases the content of volatile components in rosemary plants, such as the content of any one of α-pinene, o-cymene, camphene, hydrated sabinene, linalool and camphor, by applying gibberellins to rosemary. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] Figure 1 This is a trend chart showing the effects of different concentrations of gibberellins on rosemary plant height;

[0016] Figure 2 The effect of different concentrations of gibberellins on the height and crown width of rosemary;

[0017] Figure 3 The effect of different concentrations of gibberellins on the length and width of rosemary leaves;

[0018] Figure 4 It is the aboveground and underground biomass of rosemary in June;

[0019] Figure 5 is the total fresh weight and dry weight of rosemary;

[0020] Figure 6 The changes of antioxidant enzyme activities of rosemary from April to June;

[0021] Figure 7 This is the change chart of MDA content in rosemary from April to June;

[0022] Figure 8 GC-MS for volatile components in rosemary;

[0023] Figure 9 This is the percentage of the main volatile components of rosemary at different concentrations;

[0024] Figure 10 is the PCA score graph;

[0025] Figure 11 is the number of differentially expressed genes in the transcription factor family;

[0026] Figure 12 Volcano plot of differentially expressed genes;

[0027] Figure 13 This is the heat map of differentially expressed genes at the hierarchical level;

[0028] Figure 14 is the expression of related genes under the influence of gibberellin;

[0029] Figure 15 Perform hierarchical clustering for the expression levels of sample genes;

[0030] Figure 16 Screening for outliers and soft threshold selection;

[0031] Figure 17 This is the module hierarchical clustering tree diagram. DETAILED DESCRIPTION

[0032] The present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments.

[0033] This specific embodiment is merely an explanation of the present invention and is not intended to limit the present invention. After reading this specification, those skilled in the art may make non-creative modifications to this embodiment as needed. However, as long as such modifications are within the scope of the claims of the present invention, they are protected by patent law.

[0034] Example 1 Effect of exogenous gibberellin on the growth and development of rosemary

[0035] 1.1 Experimental Materials and Methods

[0036] 1.1.1 Experimental Materials

[0037] The plant species used in this experiment was erect rosemary, and the seedlings were purchased from Sichuan Chengdu Qianfeng Seedling Planting Co., Ltd. Five gibberellin concentration gradients were set, with GA3 concentrations of G1 (40 mg / L), G2 (80 mg / L), G3 (160 mg / L), G4 (320 mg / L), G5 (450 mg / L) and a blank control group CK. The hormone was sprayed three times throughout the growth period, ensuring that the leaves were sprayed evenly until water droplets dripped from the leaf surface.

[0038] Table 1 Experimental material information

[0039] Group Applied gibberellin concentration (mg / L) CK 0 G1 40 G 2 80 G 3 160 G 4 320 G 5 450

[0040] 1.1.2 Daily Management

[0041] In March, April and May 2023, the rosemary seedling materials planted in the nursery were sprayed with exogenous gibberellins, using a randomized block experimental design with 5 repetitions. Apply compound fertilizer, cover with thin soil and transplant into pots. Weeding can ensure that the plants have a good growth environment, so daily weeding needs to be maintained during the experimental period, and weeding is expected to be carried out once every 10-14 days. Irrigation method: The irrigation method used in this experiment is artificial sprinkler irrigation. The plants are placed outdoors for sunlight and rainwater irrigation for several consecutive days of sunshine. Artificial sprinkler irrigation is carried out when the soil is dry. The amount of irrigation each time is adjusted according to the water demand during the plant growth period to maintain normal growth of the plant.

[0042] 1.1.3 Test instruments

[0043] The instruments used in the experiments in this chapter are vernier caliper JS20F150, Zhejiang Deqing Shengtaixin Electronic Technology Co., Ltd., horizontal refrigerator-freezer conversion cabinet BC / bd-519HAN Qingdao Haier Special Freezer Co., Ltd., vertical refrigerator SC-242D Qingdao Haier Special Freezer Co., Ltd., electronic balance BT25S Sartorius Scientific Instruments (Beijing) Co., Ltd., multifunctional enzyme label detector Synergy HTX American Boten Instrument Co., Ltd., ultra-low temperature refrigerator Thermo900 Thermo Fisher Scientific (China) Co., Ltd., pipette Eppendorf research plus German Eppendorf Company, water bath HH-4PD Changzhou Jintan District Xicheng Xinrui Instrument Factory, high-speed refrigerated centrifuge Eppendorf Centrifuge 5424R German Eppendorf Company, high-speed desktop centrifuge Eppendorf Centrifuge 5805C (Eppendorf, Germany); Bioprep-24R (Hangzhou Aosheng Instrument Co., Ltd.); Ice Maker SIM-F140AY65-PC (Panasonic Corporation, Japan); Vacuum Freeze Dryer FD-1A-80 (Shanghai Hefan Instrument Co., Ltd.); Vacuum Pump AP-9925 (Tianjin Aotesense Instrument Co., Ltd.); Ultra-High Performance Liquid Chromatograph ACQUITY UPLC H-CLASS (Waters, USA).

[0044] 1.2 Experimental methods

[0045] 1.2.1 Determination of agronomic traits

[0046] When measuring phenotypic traits, three plant clusters were randomly selected from each treatment and replicate. The following indicators were measured:

[0047] Plant Height (cm): Use a tape measure to measure the height of the rosemary plant from the ground to the top.

[0048] Crown width (cm): The maximum diameter of the above-ground part was measured using a vernier caliper.

[0049] Leaf length (mm): The lengths of the three largest leaves of the selected plants were measured using a vernier caliper.

[0050] Leaf width (mm): The width of the three largest leaves of the selected plants was measured using a vernier caliper.

[0051] Number of first branches: the number of first branches on the above-ground part of the plant.

[0052] Fresh weight (g): In the last period of the experiment in June, three plants were randomly selected, the roots of the whole plants were washed, and the weight was weighed on a balance.

[0053] Dry weight (g): After measuring the fresh weight, place the sample in a well-ventilated room maintained at 25°C to maintain constant weight, and then weigh it using a balance.

[0054] 1.2.2 Determination of antioxidant enzyme indicators and malondialdehyde (MDA) content

[0055] From April to June 2023, six groups of rosemary leaves were collected monthly and mixed for determination of antioxidant enzyme activity and malondialdehyde (MDA) content. Superoxide dismutase activity was determined using the nitroblue tetrazolium photoredox (NBT) method; peroxidase activity was determined using the guaiacol oxidation method; ascorbate peroxidase and catalase were measured according to Chen Minmin's experimental method; and MDA content was determined using a thiobarbituric acid colorimetric method.

[0056] 1.3 Results and Analysis

[0057] 1.3.1 Growth dynamics observation

[0058] Beginning in March 2023, measurements of plant height, stem diameter, leaf length, and leaf width were taken for each of the six treatments. The first branch count was measured when the plants began to branch. During the first observation in March, the average plant height was 34.60 cm, the average crown width was 354.13 cm², and the average leaf length and width were 28.28 mm and 3.18 mm, respectively.

[0059] 1.3.1.1 Variation characteristics of rosemary plant height and crown width under different gibberellin concentrations

[0060] During the experiment, the height of rosemary plants maintained a steady growth trend, and the height of each treatment was CK<G5<G4<G1<G3<G2 (see Figure 1, Table 1). The plant height grew fastest from May to June, followed by March to April. The rosemary plants after the five treatments were all taller than the CK group. After the first spraying of hormones (in April), the plant height of the plant treated with G1 (40 mg / L) concentration reached 44.73 cm, 22% higher than the CK control group, and the difference between the G1 concentration and the CK control group was the greatest during this period. After three months of continuous spraying, the rosemary plant treated with G2 (80 mg / L) was the tallest, reaching 56.2 cm, which was 1.18 times that of the control group during the same period (see Figure 2 ) Gibberellic acid can promote plant growth through the germination of plant lateral buds and the elongation of stems. In April, high concentrations of gibberellins G3 (160 mg / L), G4 (320 mg / L), and G5 (450 mg / L) inhibited the growth of plant branches, which were inhibited by 13.4%, 38.4%, and 14.7% respectively compared with the CK group. In the later period, the concentrations of hormones used in this experiment can promote the growth of rosemary plants. The comparison of the crown width of various treatments in June is: CK<G1<G5<G2<G4<G3 (see Table 2). During the growth period from March to April, G1 had the fastest growth rate and showed a slow growth trend in the later period. The growth trend of the G3 group increased after the second spraying. In June, the crown width of the plants treated with this group was the largest, which was 1.5 times that of the CK group during this period.

[0061] Table 2 Comparison of plant height and crown width indices of rosemary at different stages under different concentrations of gibberellins

[0062]

[0063] 1.3.1.2 Variation of Rosemary Leaf Index under Different Gibberellic Acid Concentrations

[0064] In June, the leaves of rosemary plants were all over 33 cm long and 3.5 cm wide (see Table 3, Figure 3 In April, leaf lengths of G2, G3, and G5 showed significant differences compared to the CK group, increasing by 13.32%, 11.57%, and 7.4%, respectively. Leaf widths of G2, G3, G4, and G5 were significantly higher than those of the CK group. In May, the leaf index of all treatments increased significantly compared to the control group. In June, the G5 treatment inhibited leaf width by 1.9% compared to the CK group. All other treatments showed a significant improvement in leaf width.

[0065] Table 3 Comparison of rosemary leaf indices at different stages under different concentrations of gibberellins

[0066]

[0067] 1.3.1.3 Variation characteristics of rosemary biomass under different gibberellin concentrations

[0068] As the plant grows, the biomass of rosemary shows an upward trend. From the first spraying of hormones, the biomass continues to accumulate. At the harvest time in June, the weight of the root system first increases and then decreases with the increase of gibberellin concentration. The root weight of the G2 group is the heaviest, and is 72% higher than the root weight of the CK control group during the same period. The fresh weight of the aboveground part also shows a trend of first increasing and then decreasing with the increase of hormone concentration. The weight of branches, stems and leaves of each group has increased, which are 39.55%, 37.65%, 35.64%, 30.87% and 25.66% higher than those of the CK group, respectively, which are significantly higher than those of the CK group (see Figure 4 ).

[0069] The dryness rate of rosemary plants did not change with the change of hormone concentration. There was no significant difference between the groups. The dryness rate remained above 63% (see Figure 5 ).

[0070] 1.3.2 Determination of antioxidant enzyme activity and MDA content

[0071] The study found that when the gibberellin concentration was 0 mg / L, the APX activity of rosemary plants showed an upward trend. When gibberellin was applied, the APX enzyme activity showed a trend of first increasing and then decreasing. APX enzyme activity was highest when 40 mg / L gibberellin was sprayed at harvest time, which was 3.6 times that of the treatment without gibberellin. Among them, APX activity was highest after the second spraying of 80 mg / L, which was 6.67 times that of the treatment without gibberellin during the same period. SOD activity was highest after three sprays of 320 mg / L gibberellin, which was more than 1.5 times that of the treatment without gibberellin during the same period. After spraying gibberellin, the SOD activity of the plants first increased and then decreased with the gibberellin concentration.

[0072] After the third spraying, as the gibberellin concentration increased, the POD activity showed a trend of first increasing and then decreasing. In June, the POD activity at G3 concentration was the highest, more than 5 times that of the treatment without gibberellin. And with the increase in the number of spraying, the enzyme activity showed a trend of first increasing and then decreasing. In each period, the rosemary CAT activity showed a trend of first increasing and then decreasing with the increase in gibberellin concentration. And in each period, the rosemary CAT activity was the highest when the gibberellin concentration was sprayed. After three sprayings, the CAT activity at G2 concentration was 3.3 times that of the treatment without gibberellin (see Figure 6 ).

[0073] The MDA content showed a downward trend with the increase in the number of sprayings, and the MDA content of the plants treated with G2 concentration was the highest in each period, which was 1 times, 1.5 times, and 1.2 times that of the plants without gibberellin treatment. In general, the MDA content of rosemary plants was the highest after being sprayed once with 80 mg / L gibberellin (see Figure 7 ).

[0074] Example 2 Effect of exogenous gibberellin on the content of volatile components of rosemary

[0075] 2.1 Experimental Materials

[0076] Select the rosemary plant samples from 1.1.1 and collect them in June 2023. Each time, select leaves from the upper, middle, and lower parts of the plant and mix them together before bagging and sealing. Six groups (CK, G1, G2, G3, G4, and G5) were sampled, with three replicates per group.

[0077] 3.1.2 Instruments and reagents

[0078] The instruments used in this example are shown in Table 4, and the reagents used are shown in Table 5.

[0079] Table 4 Experimental instruments

[0080]

[0081] Table 5 Experimental reagents

[0082]

[0083] 2.2 Experimental methods

[0084] 2.2.1 Material pretreatment

[0085] After vacuum drying, the leaves were ground into powder using a grinder. The powdered sample was then placed into a 10-ml vial and sealed with a crimp seal. The vial was then placed into a headspace sample tray for analysis. High-performance gas chromatography (Agilent Technologies 7890B-5977B) was used to qualitatively analyze the volatile components from different parts of the rosemary plant.

[0086] 2.2.2 Chromatographic-Headspace Conditions

[0087] The initial temperature of the chromatogram was 35°C, held for 2 minutes, then increased to 130°C at 3°C / min, then increased to 250°C at 25°C / min, held for 3 minutes, and finally cooled to 35°C. Headspace conditions: equilibrated at 80°C, held for 30 minutes.

[0088] 2.2.3 Other conditions

[0089] The oven temperature was maintained at 80°C, the cycle temperature was 90°C, and the transfer line temperature was 100°C. GC cycle time was 70 min, separation ratio was 1:5, flow rate was 1 mL / min, M / Z was 35–600, EI was 70 eV, MS ion source temperature was 230°C, and detector temperature was 260°C.

[0090] 2.2.4 Data Processing

[0091] Excel 2021 and graphpad 8.0.2 were used to process the experimental data and draw charts.

[0092] 2.3 Results

[0093] 2.3.1 Analysis of volatile components of rosemary

[0094] GC-MS was used to analyze the volatile components of rosemary, thereby obtaining the total ion current of the sample (such as Figure 8 The mass spectral data of each group were searched through the NIST 14 mass spectral database and combined with similar references to identify 21 compounds corresponding to all peak positions. The relative content of each compound in the total volatile components was calculated by peak area normalization (see Table 6).

[0095] Table 5 shows that 21 compounds were detected in the volatile components of rosemary. The main components were alpha-pinene (33.40%), eucalyptol (31.59%), camphene (7.60%), beta-pinene (6.73%), beta-myrcene (2.14%), gamma-terpinene (2.02%), linalool (1.28%), and camphor (1.10%). The content of hydrated sabinene (5-Isopropyl-2-methylbicyclo[3.1.0]hexan-2-ol) was 0.95%. In the same group of experimental samples, two extremely close peak times may appear in a short period of time, and it is speculated that the two may be isomers.

[0096] Table 6 GC-MS compound ratio

[0097]

[0098] More than 60% of rosemary volatile substances are monoterpenes, among which eucalyptol and α-pinene are relatively high. The differences in rosemary volatile substances after treatment with different concentrations of gibberellins are as follows: Figure 9Comparison of GC-MS analysis results between different groups revealed that after applying different concentrations of gibberellins, α-pinene and eucalyptol remained the two compounds with the highest concentrations within the group. The study found that spraying low concentrations of gibberellins significantly increased the levels of some compounds, such as linalool, camphor, and 5-isopropyl-2-methylbicyclo[3.1.0]hexan-2-ol. However, with the subsequent application of high gibberellins, these compounds initially increased and then decreased with increasing gibberellin concentrations. The levels of α-pinene, camphene, and β-pinene increased slightly after gibberellin application, reaching their maximum at 80 mg / L. After applying different concentrations of gibberellins, the content of volatile components of rosemary will change differently due to the application of gibberellins. The content of α-pinene shows a trend of first increasing and then decreasing with the increase of gibberellin concentration. Among them, the content of α-pinene at G2 concentration is the highest, 11.9% higher than that of the control group; o-cymene and α-pinene show similar change trends - with the increase of the applied hormone concentration, they show a trend of first increasing and then decreasing. Among them, the content of o-cymene in G1 is the highest, 5.7% higher than that of the control group, and it decreases by 15.7% at G5 concentration; the synthesis of phellandrene is inhibited at the concentration of G1, and its relative content is 35.5% lower than that of the CK group; the content of camphor in rosemary at the concentration of G1 is 38% higher than that of the control group, while it decreases by 9.2% at the concentration of G2. Example 3 Analysis of rosemary's response to gibberellins based on comparative transcriptome

[0099] In this example, rosemary sprayed with different concentrations of gibberellins was used as experimental research material, and the RNA-seq method was used to compare the differentially expressed genes in rosemary in response to changes in gibberellins concentration, providing a theoretical basis for exploring the mechanism of rosemary's response to changes in exogenous gibberellins concentration.

[0100] 3.1 Experimental Materials

[0101] Select the rosemary plant samples in 2.1.1 and collect them in June 2023. Each time, select leaves from the upper, middle and lower parts of the plant and mix them for bagging and sealing. Figure 6 .

[0102] Table 7 Grouping of experimental materials

[0103]

[0104] 3.2 Experimental methods

[0105] 3.2.1 RNA extraction, library construction, and sequencing

[0106] The polysaccharide and polyphenol plant total RNA extraction kit was used to extract total RNA from rosemary plants, and the concentration and purity of the RNA were tested. The integrity of the RNA was determined by agarose gel electrophoresis before library construction. After the library construction was completed, the concentration of the library was accurately measured to ensure that the library quality met the requirements of downstream high-throughput sequencing. A fluorescence photometer was used for basic quantitative analysis, and the library was adjusted to a final concentration of 1.5 ng / μl. Next, the Agilent 2100 bioanalyzer was used to accurately detect the size of the insert fragments in the library. After confirming that the size of the insert fragment met the preset standard, the effective concentration of the library was accurately quantified by real-time quantitative PCR (qRT-PCR) to ensure that its effective concentration exceeded 1.5 nanomoles to ensure the quality of the library.

[0107] 3.2.2 Filtering of clean reads

[0108] The original sequencing results may contain some low-quality data. In order to ensure the quality and reliability of subsequent data analysis, the original data needs to be preprocessed to remove those low-quality read information.

[0109] 3.2.3 Reference genome alignment

[0110] In molecular biology, the sequence fragments generated during sequencing are randomly fragmented mRNAs. To accurately identify the genes from which these fragments originate, a critical step is to align the quality-controlled sequence data, known as clean reads, to a known reference genome using an alignment algorithm. HISAT2 software is widely used for this alignment process because it provides fast and accurate alignment results.

[0111] 3.2.4 Quantitative Gene Expression Analysis Based on the mapping information of genes to the reference genome, a detailed count of the number of sequence reads covering the start and end intervals of each gene (including predicted novel genes) was performed. This process utilized the featureCounts program within the subread tool suite to perform a series of precise filtering operations. These operations were designed to exclude sequence reads with an alignment quality score below 10, eliminate sequence reads that were not paired with the reference genome, and filter out sequence reads that mapped to multiple regions of the genome, thereby ensuring the accuracy and reliability of the results.

[0112] 3.2.5 Difference Analysis

[0113] After completing quantitative gene expression analysis, the next critical step is to perform a detailed statistical evaluation of the resulting expression data to identify genes whose expression levels differ significantly between the compared conditions or states. This statistical analysis process typically involves three key steps: first, normalization of the initial read count data is performed to correct for differences in sequencing depth and ensure data consistency and comparability; second, statistical methods are used to construct hypothesis tests and calculate corresponding probability values (p-values) to assess whether the observed expression differences are statistically significant; third, given that transcriptome data analysis often involves analyzing a large number of genes simultaneously, which can lead to the accumulation of false-positive results, a multiple hypothesis testing process is required to calculate the false discovery rate (FDR) to effectively control the proportion of false positives. Generally, a gene is considered to have a significant expression difference if its expression level differs by twofold or more between the two compared sample groups. Furthermore, because simultaneous analysis of multiple genes across the entire transcriptome increases the risk of false-positive results, an adjusted p-value (padj) is introduced to precisely control the proportion of false positives. The screening criteria for differentially expressed genes were |log2(FoldChange)|≥1&padj≤0.05. When both conditions were met, the genes were considered to be significantly differentially expressed.

[0114] 3.2.6 Differential gene enrichment analysis

[0115] GO functional enrichment analysis and KEGG pathway enrichment analysis were performed on the differentially expressed genes.

[0116] 3.2.7 WGCNA Analysis

[0117] WGCNA (weighted gene co-expression network analysis) is a standard method for constructing gene co-expression networks in systems biology. Using the WGCNA algorithm, widely used in biomedical research, we calculate the dissimilarity coefficients between nodes and construct a hierarchical clustering dendrogram to reveal the complex interactions between genes.

[0118] 3.2.8 Real-time fluorescence quantitative analysis

[0119] To validate the RNA-Seq results, eight differentially expressed genes were randomly selected from the GA-treated samples for quantitative PCR. Three biological replicates and three technical replicates were performed for each sample. The quantitative PCR and sample requirements were the same as for RNA-Seq. Reverse transcription was performed using 1 μl of Biomed Biotech Total RNA, 12.5 μl of 2*Taq PCR MasterMix, 0.5 μl of Forword Primer, 0.5 μl of Rever Primer, and 10.5 μl of ddH2O. The reaction protocol is shown in Table 8.

[0120] Table 8 Reverse transcription reaction procedure

[0121]

[0122] After RNA was reverse transcribed into cDNA, RT-qPCR reaction was performed using a fluorescent quantitative PCR kit on an enzyme-free 96-well plate. The PCR reaction mixture system for each well was 10 μl, consisting of TB Green Premix Ex TaqⅡ (2.4 μl), ForwordPrimer (0.2 μl), Rever Primer (0.2 μl), enzyme-free ddH2O (1 μl) and cDNA template diluted tenfold (1 μl). Each group of experiments maintained three biological replicates and three technical replicates. The PCR amplification cycle conditions were as follows: first, maintain 95°C for 5 minutes in the preheating stage, then perform 40 cycles of 95°C for 30 seconds and 60°C for 30 seconds in the polymerase chain reaction stage, and finally, the PCR run ended after 95°C for 15 seconds, 60°C for 1 minute, and 95°C for 15 seconds in the melting curve stage, and the Ct value was recorded for subsequent analysis. The GAPDH gene was used as the internal reference gene control, and 2 -△△Ct Gene expression was calculated using the RT-qPCR and RNA-Seq data visualization method. GraphPad Prism8 was used for plotting.

[0123] 3.3 Results and Analysis

[0124] 3.3.1 Quality evaluation of raw sequence data A total of 51,058,806, 39,264,268, 41,955,982, 42,231,571, 40,850,387, and 43,608,466 clean reads were screened out from the six groups of samples, respectively (Table 9).

[0125] Table 9 Original sequence quality evaluation table

[0126]

[0127] 3.3.2 Reference genome comparison

[0128] The mapping rates of read 1 and read 2 were calculated. The mapping rates of each type of sample to the reference genome were all above 85% (Table 10). The experimental data mapping rate met the standard, and the next experiment could be carried out.

[0129] Table 10 Reference gene alignment table

[0130]

[0131] 3.3.3 Analysis of gene expression levels

[0132] According to the FPKM value, 53,874 expressed genes were found in the gibberellin concentration gradient samples from the CK group to the G5 group, of which 2,761 genes were more highly expressed than those in the CK group after the application of gibberellin.

[0133] 3.3.4 Principal Component Analysis

[0134] Principal Component Analysis (PCA), as a commonly used multivariate statistical analysis method, is widely used to evaluate the differences between different groups and the similarities of samples within the same group. This method relies on linear algebra techniques and is designed to process and reduce the dimensionality of high-dimensional data, such as gene expression data, which may involve thousands of variables. In the process of data dimensionality reduction, PCA calculates the principal components of the data to extract the most critical information features. In this study, we used the PCA method to analyze the gene expression levels of all collected samples, where the gene expression levels were quantified in units of reads per kilobase per million (FPKM), in order to reduce the complexity of the data while retaining the most important variation information (see Figure 10 ).

[0135] 3.3.5 Prediction of differential transcription factors

[0136] Using rosemary transcription factors, we predicted and screened the differentially expressed transcription factors of rosemary. After the experimental treatment, a total of 53,873 differentially expressed genes were identified, which were distributed in 97 transcriptome families. The top 10 transcription factor families with the most differentially expressed genes were AP2 / ERF-ERF, MYB, bHLH, C2H2, NAC, WRKY, MYB-related, bZIP, GRAS, and C3H, with 221, 214, 207, 174, 173, 134, 110, 106, 106, and 97 differentially expressed genes, respectively. Figure 11 shown.

[0137] 3.3.6 Analysis of significantly differentially expressed genes

[0138] Using |log2(FoldChange)|≥1&padj≤0.05 as the screening criteria, genes with significant differential expression were screened. 3,726, 4,501, 4,124, 5,794, and 4,465 differentially expressed genes were screened in the five comparison groups, respectively. Among them, 1,842 genes were upregulated and 1,884 genes were downregulated in the G1 vs CK group, 2,495 genes were upregulated and 2,006 genes were downregulated in the G2 vs CK group, 2,230 genes were upregulated and 1,894 genes were downregulated in the G3 vs CK group, 2,956 genes were upregulated and 2,838 genes were downregulated in the G4 vs CK group, and 2,436 genes were upregulated and 2,029 genes were downregulated in the G5 vs CK group (see Table 11, Figure 12 ).

[0139] Table 11 Table of the number of genes with significant differences in expression in each group

[0140]

[0141] The differentially expressed genes were subjected to hierarchical cluster analysis. The heat map showed that the clustering divided the six groups into three categories, of which G1 and G2 were in one category, G3, G4, and G5 were in one category, and the CK group was in another category. There were significant differences between G3, G4, and G5 and the CK group (see Figure 13 ).

[0142] 3.3.7 Differentially expressed gene enrichment analysis

[0143] 3.3.7.1GO functional enrichment analysis

[0144] GO (Gene Ontology) is a comprehensive database that describes gene functions, which can be divided into biological processes, cellular components, and molecular functions. The GO function enrichment threshold is a padj value less than 0.05. GO analysis of the differentially expressed genes between the groups treated with different concentrations of gibberellins and the CK group showed that in the G1 vs CK group, the genes enriched in biological processes were more likely to be involved in DNA metabolic process, movement of cell or subcellular component, and microtubule-based movement; in the molecular function classification, a large number of genes were enriched in molecular functions such as protein dimerization activity, terpene synthase activity, and transferase activity; in the G2 vs CK group, the differentially expressed genes were significantly enriched in biological processes such as DNA metabolic process, regulation of transferase activity, and regulation of kinase activity, and in molecular function, they were significantly enriched in pathways such as transferase activity, hydrolase activity, and protein kinase binding. In the G3 vs CK control group, in addition to DNA metabolism and photosynthesis, the biological processes that were significant were similar to those in the G4 vs CK group and the G5 vs CK group.

[0145] 3.3.7.2 KEGG pathway enrichment analysis

[0146] In order to gain a deeper understanding of the relationship between biological processes and genes, and thus explore the response mechanism of rosemary to gibberellin concentration, KEGG pathway enrichment analysis was performed on the differentially expressed genes. The results (Tables 12-16) showed that there were 212 significantly differentially expressed genes in 8 metabolic pathways in the G1 vs CK group, 250 significantly differentially expressed genes in 9 metabolic pathways in the G2 vs CK group, 450 significantly differentially expressed genes in 15 metabolic pathways in the G3 vs CK group, 319 significantly differentially expressed genes in 10 metabolic pathways in the G4 vs CK group, and 271 significantly differentially expressed genes in 10 metabolic pathways in the G5 vs CK group, including plant hormone signal transduction, cutin, suberine and wax biosynthesis, motor proteins, homologous recombination, monoterpenoid biosynthesis, and so on. Significantly enriched differentially expressed genes in these pathways contribute to the differences in rosemary's response to different gibberellin concentrations. These enriched pathways provide insights into the metabolic changes in rosemary following treatment with different gibberellins.

[0147] Table 12 Differentially enriched gene pathways in G1 vs CK groups

[0148]

[0149] Table 13 Differentially enriched gene pathways in G2 vs CK groups

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[0151] Table 14 Differentially enriched gene pathways in G3 vs CK groups

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[0153] Table 15 Differentially enriched gene pathways in G4 vs CK groups

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[0155] Table 16 Differentially enriched gene pathways in G5 vs CK groups

[0156]

[0157] 3.3.8 Real-time fluorescence quantitative PCR verification

[0158] In order to verify the accuracy and reliability of transcriptome sequencing results, the study combined the functions and FC values of significantly differentially expressed genes and randomly selected 8 significantly differentially expressed genes from two pathways most relevant to plant growth and development and rosemary secondary metabolites (rosmarinic acid synthesis pathway, monoterpenoid synthesis pathway, and flavonoid synthesis) for qPCR verification. The results showed that the expression profiles of the selected differentially expressed genes were basically consistent with the transcriptome sequencing results, showing basically the same up-regulation and down-regulation trends ( Figure 14 ). Therefore, the transcriptome sequencing results obtained in this study have a certain degree of accuracy and reliability, and can accurately reflect the expression patterns of most genes in rosemary secondary metabolites and growth and development under the influence of different concentrations of gibberellins, and can be used for subsequent related data analysis. Among the verified genes, Ro477420, which is related to rosmarinic acid synthesis, has the highest expression level under the influence of G4 concentration and the lowest expression level under CK treatment. Ro262510, which affects the synthesis pathway of monoterpenoids in rosemary plants, has a high expression level under the influence of G2 and G4 concentrations, and is significantly higher than the CK group. In the plant flavonoid synthesis pathway, Ro414430 and Ro263240 have the highest gene expression levels at G2 concentration at the same time.

[0159] 3.3.9 WGCNA co-expression analysis

[0160] According to the RNA-Seq results of several groups of samples affected by gibberellins, WGCNA analysis was performed on these groups of samples, and hierarchical clustering of the expression levels of sample genes was performed. It was found that most biological samples were closely clustered and there were no outliers ( Figure 15 ). According to the threshold parameter β when the fitting curve is closest to 0.8 for the first time, β=8( Figure 16 ) Screening of co-expression modules. After cluster analysis of the modules, two modules with close distances were merged to obtain 18 modules. The correlation between each module and each sample is as follows Figure 17As shown, according to the metabolite differences and gene difference analysis after the influence of gibberellin spraying, it was found that the rosemary fragrance under G2 and G3 concentrations began to show a certain degree of difference, and the results showed that the salmon, gray, and tan modules had a high correlation with the rosemary samples after gibberellin spraying, among which the salmon module and the gray module were positively correlated with the gibberellin treatment, and the tan module was negatively correlated with the gibberellin spraying.

[0161] GA3 is a common and widely used plant growth regulator, the second plant hormone identified after the discovery of auxin. Numerous studies have shown that the application of gibberellins (GAs) affects plant growth and development, as well as secondary metabolites. Wu Shan et al. found that GAs can affect stem elongation, thereby promoting lignin synthesis and thus affecting the accumulation of cannabinoids in cannabis plants. GAs also have different effects on primary terpenes in the MVA and MEP pathways, affecting terpenoid synthesis. For example, GA3 treatment increases sesquiterpenoid biosynthesis in the MVA pathway while decreasing that in the MEP pathway. Sugimoto et al. have shown that low concentrations of GAs can stimulate alkaloid production. Consequently, GAs are widely used in plant cultivation. Therefore, further investigation of the mechanisms by which rosemary responds to GAs is of great significance, and transcriptomics analysis can help uncover new avenues for this research. This study sequenced six rosemary samples, totaling 18 sequences. In this study, a total of 116.59 Gb of high-quality data was obtained. The transcriptome data were compared with the GO and KEGG databases for gene functional annotation. GO functional analysis revealed that after gibberellin spraying, the most diverse pathways were significantly enriched for differentially expressed genes under the influence of G2 concentration. In addition to DNA replication and metabolic processes shared by other groups, other biological processes involved enzyme regulation, such as transferase and kinase activity, were also significantly enriched under the influence of G2 concentration. Furthermore, molecular functions such as transferase activity, hydrolase activity, oxidoreductase activity, and protein kinase binding were also significantly enriched. KEGG enrichment analysis revealed that pathways significantly enriched for differentially expressed genes included cutin, suberine, and wax biosynthesis, plant hormone signal transduction, phenylpropanoid biosynthesis, and flavonoid biosynthesis. Among these pathways, 14 pathways were significantly enriched for differentially expressed genes under the influence of G3 concentration. However, under the influence of high concentrations of gibberellins, a small number of differentially expressed genes were enriched in several synthesis pathways of terpenoids, one of the secondary metabolites of rosemary, such as monoterpenoid biosynthesis and diterpenoid biosynthesis. Among them, the genes Ro262510 and Ro298770 for the synthesis of the monoterpenoid eucalyptol both reached the highest expression levels at G4 concentration, which was consistent with the changes in eucalyptol content detected by GC-MS in metabolomics.

Claims

1. A method for increasing the content of volatile components of rosemary, characterized in that, Apply gibberellins to rosemary plants.

2. A method for improving the volatile component content of rosemary according to claim 1, characterized in that, The concentration of the gibberellin is 40-80 mg / L.

3. A method for improving the volatile component content of rosemary according to claim 1, characterized in that, The volatile components are terpenoids.

4. A method for improving the volatile component content of rosemary according to claim 1, characterized in that, The volatile component is any one of α-pinene, o-cymene, camphene, hydrated sabinene, linalool and camphor.

5. A method for improving the volatile component content of rosemary according to claim 1, characterized in that, The volatile components are hydrated sabinene, o-cymene, linalool and camphor, and the concentration of the gibberellin is 40 mg / L.

6. A method for improving the volatile component content of rosemary according to claim 1, characterized in that, The volatile component is α-pinene, and the concentration of the gibberellin is 80 mg / L.

7. A method for improving the volatile component content of rosemary according to claim 1, characterized in that, Apply gibberellins to rosemary in March, April, and May each year.

8. A method for improving the volatile component content of rosemary according to claim 6, characterized in that, Spray once a month, and the amount of spraying should be based on the amount of water droplets dripping from the leaves.

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