A method for screening key enzyme genes and metabolites of garlic fructan stress response based on transcriptome and metabolome

Abstract

The application discloses a method for screening garlic fructan adversity response key enzyme genes and metabolites based on transcriptome and metabolome, and the method can better analyze the relationship between genes and metabolites by jointly analyzing the fructan-related differentially expressed genes measured by the transcriptome and the fructan-related metabolism substances with obvious metabolism changes measured by the metabolome, and constructing a gene-metabolite network interaction diagram.

Description

Technical Field

[0001] This invention relates to the field of multi-omics joint analysis technology, specifically to a method for screening key enzyme genes and metabolites in garlic fructan stress response based on transcriptomics and metabolomics. Background Technology

[0002] Fructan is a water-soluble oligosaccharide or polysaccharide, a non-cellular carbohydrate composed of multiple fructose residues linked by glycosidic bonds to a single sucrose end. As an important osmotic regulator, the metabolism of fructan is closely related to plant stress resistance. Studies have found that the synthesis and catabolism of fructan in plants is an important protective mechanism for plant adaptation to adverse environmental factors, and its accumulation can enhance plant resistance to various environmental stresses (Xu Huanhuan et al., 2014). There are three main reasons why fructan improves plant stress resistance (Sun Yongmei et al., 2015): (1) By accumulating fructan, the osmotic potential is regulated, which enhances the water retention capacity of cells. For example, under low temperature conditions, fructan releases soluble fructose through depolymerization, and then improves the cold resistance of plants by regulating the osmotic pressure of cells; (2) Fruuctan can stabilize the phospholipid bilayer by lowering the phase transition temperature of lipid gel phase and liquid crystal phase, and play a protective role for the membrane. For example, Van den Ende (2001) and other experiments have shown that low temperature increases the degree of polymerization of fructan can reduce cell membrane leakage; (3) Through fructan metabolism, other protective substances and energy are produced. For example, low temperature promotes the accumulation of fructan while accompanied by a certain degree of respiration consumption.

[0003] The plant response to abiotic stress is a complex life process, generating numerous metabolic intermediates and end products, including metabolic regulators and signal transduction factors, throughout the regulatory network. In recent years, studying the dynamic regulation of plant metabolism under stress has become a hot topic in molecular biology research. Modern detection techniques allow for qualitative and quantitative analysis of various metabolites in plants under stress, revealing the patterns and networks of metabolic regulation under stress. However, while transcriptome sequencing can yield a large number of differentially expressed genes and regulatory metabolic pathways, the difficulty in directly linking genes to phenotypes leads to an overwhelming number of differentially expressed genes, making it challenging to identify key signaling pathways and often failing to achieve the intended research objectives. The metabolome serves as a bridge between the genome and phenotype; its analysis can more effectively reveal biological and biochemical / molecular mechanisms. Joint analysis of the transcriptome and metabolome can better identify key regulatory metabolic pathways, pinpoint key regulatory genes, and explain the molecular mechanisms of growth and development, environmental responses, physiological states, and pathological responses in organisms.

[0004] Currently, there is no technology for screening genes and metabolites related to stress responses of garlic fructans, and there are few reports on key genes and metabolites involved in garlic fructan metabolism; therefore, its metabolic mechanism in garlic remains unclear. Thus, a reliable analytical method is needed to reveal the metabolic mechanism of fructans in garlic, which is of great significance for expanding and deepening research on plant fructans. Summary of the Invention

[0005] The purpose of this invention is to provide a method for screening key enzyme genes and metabolites in garlic fructan stress response based on transcriptomics and metabolomics. This invention utilizes a combined transcriptomics and metabolomics analysis method, combining differentially expressed fructan-related genes detected by transcriptomics with substances showing significant fructan-related metabolic changes detected by metabolomics. This allows for the construction of a gene-metabolite network interaction map, leading to a better understanding of the relationship between genes and metabolites.

[0006] The objective of this invention is achieved through the following technical solution:

[0007] A method for screening key enzyme genes and metabolites in garlic fructan stress response based on transcriptomics and metabolomics is proposed. The method screens key genes that are differentially expressed after garlic fructan responds to stress by transcriptomics screening, and screens related metabolites of garlic fructan stress response by metabolomics screening. Finally, a gene-metabolite correlation network diagram is constructed to screen key enzyme genes and metabolites in garlic fructan stress response.

[0008] In one specific embodiment, the steps of the method described in this invention are as follows:

[0009] (1) Transcriptome sequencing revealed key enzyme genes for fructan stress response.

[0010] Total RNA was extracted from garlic samples before and after stress response using the TRNzol method. After purification, the RNA was used as a template for constructing transcriptome libraries. The constructed libraries were then sequenced using Illumina HiSeq. Transcriptome data were analyzed using a fold difference value as the significance of expression differences, i.e., p-value (|log2Fold Change|>=1, FDR<0.05). Differentially expressed unigenes before and after stress response were screened. Based on the KEGG database (http: / / www.genome.jp / KEGG / ), differentially expressed genes and pathways involved in garlic stress response were identified.

[0011] (2) Metabolomics sequencing was used to obtain differential carbohydrate metabolites in response to stress.

[0012] Garlic samples before and after stress response were freeze-dried under vacuum, ground into powder, dissolved in extract, filtered, and then analyzed using ultra-high performance liquid chromatography (UPLC) and tandem mass spectrometry (MS / MS). Qualitative analysis of metabolites was performed based on the MWDB (metware database) and a public database of metabolite information. Quantitative analysis was performed using multiple reaction monitoring (MRM) mode of triple quadrupole mass spectrometry. After qualitative and quantitative analysis of the detected metabolites, the fold changes in metabolite quantitative information before and after stress response were compared. Differential metabolites were screened using fold change values ​​from univariate analysis: fold change ≥ 2 and fold change ≤ 0.5.

[0013] (3) Combined analysis of transcriptomics and metabolomics

[0014] The differentially expressed metabolites obtained in step (2) were mapped to the KEGG pathway database. Differentially expressed genes related to fructan obtained in step (1) and differentially expressed metabolites related to fructan obtained from the metabolome in step (2) were selected. Genes and metabolites with correlation coefficients (i.e., Pearson coefficients greater than 0.8) were selected for joint analysis. An interaction network diagram was constructed using R language to obtain the key enzyme genes and metabolites of garlic fructan stress response.

[0015] Unless otherwise specified, the methods described in this invention can be conventional methods in the art, such as the TRNzol method for extracting total RNA from garlic samples before and after stress response, Illumina HiSeq sequencing, vacuum freeze-drying, grinding, extraction, filtration, and data acquisition using ultra-high performance liquid chromatography (UPLC) and tandem mass spectrometry (MS / MS) systems.

[0016] The adversity described in this invention can refer to the adversities that are conventional in the art and can cause stress responses in plants, such as drought, high salinity, extreme temperature or trauma.

[0017] In one embodiment, the garlic in the context of the present invention after stress response refers to garlic that has been subjected to stress for 6 to 10 days.

[0018] After the total RNA is purified in step (1) of this invention, the purity of the RNA can be detected by Nanodrop using conventional methods. After the sample is qualified, the transcriptome library is constructed. After the library is constructed, it can be tested using conventional methods. After the library is qualified, Illumina HiSeq sequencing is performed according to the conventional effective concentration and target sequencing data volume in the art.

[0019] Since the method described in this invention is parameter-free transcriptome sequencing, after obtaining clean reads during the Illumina HiSeq sequencing process, the Trinity software is needed to assemble the filtered clean reads to obtain reference sequences for subsequent analysis.

[0020] The public database of metabolite information described in this invention is a commonly used database in the field, such as [KEGG: Kyoto Encyclopedia of Genes and Genomes] https: / / www.kegg.jp / .

[0021] Advantages of this invention over existing technologies:

[0022] (1) Based on the results of differential metabolite analysis and transcriptome differential gene analysis, differentially expressed genes and metabolites in the same group were simultaneously mapped onto the KEGG pathway map to better understand the relationship between genes and metabolites. Differentially expressed genes related to fructans detected by transcriptome analysis and differentially expressed metabolites related to carbohydrates detected by metabolome analysis were selected, and results with high correlation coefficients (Pearson coefficient greater than 0.8) were jointly analyzed. An interaction network diagram was constructed using R language to better analyze the relationship between genes and metabolites.

[0023] (2) This invention is the first to disclose the gene types of key enzymes in garlic fructan metabolism, sugar metabolites in fructan metabolism, major metabolic pathways in fructan metabolism, and a correlation network diagram between genes and metabolites. It enables the accurate and rapid identification of genes and metabolites related to fructan stress responses. This invention not only reveals the metabolic mechanism of fructan in stress regulation but also provides important reference for elucidating the mechanism of action of plant fructan in stress regulation in the future. Detailed Implementation

[0024] The present invention will be further described below with reference to embodiments. It should be understood that the specific embodiments described herein are only for explaining the present invention and are not intended to limit the present invention. Any simple improvements to the preparation method of the present invention under the premise of the concept of the present invention are within the protection scope of the present invention. Experimental methods in the following embodiments that do not specify specific conditions are generally carried out according to well-known means in the art. Unless otherwise specified, the experimental materials used in the following embodiments were all purchased from conventional biochemical reagent stores.

[0025] Example 1

[0026] (1) Experimental materials and treatment

[0027] This study used "Ledu Purple-skinned Garlic" as the experimental material. Uniformly sized garlic bulbs that had broken dormancy were selected and sown in pots. The pots were placed in a plant growth chamber (temperature: 25℃ during the day, 15℃ at night; light: 14h; relative humidity: 70%) for cultivation until the garlic seedlings reached a height of about 10cm. The plants were then divided into two treatments: ① Drought stress: watering was stopped, and other environmental conditions were the same as the control group; ② Normal cultivation (CK): cultivation at 25℃ served as a control. Each treatment was repeated three times, with 10 plastic buckets per replicate, each bucket containing 4 plants. The plastic buckets were designed as a completely randomized block design. Garlic leaves were collected on day 0 and day 6 after the low-temperature stress treatment, with three replicates for each treatment. After sampling, the leaves were immediately flash-frozen in liquid nitrogen and then stored at -80℃ for subsequent experiments.

[0028] (2) Key enzyme genes for fructan metabolism were obtained by parameter-free transcriptome sequencing.

[0029] ①RNA detection and library construction

[0030] Total RNA was extracted from freeze-dried leaf samples from different treatment groups using the TRNzol method. After purification, RNA purity was assessed using Nanodrop. Once samples passed the purity test, they were used as templates for library construction. Ribosomal RNA was removed from the total RNA to obtain mRNA. Fragmentation buffer was then added to break the RNA into short fragments. Using these short fragments as templates, first-strand cDNA was synthesized using six-base random primers. Second-strand cDNA was then synthesized using buffer, dNTPs (dUTP, dATP, dGTP, and dCTP), and DNA polymerase I. The double-stranded cDNA was then purified using AMPure XP beads. The purified double-stranded cDNA underwent end repair, A-tailing, and ligation with sequencing adapters. Fragment size selection was performed using AMPure XP beads, and finally, PCR enrichment was conducted to obtain the final cDNA library. After library approval, different libraries were pooled according to the target data volume and sequenced using the Illumina HiSeq platform. After filtering the raw sequencing data, high-quality reads are obtained. Since this invention relates to parameter-free transcriptome sequencing, after obtaining clean reads, Trinity software is needed to assemble the filtered clean reads to obtain reference sequences for subsequent analysis.

[0031] ② Screening of differentially expressed genes and key enzyme genes in fructan stress response

[0032] Based on the reference sequences obtained above, differentially expressed unigenes at different stages were screened from the transcriptome data using a fold difference value and a significant expression difference (p-value (|log2Fold Change|>=1, and FDR<0.05)). Key enzyme genes related to fructan metabolism were screened using gene annotation results in the database, and pathway analysis was performed on the screened genes involved in this invention based on the KEGG database (http: / / www.genome.jp / KEGG / ).

[0033] (3) Metabolomics sequencing was used to obtain differential carbohydrate metabolites in response to stress.

[0034] ① Sample preparation and extraction

[0035] The freeze-dried leaves from different treatment groups were crushed at 30 Hz for 1.5 min using a mixing mill (MM 400, Retsch) equipped with zirconia beads. 100 mg of powder was weighed and extracted overnight at 4 °C with 0.6 mL of 70% water-methanol. After centrifugation at 10000 g for 10 min, the extract (CNWBOND Carbon GCB SPE cartridge, 250 mg, 3 mL; ANPEL, Shanghai, China, www.ANPEL.com.cn / cnw) was absorbed and filtered (SCAA-104, 0.22 μm pore size; ANPEL, Shanghai, China, http: / / www.ANPEL.com.cn / ) before UPLC-MS / MS analysis. Analysis was performed using a UPLC-ESI-MS / MS system (UPLC, Shim-pack UFLC SHIMADZU CBM30A system, www.shimadzu.com.cn / ; MS, Applied Biosystems 4500Q TRAP, www.appliedbiosystems.com.cn / ).

[0036] ② High-performance liquid chromatography (UPLC) analysis conditions

[0037] The liquid chromatography column used was a Waters ACQUITY UPLC HSS T3C18 (1.8 μm, 2.1 mm * 100 mm); the mobile phase consisted of solvent A (pure water containing 0.04% acetic acid) and solvent B (acetonitrile containing 0.04% acetic acid). The elution gradient was as follows: 0.00 min, the proportion of phase B was 5%; within 10.00 min, the proportion of phase B increased linearly to 95% and remained at 95% for 1 min; from 11.00 to 11.10 min, the proportion of phase B decreased to 5% and equilibrated to 5% for 14 min. The column oven temperature was set to 40 °C; the flow rate was 0.35 mL / min; and the injection volume was 4 μL.

[0038] ③Mass spectrometry (MS) analysis conditions

[0039] LIT and triple quadrupole (QQQ) scans were obtained on a triple quadrupole mass spectrometer (Q TRAP) API 4500Q TRAPUPLC / MS / MS system equipped with an ESI Turbo ion spray interface, allowing for both positive and negative ion modes, and controlled by Analyst 1.6.3 software (AB Sciex). The ESI source operating parameters were as follows: ion source, turbine spray; source temperature 550 °C; ion spray voltage (IS) 5500 V (positive ion mode) / -4500 V (negative ion mode); ion source gas I (GSI), gas II (GSII), and curtain gas (CUR) were set to 50, 60, and 30.0 psi, respectively; collision gas (CAD) was set to high. Instrument tuning and mass calibration were performed in QQQ and LIT modes using 10 μmol / L and 100 μmol / L polyethylene glycol solutions, respectively. Multiple reaction monitoring (MRM) experiments were performed using triple quadrupole mass spectrometry with a collision gas (nitrogen) setting of 5 psi to obtain QQQ scans. The declustering voltage (DP) and collision energy (CE) for each MRM transition were determined through further DP and CE optimization. A specific set of MRM transitions was monitored at each epoch based on the metabolites eluted during this period.

[0040] ④ Qualitative and quantitative analysis of metabolites

[0041] Qualitative analysis of metabolites was performed using the MWDB (Metware Database) and a public database of metabolite information. Substances were identified based on secondary spectral information, and isotopic signals, repetitive signals from K+, Na+, and NH4+ ions, as well as repetitive signals from fragment ions that are themselves larger molecular weight substances, were removed during the analysis. Quantitative analysis was performed using multiple reaction monitoring (MRM) mode of triple quadrupole mass spectrometry. In MRM mode, the quadrupole first screens for precursor ions (parent ions) of the target substance, excluding ions corresponding to other molecular weight substances to initially eliminate interference. After the precursor ions are induced to ionize in the collision chamber, they break into many fragment ions. These fragment ions are then filtered by the triple quadrupole to select a characteristic fragment ion, eliminating interference from non-target ions, making the quantification more accurate and reproducible. After obtaining the metabolite mass spectrum analysis data from different samples, peak areas were integrated for all substances, and the mass spectrum peaks of the same metabolite in different samples were integrated and corrected.

[0042] ⑤ Screening of differential carbohydrate metabolites

[0043] After qualitative and quantitative analysis of the detected metabolites, the fold changes in metabolite quantification information within each group were compared, taking into account the specific sample groupings. The fold changes (≥2 and ≤0.5) from univariate analysis were used to further screen for differentially expressed carbohydrate metabolites. Their main metabolic pathways were then analyzed based on the KEGG database (http: / / www.genome.jp / KEGG / ).

[0044] (4) Combined analysis of transcriptomics and metabolomics

[0045] Based on the results of differential metabolite analysis and transcriptome differential gene analysis, differentially expressed genes and metabolites in the same group were simultaneously mapped onto a KEGG pathway map to better understand the relationship between genes and metabolites. Differentially expressed genes related to fructans detected by transcriptome analysis and differentially expressed metabolites related to carbohydrates detected by metabolome analysis were selected, and results with high correlation coefficients (Pearson coefficient greater than 0.8) were jointly analyzed. An interaction network diagram was constructed using R language to better analyze the relationship between genes and metabolites.

Claims

1. A method for screening key enzyme genes and metabolites of garlic fructan stress response based on transcriptome and metabolome, characterized in that, The key genes differentially expressed in response to adversity of garlic fructan are screened through transcriptome screening, the adversity response related metabolites of garlic fructan are screened through metabolome screening, and finally the gene-metabolite correlation network diagram is constructed to screen the key enzyme genes and metabolites of garlic fructan in response to adversity; the specific steps are as follows: (1) Transcriptional sequencing obtains key enzyme genes of fructan in response to adversity The total RNA of garlic samples before and after adversity response is extracted by TRNzol method, and after purification, it is used as a test template for the construction of a transcriptome library. The constructed library is subjected to Illumina HiSeq sequencing, and the transcriptional data adopts a two-fold difference value as the expression difference significance, that is, p-value(|log2Fold Change| >= 1, and FDR < 0.05, to screen the difference unigene before and after adversity response. Based on the KEGG database, the differentially expressed genes and pathways involved in the adversity response of garlic are screened. (2) Metabolome sequencing obtains sugar differential metabolites in response to adversity The garlic samples before and after adversity response are vacuum freeze-dried, ground into powder, dissolved and filtered in the extraction solution, and then subjected to data acquisition and analysis using ultra-high performance liquid chromatography and tandem mass spectrometry system. Based on the database MWDB and the public database of metabolite information, qualitative analysis of metabolites is performed. Quantitative analysis is completed by using the multiple reaction monitoring mode of triple quadrupole mass spectrometry. After qualitative and quantitative analysis of the detected metabolites, the difference fold change of the quantitative information of the metabolites before and after adversity response is compared, and the difference fold value is combined with the difference fold value of the single variable analysis. The difference fold value ≥ 2 and the difference fold value ≤ 0.5 are used to screen the differential metabolites. (3) Joint analysis of transcriptome and metabolome The differential metabolites obtained in step (2) are mapped to the KEGG pathway database, the differential expression genes related to fructan obtained in step (1) and the differential metabolites related to fructan measured by metabolome in step (2) are selected, the correlation coefficient of genes and metabolites, that is, the Pearson coefficient greater than 0.8 is selected for joint analysis, and the interaction network diagram is constructed by R language, that is, the key enzyme genes and metabolites of garlic fructan in response to adversity are obtained.

2. The method for screening key enzyme genes and metabolites of garlic fructan in response to stress according to claim 1, characterized in that, The adversity is drought, high salt, extreme temperature or trauma.

3. The method for screening key enzyme genes and metabolites of garlic fructan in response to stress according to claim 1, characterized in that, The garlic after adversity response refers to the garlic 6-10 days after adversity.

4. The method of claim 1, wherein the key enzyme genes and metabolites of fructan in garlic are screened under stress response. In step (1), after total RNA purification, the purity of RNA is detected by Nanodrop.

5. The method of claim 1, wherein the method is characterized in that, In step (1), the library is detected after the construction of the transcriptome library.

6. The method of claim 1, wherein the method is characterized by, In step (1), during the Illumina HiSeq sequencing process, after obtaining clean reads, the filtered clean reads are spliced using Trinity software to obtain reference sequences for subsequent analysis.