Method for regulating tea tree leaf development by using DNA methylation

Abstract

The present application relates to tea tree cultivation technical field, specifically to a kind of method for regulating tea tree leaf development using DNA methylation.The method combines DNA methylation, gene transcription, material metabolism three levels, in the process of tea tree leaf development, by using the change rule of DNA methylation to regulate the development process of tea tree leaf, effectively regulate the growth of tea tree leaf, with the advantage of strong regulation pertinence, it is beneficial to improve tea utilization, tea tree breeding.

Description

Technical Field

[0001] This invention relates to the field of tea tree cultivation technology, specifically to a method for regulating tea leaf development using DNA methylation. Background Technology

[0002] tea tree( Camellia sinensis Tea is an important economic crop, and its leaves are processed into one of the world's most popular non-alcoholic beverages. The abundant secondary metabolites in tea are a crucial material basis for the flavor and aroma of finished tea, including catechins and terpenes. The types and contents of these secondary metabolites vary depending on the developmental stage of the tea leaves, directly affecting the quality and yield of the finished tea. Currently, research on secondary metabolism during tea leaf development mainly involves gene transcription, post-transcriptional modifications, and metabolic levels. As a fundamental type of epigenetic modification, DNA methylation plays a vital role in many biological processes in plants. Throughout the plant's life cycle, the level of DNA methylation in different tissues or organs is strictly regulated, thus influencing growth, development, and metabolism. However, research on the regulation of important secondary metabolism by DNA methylation during tea leaf development is scarce. Summary of the Invention

[0003] The purpose of this invention is to overcome the shortcomings of the prior art and provide a method for regulating tea leaf development by using DNA methylation. This method can effectively regulate the growth of tea leaves through DNA methylation and has the advantage of strong targeted regulation.

[0004] To achieve the above objectives, the present invention provides the following technical solution: A method for identifying the developmental process of tea leaves is provided, which determines the developmental process of tea leaves by analyzing the whole-genome DNA methylation level of tea leaves, wherein the developmental process of tea leaves is positively correlated with the whole-genome DNA methylation level.

[0005] In some implementations, the developmental process of tea leaves is determined by observing the methylation level of CHH sites in the whole genome DNA methylation.

[0006] A method for identifying gene expression levels in tea leaves is provided, which determines gene expression levels in tea leaves by analyzing the methylation level of the whole genome DNA of tea leaves. Except for the CHH site methylation level in DNA methylation located in promoter and intergenic regions, which is positively correlated with gene expression, the methylation levels of other DNA methylation sites are all significantly negatively correlated with gene expression.

[0007] This provides a method for regulating DNA methylation levels in tea leaves by downregulating DNA methyltransferases. CMT2 , CMT3 , MET1 and DNA demethyltransferase DME Increase the expression level to enhance DNA methylation.

[0008] This study provides an application of DNA methylation in regulating the secondary metabolism of flavonoids and terpenes during tea leaf development.

[0009] In some embodiments, when the flavonoid is a catechin, the total amount of catechin is reduced by promoting DNA methylation levels, wherein the content of catechin gallate and epicatechin among the catechins increases, while the content of the remaining catechins decreases.

[0010] In some implementations, upstream genes involved in the synthesis of terpene secondary metabolites are downregulated by promoting DNA methylation levels. HMGR , DXS , GGPPS Expression levels and genes upregulated in the synthesis of terpenoid secondary metabolites IDI and DXR Expression level.

[0011] The beneficial effects of this invention are: (1) A method for identifying the development process of tea leaves in this invention is to determine the development process of tea leaves by analyzing the whole genome DNA methylation level of tea leaves. Since the development process of tea leaves is positively correlated with the whole genome DNA methylation level, the higher the whole genome DNA methylation level of tea leaves, the higher the degree of tea leaf development, thereby identifying whether tea leaves are young leaves or old leaves.

[0012] (2) A method for identifying gene expression levels in tea leaves according to the present invention found that gene expression levels decrease significantly with increasing DNA methylation levels. When CHH methylation exists in the promoter and intergenic regions, it promotes gene expression. Therefore, the gene expression level of tea leaves is determined by analyzing the DNA methylation level of the whole genome of tea leaves. Except for the CHH site methylation level in the DNA methylation located in the promoter and intergenic regions, which is positively correlated with gene expression levels, the other DNA methylation levels are significantly negatively correlated with gene expression levels. This method can better predict the gene expression level of tea leaves.

[0013] (3) The method of regulating the DNA methylation level of tea leaves in this invention has discovered genes related to de novo DNA methylation synthesis. CMT2 ( CSS0038763 Genes related to DNA methylation maintenance MET1 ( CSS0042457 )and CMT3 ( CSS0034027 Genes related to demethylation DME ( CSS0002130 The expression levels of all of these enzymes were significantly downregulated, therefore, downregulation of DNA methyltransferases was effective. CMT2 , CMT3 , MET1 and DNA demethyltransferase DME This increases DNA methylation levels, which in turn regulates the properties of tea leaves.

[0014] (4) The method of regulating the DNA methylation level of tea leaves in this invention has found that DNA methylation has a potential regulatory effect on the metabolism of flavonoids and terpenes during the development of tea leaves. Therefore, the metabolism of flavonoids and terpenes can be regulated by regulating the DNA methylation level, thereby adjusting the taste and aroma of the finished tea. Attached Figure Description

[0015] Figure 1 These are representative images of young and old leaf samples.

[0016] Figure 2 This is an overview of DNA methylation in tea leaves. (A) Average methylation level of CHH, CHG, and CpG sites across the whole genome. (B) Number and percentage of CHH, CHG, and CpG sites across the whole genome. (CD) Distribution of methylation levels at CHH, CHG, and CpG sites.

[0017] Figure 3 The following are chromosome-level methylation maps of tea leaves: (A) Distribution of CHH, CHG, and CpG methylation levels along chromosomes in TL and OL: af, CHH, CHG, and CpG methylation levels; g, gene density; h, transposon element density; (B) Distribution of CHH, CHG, and CpG DNA methylation levels along chromosome 1 in TL and OL; (C) Correlation between DNA methylation levels and gene and transposon element densities.

[0018] Figure 4 The comparison of DNA methylation status between TL and OL is as follows: (A) Average methylation level of CHH, CHG, and CpG sites in TL and OL; (B) Number of methylation sites of CHH, CHG, and CpG in TL and OL; (C) Methylation level of CHH, CHG, and CpG windows in gene elements and their upstream and downstream 2kb regions; (D) Methylation level of CHH, CHG, and CpG windows in transposon elements and their upstream and downstream 2kb regions.

[0019] Figure 5The statistics are as follows: (A) Number of differentially methylated regions of CHH, CHG, and CpG; (B) Distribution of the degree of methylation difference of CHH-, CHG-, and CpG-DMRs; (C) Proportion of CHH-, CHG-, and CpG-DMRs in different genomic regions; (D) Overlap of differentially methylated genes (DMGs) of different methylation types.

[0020] Figure 6 The statistics show the expression of TL and OL genes. (A) Average level of TL and OL gene expression. (B) Distribution of TL and OL gene expression.

[0021] Figure 7 The data includes an overview of differentially expressed genes (A), a volcano plot of differentially expressed genes (BC), and KEGG enrichment analysis of differentially expressed genes.

[0022] Figure 8 Expression levels of methylation-related genes in TL and OL (A) Heatmap of methylation-related gene expression (BE) Differentially expressed genes (DEGs) among methylation-related genes — CMT2 , CMT3 , MET1 , DME The expression of .

[0023] Figure 9 The correlation analysis between DNA methylation and gene expression level (A) Correlation analysis between genes with different methylation levels and their expression levels (B) Correlation analysis between DMR-DEGs methylation level and their expression levels.

[0024] Figure 10 The analysis included a combined DNA methylome and transcriptome analysis (A) Venn diagram of co-differential genes and (B) KEGG enrichment analysis of co-differential genes.

[0025] Figure 11 This refers to the content of eight catechin monomers (AI) in TL and OL, including the total catechin (TC), catechin gallate (CG), gallocatechin gallate (GCG), epigallocatechin gallate (EGCG), epicatechin gallate (ECG), epigallocatechin (EGC), catechin (C), ester-type catechin (GC), and epicatechin (EC) in TL and OL.

[0026] Figure 12Comparison of volatile metabolites in TL and OL: (A) Types of volatile substances in TL and OL; (B) Proportion of volatile substances in TL and OL; (C) Content of monoterpenes, sesquiterpenes and their derivatives in TL and OL (gray in the heatmap represents undetected); (D) Content of linalool, terpineol, nerolidol, τ-cadinol and α-cadinol in TL and OL.

[0027] Figure 13 The statistics show the gene composition related to the flavonoid metabolism pathway (A) expression level of DMR-DEGs related to the flavonoid metabolism pathway (B) Venn diagram of DMGs and DEGs related to the flavonoid metabolism pathway (C) percentage of different gene types among genes related to the flavonoid metabolism pathway.

[0028] Figure 14 This is a comprehensive transcriptomic and methylome analysis of flavonoid metabolism (A) flavonoid metabolism pathways.

[0029] Figure 15 Statistics on genes related to terpene metabolism pathways: (A) Expression levels of DMR-DEGs related to terpene metabolism pathways; (B) Venn diagram of DMGs and DEGs related to terpene metabolism pathways; (C) Percentage of different gene types among genes related to terpene metabolism pathways.

[0030] Figure 16 This is a comprehensive transcriptomic and methylome analysis of terpene metabolism. (A) Gene expression levels and methylation levels in the terpene metabolism pathway. (B) Visualization of DMRs of key genes in the terpene metabolism pathway. Detailed Implementation

[0031] Preferred embodiments of the invention will now be described in more detail with reference to the accompanying drawings. While preferred embodiments of the invention are shown in the drawings, it should be understood that the invention can be implemented in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided so that the invention will be thorough and complete, and will fully convey the scope of the invention to those skilled in the art.

[0032] To better illustrate the implementation method of the embodiments, the materials and testing methods will be described.

[0033] Material To illustrate the effectiveness of this invention, the following tea leaves were used uniformly: In July 2022, five-year-old Lingtou Dancong tea trees with no signs of disease or pests and uniform growth were selected from a tea garden in Conghua District, Guangzhou City, Guangdong Province (N23.55°, E113.58°) as the sampling subjects. Tender leaves (TL) and old leaves (OL) were picked. Figure 1It was immediately placed in liquid nitrogen and frozen, and then stored at -80°C for subsequent experiments.

[0034] Detection methods DNA methylation sequencing and analysis DNA extraction Genomic DNA was extracted using the Polyphenol and Polysaccharide Plant Genomic DNA Extraction Kit (DP360) from Tiangen Biotech Co., Ltd. (Beijing, China). The specific operating steps are as follows: Sample grinding: Take fresh leaf samples and grind them with liquid nitrogen, weighing approximately 100 mg.

[0035] Sample lysis: Quickly add 400 μL of buffer GPS and 10 μL of RNase A (10 mg / mL). Vortex the suspension and incubate at 65°C for 15 min, inverting the container every 5 min during the incubation. After the incubation, add 100 μL of buffer GPA, vortex for 1 min, and centrifuge at 12000 rpm for 5 min.

[0036] DNA precipitation: Transfer the supernatant after centrifugation to a CS filter column containing the collection column, centrifuge at 12000 rpm for 1 min, transfer the filtrate to a new centrifuge tube, add an equal volume of ethanol and mix well. At this point, flocculent precipitate will be formed.

[0037] DNA adsorption: The solution and flocculent precipitate were transferred together to the RNase-Free adsorption column CR2, centrifuged at 12000 rpm for 1 min, the filtrate was discarded and the RNase-Free adsorption column CR2 was placed into the collection column.

[0038] Protein removal: Add 550 μL of protein removal solution RD to the RNase-Free adsorption column CR2, centrifuge at 12000 rpm for 1 min, discard the waste liquid, and then place the RNase-Free adsorption column CR2 into the collection column.

[0039] DNA washing: Add 700 μL of washing buffer PW to the RNase-Free adsorption column CR2, centrifuge at 12000 rpm for 1 min, discard the waste liquid, and repeat this step twice.

[0040] Drying: Place the RNase-Free adsorption column CR2 into the collection column, centrifuge at 12000 rpm for 2 min, then transfer to a new collection column and dry at room temperature for 5-10 min.

[0041] DNA elution: Add 60 μL of elution buffer TB to the RNase-Free adsorption column CR2 and incubate at room temperature for 4 min. Collect the eluent after centrifugation at 12000 rpm for 2 min.

[0042] DNA integrity was detected by agarose gel electrophoresis (1% gel concentration, 120 V voltage, 45 min time); DNA integrity was assessed by NanoDrop. TM DNA purity was determined using an 8000 micro-spectrophotometer; via Qubit ® DNA concentration was detected using a 2.0 fluorometer.

[0043] Library construction and sequencing Take 1 μL of genomic DNA to start library construction, and use the EZDNA Methylation-Gold™ Kit (D5006) from Shanghai Biotech Co., Ltd. (Shanghai, China) to treat with bisulfite and construct a WGBS library. The specific operation procedure is as follows: DNA fragmentation: The gDNA sample volume of the added unmethylated λ phage DNA control was adjusted to 80 μL using 1 × TE, and the DNA was fragmented to 350 bp.

[0044] End repair and adapter addition: Repair the 3' and 5' protruding bases to make the ends flat and connect the sequencing adapter.

[0045] Adding an A to the 3' end and a ligator: After adding an A to the 3' end of the padded fragment and phosphorylating the 5' end, a sequencing adapter is ligated.

[0046] Fragment screening: Fragments of 300-600 bp were screened and recovered using magnetic bead separation method.

[0047] Bisulfite treatment: Unmethylated C bases in the genome are converted to U, and after PCR amplification, they become T, which distinguishes them from the original methylated C bases.

[0048] Sequencing: After library construction, ThermoFisher Qubit was used. ® Preliminary quantification was performed using a 2.0 fluorometer, followed by insertion size detection of the library using an Aglient 2100 Bioanalyzer. If the detection met expectations, a ThermoFisher StepOnePlus was used. TM Real-Time PCR system was used for qPCR testing to ensure library quality. Libraries that passed sequencing quality were then sequenced using Illumina Hiseq X for PE150 sequencing.

[0049] Data processing Sequencing data quality control and filtering: Row reads are stored in FASTQ format and contain the sequenced reads and their corresponding quality information. Reads contaminated with adapters, of low quality, or with an N ratio greater than 10% are removed to obtain clean reads.

[0050] Bisulfite conversion assessment: using Bismark (v0.23.1) (Krueger) et al. (2011) Detection of methylation status of λ phage DNA to assess bisulfite conversion rate of target genome.

[0051] Sequence alignment and C-site methylation level detection: Bismark was used to align clean reads to the genome of early-maturing tea tree (Xia et al. After (2019), using BatMeth2 (Zhou et al. C-site methylation levels were detected using a method (2019). A C-site coverage rate of 4 or higher was used as a threshold for subsequent analysis. The formula for calculating the methylation level is as follows (mC is the total number of methylated C-sites, CT is the total number of C-sites):

[0052] Calculation of methylation levels along gene elements and transposon elements: using EDTA (v2.0.1) (Ou et al. , 2019) and Repeatmasker (4.1.2-p1) (Tarailo-Graovac et al. (2009) Annotated transposon elements in the early germination genome of *Shucha*. Gene elements and related transposon regions were divided into body, upstream (2 kb), and downstream (2 kb) regions, and each region was further divided into 100 bins. The methylation levels of the body, upstream, and downstream regions of the elements were calculated using Bismark.

[0053] Differentially methylated regions (DMRs) and differentially methylated genes (DMGs) were identified using a sliding criterion of 600 bp region size and 200 bp step size, employing methylKit (v1.24.0) (Akalin). et al. (2012) Calculate the methylation level of the region. When the difference in methylation level of the same region between samples is greater than 20% and q-value When the methylation value is less than 0.05, the region is defined as a DMR. If the body, upstream, or intergenic region of a gene overlaps with a DMR, the gene is defined as a differentially methylated gene (DMG).

[0054] KEGG pathway enrichment analysis: DMGs were used as target genes, and the whole genome was used as background. ClusterProfiler (v4.6.0) (Wu et al. (2021) KEGG pathway enrichment analysis was performed, and the enriched pathways were subjected to hypergeometric distribution test. q-value If the value is less than 0.05, the pathway is considered to be significantly enriched.

[0055] Transcriptome sequencing and analysis RNA extraction RNA was extracted using the Plant Total RNA Mini-Extraction Kit B (R4151B) from Guangzhou Meiji Biotechnology Co., Ltd. (Guangzhou, China). The specific steps are as follows: Sample grinding: Grind the fresh leaf sample with liquid nitrogen and weigh about 100 mg into a centrifuge tube.

[0056] Sample lysis: Add 0.8 mL of buffer RLC to a centrifuge tube, vortex for 15 s, let stand at room temperature for 5 min, and then centrifuge at 14000 × g for 5 min.

[0057] DNA removal: Attach the gDNA filter column to a 2 mL collection tube, transfer the supernatant to the gDNA filter column, centrifuge at 14000 × g for 2 min, and discard the gDNA filter column.

[0058] RNA adsorption: Add 0.5 times the volume of anhydrous ethanol to the filtrate, mix well by pipetting, and then transfer 700 μL of the mixture to a HiPure RNA Mini column and centrifuge at 12000 × g for 1 min.

[0059] Secondary DNA removal: Discard the filtrate, add 500 μL of buffer RW1 to the column, and centrifuge at 10000 × g for 1 min.

[0060] Salt removal: Discard the filtrate, add 500 μL of buffer RW2 to the column, and centrifuge at 12000 × g for 1 min. Repeat this step twice.

[0061] Drying: Discard the filtrate and centrifuge at 12000 × g for 2 min.

[0062] RNA elution: Transfer the column to a 1.5 mL centrifuge tube and add 40 μL of nuclease-free water to the center of the column membrane. Incubate at room temperature for 2 min, then centrifuge at 12000 × g for 1 min.

[0063] RNA integrity and concentration were detected using the Agilent RNA 6000 Nano Kit and Agilent 2100 Bioanalyzer; RNA was analyzed using a Kaiao K5500 micrometer. ® RNA purity was determined using an ultra-micro spectrophotometer.

[0064] Library construction and sequencing Library construction: 1-3 μg of RNA was used for transcriptome sequencing library construction. This was performed according to the VAHTS Universal V6RNA-seq Library Prep Kit for Illumina. ® The (NR604-01 / 02) operating instructions describe the library construction using different index tags. mRNA with polyA tails is enriched using Oligo(dT) magnetic beads. Fragmentation buffer is then added to break the mRNA into short fragments. Using the mRNA as a template, the first strand of cDNA is synthesized using six-base random hexamers. The RNA template strand is then degraded with RNase H, and the second strand of cDNA is synthesized using dNTPs in a DNA polymerase I system. The double-stranded cDNA is then purified using AMPure P beads. The purified double-stranded cDNA undergoes end repair, A-tailing, and ligation with sequencing adapters. Fragment size selection is then performed, followed by PCR amplification to obtain the final cDNA library.

[0065] Library check: After the library is built, first use ThermoFisher Qubit. ® 3.0 Preliminary quantification was performed by diluting the library to 1 ng / μL. Subsequently, the insert size of the library was detected using an Agilent 2100. After the insert size met the expectations, the effective concentration of the library was accurately quantified by qPCR (effective concentration of library >10 nM).

[0066] Sequencing: After the library passes the test, sample pooling is performed according to the effective concentration of the library and the target data volume. Sequencing is performed simultaneously with synthesis using the PE150 sequencing strategy on the Illumina platform.

[0067] Data processing Sequencing data quality control and filtering: Row reads are stored in FASTQ format, containing the measured reads and their corresponding quality information. Reads with adapters, containing N bases, and low-quality reads (more than 50% of the total read length has Qphred ≤ 20) are removed to obtain clean reads. Simultaneously, Q30 and GC content are calculated for clean reads to ensure high-quality sequencing data.

[0068] Sequence alignment and gene expression quantification: HISAT2 (v2.2.1) (Kim) was used. et al. (2015) Aligned cleanreads to the early Shucha genome. FeatureCounts (v2.0.1) (Liao et al. (2014) The expression level of each gene was calculated by counting the sequences on the pair in terms of transcripts per million mapped reads per thousand bases.

[0069] Differentially expressed gene (DEG) identification: using DESeq2 (v1.38.1) (Love et al. , 2014; Varet et al. (2016) Comparative analysis of gene expression among groups was conducted, and the Benjamini & Hochberg method was applied to analyze gene expression. p- value Correction is performed to obtain p-adjust If a gene has a |log2foldchange| ≥ 2 between groups and p-adjust If the value is <0.05, the gene is defined as a differentially expressed gene (DEG).

[0070] KEGG pathway enrichment analysis: Using DEGs as target genes and the whole genome as background, KEGG pathway enrichment analysis was performed using clusterProfiler (v4.6.0). Hypergeometric distribution tests were conducted on the enriched pathways. q-value If the value is less than 0.05, the pathway is considered to be significantly enriched.

[0071] Combined DNA methylome and transcriptome analysis Identification of co-differential genes (DMR-DEG): If a gene has DMR in the promoter, exon, intron and intergenic regions, and the gene is DEG, then the gene is defined as a co-differential gene (DMR-DEG).

[0072] KEGG pathway enrichment analysis: Using DMR-DEGs as target genes and the whole genome as background, KEGG pathway enrichment analysis was performed using clusterProfiler. Hypergeometric distribution tests were then conducted on the enriched pathways. q- value If the value is less than 0.05, the pathway is considered to be significantly enriched.

[0073] Metabolite detection 1. Detection of volatile metabolites Volatile metabolites were detected using headspace solid-phase microextraction combined with gas chromatography-tandem mass spectrometry (HS-SPME / GC-MS). The specific method is as follows: Sample preparation: Weigh 0.2 g of fresh leaf sample ground with liquid nitrogen and place it in a headspace vial. Add 5 mL of saturated sodium chloride solution and 86.4 ng of ethyl caprylate, and seal quickly with aluminum foil.

[0074] Adsorption of volatile metabolites: After the mixture was heated in a metal bath at 80°C for 15 min, a divinylbenzene / carboxyl / polydimethylsiloxane fiber (inner diameter: 50 / 30 μm, length: 2 cm) was inserted into the headspace vial and adsorbed at 80°C for 40 min.

[0075] Detection of volatile substances: After adsorption, the SPME fiber was inserted into the gas chromatograph injection port and desorbed at 250℃ for 3 min. Using an Agilent 1890B gas chromatograph and a 5977A mass spectrometer, an HP-5MS capillary column (30 m × 0.25 mm × 0.25 μm) was selected, loaded with high-purity helium at a rate of 1.0 mL / min, and detected in splitless mode with an initial temperature of 50℃ for 1 min, followed by heating to 220℃ at a rate of 5℃ / min and maintaining for 5 min. The mass spectrometer ion source temperature was 230℃, the electron energy was 70 eV, the scan range was 30–400 atomic mass units (amu), and the solution delay time was 4 min.

[0076] Qualitative and quantitative analysis of volatile metabolites: Volatile metabolites were qualitatively analyzed based on mass spectrometry matching factor (MSF) and retention index (RI). The retention times of C9-C21 n-alkane standards under the above detection conditions were used as a reference to calculate the RI. The calculated RI was compared with the NIST 14 database (Acree). et al. A comparison was made between the calculated RI and the reported RI (2010). If the difference between the calculated RI and the reported RI for a substance was less than 20 and the MSF was greater than 80, the substance was included in subsequent analyses. Relative quantification was performed by comparing the peak area with that of the internal standard ethyl caprylate.

[0077] 2. Catechin detection High-performance liquid chromatography (HPLC) was used to qualitatively and quantitatively analyze eight catechin monomers: catechin (C), epicatechin (EC), gallocatechin (GC), epigallocatechin (EGC), catechin gallate (CG), epicatechin gallate (ECG), gallocatechin gallate (GCG), and epigallocatechin gallate (EGCG). The specific steps are as follows: Sample preparation: Fresh leaf samples were freeze-dried using a FreeZone 2.5 vacuum freeze dryer. 0.2 g of the freeze-dried sample was weighed and added to 8 mL of 70% methanol (v / v) solution. After ultrasonic shaking in a water bath for 30 min, the sample was centrifuged at 10000 rpm for 3 min. The supernatant was filtered through a 0.22 μm nylon 66 filter membrane and added to the sample for testing.

[0078] Sample analysis: A Waters 220 Alliance E2695 high-performance liquid chromatograph equipped with a 2489 UV-Vis detector and a Waters XSelect HSS C18 column (5 µm, 4.6 mm × 250 mm) was used for sample analysis. The specific chromatographic conditions were as follows: detection wavelength was 280 nm, column temperature was 25℃, mobile phase A was 0.1% formic acid (v / v), mobile phase B was 100% acetonitrile, flow rate was 1 mL / min, and gradient elution was used. The ratio of mobile phase A to mobile phase B was 92:8 in the first 0-5 min, 75:25 in the first 5-14 min, and 92:8 in the first 14-30 min.

[0079] Qualitative and quantitative analysis of catechins: A standard curve was prepared using catechin standards, and the sample results were compared with the standard curve to perform qualitative and quantitative analysis of each catechin monomer.

[0080] 3. Data Statistical Analysis Unpaired t-tests and Spearman correlation analysis were performed using GraphPad Prism 9.5.1, and the results were plotted. In the hypothesis testing, if... p-value If <0.05, it is considered to be a significant difference (*). p-value A value <0.01 is considered highly significant (*). Using TBtools (Chen...) et al. Circos plots and point heatmaps were drawn in 2020.

[0081] Example Analysis of DNA methylation status changes during tea leaf development 1. Overall DNA methylation status of tea leaves To investigate the dynamic changes in DNA methylation during tea leaf development, we performed whole-genome bisulfite sequencing on TL and OL samples. The average number of sequences per biological replicate was approximately 1.5 × 10⁻⁶. 8 The number of reads showed a unique alignment rate of approximately 40%, and the average bisulfite conversion rate was above 99%, indicating that the data quality was sufficient to support subsequent analysis (Table 1). At the whole-genome scale, the average methylation levels of CpG, CHG, and CHH sites in tea leaves were 84.70%, 68.22%, and 10.90%, respectively, showing significant differences among them. Figure 2 A). In terms of methylation level distribution, all three sites exhibit a bimodal distribution ( Figure 2 (C, 2D), where the CHH sites mostly exhibit low methylation levels. Conversely, the number of the three methylation sites is 0.95 × 10⁻⁶, respectively. 7 1.06 × 10 7 and 2.34 × 10 7 The percentages were approximately 21.81%, 24.41%, and 53.78%, respectively. Among these, the number of CHH methylation sites differed significantly from those of CpG and CHG, while the number of CpG and CHG methylation sites did not differ significantly. Figure 2 B). An investigation into the distribution of DNA methylation levels along the chromosome revealed that the CHH, CHG, and CpG methylation levels in TL and OL showed a similar distribution on the same chromosome. Figure 3 A) The methylation levels of the CHG and CpG windows were significantly negatively correlated with gene density and significantly positively correlated with transposon element density, while the methylation levels of the CHH window were significantly positively correlated with gene density and significantly negatively correlated with transposon element density. Figure 3 B, 3C).

[0082] In summary, the methylation modifications of the three types of sites differed significantly, and the number of methylated sites showed an opposite trend to the methylation level of the sites. However, the methylation levels of the same type of sites were relatively similar in their macroscopic distribution along the chromosome.

[0083] Table 1. Statistics of whole-genome bisulfite sequencing results

[0084] 2. Changes in DNA methylation status during tea leaf development During tea leaf development, the average methylation levels of CpG, CHG, and CHH sites in OL were 85.78%, 69.85%, and 14.71%, respectively, all significantly higher than those in TL (83.61%, 66.58%, and 7.10%). Figure 4A). Similar to the overall methylation trend of tea leaves, the number of methylation sites of various types in both OL and TL is inversely proportional to their methylation degree. Specifically, the number of CHH methylation sites in OL is 2.90 × 10⁻⁶. 7 The value was significantly higher than TL (1.79 × 10⁻⁶). 7 () Figure 4 B). Analysis of gene element methylation levels revealed ( Figure 4 C), along the upstream direction near the transcription start site (TSS) and along the downstream direction near the transcription termination site (TTS), the methylation levels of CpG and CHG windows showed a slow decreasing trend, while the CHH window showed a sharp decreasing trend, with significant differences in levels between samples. In the body region, the methylation levels of all three types of windows showed a trend of first increasing and then decreasing, with significant differences in levels between CHG and CHH windows between samples. In transposon elements ( Figure 4 D), along the direction closer to TSS and TTS, the methylation levels of all three types of windows showed a slow increasing trend, while there was no significant change in the body region. Among them, the methylation level of the CHH window showed the most significant difference between TL and OL.

[0085] In summary, during the development of tea leaves, the overall methylation status underwent significant changes in degree, quantity, and distribution, with the main changes occurring in the CHH type.

[0086] 3. Screening and analysis of DMRs during tea leaf development To further investigate the differences in DNA methylation between TL and OL, differentially methylated regions (DMRs) of CHH, CHG, and CpG were analyzed. Compared with TL, a total of 247,907 DMRs were identified in OL, including 212,705 CHH-DMRs, 22,404 CHG-DMRs, and 12,798 CpG-DMRs. Figure 4A). After classifying DMRs into hypermethylated (hyper) and hypomethylated (hypo) types, it was found that the number of hyper-DMRs (227,830) was significantly greater than that of hypo-DMRs (20,077). Specifically, CHH-DMRs contained 212,587 hyper CHH-DMRs and 118 hypo CHH-DMRs, CHG-DMRs contained 9,040 hyper CHG-DMRs and 13,364 hypo CHG-DMRs, and CpG-DMRs contained 6,203 hyper CpG-DMRs and 6,595 hypo CpG-DMRs. The number of DMRs of the two types was not significantly different in CHG and CpG, but the number of hyper CHH-DMRs was much higher than that of hypo CHH-DMRs. Regarding the degree of methylation difference, all types of DMRs showed a methylation difference of over 25%, with hypo CpG-DMRs and hyper CHH-DMRs showing the largest average differences, at 28.45% and 28.19%, respectively.

[0087] To further explore potential regulatory sites of DNA methylation, the distribution of differentially methylated genes (DMGs) in different genomic regions was analyzed. The results showed that most DMRs were located in intergenic regions (68.75%), followed by gene body regions (17.19%) and promoter regions (14.06%). Notably, in CHH-DMRs, the proportion of DMRs in promoter regions was higher than that in body regions. Furthermore, almost all CHH-DMRs in different gene regions were hypertypes, while in CHG-DMRs and CpG-DMRs, hypertypes and hypotypes were distributed approximately equally in the gene regions. Associating DMRs with genes revealed that among differentially methylated genes (DMGs), the CHH type was the most numerous (17743), followed by CHG (6561) and CpG (4627). Among these, 2262 DMGs were shared, while CHH, CHG, and CpG had 10056, 713, and 346 DMGs unique to each, respectively.

[0088] In summary, hypermethylation of CHH mainly occurs during tea leaf development, with an average difference of over 25%, and is mainly located in the intergenic region. This may regulate gene transcription by affecting the methylation level near genes.

[0089] Comparative analysis of gene expression levels during tea leaf development 1. Overall Gene Expression Levels During Tea Leaf Development To further explore the potential regulatory role of DNA methylation in gene expression, transcriptome sequencing was performed on TL and OL genes. The number of sequencing reads for TL were 44,250,328, 45,713,456, and 46,698,202, with an average of 45,553,995 reads. The number of aligned reads were 37,010,415, 38,341,795, and 39,275,338, respectively, with an average unique alignment rate of 83.87%. The number of sequencing reads for OL were 45,238,576, 40,076,834, and 47,619,586, with an average of 44,311,665 reads. The number of aligned reads were 38,836,443, 34,312,466, and 40,891,444, respectively, with an average unique alignment rate of 85.78%. Both showed high data quality. Compared to TL, the average gene expression level in OL was lower (…). Figure 5 A). In terms of gene expression distribution, most genes in TL and OL are in a low expression state ( Figure 5 B), and the distribution probability of TL in the high expression range is higher than that of OL.

[0090] In summary, gene expression abundance decreased significantly during tea leaf development.

[0091] Table 2. Statistics of transcriptome alignment results

[0092] 2. Screening and analysis of DEGs during tea leaf development Based on the fold change in expression levels between groups greater than 2 and p-adjust A value <0.05 was used as a screening criterion for differentially expressed genes (DEGs), and a total of 7253 DEGs were identified. Compared with TL, 4531 genes were downregulated and 2722 genes were upregulated in OL. Figure 6A). KEGG pathway enrichment analysis of DEGs revealed that among differentially upregulated genes, the top 10 significantly enriched pathways were photosynthesis, glyoxylate and dicarboxylate metabolism, tryptophan metabolism, nitrogen metabolism, carbon fixation in photosynthetic organisms, glutathione metabolism, glucosinolate biosynthesis, monoterpenoid biosynthesis, sesquiterpenoid and triterpenoid biosynthesis, and glycine, serine, and threonine metabolism. Figure 6 B); The differentially downregulated genes were significantly associated with the following pathways: flavonoid biosynthesis, phenylpropanoid biosynthesis, stilbenoid, diarylheptanoid, and gingerol biosynthesis, phenylalanine metabolism, isoquinoline alkaloid biosynthesis, DNA replication, cysteine ​​and methionine metabolism, starch and sucrose metabolism, homologous recombination, and flavone and flavonol biosynthesis. Among these, DEGs are mainly involved in the regulation of important secondary metabolites, such as flavonoids, phenylpropanoids, monoterpenes, sesquiterpenes, and triterpenes.

[0093] In summary, significant changes occurred in the expression of genes related to the regulation of flavonoid and terpene metabolism during the development of tea leaves.

[0094] 3. Changes in the expression of DNA methylation-related genes during tea leaf development To investigate the potential causes of DNA hypermethylation during tea leaf development, changes in the expression levels of methylation-related genes were examined (Tong...). et al. , 2021). Compared to TL, most of the OL samples were associated with de novo methylation ( de novo The expression levels of genes related to methylation, methylation maintenance, and demethylation were all downregulated. Figure 7 A). Among them, genes related to de novo synthesis of DNA methylation. CMT2 ( CSS0038763 Genes related to DNA methylation maintenance MET1 ( CSS0042457 )and CMT3 ( CSS0034027 Genes related to demethylation DME ( CSS0002130 The expression levels of all of them were significantly downregulated. Figure 7 B-7C).

[0095] In summary, during the development of tea leaves, the main factors are... CMT2 , MET1 , CMT and DME They jointly participate in the formation of DNA hypermethylation.

[0096] Association between DNA methylation level and gene expression level during tea leaf development 1. Correlation analysis between DNA methylation level and gene expression level during tea leaf development To investigate the correlation between DNA methylation and gene expression levels, all genes were sorted according to their methylation levels and divided into three categories: low, middle, and high. Their expression levels were then statistically analyzed. Except in the promoter region, where gene expression levels initially decreased and then increased with increasing CHH methylation levels, gene expression levels in all other regions showed a decreasing trend with increasing DNA methylation. The decrease in gene expression levels was most significant with increasing methylation in the body region. Figure 8 A). Because the degree of DNA methylation regulation of gene expression may be affected by the magnitude of methylation changes, the influence of DMRs in different genomic regions on DEG expression levels was further investigated. In terms of DMR distribution, most DMRs associated with DEGs were located in intergenic regions (…). Figure 9(B) This is consistent with the above results. Regarding the correlation with expression levels, when DMRs are located in the promoter, body, and intergenic regions, gene expression levels significantly decrease with increasing methylation differences in CpG-DMRs and CHG-DMRs. For CHH-DMRs, when located in the promoter and intergenic regions, gene expression levels significantly increase with increasing methylation differences, while there is no significant effect on gene expression in the body region.

[0097] In summary, as tea leaves develop, increased methylation levels in CHH and CpG morphological regions may inhibit gene expression, while increased methylation levels in CHH morphological regions may promote gene expression.

[0098] 2. Identification and analysis of co-differential genes during tea leaf development To investigate the potential regulatory role of DNA methylation in the biological functions of tea leaf development, a ensemble analysis was performed on the identified DMGs and DEGs, and the intersection was defined as co-differential genes (DMR-DEGs). Figure 8 A). The results showed that only a small percentage of DMGs (26.39%) overlapped with DEGs, while this small percentage of genes overlapped with the majority of DEGs (68.74%), indicating that DNA methylation may affect the expression of most genes. Next, KEGG pathway enrichment analysis was performed on DMR-DEGs. The results showed that the top 10 significantly enriched pathways were: isoquinoline alkaloid biosynthesis, flavone and flavonol biosynthesis, stilbenoid, diarylheptanoid, and gingerol biosynthesis, sesquiterpenoid and triterpenoid biosynthesis, starch and sucrose metabolism, monoterpenoid biosynthesis, cysteine ​​and methionine metabolism, tryptophan metabolism, phenylpropanoid biosynthesis, and flavonoid biosynthesis. Figure 8B). Consistent with the enrichment results of DEGs, DMR-DEGs were also significantly enriched in pathways related to secondary metabolism, particularly in the metabolism of flavonoids and terpenes.

[0099] In summary, DNA methylation during tea leaf development has a potential regulatory role in the metabolism of flavonoids and terpenes.

[0100] Analysis of Metabolic Changes During Tea Leaf Development To further investigate the effects of DNA methylation on flavonoid metabolism during tea leaf development, HPLC was used to determine the changes in the content of catechins, the most abundant flavonoid in tea leaves. The results showed that the total catechin content (TC) decreased significantly with leaf development. Among ester-type catechins, the contents of GCG, EGCG, and ECG all decreased significantly, while the CG content increased significantly. Among non-ester-type catechins, the contents of EGC, C, and GC all decreased significantly, while the EC content decreased significantly.

[0101] The above results indicate that the total amount of catechins decreases significantly during the development of tea leaves. Except for CG and EC, the content of other catechin monomers is significantly reduced.

[0102] Analysis of changes in terpene metabolites during tea leaf development To further investigate the effects of DNA methylation on terpene metabolism during tea leaf development, GC-MS was used to detect changes in volatile metabolites during leaf development. A total of 58 volatile metabolites were detected in the TL and OL assays, including 20 alkenes, 10 alcohols, 7 aldehydes, 6 alkanes, 5 esters, 5 ketones, and 5 other compounds. Figure 11 A). 44 and 41 compounds were detected in TL and OL samples, respectively, with alkenes and alcohols being the most abundant. Next, we focused on terpenes and their derivatives (Xu) that exhibit significant changes in gene expression and DNA methylation levels and make important contributions to tea quality. et al. (2018). A total of 22 terpenes and their derivatives were detected in TL and OL, but only 9 substances were detected in OL. Figure 11 C). Among them, the contents of τ-cadinol, nerolidol, α-cadinol, and linalool in TL were 22.60 times, 13.74 times, 4.40 times, and 2.70 times that of OL, respectively. Figure 11 D), while the terpineol content in OL is 1.88 times that in TL.

[0103] In summary, during the development of tea leaves, the types and contents of volatile metabolites decrease, and important aroma components are significantly reduced.

[0104] Comprehensive Analysis of Important Metabolic Changes During Tea Leaf Development A total of 48 DEGs were identified in flavonoid-related metabolic pathways, of which 35 were DMR-DEGs. Among them, compared with TL, the expression levels of 8 genes in OL were significantly upregulated and the expression levels of 27 genes were significantly downregulated. Figure 12 A, 14B). Compared to TL, OL has a higher rate of change in the phenylpropanone metabolic pathway. PAL and 4CL Expression levels were all significantly downregulated, in C4H middle, CSS0002737 Significantly lowered, while CSS0049143 and CSS0029120 Significantly upward ( Figure 12 A, 15A). A total of 28 DMR-DEGs were identified in the flavonoid synthesis pathway, of which 22 genes showed significantly downregulated expression and 6 genes showed significantly upregulated expression. Except... LAR ( CSS0032189 and CSS0001408 In addition to a significant upregulation of expression levels, the remaining... LAR The expression levels were significantly downregulated, which is consistent with the differences in the content of C and GC in TL and OL. ANR Expression levels were significantly downregulated, consistent with the significant decrease in EGC content in OL. Regarding ester-type catechin synthesis, the contents of GCG, ECG, and EGCG in OL were all significantly lower than in TL, which is consistent with... SCPL The trend of expression level changes is consistent.

[0105] Furthermore, most DMR-DEGs are in a hypermethylated state ( Figure 12 B), of which the proportion of genes with significantly downregulated expression is relatively large ( Figure 12 C). Important synthetic genes, such as SCPL1A ( CSS0038512 )and LAR ( CSS0013831 HyperDMRs are present in all of them. Among these hyperDMRs, hyperCHG-DMRs and hyperCpG-DMRs are likely the main reasons for the significant decrease in gene expression levels. Figure 13 B).

[0106] In summary, the expression levels of genes related to the flavonoid metabolism pathway may be mainly affected by DNA hypermethylation, ultimately leading to the differential accumulation of catechins during tea leaf development.

[0107] Comprehensive analysis of terpene metabolism during tea leaf development A total of 75 DEGs were identified in the terpene synthesis pathway, of which 23 DMR-DEGs were significantly upregulated and 34 DMR-DEGs were significantly downregulated. Figure 14 A, 16B). Compared to TL, in OL, genes upstream of the terpene synthesis pathway include HMGR , DXS , GGPPS The expression levels were all significantly downregulated, while IDI and DXR Expression levels were all significantly upregulated. Figure 14 A).

[0108] Compared to TL, the expression levels of most genes related to monoterpene synthesis were significantly upregulated in OL, but only a small number of monoterpenoid compounds were detected in OL. ATS The expression level of terpineol showed a consistent trend with the change in terpineol content. NES The expression levels of both were significantly downregulated, which is consistent with the low levels of nerolidol in OL.

[0109] Similar to the methylation state of DEGs in the aforementioned flavonoid metabolic pathways, most DMR-DEGs are in a hypermethylated state. Figure 14 B). In NES ( CSS0013839 and CSS0000223 In the ), except for a few CHG-DMRs and CpG-DMRs located in the intergenic and body regions, the remaining regions are in a hypermethylated state. Figure 15 B). Among these DMRs, hyper CHG-DMRs may primarily cause... NES ( CSS0013839 Downregulation of expression levels, with hyper CHH-DMRs, hypo CHG-DMRs, and hypo CpG-DMRs likely being the primary cause. NES ( CSS000013839 Downregulation of expression levels.

[0110] In summary, the expression levels of genes synthesizing terpenes are affected by DNA hypermethylation to varying degrees, ultimately leading to changes in the content of volatile metabolites during tea leaf development.

[0111] English Abbreviations (Symbol List) ; ;

[0112] The above description is merely a preferred embodiment of the present invention and is not intended to limit the invention. Various modifications and variations can be made to the present invention by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A method for identifying the developmental process of tea leaves, characterized in that, The developmental process of tea leaves can be determined by observing the methylation level of CHH sites located in promoter and intergenic regions of whole-genome DNA methylation. The methylation level of the CHH sites located in the promoter and intergenic space region is positively correlated with gene expression levels.

2. A method for identifying gene expression levels in tea leaves, characterized in that, Gene expression levels in tea leaves were determined by analyzing the methylation levels of CHH sites located in promoter and intergenic regions within the whole-genome DNA methylation. The methylation level of CHH sites in DNA methylation located in promoter and intergenic regions is positively correlated with gene expression levels.

3. A method for regulating the DNA methylation level of tea leaves, characterized in that, By downregulating DNA methyltransferase CMT2 , CMT3 , MET1 and DNA demethyltransferase DME Increase the expression level to enhance DNA methylation.

4. The application of DNA methylation in regulating flavonoid and terpene secondary metabolism during tea leaf development, characterized by: By promoting DNA methylation levels, the expression levels of upstream genes HMGR, DXS, and GGPPS that synthesize terpenoid secondary metabolites are downregulated, while the expression levels of genes IDI and DXR that synthesize terpenoid secondary metabolites are upregulated, thereby regulating flavonoid and terpenoid secondary metabolism.

5. The application according to claim 4, characterized in that, When the flavonoid is a catechin, the total amount of catechin is reduced by promoting DNA methylation level. Specifically, the content of catechin gallate and epicatechin increases, while the content of other catechins decreases.

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