Camellia oleifera drought resistance comprehensive evaluation method based on multi-dimensional indexes and application thereof

Abstract

The invention discloses a comprehensive evaluation method for drought resistance of camellia oleifera based on multi-dimensional indexes and application of the comprehensive evaluation method, and relates to the technical field of plant stress resistance breeding. Performing drought stress treatment on the tea-oil tree material to be tested; 27 indexes of the tea-oil tree material to be tested are measured; a membership function analysis method is combined with principal component analysis, 19 key indexes are selected, and membership function values and weight coefficients are calculated; calculating a drought resistance coefficient; calculating drought resistance comprehensive evaluation values, and sorting according to the comprehensive evaluation values; and selecting a drought-resistant variety and a sensitive variety according to the sequence, and carrying out transcriptome comparative analysis and screening to obtain a drought-resistant key gene. According to the method, multi-dimensional indexes are constructed, key indexes are screened from the indexes, objectivity of evaluation results can be guaranteed conveniently, the drought-resistant varieties and sensitive varieties with typicality can be rapidly screened out from drought-resistant sequencing, drought-resistant key genes can be conveniently obtained through screening, then the drought-resistant key genes are applied to subsequent camellia oleifera molecular breeding, and good application prospects are achieved.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of plant stress resistance breeding, and particularly relates to a comprehensive evaluation method for drought resistance of Camellia oleifera based on multi-dimensional indexes and application thereof. BACKGROUND

[0002] Camellia oleifera is an important woody oil tree species in China, which has high economic value and ecological function. However, with the global climate change leading to frequent droughts, plants under drought stress will show leaf wilting, reduced photosynthetic efficiency, intensified oxidative damage, and even plant death, which seriously affects the growth and yield of Camellia oleifera. At present, the research on drought resistance of Camellia oleifera is mostly limited to a few varieties, and the evaluation indexes are focused on a single physiological level. There is no comprehensive evaluation method for drought resistance of Camellia oleifera based on multi-dimensional omics data, and the molecular regulation mechanism of key drought resistance genes (such as WRKY, SOD, NAC) is insufficient, which makes it impossible to provide efficient and accurate molecular markers and gene resources for Camellia oleifera stress resistance breeding. SUMMARY

[0003] The present application aims to provide a comprehensive evaluation method for drought resistance of Camellia oleifera based on multi-dimensional indexes and application thereof, so as to solve the problem of lack of multi-variety comparison and in-depth analysis of molecular mechanisms in the prior art.

[0004] To achieve the above-mentioned purpose, the present application provides the following technical scheme:

[0005] A comprehensive evaluation method for drought resistance of Camellia oleifera based on multi-dimensional indexes, specifically comprising the following steps:

[0006] Step S1, selecting Camellia oleifera materials for testing, wherein the Camellia oleifera materials for testing are 2-year-old container seedlings, and at least 10 different Camellia oleifera main cultivars are included;

[0007] Step S2, using a continuous drought method to perform drought stress treatment on the Camellia oleifera materials for testing, and setting four water gradients of normal water supply, light drought stress, moderate drought stress and severe drought stress;

[0008] Step S3, measuring 27 indexes of the Camellia oleifera materials for testing under drought stress treatment;

[0009] Step S4, selecting 19 key indexes for evaluating drought resistance of Camellia oleifera from the 27 indexes by using a membership function analysis method combined with principal component analysis, converting 8 principal components into membership function values of 8 comprehensive indexes by principal component analysis, and respectively calculating the membership function values and weight coefficients of each comprehensive index;

[0010] Step S5, calculating the drought resistance coefficients of each Camellia oleifera variety according to the indexes measured in step S3;

[0011] Step S6, according to the membership function value and the weight coefficient obtained in step S4, the drought resistance comprehensive evaluation value of each camellia oleifera variety is calculated by using the comprehensive evaluation value formula, and the drought resistance of each camellia oleifera variety is sorted according to the comprehensive evaluation value, so as to realize the comprehensive evaluation of the drought resistance of camellia oleifera;

[0012] Step S7, according to the drought resistance of each camellia oleifera variety, the optimal camellia oleifera variety in the drought resistance sorting is selected as the drought resistance variety research object, and the last camellia oleifera variety in the drought resistance sorting is selected as the sensitive variety research object, the drought resistance key gene is screened through transcriptome comparison analysis, and the drought resistance key gene is combined and applied in camellia oleifera molecular breeding.

[0013] Preferably, the 19 key indicators in step S4 include root crown ratio, root ratio, aboveground dry weight, ground diameter growth, height diameter ratio, total P content, total chlorophyll content, chlorophyll a content, chlorophyll b content, Pn, Gs, Tr, Ci, WUE, MDA content, soluble starch content, SOD, CAT and APX activity.

[0014] Preferably, the 27 indicators in step S4 further include plant height growth, root dry weight, dry matter growth, total N content, total K content, soluble sugar content, soluble protein content and POD.

[0015] Preferably, the calculation formula of the drought resistance coefficient in step S5 is: , wherein, is the drought resistance coefficient.

[0016] Preferably, the comprehensive evaluation value formula in step S6 is: , wherein, is the comprehensive evaluation value, is the weight coefficient of the first principal component, the weight coefficient is obtained by normalizing the variance contribution rate of principal component analysis, is the membership function value of the first principal component, the membership function value is calculated by range standardization, is the number of principal components, .

[0017] Preferably, the specific operation of the transcriptome alignment analysis in step S7 is as follows: using an RNA purification kit, total RNA is extracted from the leaves of drought-resistant and sensitive varieties under different drought stress treatments. Transcriptome sequencing of drought-resistant and sensitive varieties after drought stress treatment is performed using Illumina NovaSeq 150bp paired-end sequencing technology. Differentially expressed genes between the two are analyzed using the DESeq2 tool to preliminarily screen candidate genes related to drought resistance. Specific primers are designed using candidate genes. The relative expression level of target genes under different water gradients is calculated using the 2−ΔΔCt method. The reliability of gene expression patterns is verified using qRT-PCR technology. The drought resistance of Camellia oleifera is judged based on gene expression levels to determine the final key drought resistance genes.

[0018] Preferably, the key drought-resistant genes include the SOD gene, WRKY53 gene, NAC gene, FAD gene, and NewGene_26696 gene.

[0019] Preferably, the duration of each moisture gradient treatment in step S2 is 30 days.

[0020] Preferably, the principal component analysis in step S4 is performed using one or more of the following software: SPSS, SAS, Python, and R.

[0021] An application of a comprehensive evaluation method for drought resistance of Camellia oleifera based on multi-dimensional indicators, wherein the application is the application of key drought-resistant genes obtained by screening in the molecular breeding of Camellia oleifera.

[0022] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0023] This invention establishes a comprehensive evaluation method for the drought resistance of Camellia oleifera based on multi-dimensional indicators. It constructs a multi-dimensional indicator system encompassing 27 indicators, including growth morphology, physiological metabolism, photosynthetic characteristics, and antioxidant enzyme activity. Key indicators are selected from this system to ensure the objectivity and accuracy of the evaluation results. Furthermore, the combination of membership function method and principal component analysis avoids biases caused by subjective assignment, allowing for comprehensive comparison and calculation of indicators with different properties under a unified dimension. This enhances the scientific rigor and reliability of the comprehensive evaluation. Through comprehensive drought resistance ranking, typical drought-resistant and sensitive varieties can be quickly and accurately screened as research subjects. Furthermore, drought-related genes can be rapidly screened from several genes for application in subsequent molecular breeding of Camellia oleifera, greatly improving breeding efficiency and demonstrating promising application prospects. Attached Figure Description

[0024] Figure 1 This is a schematic diagram illustrating the steps of the comprehensive evaluation method of the present invention.

[0025] Figure 2 This is a schematic diagram of the expression pattern of the SOD gene under drought stress according to the present invention.

[0026] Figure 3 This is a schematic diagram of the expression pattern of the APX gene under drought stress according to the present invention.

[0027] Figure 4 This is a schematic diagram of the expression pattern of the CYP gene under drought stress according to the present invention.

[0028] Figure 5 This is a schematic diagram of the expression pattern of the FAD gene under drought stress according to the present invention.

[0029] Figure 6 This is a schematic diagram of the expression pattern of the NAC gene under drought stress according to the present invention.

[0030] Figure 7 This is a schematic diagram of the expression pattern of the WRKY gene under drought stress according to the present invention.

[0031] Figure 8 This is a schematic diagram of the expression pattern of the NewGene_26696 gene under drought stress according to the present invention. Detailed Implementation

[0032] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and embodiments.

[0033] In this embodiment, as Figure 1 - Figure 8 As shown, a comprehensive evaluation method for drought resistance of Camellia oleifera based on multi-dimensional indicators is presented. These multi-dimensional indicators refer to measurement parameters selected from multiple biological aspects such as growth morphology, physiological metabolism, photosynthetic characteristics, and antioxidant enzyme activity, facilitating a comprehensive assessment of drought resistance. The method specifically includes the following steps:

[0034] Step S1: Select the camellia oleifera material for testing. The camellia oleifera material for testing is a 2-year-old container seedling, and includes at least 10 different main varieties of camellia oleifera. In this embodiment, the 10 varieties of camellia oleifera for testing shown in Table 1 below are used to conduct a comprehensive evaluation of the drought resistance of camellia oleifera.

[0035] Table 1 - Camellia oleifera varieties tested

[0036] Serial number Variety name Origin 1 Huajin Camellia seedling base of Jiujing Ecological Agricultural Development Co., Ltd. 2 Huaxin Camellia seedling base of Jiujing Ecological Agricultural Development Co., Ltd. 3 Huaer Camellia seedling base of Jiujing Ecological Agricultural Development Co., Ltd. 4 Xianglin 210 Camellia seedling base of Jiujing Ecological Agricultural Development Co., Ltd. 5 Xianglin 1 Camellia seedling base of Jiujing Ecological Agricultural Development Co., Ltd. 6 Ganzhouyou 1 Ganzhou Forestry Science Institute 7 Ganzhouyou 7 Ganzhou Forestry Science Institute 8 Ganzhouyou 10 Ganzhou Forestry Science Institute 9 GLS Ganzhouyou 1 Ganzhou Forestry Science Institute 10 GLS Ganzhouyou 4 Ganzhou Forestry Science Institute

[0037] Step S2: The tested Camellia oleifera materials were subjected to drought stress using the continuous drought method, with four water gradients set up: normal water supply, mild drought stress, moderate drought stress, and severe drought stress.

[0038] Specifically, the drought stress treatment experiment was a pot experiment, and water was controlled by continuous drought method. The duration of the four water gradient treatments was 30 days. The soil water gradients for each treatment are shown in Table 2 below.

[0039] Table 2 – Soil Moisture Gradients for Each Treatment

[0040] Drought gradient Field maximum water holding capacity Soil quality water content Normal water supply 65%～75% 25%～38% Mild drought 44%～54% 17%～21% Moderate drought 30%～40% 11%～15% Severe drought 16%～26% 6%～9%

[0041] Step S3: Determine 27 indicators of the tested Camellia oleifera materials under drought stress treatment;

[0042] Specifically, the 27 indicators include 19 key indicators, as well as plant height growth, root dry weight, dry matter increase, total nitrogen (N) content, total potassium (K) content, soluble sugar content, soluble protein content, and phosphorus (POD). Plant height growth refers to the net increase in plant height within a certain growth cycle, directly reflecting the growth vitality of the above-ground parts of the camellia plant. This indicator can quickly determine whether the plant has experienced growth stagnation due to drought. Root dry weight is the weight of the camellia root system after it has been completely separated from the soil and dried, directly reflecting the robustness of the root system. This indicator can determine the root absorption area and water absorption capacity. Dry matter increase refers to the net accumulation of dry matter in the entire camellia plant within a certain period, comprehensively reflecting the efficiency of photosynthetic product accumulation and distribution. This indicator directly reflects the plant's ability to maintain a balance between survival and growth under drought conditions. Total nitrogen content refers to the total nitrogen content in the camellia plant. Nitrogen is a mineral that is essential for plant growth. The core elements for the synthesis of proteins, chlorophyll, nucleic acids, and other key substances in plants are potassium. This indicator ensures chlorophyll synthesis and enzyme activity maintenance. Total potassium content refers to the total potassium content in the Camellia oleifera plant. Potassium plays a crucial role in maintaining cell osmotic pressure, stomatal movement, and photosynthesis. This indicator can determine the cell's water retention capacity and antioxidant capacity. Soluble sugar content refers to the total amount of water-soluble monosaccharides, disaccharides, and other sugars in the Camellia oleifera plant. Changes in its content directly reflect the plant's osmotic adaptation to adverse conditions. This indicator can determine the plant's osmotic regulation capacity and dehydration resistance. Soluble protein content refers to the total amount of protein in the Camellia oleifera plant that can dissolve in water or dilute salt solutions. This indicator can determine antioxidant and osmotic regulation capacity. POD is peroxidase, used to reduce cell membrane lipid peroxidation damage. This indicator can determine the plant's ability to scavenge ROS. The specific indicators are shown in Table 3 below. Drought resistance coefficient can be calculated through these indicators.

[0043] Table 3 - Principal Component Score Coefficient Matrix

[0044] Specifically, this invention establishes a multi-dimensional evaluation method for the drought resistance of Camellia oleifera by integrating 19 key indicators, including root-to-shoot ratio, root-to-plant ratio, aboveground dry weight, ground diameter growth, height-to-diameter ratio, total phosphorus content, total chlorophyll content, chlorophyll a content, chlorophyll b content, Pn, Gs, Tr, Ci, WUE, MDA content, soluble starch content, SOD, CAT, and APX activity. This method replaces the traditional single-indicator evaluation method. Total phosphorus content refers to the total phosphorus content in the Camellia oleifera plant, Pn is the net photosynthetic rate, which refers to the amount of CO2 absorbed by the leaves per unit time and per unit leaf area, and Gs is the stomatal conductance. Tr is the rate of CO2 or water conduction through the stomata of a leaf per unit time and per unit leaf area; transpiration rate is the amount of water lost through transpiration from the leaves of the tea plant per unit time and per unit leaf area; Ci is the intercellular CO2 concentration, the CO2 concentration in the intercellular spaces of the mesophyll cells of the tea plant; WUE is the water use efficiency, the ratio of net photosynthetic rate (Pn) to transpiration rate (Tr) of the tea plant; MDA is malondialdehyde, the content of malondialdehyde, the end product of membrane lipid peroxidation, in the tea plant; SOD is superoxide dismutase; CAT is catalase; APX is ascorbate peroxidase.

[0045] Step S4: Using membership function analysis combined with principal component analysis, 19 key indicators for evaluating the drought resistance of Camellia oleifera were selected from 27 indicators. Through principal component analysis, the 8 principal components were transformed into membership function values ​​of 8 comprehensive indicators, and the membership function value and weight coefficient of each comprehensive indicator were calculated respectively.

[0046] Specifically, membership functions are used to transform the measured values ​​of each indicator into standardized values ​​between 0 and 1 to eliminate the influence of dimensions. Principal component analysis is used for dimensionality reduction, extracting eight comprehensive indicators from multiple indicators and determining their weights based on their variance contribution rates, thereby achieving a comprehensive evaluation of multiple indicators. The 19 key indicators in step S4 include root-to-shoot ratio, root-to-total-plant ratio, aboveground dry weight, diameter growth, height-to-diameter ratio, total phosphorus content, total chlorophyll content, chlorophyll a content, chlorophyll b content, Pn, Gs, Tr, Ci, WUE, MDA content, and other parameters. Soluble starch content, SOD, CAT and APX activities, 19 key indicators all showed high variance contribution rates in principal component analysis, which can reflect the differences in drought resistance of Camellia oleifera to the greatest extent and reflect the response mechanism of Camellia oleifera under drought stress. Principal component analysis was performed using one or more of SPSS, SAS, Python and R language software. The principal component analysis was based on the characteristic criterion of eigenvalue greater than 1 and the cumulative contribution rate was comprehensively considered. The cumulative contribution rate of the 8 principal components reached 97.078%, which can fully represent most of the information of the original indicators.

[0047] Step S5: Calculate the drought resistance coefficient of each camellia oleifera variety based on the indicators measured in step S3;

[0048] Specifically, the formula for calculating the drought resistance coefficient in step S5 is as follows: ,in, The drought resistance coefficient represents the ability of a certain indicator to be maintained under drought stress. The larger the value, the less affected the indicator is by drought and the stronger its drought resistance.

[0049] Step S6: Based on the membership function value and weight coefficient obtained in step S4, calculate the comprehensive drought resistance evaluation value of each camellia oleifera variety using the comprehensive evaluation value formula, and rank the drought resistance of each camellia oleifera variety according to the size of the comprehensive evaluation value to achieve a comprehensive evaluation of the drought resistance of camellia oleifera.

[0050] Specifically, the formula for the comprehensive evaluation value in step S6 is: ,in, For comprehensive evaluation, For the first The weight coefficients of each principal component are obtained by normalizing the variance contribution rate of the principal component analysis. For the first The membership function values ​​of each principal component are obtained through range standardization. Number of main components Based on the relationship between each indicator and the drought resistance of camellia oleifera, the indicators are divided into positive and negative indicators. A larger positive indicator value indicates stronger drought resistance, while a larger negative indicator value indicates weaker drought resistance. The positive indicators are... Negative indicators are ,in, This represents the original measured value for a specific camellia oleifera variety under this indicator. The minimum value for this index among all tested camellia oleifera varieties. This represents the maximum value for this index for all tested camellia oleifera varieties. The membership function values ​​of this variety under this indicator are calculated as shown in Table 4 below, where U(X1) is membership function value 1, U(X2) is membership function value 2, U(X3) is membership function value 3, U(X4) is membership function value 4, U(X5) is membership function value 5, U(X6) is membership function value 6, U(X7) is membership function value 7, and U(X8) is membership function value 8.

[0051] Table 4 – Ranking of Membership Function Values ​​(U) and Comprehensive Evaluation Values ​​(D) of Different Camellia oleifera Varieties under Drought Stress

[0052] Step S7: Based on the drought resistance ranking of each Camellia oleifera variety, select the Camellia oleifera variety with the best drought resistance ranking as the research object of drought resistance varieties, and select the Camellia oleifera variety with the lowest drought resistance ranking as the research object of sensitive varieties. Screen the key drought resistance genes through transcriptome comparison analysis, and apply the combination of key drought resistance genes to the molecular breeding of Camellia oleifera.

[0053] Further, the specific operation of transcriptome alignment analysis in step S7 is as follows: using an RNA purification kit, total RNA was extracted from the leaves of drought-resistant and sensitive varieties under different drought stress treatments. Transcriptome sequencing was performed on the drought-resistant and sensitive varieties after drought stress treatment using Illumina NovaSeq 150bp paired-end sequencing technology. Differentially expressed genes between the two were analyzed using the DESeq2 tool to preliminarily screen candidate genes related to drought resistance. Specific primers were designed for the candidate genes, and the relative expression level of the target gene under different water gradients was calculated using the 2−ΔΔCt method. The reliability of the gene expression pattern was verified using qRT-PCR technology. The drought resistance of Camellia oleifera was judged based on the gene expression level, and the final key drought resistance genes were determined.

[0054] Specifically, in this embodiment, two Camellia oleifera varieties with significant differences in drought resistance were selected as the core research objects to ensure the specificity and comparability of gene screening. Through multi-dimensional comprehensive evaluation, the Huashuo variety was determined to be a drought-resistant variety, maintaining strong growth adaptability and physiological regulation ability even under severe drought stress. The GLS Ganzhou Oil No. 4 variety was determined to be a sensitive variety, with significantly inhibited growth and nutrient absorption under severe drought, showing a clear difference in drought resistance compared to Huashuo. Therefore, the Huashuo variety was selected as the drought-resistant variety research object, and the GLS Ganzhou Oil No. 4 variety was selected as the sensitive variety research object. Four water gradient treatments were performed on the GLS Ganzhou Oil No. 4 variety and the GLS variety. After 30 days of treatment, functional leaves were collected from each treatment group. Mature leaves free from pests and diseases and with consistent growth were selected. Three biological replicates were set up for each treatment group to ensure sample representativeness. An RNA purification kit was used, and the operation was strictly followed according to the kit instructions to extract total RNA from the leaves. The purpose was to obtain RNA samples with high purity and good integrity, and to avoid interference from impurities such as proteins and genomic DNA in subsequent transcriptome sequencing and qRT-PCR experiments. The extraction operation was carried out using existing technology.

[0055] Illumina NovaSeq 150bp paired-end sequencing technology was used. This technology features high sequencing depth, high accuracy, and high throughput, comprehensively covering transcriptome information of tea leaves under different drought stresses, and obtaining massive gene expression data. The sequencing sample range included transcriptome sequencing of samples from four water gradient treatment groups for each variety to ensure the capture of gene expression differences between the two under different drought levels. The gene expression data obtained from sequencing were analyzed using the DESeq2 tool. By comparing the gene expression levels of "Asus (drought resistant)" and "GLS4 (sensitive)" under the same water gradient, genes with significant differences in expression levels were screened. The difference judgment was based on the standard criteria for transcriptome differential analysis. For example: and A preliminary set of candidate genes related to drought resistance in Camellia oleifera was obtained. For candidate genes screened from the transcriptome, such as SOD gene, WRKY53 gene, NAC gene, FAD gene, and NewGene_26696 gene, specific primers were designed based on the candidate genes. UBQ5 was selected as an internal reference gene. The primer sequences have been determined as follows: F:AATGTGAAGGCGAAGATCCAA, R:ACGGAGACGGAGGACGAGAT, to ensure strong primer specificity and consistent amplification efficiency. The specific primer sequences of some key genes are shown in Table 5 below.

[0056] Table 5 - Gene Information Table

[0057] Specifically, Figure 2 - Figure 8 This is a bar chart showing the relative expression levels of genes under different treatments, used to illustrate the differences in gene expression across different treatment groups. The vertical axis (Y-axis) quantifies the gene expression level, and the horizontal axis (X-axis) includes four groups: SCK group (normal water supply), SM1 group (mild drought stress), SM2 group (moderate drought stress), and SM3 group (severe drought stress). Each bar represents the relative expression level of the gene in the corresponding treatment group, and the error bars above the bars reflect the degree of data variation.

[0058] The SOD gene is the superoxide dismutase gene, which is used to scavenge superoxide anion free radicals and protect cells from oxidative damage. Figure 2 It can be seen that the relative expression level of SOD was the lowest in the SCK group, indicating that the expression level of the SOD gene was low under the control conditions. The relative expression levels of SOD in the SM1, SM2 and SM3 groups were significantly higher than those in the SCK group. Moreover, the SOD expression level showed an upward trend with the treatment, and the difference in SOD expression level between the groups was significant. This indicates that the gene helps to enhance the plant's antioxidant capacity and cope with the oxidative stress caused by drought.

[0059] APX is ascorbate peroxidase, which, through... Figure 3 It can be seen that: the value of the vertical axis (Y-axis) ranges from 0 to 3. The relative expression level of APX gene in the SCK group is about 1, which represents the basal expression level. The relative expression level of APX gene in the SM1 group is significantly increased and is significantly different from that in the SCK group. The relative expression level of APX gene in the SM2 group is significantly decreased and is much lower than that in the SCK group. The relative expression level of APX gene in the SM3 group has rebounded and is significantly different from that in the SCK group and is also highly significantly different from that in the SM2 group. This indicates that drought stress has a complex regulatory effect on the expression of APX gene, and that this gene helps to cope with oxidative stress caused by adversity under mild drought stress.

[0060] CYP is a cytochrome P450 enzyme that, through... Figure 4 It can be seen that: the value of the vertical axis (Y-axis) ranges from 0 to 6. The relative expression level of the CYP gene in the SCK group is about 2, which represents the basal expression level. The relative expression level of CYP in the SM1 and SM2 groups is lower than that in the SCK group. The relative expression level of CYP in the SM3 group is significantly increased, and there are significant differences compared with the SCK, SM1 and SM2 groups. This indicates that the gene helps the plant cope with specific environmental stresses such as severe drought stress.

[0061] The FAD gene is a fatty acid desaturase gene, used to maintain membrane lipid stability and reduce MDA accumulation. Figure 5 It can be seen that: the vertical axis (Y-axis) ranges from 0 to 8. The relative expression level of the FAD gene in the SCK group is about 1, which represents the basal expression level. The relative expression level of the FAD gene in the SM1 group shows an upward trend, but there is no significant difference compared with the SCK group. The relative expression level of the FAD gene in the SM2 group is extremely low, much lower than that in the SCK group. The relative expression level of the FAD gene in the SM3 group increases significantly, and there are significant differences compared with the SCK, SM1 and SM2 groups. This indicates that drought stress has a complex regulatory effect on the expression of the FAD gene, and that this gene helps to enhance the plant's antioxidant capacity and cope with the oxidative stress caused by drought.

[0062] The NAC gene is a stress-responsive transcription factor that participates in activating proline synthesis genes and enhancing osmotic regulation. Figure 6It can be seen that: the value of the vertical axis (Y-axis) ranges from 0 to 2.5. The relative expression level of NAC gene in the SCK group is about 1.3, which represents the basal expression level. The relative expression level of NAC gene in the SM1 group is lower than that in the SCK group. The relative expression level in the SM2 group is further reduced. The relative expression level of NAC gene in the SM3 group is significantly increased and is significantly different from that in the SCK, SM1 and SM2 groups. This indicates that drought stress has a complex regulatory effect on the expression of NAC gene, and that this gene helps to enhance the plant's antioxidant capacity and cope with the oxidative stress caused by drought.

[0063] The WRKY53 gene is a transcription factor of the WRKY family, used to regulate the phenylpropanone metabolic pathway, increase lignification, and reduce water loss. Figure 7 It can be seen that: the relative expression level of WRKY53 gene in the SCK group is about 1, which represents the basal expression level; the relative expression level of WRKY in the SM1 group is significantly increased, showing a highly significant difference compared with the SCK group; the relative expression level of WRKY in the SM2 group is decreased, but is still much higher than that in the SCK group, and shows a highly significant difference compared with the SCK group; the relative expression level of WRKY in the SM3 group continues to remain at a high level, showing a highly significant difference compared with the SCK group. At the same time, there are significant differences between the SM1 group and the SM2 and SM3 groups, indicating that this gene continuously participates in the regulation of stress response throughout the treatment process and helps to cope with environmental stress.

[0064] The NewGene_26696 gene is specifically associated with the ubiquitin-mediated protein degradation pathway, through... Figure 8 It can be seen that the relative expression level of NewGene_26696 in the SCK group is about 1.5, which represents the basal expression level. The relative expression level in the SM1 group is lower than that in the SCK group. The relative expression level in the SM2 group is further reduced. The relative expression level of NewGene_26696 in the SM3 group is significantly increased, and there are extremely significant differences compared with the SCK, SM1 and SM2 groups. This gene helps to enhance the plant's antioxidant capacity and cope with oxidative stress caused by drought.

[0065] Specifically, using leaf RNA from the Huashuo and GLS Ganzhou Oil No. 4 varieties under various water gradient treatments as templates, qRT-PCR experiments were conducted. The relative expression level of the target gene was calculated using the 2−ΔΔCt method. The expression level of the internal reference gene UBQ5 was used as a reference to standardize the expression level of the target gene in different varieties and different water gradients, thus eliminating the influence of differences in RNA amount and reverse transcription efficiency among samples. The value is the difference between the target gene and the internal reference gene in a single sample. , The value represents the cycle number at which the qPCR amplification curve reaches the threshold; a smaller value indicates a higher initial gene expression level. (Calculation...) The value, with "ASUS-SCK group" as the calibration group and the relative expression level set to 1, then... Calculate the relative expression level: This process involves uniformly converting the expression levels of target genes from different varieties and water gradients into "folds relative to the ASUS-SCK group," achieving standardized cross-sample comparison. Then, the "relative expression levels of target genes" obtained from qRT-PCR are compared with the "gene expression trends" obtained from transcriptome sequencing to verify their consistency. The verification conditions are: consistent trends within varieties and consistent differences between varieties. Intra-variety consistent trends mean that the direction of expression change shown by qRT-PCR for the same variety under different water gradients is consistent with the transcriptome. Inter-variety consistent differences mean that the difference in expression levels between ASUS and GLS4 shown by qRT-PCR under the same water gradient is consistent with the transcriptome. Only when the candidate gene meets the criteria of "consistent trends" and "directly associated with drought resistance" is the expression level considered consistent. Only when a candidate gene is identified as a key drought-resistant gene can it be confirmed. If a candidate gene shows in the transcriptome that "the expression level of the Huashuo variety is significantly upregulated / downregulated under drought stress, and is significantly different from that of the GLS Ganzhou Oil No. 4 variety", and the qRT-PCR results replicate this trend, then the gene is confirmed as the final key drought-resistant gene, which is directly related to the drought resistance of Camellia oleifera. The key drought-resistant gene is a gene that is verified by transcriptome sequencing and qRT-PCR, shows significant expression differences between drought-resistant and sensitive varieties, and is closely related to the drought resistance of Camellia oleifera. It may include the SOD gene, WRKY53 gene, NAC gene, FAD gene, and NewGene_26696 gene. The key drought-resistant gene can be used alone or in combination for molecular marker-assisted selection or transgenic breeding of Camellia oleifera.

[0066] Furthermore, an application of a comprehensive evaluation method for drought resistance of Camellia oleifera based on multi-dimensional indicators is proposed. This method is applied to the molecular breeding of Camellia oleifera using key drought-resistant genes obtained through screening. It is mainly applied in the field of molecular breeding for stress resistance of Camellia oleifera, aiming to improve the drought resistance characteristics of Camellia oleifera varieties through genetic engineering, cultivate new Camellia oleifera varieties with strong drought resistance and stable yield, and alleviate the negative impact of drought stress caused by global climate change on the growth, development and yield of Camellia oleifera.

[0067] Specifically, the selected drought-resistant key genes are used as molecular markers. Using the specific primers in Table 5, the expression levels of these genes in different Camellia oleifera varieties are detected by qRT-PCR. Based on the gene expression levels, drought-resistant Camellia oleifera varieties are screened out, shortening the breeding cycle and improving breeding efficiency. For example, the expression level of the SOD gene can be detected during the seedling stage of Camellia oleifera to preliminarily determine the ROS scavenging ability of the varieties and screen out potential drought-resistant varieties. Then, the selected drought-resistant key genes are applied to the molecular breeding of Camellia oleifera. Through genetic engineering, key drought-resistant genes are introduced into Camellia oleifera varieties with weak drought resistance, or key drought-resistant genes are used as molecular markers to assist in the stress resistance breeding of Camellia oleifera and cultivate new Camellia oleifera varieties with strong drought resistance.

[0068] In summary, this invention provides a comprehensive evaluation method for the drought resistance of Camellia oleifera based on multi-dimensional indicators. By integrating growth, physiological, photosynthetic, and transcriptomic data, key drought-resistant genes such as SOD, WRKY53, NAC, and FAD are screened out, which facilitates the cultivation of new Camellia oleifera varieties with strong drought resistance and has good application prospects.

[0069] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

Claims

1. A comprehensive evaluation method for drought resistance of Camellia oleifera based on multi-dimensional indicators, characterized in that, Specifically, the following steps are included: Step S1: Select test Camellia oleifera materials, wherein the test Camellia oleifera materials are 2-year-old container seedlings, and include at least 10 different main Camellia oleifera varieties; Step S2: The tested Camellia oleifera materials were subjected to drought stress using the continuous drought method, with four water gradients set up: normal water supply, mild drought stress, moderate drought stress, and severe drought stress. Step S3: Determine 27 indicators of the tested Camellia oleifera materials under drought stress treatment; Step S4: Using membership function analysis combined with principal component analysis, 19 key indicators for evaluating the drought resistance of Camellia oleifera are selected from the 27 indicators. Through principal component analysis, the 8 principal components are transformed into membership function values ​​of 8 comprehensive indicators, and the membership function value and weight coefficient of each comprehensive indicator are calculated respectively. Step S5: Calculate the drought resistance coefficient of each camellia oleifera variety based on the indicators measured in step S3; Step S6: Based on the membership function value and weight coefficient obtained in step S4, calculate the comprehensive drought resistance evaluation value of each camellia oleifera variety using the comprehensive evaluation value formula, and rank the drought resistance of each camellia oleifera variety according to the size of the comprehensive evaluation value to achieve a comprehensive evaluation of the drought resistance of camellia oleifera. Step S7: Based on the drought resistance ranking of each Camellia oleifera variety, select the Camellia oleifera variety with the best drought resistance ranking as the research object of drought resistance varieties, and select the Camellia oleifera variety with the lowest drought resistance ranking as the research object of sensitive varieties. Screen the key drought resistance genes through transcriptome comparison analysis, and apply the combination of key drought resistance genes to the molecular breeding of Camellia oleifera.

2. The comprehensive evaluation method for drought resistance of Camellia oleifera based on multi-dimensional indicators according to claim 1, characterized in that, The 19 key indicators in step S4 include root-to-shoot ratio, root-to-total-plant ratio, aboveground dry weight, ground diameter growth, height-to-diameter ratio, total phosphorus content, total chlorophyll content, chlorophyll a content, chlorophyll b content, Pn, Gs, Tr, Ci, WUE, MDA content, soluble starch content, SOD, CAT, and APX activity.

3. The comprehensive evaluation method for drought resistance of Camellia oleifera based on multi-dimensional indicators according to claim 1, characterized in that, The 27 indicators in step S4 also include plant height growth, root dry weight, dry matter growth, total N content, total K content, soluble sugar content, soluble protein content, and POD.

4. The comprehensive evaluation method for drought resistance of Camellia oleifera based on multi-dimensional indicators according to claim 1, characterized in that, The formula for calculating the drought resistance coefficient in step S5 is as follows: ,in, This is the drought resistance coefficient.

5. The comprehensive evaluation method for drought resistance of Camellia oleifera based on multi-dimensional indicators according to claim 1, characterized in that, The formula for the comprehensive evaluation value in step S6 is: ,in, For comprehensive evaluation, For the first The weighting coefficients of each principal component are obtained by normalizing the variance contribution rate of the principal component analysis. For the first The membership function values ​​of each principal component are obtained through range standardization. Number of main components .

6. The comprehensive evaluation method for drought resistance of Camellia oleifera based on multi-dimensional indicators according to claim 1, characterized in that, The specific operation of transcriptome alignment analysis in step S7 is as follows: Total RNA was extracted from the leaves of drought-resistant and sensitive varieties under different drought stress treatments using an RNA purification kit. Transcriptome sequencing was performed on both drought-resistant and sensitive varieties after drought stress treatment using Illumina NovaSeq 150bp paired-end sequencing technology. Differentially expressed genes were analyzed using the DESeq2 tool to preliminarily screen candidate genes related to drought resistance. Specific primers were designed based on these candidate genes. The relative expression levels of target genes under different water gradients were calculated using the 2−ΔΔCt method. The reliability of the gene expression pattern was verified using qRT-PCR technology. The drought resistance of Camellia oleifera was determined based on the gene expression levels, and the final key drought-resistant genes were identified.

7. The comprehensive evaluation method for drought resistance of Camellia oleifera based on multi-dimensional indicators according to claim 6, characterized in that, The key drought-resistant genes include the SOD gene, WRKY53 gene, NAC gene, FAD gene, and NewGene_26696 gene.

8. The comprehensive evaluation method for drought resistance of Camellia oleifera based on multi-dimensional indicators according to claim 1, characterized in that, The duration of each moisture gradient treatment in step S2 is 30 days.

9. The comprehensive evaluation method for drought resistance of Camellia oleifera based on multi-dimensional indicators according to claim 1, characterized in that, The principal component analysis in step S4 uses one or more of the following software: SPSS, SAS, Python, and R.

10. An application of a comprehensive evaluation method for drought resistance of Camellia oleifera based on multi-dimensional indicators according to any one of claims 1-9, characterized in that, The application described is the use of the key drought-resistant genes obtained through screening in the molecular breeding of Camellia oleifera.

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