Drought-resistant physiological detection method for chenopodiaceae plant kochia scoparia

Abstract

The invention discloses a chenopodiaceae plant kochia scoparia drought-resistant physiological detection method, and relates to the technical field of drought-resistant physiological detection.The method comprises the steps that S1, samples are prepared and collected; s2, gene expression analysis; s3, carrying out molecular biological verification; and S4, data analysis and conclusion. According to the chenopodium plant kochia scoparia drought resistance physiological detection method, gene expression changes of the kochia scoparia under drought stress are analyzed through gene expression analysis, differentially expressed genes under the drought stress are screened out, and the relationship between the functions of the differentially expressed genes and drought resistance is verified through molecular biology verification; according to the gene expression data and the molecular biology verification result, the conclusion of the drought resistance of the kochia scoparia is obtained, the purpose of physiological detection of drought resistance of the kochia scoparia is achieved, the whole detection process is accurate and efficient, the expression conditions of a large number of genes can be detected at the same time, the detection efficiency is greatly improved, and the drought resistance and adaptability of the kochia scoparia are evaluated more accurately.

Description

Technical Field

[0001] The invention relates to the technical field of drought resistance physiological detection, and in particular to a method for detecting drought resistance physiologically of a Chenopodiaceae plant Kochia scoparia. Background Art

[0002] Kochia scoparia is a plant of the genus Chenopodiaceae in the Amaranthaceae family, and also belongs to the Chenopodiaceae family. Kochia scoparia is a semi-shrub, 20 to 80 cm tall, with a woody stem that is usually low, no more than 10 cm tall, branched, yellowish brown or dark brown; the branches of the current year are light yellowish brown or light red. The leaves are alternate, slightly flat, and strip-shaped, with the regular leaves clustered on short axillary branches. In China, Kochia scoparia is distributed in Heilongjiang, Liaoning, Inner Mongolia, Hebei, Shanxi, Shaanxi, Ningxia, western Gansu, Xinjiang and Tibet, and grows on hillsides, sandy land, deserts, etc. Kochia scoparia has a strong ability to adapt to arid habitat conditions and is an excellent forage grass in desert areas, and all kinds of livestock like to eat it.

[0003] As an excellent forage in desert areas, Kochia scoparia has strong drought resistance. By conducting drought resistance physiological tests on it, we can gain a deeper understanding of its drought resistance mechanism and provide a theoretical basis for breeding better drought-resistant varieties. At the same time, it also helps to evaluate the growth potential and adaptability of Kochia scoparia in arid areas, and provide a scientific basis for the rational use and protection of this plant resource. At present, the detection methods of Kochia scoparia's drought resistance physiology mainly include measuring morphological indicators (such as root-crown ratio, seedling height, etc.) and physiological and biochemical indicators (such as chlorophyll content, carotenoid content, cell membrane permeability, free proline content, etc.); these indicators can reflect the growth status, physiological changes and drought resistance of Kochia scoparia under drought stress.

[0004] However, in the actual detection process, since the existing detection methods mainly rely on the determination of multiple physiological and biochemical indicators, there may be correlation or redundancy between different indicators, and the changing trends and correlations of different indicators under drought stress may vary depending on factors such as specific plants, growth stages and stress levels, the evaluation results are not accurate or comprehensive, and the determination methods of some indicators are more complicated or time-consuming. For example, the determination of free proline requires extraction using the sulfosalicylic acid method and a series of chemical reactions to obtain the results, which not only increases the measurement cost, but also limits the measurement efficiency.

[0005] Therefore, it is urgent to improve this shortcoming. The present invention studies and improves the existing technology and its shortcomings, and provides a method for detecting the drought resistance of the Chenopodiaceae plant Kochia scoparia. Summary of the invention

[0006] The purpose of the present invention is to provide a method for detecting the drought resistance of the Chenopodiaceae plant Kochia scoparia to solve the problems raised in the above background technology.

[0007] To achieve the above object, the present invention provides the following technical solution: a method for detecting the drought resistance of the Chenopodiaceae plant Kochia scoparia, comprising the following steps:

[0008] S1. Sample preparation and collection: Obtain Kochia scoparia plant samples for subsequent analysis to ensure that the collected samples are representative. The collected Kochia scoparia plant samples were quickly frozen and stored in a -80°C refrigerator to prevent RNA degradation. Before RNA extraction, the samples were taken out of the refrigerator and thawed on ice.

[0009] S2. Gene expression analysis: extract total RNA from the collected samples and perform quality inspection, then reverse transcribe RNA into cDNA to prepare for subsequent sequencing or chip analysis, use high-throughput sequencing technology or gene chip technology to sequence or hybridize cDNA to obtain gene expression data, and then perform bioinformatics analysis on the gene expression data to screen out genes that are differentially expressed under drought stress;

[0010] S3. Molecular biological verification: Screen candidate genes related to drought resistance from differentially expressed genes, and introduce candidate genes into appropriate host cells for expression verification through gene cloning, expression vector construction, cell transfection and other technologies, and then verify the functions of candidate genes to determine their role in drought resistance;

[0011] S4. Data analysis and conclusion: Through statistical analysis of gene expression data and molecular biological verification results, the drought resistance of Kochia scoparia was concluded;

[0012] S5. Repeat the experiment: Repeat steps S1 to S4 to conduct biological replication experiments, and perform statistical analysis on the results to improve the reliability and accuracy of the experiment.

[0013] Furthermore, the specific operation of step S1 is: selecting Kochia scoparia plants with consistent growth conditions and at the same growth stage as test materials, and subjecting the selected Kochia scoparia plants to drought stress treatment to simulate a drought environment, and then collecting leaves or other tissues of the Kochia scoparia plants as samples at a specific time point after the drought stress treatment.

[0014] Furthermore, before the drought stress treatment begins, the Kochia scoparia plants are pre-treated by watering, fertilizing, etc. to ensure that the plants are in the best growth state, and the drought stress treatment includes setting the drought stress degree and selecting the stress time point, as follows:

[0015] Setting the degree of drought stress: According to the research needs, different degrees of drought stress can be set, such as mild, moderate and severe drought, by controlling the amount of irrigation (gradually reducing the amount of irrigation according to the set degree of drought stress, and using the weighing method or soil moisture meter to monitor the changes in soil moisture), soil moisture (changing the soil texture by adding media such as sand, gravel and vermiculite, reducing the soil water holding capacity, or directly reducing the soil moisture content to simulate a drought environment) or air humidity (in a controlled environment chamber, adjusting the relative humidity through a humidifier or dehumidifier to simulate a drought environment) to achieve this;

[0016] Select stress time point: Determine the start time, duration and sampling time point of drought stress.

[0017] Furthermore, the step S2 specifically includes the following sub-steps:

[0018] S21. RNA extraction: Use RNA extraction reagents (such as TRIzol, etc.) to extract total RNA from the collected samples, perform RNA quality testing and purification to ensure the integrity and purity of the RNA;

[0019] S22, RNA reverse transcription: Use a reverse transcription kit to perform reverse transcription reaction and set the reaction conditions to reverse transcribe the extracted total RNA into cDNA for subsequent gene expression analysis;

[0020] S23. Construction of gene expression profile: Sequencing or hybridizing cDNA using high-throughput sequencing technology (such as RNA-Seq) or gene chip technology, and obtaining the gene expression profile of Kochia scoparia under drought stress by comparing with the reference genome or gene database;

[0021] S24. Analysis of differentially expressed genes: Use bioinformatics software to analyze the gene expression profile, screen out genes that are differentially expressed under drought stress, and judge their role in the drought resistance process based on the changes in the expression levels of the differentially expressed genes.

[0022] Furthermore, in step S21, RNA purification is an optional operation, which is performed only when the quality test fails (more impurities or protein contamination occurs during RNA extraction). Specifically, RNA purification is performed using an RNA purification column, and the dissolved RNA sample is passed through the purification column, and washing and elution steps are performed according to the instructions of the kit to finally obtain purified RNA.

[0023] Furthermore, the step S3 specifically includes the following sub-steps:

[0024] S31. Candidate gene screening: Based on information such as gene functional annotation, literature reports or experimental verification, genes with potential drought resistance functions, i.e. candidate genes related to drought resistance, are selected from the screened differentially expressed genes;

[0025] S32. Gene cloning and expression verification: clone the selected candidate genes, construct expression vectors, and then introduce the expression vectors into host cells for expression verification, such as Escherichia coli, yeast or plant cells;

[0026] S33. Functional analysis: Study the role of cloned candidate genes in drought resistance by gene knockout, overexpression or mutation, perform functional analysis on cloned candidate genes, and verify the functions of candidate genes using molecular biology techniques (such as protein blotting, enzyme activity assay, etc.).

[0027] Furthermore, in step S33, the three gene function analysis methods are specifically performed as follows:

[0028] Gene knockout: Deleting or disrupting candidate genes in the genome through gene editing technology (such as CRISPR / Cas9) to study the effect of gene deletion on plant drought resistance;

[0029] Gene overexpression: By constructing expression vectors, candidate genes are overexpressed in plants to study the effects of overexpression on plant drought resistance;

[0030] Gene mutation: The specific amino acid sequence in the candidate gene is changed through site-directed mutagenesis to study the effect of changes in gene function on plant drought resistance.

[0031] Furthermore, in step S33, the molecular biology technology verification specifically includes:

[0032] Western blotting: using specific antibodies to detect the expression level and distribution of proteins encoded by candidate genes in plants. Specifically, by comparing the expression changes of proteins under different drought stress conditions, the role of candidate genes in drought resistance can be inferred.

[0033] Enzyme activity assay: On the premise that the protein encoded by the candidate gene has enzyme activity, enzyme activity assay is used to evaluate its activity changes under drought stress, which helps to understand how the candidate gene affects the plant's drought resistance by regulating enzyme activity.

[0034] Furthermore, the specific operation of step S4 is: performing statistical analysis on the gene expression data and molecular biology verification results, comparing the gene expression changes of Kochia scoparia under different drought stress levels and time points, evaluating the drought resistance of Kochia scoparia based on the analysis results, obtaining the gene expression changes of Kochia scoparia under drought stress and its relationship with drought resistance, exploring possible drought resistance mechanisms, and proposing subsequent drought-resistant variety breeding and cultivation management recommendations.

[0035] The present invention provides a method for detecting the drought resistance of the Chenopodiaceae plant Kochia scoparia, which has the following beneficial effects:

[0036] This method uses gene expression analysis to analyze the changes in gene expression of Kochia scoparia under drought stress, screens out differentially expressed genes under drought stress, and verifies the functions of the differentially expressed genes and their relationship with drought resistance through molecular biology verification, thereby drawing conclusions about the drought resistance of Kochia scoparia based on the gene expression data and the molecular biology verification results, and achieving the purpose of physiological detection of drought resistance of Kochia scoparia. The entire detection process is accurate and efficient. Compared with existing detection methods, it can simultaneously detect the expression of a large number of genes, greatly improving the detection efficiency, and more accurately evaluating the drought resistance and adaptability of Kochia scoparia, which is of great significance for physiological detection of drought resistance of Kochia scoparia. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] Figure 1 A schematic diagram of the operation steps of a method for detecting drought resistance of the Chenopodiaceae plant Kochia scoparia according to the present invention;

[0038] Figure 2 This is a schematic flow chart of step S2 of a method for detecting drought resistance of the Chenopodiaceae plant Kochia scoparia of the present invention;

[0039] Figure 3 This is a schematic flow chart of step S3 of a method for detecting drought resistance of the Chenopodiaceae plant Kochia scoparia of the present invention. DETAILED DESCRIPTION

[0040] The following embodiments of the present invention are described in further detail in conjunction with the accompanying drawings and examples. The following examples are used to illustrate the present invention, but are not intended to limit the scope of the present invention.

[0041] like Figure 1-Figure 3 As shown, a method for detecting the drought resistance of the Chenopodiaceae plant Kochia scoparia comprises the following steps:

[0042] S1. Sample preparation and collection: Obtain Kochia scoparia plant samples for subsequent analysis, ensure that the collected samples are representative, and quickly freeze and store the collected Kochia scoparia plant samples in a -80°C refrigerator to prevent RNA degradation. Before RNA extraction, take the samples out of the refrigerator and thaw on ice; Specific operations: Select Kochia scoparia plants with consistent growth conditions and at the same growth stage as test materials, and subject the selected Kochia scoparia plants to drought stress treatment to simulate a drought environment, and then collect leaves or other tissues of the Kochia scoparia plants as samples at specific time points after the drought stress treatment;

[0043] In this embodiment, before the drought stress treatment begins, the Kochia scoparia plants are pre-treated by watering, fertilizing, etc. to ensure that the plants are in the best growth state, and the drought stress treatment includes setting the drought stress degree and selecting the stress time point, as follows:

[0044] Setting the degree of drought stress: According to the research needs, different degrees of drought stress can be set, such as mild, moderate and severe drought, by controlling the amount of irrigation (gradually reducing the amount of irrigation according to the set degree of drought stress, and using the weighing method or soil moisture meter to monitor the changes in soil moisture), soil moisture (changing the soil texture by adding media such as sand, gravel and vermiculite, reducing the soil water holding capacity, or directly reducing the soil moisture content to simulate a drought environment) or air humidity (in a controlled environment chamber, adjusting the relative humidity through a humidifier or dehumidifier to simulate a drought environment) to achieve this;

[0045] Select stress time point: determine the start time, duration and sampling time point of drought stress;

[0046] S2. Gene expression analysis: extract total RNA from the collected samples and perform quality inspection, then reverse transcribe RNA into cDNA to prepare for subsequent sequencing or chip analysis, use high-throughput sequencing technology or gene chip technology to sequence or hybridize cDNA to obtain gene expression data, and then perform bioinformatics analysis on the gene expression data to screen out genes that are differentially expressed under drought stress;

[0047] S21. RNA extraction: Use RNA extraction reagents (such as TRIzol, etc.) to extract total RNA from the collected samples, perform RNA quality testing and purification to ensure the integrity and purity of the RNA;

[0048] In this example, the detailed operation of RNA extraction is as follows:

[0049] 1) Cell or tissue lysis:

[0050] Place a sample no larger than 10% of the volume of TRIzol reagent in a pre-cooled mortar and grind it with a small amount of liquid nitrogen until the sample is powdery.

[0051] Transfer the ground sample to a 1.5 ml RNase-free centrifuge tube containing 1 ml TRIzol reagent and vortex vigorously to mix the sample to fully lyse the cells or tissues.

[0052] 2) Denaturation of nucleoprotein complex: Place the homogenized sample at room temperature for 5 minutes to completely dissociate the nucleoprotein complex;

[0053] 3) Inactivation of endogenous ribonuclease (RNase):

[0054] Add 0.2 ml of chloroform, shake the centrifuge tube vigorously for 15 seconds, and then leave it at room temperature for 2 to 3 minutes;

[0055] Centrifuge at 12000 g for 15 min at 4 °C to separate the solution into three layers: an upper aqueous phase (containing RNA), an intermediate phase, and a lower organic phase;

[0056] 4) RNA precipitation:

[0057] Transfer the upper aqueous phase to a new 1.5 ml RNase-free centrifuge tube, avoiding aspirating the middle layer;

[0058] Add an equal volume of isopropanol, gently invert to mix, and leave at room temperature for 10 minutes;

[0059] Centrifuge at 12000 g for 10 min at 4°C. The RNA will form a gel-like precipitate at the bottom of the tube.

[0060] 5) RNA washing:

[0061] Discard the supernatant, add 1 ml of 75% anhydrous ethanol (prepared with DEPC water), vortex gently to mix, and wash the RNA precipitate;

[0062] Centrifuge at 7500 rpm for 5 min at 4°C and discard the supernatant;

[0063] 6) RNA drying and dissolution:

[0064] Open the centrifuge tube cap and dry the RNA precipitate at room temperature or on a heating block at 37°C for 5 to 10 minutes until the ethanol is completely evaporated. However, avoid over-drying, otherwise the RNA will be difficult to dissolve;

[0065] Dissolve the RNA precipitate with an appropriate amount of DEPC-treated water or RNase-free water and vortex gently to ensure that the RNA is completely dissolved;

[0066] In this example, the detailed operation of RNA quality detection is as follows:

[0067] 1) Ultraviolet absorption spectrum detection:

[0068] Use a spectrophotometer to measure the absorbance of RNA (A260 / A280) to assess the concentration and purity of RNA. Normally, the A260 / A280 ratio should be between 1.8-2.1, indicating that the RNA is of high purity.

[0069] 2) Agarose gel electrophoresis detection:

[0070] RNA samples are added to an agarose gel and electrophoresed. The quality of the RNA is assessed based on its size, morphology, and integrity. Agarose gel electrophoresis can distinguish between different types of RNA, such as rRNA, mRNA, and tRNA, and detect degraded or contaminating RNA (such as DNA or protein).

[0071] 3) Rayleigh ratio (RQI) detection:

[0072] The RQI value can be calculated manually by analyzing the electrophoresis image or by using commercial instruments for automated measurement. The RQI value ranges from 0 to 10, with values ​​closer to 10 indicating better RNA integrity.

[0073] RNA purification is an optional operation, which is performed only when the quality test fails (many impurities or protein contamination occur during RNA extraction). Specifically, RNA purification columns are used for purification. The dissolved RNA sample is passed through the purification columns, and the washing and elution steps are performed according to the instructions of the kit to finally obtain purified RNA;

[0074] S22, RNA reverse transcription: Use a reverse transcription kit to perform reverse transcription reaction and set the reaction conditions to reverse transcribe the extracted total RNA into cDNA for subsequent gene expression analysis;

[0075] In this example, the detailed operation of RNA reverse transcription is as follows:

[0076] 1) Reagent preparation: Melt all reagents in the reverse transcription kit (such as reverse transcriptase, buffer, primers, RNase-free water, etc.) on ice and mix gently; and prepare appropriate amounts of RNA template, primers and reverse transcription reaction solution according to experimental requirements;

[0077] 2) Preparation of reverse transcription reaction system

[0078] Primer selection: Choose appropriate primers according to the experimental purpose and RNA type, including Oligo dT, random primers and specific primers. Oligo dT is suitable for reverse transcription of eukaryotic mRNA, random primers are suitable for all types of RNA, especially when the target RNA is of low abundance or has secondary structure, and specific primers are used to initiate specific reverse transcription reactions;

[0079] Prepare the reaction solution: In an RNase-free centrifuge tube, add appropriate amount of reverse transcriptase, buffer, primer, RNA template and RNase-free water according to the instructions of the reverse transcription kit to prepare the reverse transcription reaction solution. Note that the concentration of primers and the amount of RNA template should be adjusted according to experimental requirements;

[0080] 3) Heat denaturation treatment: Before reverse transcription, the RNA template is subjected to heat denaturation treatment. The RNA template is heated at 65°C for 5 to 10 minutes and then immediately cooled on ice to open the secondary structure of the RNA and improve the efficiency of reverse transcription.

[0081] 4) Reverse transcription reaction: the prepared reverse transcription reaction solution is placed in a PCR instrument, and the reverse transcription reaction is performed according to the set reaction conditions. The reaction conditions of this embodiment include: reacting at 42-50° C. for 30-60 minutes (the specific time depends on the amount of RNA template and the activity of reverse transcriptase), and then heating at 85° C. for 5 minutes to inactivate the reverse transcriptase;

[0082] S23. Construction of gene expression profile: Use high-throughput sequencing technology RNA-Se to sequence or hybridize cDNA, and obtain the gene expression profile of Kochia scoparia under drought stress by comparing with reference genome or gene database;

[0083] S24. Analysis of differentially expressed genes: Use bioinformatics software to analyze gene expression profiles, screen out genes that are differentially expressed under drought stress, and determine their role in drought resistance based on changes in the expression levels of differentially expressed genes;

[0084] S3. Molecular biological verification: Screen candidate genes related to drought resistance from differentially expressed genes, and introduce candidate genes into appropriate host cells for expression verification through gene cloning, expression vector construction, cell transfection and other technologies, and then verify the functions of candidate genes to determine their role in drought resistance;

[0085] S31. Candidate gene screening: Based on information such as gene functional annotation, literature reports or experimental verification, genes with potential drought resistance functions, i.e. candidate genes related to drought resistance, are selected from the screened differentially expressed genes;

[0086] S32. Gene cloning and expression verification: clone the selected candidate genes, construct expression vectors, and then introduce the expression vectors into host cells for expression verification, such as Escherichia coli, yeast or plant cells;

[0087] S33. Functional analysis: Study the role of cloned candidate genes in drought resistance by gene knockout, overexpression or mutation, perform functional analysis on cloned candidate genes, and verify the function of candidate genes by molecular biology techniques (such as protein blotting, enzyme activity assay, etc.);

[0088] In this embodiment, the three gene function analysis methods are specifically performed as follows:

[0089] Gene knockout: Deleting or disrupting candidate genes in the genome through gene editing technology (such as CRISPR / Cas9) to study the effect of gene deletion on plant drought resistance;

[0090] Gene overexpression: By constructing expression vectors, candidate genes are overexpressed in plants to study the effects of overexpression on plant drought resistance;

[0091] Gene mutation: Changing specific amino acid sequences in candidate genes through site-directed mutagenesis to study the effects of changes in gene function on plant drought resistance;

[0092] In this embodiment, the molecular biology technology verification specifically includes:

[0093] Western blotting: using specific antibodies to detect the expression level and distribution of proteins encoded by candidate genes in plants. Specifically, by comparing the expression changes of proteins under different drought stress conditions, the role of candidate genes in drought resistance can be inferred.

[0094] Enzyme activity assay: On the premise that the protein encoded by the candidate gene has enzyme activity, enzyme activity assay is used to evaluate its activity changes under drought stress, which helps to understand how the candidate gene affects the drought resistance of plants by regulating enzyme activity;

[0095] S4. Data analysis and conclusion: The drought resistance of Kochia scoparia was concluded by statistically analyzing the gene expression data and molecular biology verification results; Specific operations: Statistical analysis was performed on the gene expression data and molecular biology verification results, and the gene expression changes of Kochia scoparia under different drought stress levels and time points were compared. Based on the analysis results, the drought resistance of Kochia scoparia was evaluated, and the gene expression changes of Kochia scoparia under drought stress and their relationship with drought resistance were obtained. The possible drought resistance mechanism was explored, and subsequent drought-resistant variety breeding and cultivation management suggestions were put forward;

[0096] S5. Repeat the experiment: Repeat steps S1 to S4 to conduct biological replication experiments, and perform statistical analysis on the results to improve the reliability and accuracy of the experiment.

[0097] The embodiments of the present invention are given for the purpose of illustration and description, and are not intended to be exhaustive or to limit the invention to the disclosed forms. Many modifications and variations will be apparent to those of ordinary skill in the art. The embodiments are selected and described in order to better illustrate the principles and practical applications of the present invention and to enable those of ordinary skill in the art to understand the present invention and thereby design various embodiments with various modifications suitable for specific uses.

Claims

1. A method for detecting the drought resistance of the Chenopodiaceae plant Kochia scoparia, characterized in that: The following steps are involved: S1. Sample preparation and collection: Obtain Kochia scoparia plant samples for subsequent analysis, and quickly freeze and store the collected Kochia scoparia plant samples in a -80°C refrigerator to prevent RNA degradation; S2. Gene expression analysis: extract total RNA from the collected samples, then reverse transcribe the RNA into cDNA, sequence or hybridize the cDNA to obtain gene expression data, and then perform bioinformatics analysis on the gene expression data to screen out genes that are differentially expressed under drought stress; S3. Molecular biological verification: Screen candidate genes related to drought resistance from differentially expressed genes, introduce the candidate genes into appropriate host cells for expression verification, and then verify the functions of the candidate genes; S4. Data analysis and conclusion: Through statistical analysis of gene expression data and molecular biology verification results, the drought resistance of Kochia scoparia was concluded.

2. The method for detecting drought resistance of the Chenopodiaceae plant Kochia scoparia according to claim 1, characterized in that: The specific operation of step S1 is as follows: selecting Kochia scoparia plants with consistent growth conditions and at the same growth stage as test materials, and subjecting the selected Kochia scoparia plants to drought stress treatment to simulate a drought environment, and then collecting leaves or other tissues of the Kochia scoparia plants as samples at a specific time point after the drought stress treatment.

3. The method for detecting drought resistance of the Chenopodiaceae plant Kochia scoparia according to claim 2, characterized in that: Before the drought stress treatment begins, the Kochia scoparia plants are watered and fertilized to ensure that the plants are in the best growth state, and the drought stress treatment includes setting the drought stress degree and selecting the stress time point, as follows: Setting the degree of drought stress: According to the research needs, different degrees of drought stress can be set, which can be achieved by controlling the irrigation amount, soil moisture or air humidity; Select stress time point: Determine the start time, duration and sampling time point of drought stress.

4. The method for detecting drought resistance of the Chenopodiaceae plant Kochia scoparia according to claim 1, characterized in that: The step S2 specifically includes the following sub-steps: S21. RNA extraction: Use RNA extraction reagent to extract total RNA from the collected samples, and perform RNA quality testing and purification; S22, RNA reverse transcription: Use a reverse transcription kit to perform a reverse transcription reaction, and set the reaction conditions to reverse transcribe the extracted total RNA into cDNA; S23. Construction of gene expression profile: Sequencing or hybridizing cDNA using high-throughput sequencing technology or gene chip technology, and obtaining the gene expression profile of Kochia scoparia under drought stress by comparing with reference genome or gene database; S24. Analysis of differentially expressed genes: Use bioinformatics software to analyze the gene expression profile, screen out genes that are differentially expressed under drought stress, and judge their role in the drought resistance process based on the changes in the expression levels of the differentially expressed genes.

5. The method for detecting drought resistance of the Chenopodiaceae plant Kochia scoparia according to claim 4, characterized in that: In step S21, RNA purification is an optional operation, which is performed only when the quality test fails. Specifically, RNA purification is performed using an RNA purification column, and the dissolved RNA sample is passed through the purification column, and washing and elution steps are performed according to the instructions of the kit to finally obtain purified RNA.

6. The method for detecting drought resistance of the Chenopodiaceae plant Kochia scoparia according to claim 1, characterized in that: The step S3 specifically includes the following sub-steps: S31. Candidate gene screening: Based on the functional annotation of genes, literature reports or experimental verification information, genes with potential drought resistance functions, i.e. candidate genes related to drought resistance, are selected from the screened differentially expressed genes; S32. Gene cloning and expression verification: clone the selected candidate genes, construct expression vectors, and then introduce the expression vectors into host cells for expression verification; S33. Functional analysis: Study the role of cloned candidate genes in drought resistance by gene knockout, overexpression or mutation, perform functional analysis on cloned candidate genes, and verify the functions of candidate genes using molecular biology techniques.

7. The method for detecting drought resistance of the Chenopodiaceae plant Kochia scoparia according to claim 6, characterized in that: In step S33, the three gene function analysis methods are specifically performed as follows: Gene knockout: Deleting or destroying candidate genes in the genome through gene editing technology to study the effect of gene deletion on plant drought resistance; Gene overexpression: By constructing expression vectors, candidate genes are overexpressed in plants to study the effects of overexpression on plant drought resistance; Gene mutation: The specific amino acid sequence in the candidate gene is changed through site-directed mutagenesis to study the effect of changes in gene function on plant drought resistance.

8. The method for detecting drought resistance of the Chenopodiaceae plant Kochia scoparia according to claim 6, characterized in that: In step S33, the molecular biology technology verification specifically includes: Western blotting: using specific antibodies to detect the expression level and distribution of proteins encoded by candidate genes in plants. Specifically, by comparing the expression changes of proteins under different drought stress conditions, the role of candidate genes in drought resistance can be inferred. Enzyme activity assay: On the premise that the protein encoded by the candidate gene has enzyme activity, enzyme activity assay is used to evaluate its activity changes under drought stress.

9. The method for detecting drought resistance of the Chenopodiaceae plant Kochia scoparia according to claim 1, characterized in that: The specific operation of step S4 is: performing statistical analysis on the gene expression data and molecular biology verification results, comparing the gene expression changes of Kochia scoparia under different drought stress levels and time points, evaluating the drought resistance of Kochia scoparia based on the analysis results, and obtaining the gene expression changes of Kochia scoparia under drought stress and its relationship with drought resistance.

10. The method for detecting drought resistance of the Chenopodiaceae plant Kochia scoparia according to claim 1, characterized in that: The method further comprises the steps of: S5. Repeat the experiment: Repeat steps S1 to S4 to conduct biological replication experiments, and perform statistical analysis on the results to improve the reliability and accuracy of the experiment.

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