Drought-resistant maize water-saving variety stoma density related microRNA probe and its detection method and application

Abstract

The application discloses a corn drought-resistant water-saving variety stomatal density related microRNA probe and a detection method and application thereof. The application solves the problems of predicting and regulating corn drought resistance and stomatal density. The application specifically discloses the following application of any one of miRNA or a substance for detecting the miRNA: A1) application in increasing the number of stomata of a gramineous plant and / or in preparing a product for increasing the number of stomata of a gramineous plant; A2) application in increasing the density of stomata of a gramineous plant and / or in a product for increasing the density of stomata of a gramineous plant; A3) application in reducing the drought resistance of a gramineous plant and / or in preparing a product for reducing the drought resistance of a gramineous plant; and A4) application in increasing the in-vitro water loss rate of a gramineous plant and / or in preparing a product for increasing the in-vitro water loss rate of a gramineous plant, wherein the miRNA sequence is shown in sequence 1. The drought resistance and the stomatal density of leaves of a corn variety to be detected can be identified by detecting the expression amount of the miRNA, and the application can be used in industrial production.

Description

Technical Field

[0001] This invention specifically relates to microRNA probes related to stomatal density in drought-resistant and water-saving maize varieties, their detection methods, and applications. Background Technology

[0002] Currently, agriculture accounts for 70% of global water use. The global population has increased from 5 billion in 1990 to over 7.5 billion, and is projected to reach 9.7 billion to 10 billion by 2050. Food demand is expected to increase by 60% by 2050, requiring even more water for agriculture (World Water Assessment Programme). Maize is a water-intensive crop; from 1983 to 2009, drought caused a 7% loss in global maize yields (0.15 tons / hectare). China is the world's second-largest maize producer, with an annual maize planting area of ​​41 million hectares and a yield of 261 million tons, accounting for 23.18% of global food production (National Bureau of Statistics of China, 2020). In China, approximately 60% of maize-growing areas face water shortages, resulting in a 20-30% yield reduction annually. Therefore, selecting drought-resistant maize varieties is crucial; however, drought is a quantitative trait controlled by multiple genes, and few single genes significantly enhance plant drought resistance. Conventional methods for determining maize drought resistance primarily rely on phenotypes and yields after drought stress. However, this approach is time-consuming, labor-intensive, and heavily influenced by the growing environment. miRNAs, highly conserved small molecules in terrestrial plants, can simultaneously target and regulate hundreds of genes. Therefore, finding a miRNA probe technology to identify crop drought sensitivity represents a new direction for drought-resistant maize cultivation and breeding screening. Summary of the Invention

[0003] The technical problem solved by this invention is how to provide a molecular marker related to drought resistance in maize, and a method for regulating maize drought resistance, stomatal density / number and in vitro water loss rate.

[0004] To address the above problems, the present invention provides the following applications.

[0005] The use of miRNA, a substance that increases the expression of the gene encoding said miRNA, or a substance that increases the activity or content of said miRNA in any of the following:

[0006] A1) Application in increasing the number of stomata in grasses and / or in the preparation of products that increase the number of stomata in grasses;

[0007] A2) Application in products that increase the stomatal density of grasses and / or increase the stomatal density of grasses;

[0008] A3) Application in reducing the drought tolerance of grasses and / or in the preparation of products that reduce the drought tolerance of grasses;

[0009] A4) Improving the in vitro water loss rate of gramineous plants and / or preparing products that improve the in vitro water loss rate of gramineous plants;

[0010] The miRNA is any one of the following:

[0011] B1) The nucleotide sequence is the RNA molecule shown in Sequence 1;

[0012] B2) An RNA molecule obtained by substituting and / or deleting and / or adding nucleotide residues of the protein described in B1) and having the same function as the nucleotides shown in B1).

[0013] B3) A fusion RNA molecule obtained by linking a tag to the N-terminus and / or C-terminus of B1) or B2).

[0014] In the above text, the drought tolerance index can be the survival rate. The survival rate can be the rehydration survival rate. The grass species can be grass species at the three-leaf stage.

[0015] The grasses mentioned above can be grasses in the three-leaf-one-heart stage.

[0016] In the above text, the leaves may refer to the 12th, 13th, and 14th leaves.

[0017] In the aforementioned RNA, the 80% or more identity can be at least 81%, 82%, 83%, 84%, 85%, 86%, 87%, 88%, 89%, 90%, 91%, 92%, 95%, 96%, 98%, 99%, or 100% identity.

[0018] Of the aforementioned RNA sequences, sequence 1 (SEQ ID No. 1) consists of 21 nucleotide residues. It is named zma-miR399 or miR399. Its encoding gene is the miR399 gene.

[0019] In the above applications, the miRNA is derived from corn.

[0020] In the above text, the substance regulating the expression of the gene encoding the gene can be a substance that performs at least one of the following five types of regulation: 1) regulation at the transcriptional level of the gene; 2) regulation after transcription of the gene (i.e., regulation of splicing or processing of the primary transcript of the gene); 3) regulation of RNA transport of the gene (i.e., regulation of mRNA transport of the gene from the nucleus to the cytoplasm); 4) regulation of translation of the gene; and 5) regulation of mRNA degradation of the gene.

[0021] In the above applications, the substance that enhances the expression of the gene encoding the miRNA is any one of the following:

[0022] D1) Nucleic acid molecules that enhance the expression of the genes encoding the above miRNAs;

[0023] D2) expresses the gene encoding the nucleic acid molecule described in D1);

[0024] D3) contains an expression cassette containing the gene described in D2);

[0025] D4) A recombinant vector containing the gene described in D2), or a recombinant vector containing the expression cassette described in D3);

[0026] D5) Recombinant microorganisms containing the gene described in D2), or recombinant microorganisms containing the expression cassette described in D3), or recombinant microorganisms containing the recombinant vector described in D4);

[0027] D6) A transgenic plant cell line containing the gene described in D2), or a transgenic plant cell line containing the expression cassette described in D3), or a transgenic plant cell line containing the recombinant vector described in D4;

[0028] D7) Transgenic plant tissue containing the gene described in D2), or transgenic plant tissue containing the expression cassette described in D3), or transgenic plant tissue containing the recombinant vector described in D4;

[0029] D8) A transgenic plant organ containing the gene described in D2), or a transgenic plant organ containing the expression cassette described in D3), or a transgenic plant organ containing the recombinant vector described in D4).

[0030] In the nucleic acid molecule described in D1), those skilled in the art can easily mutate the nucleic acid molecule regulating the expression of the RNA-coding gene of the present invention using known methods, such as directed evolution or point mutation. Those artificially modified nucleotides that have 80% or more of the same sequence as the nucleic acid molecule regulating the expression of the RNA-coding gene isolated in the present invention, and that have the function of controlling the expression of the RNA-coding gene, are all derived from and equivalent to the nucleotide sequences of the present invention.

[0031] The aforementioned 80% or higher identity can be 81%, 82%, 83%, 84%, 85%, 86%, 87%, 88%, 89%, 90%, 91%, 92%, 93%, 94%, 95%, 96%, 97%, 98%, or 99%.

[0032] In this article, identity refers to the similarity of amino acid or nucleotide sequences. The identity of amino acid sequences can be determined using homology search sites on the internet, such as the BLAST page on the NCBI homepage. For example, in Advanced BLAST 2.1, using blastp as the procedure, setting the Expect value to 10, setting all filters to OFF, using BLOSUM62 as the matrix, setting the Gap existence cost, Per residue gap cost, and Lambda ratio to 11, 1, and 0.85 (default values) respectively, and performing a search to calculate the identity of amino acid sequences, then the identity value (%) can be obtained.

[0033] To address the aforementioned problems, the present invention also provides a method for cultivating grasses with high stomatal density, high number of stomata, or high detached water loss rate.

[0034] The method includes increasing the expression level of the gene encoding the miRNA in the target gramineous plant, and / or obtaining a gramineous plant with high stomatal density, high number of stomata, or high in vitro water loss rate, wherein the stomatal density and water loss rate of the gramineous plant with high stomatal density, high number of stomata, or high in vitro water loss rate are higher than those of the target gramineous plant, and / or the number of stomata is greater than that of the target gramineous plant.

[0035] To address the aforementioned problems, the present invention also provides a method for cultivating low drought-tolerant grasses.

[0036] The method includes increasing the expression level of the encoding gene of the above-mentioned miRNA in the target gramineous plant, and / or, the activity and / or content of the miRNA in drought-resistant gramineous plants, wherein the drought resistance of the drought-resistant gramineous plants is lower than that of the target gramineous plant.

[0037] The above method, wherein increasing the expression of the coding gene of the above-mentioned RNA in grass plants includes introducing the above-mentioned nucleic acid molecule or coding gene or vector into the target plant.

[0038] To address the above problems, the present invention also provides the following applications.

[0039] The following applications of miRNA or substances for detecting said miRNA:

[0040] A1) Application in detecting or assisting in the detection of drought resistance in grasses and / or in the preparation of products for detecting or assisting in the detection of drought resistance in grasses;

[0041] A2) Application in detecting or assisting in the detection of stomatal density in grasses and / or in the preparation of products for detecting or assisting in the detection of stomatal density in grasses;

[0042] A3) Application in detecting or assisting in the detection of the number of stomata in grasses and / or in the preparation of products for detecting or assisting in the detection of the number of stomata in grasses;

[0043] The miRNA sequence is shown in Sequence 1.

[0044] The drought resistance indicators mentioned above are stomatal density, stomatal number, ASI, relative leaf water content, rehydration survival rate, and leaf water loss rate.

[0045] In the above text, the substance used to detect the miRNA can be a substance used to detect the expression level of the miRNA.

[0046] In the above text, the substance used to detect the miRNA can be a substance used to detect the expression level of the miRNA.

[0047] To address the aforementioned problems, the present invention also provides a product.

[0048] The product contains the substance described above for detecting miRNA expression levels, and may be any one of the following G1)-G3):

[0049] G1) Detecting or assisting in the detection of drought resistance in leaves of grasses and / or preparing products for detecting or assisting in the detection of drought resistance in leaves of grasses;

[0050] G2) Applications in the detection or auxiliary detection of stomatal density of grasses and / or in the preparation of products for the detection or auxiliary detection of stomatal density of grasses;

[0051] G3) Applications in detecting or assisting in the detection of the number of stomata in grasses and / or in the preparation of products for detecting or assisting in the detection of the number of stomata in grasses.

[0052] To address the aforementioned problems, the present invention also provides a method for identifying or assisting in the identification of stomatal density in grasses.

[0053] The method includes detecting the expression level of the above-mentioned miRNA in the target gramineous plant, and identifying or assisting in identifying the stomatal density of the gramineous plant based on the expression level of the miRNA in the target gramineous plant.

[0054] The stomatal density of grasses with high miRNA expression levels is greater than that of grasses with low miRNA expression levels.

[0055] To address the aforementioned problems, the present invention also provides a method for identifying or assisting in the identification of the number of stomata in grasses.

[0056] The method includes detecting the expression level of the above-mentioned miRNA in the target gramineous plant, and identifying or assisting in identifying the number of stomata in the gramineous plant based on the expression level of the miRNA in the target gramineous plant.

[0057] The number of stomata in grasses with high miRNA expression levels is greater than the number of stomata in grasses with low miRNA expression levels.

[0058] To address the aforementioned problems, the present invention also provides a method for identifying or assisting in the identification of drought resistance in grasses.

[0059] The method includes detecting the expression level of the above-mentioned miRNA in the target gramineous plant, and identifying or assisting in identifying the drought resistance of the gramineous plant based on the expression level of the miRNA in the target gramineous plant.

[0060] Grass plants with high miRNA expression levels have lower drought tolerance than grass plants with low miRNA expression levels.

[0061] In the above text, the grasses mentioned can be plants of the genus *Zea*. The *Zea* species can be maize varieties ZY8911, DK159, ND108, JD50, HD188, NH101, LP206, and DK517.

[0062] Beneficial effects

[0063] This invention discloses a microRNA probe related to stomatal density in drought-resistant and water-saving maize varieties, along with its detection method and applications. The problem addressed is the prediction and regulation of drought tolerance in maize. Specifically, the invention discloses the following applications of the miRNA or substances for detecting the miRNA: A1) in increasing the number of stomata in gramineous plants and / or in preparing products that increase the number of stomata in gramineous plants; A2) in increasing the stomatal density in gramineous plants and / or in preparing products that increase the stomatal density in gramineous plants; A3) in reducing the drought tolerance of gramineous plants and / or in preparing products that reduce the drought tolerance of gramineous plants; A4) in increasing the in vitro water loss rate of gramineous plants and / or in preparing products that increase the in vitro water loss rate of gramineous plants, wherein the miRNA sequence is shown in Sequence 1. The drought tolerance and stomatal density of leaves in the tested maize varieties can also be identified by detecting the expression level of the miRNA, which can be used in industrial production. Attached Figure Description

[0064] Figure 1Phenotypic and physiological responses of different resistant maize varieties under ample water and drought conditions are shown in Figures A and B. Plants were fully watered within 10 days of germination. After drought, watering was stopped for 7 days, during which time photographs were taken and samples were collected. Figure B shows plants in the drought group that were not watered for 15 days, then re-watered for 3 days, during which time photographs were taken. Figure C shows the relative water content (RWCs) of leaves in three different maize varieties under drought and ample water conditions. Figure D shows the comparison of survival rates among different maize varieties 3 days after re-watering. Figure E shows the average number of stomata in the first three leaves, at the midpoint of each leaf (1000 μm × 300 μm), with a V value of Mean ± SD (n = 9). Figure F shows the total number of stomata in the first three leaves. Figure G shows the water loss rate of the third leaf of maize seedlings, with a V value of Mean ± SD (n ≥ 3). For each treatment, the differences in the bars of different letters were significant (P ≤ 0.05), validating the accuracy of the previous classification.

[0065] Figure 2 This is a graph showing miRNAs significantly associated with different maize varieties in the three maize genotypes for whole-miRNA analysis. The graph displays a heatmap of differentially expressed miRNAs in the three maize genotypes (n=3). The color bars show the log2 (UMI reads) between different genotypes, and the color codes in the upper corners represent the relative gene expression levels. Red, black, and green represent high, medium, and low gene expression levels, respectively. Upregulation and downregulation of miRNAs in the three maize genotypes are represented by: upregulation: Log2-fold change ≥1; downregulation: Log2-fold change ≤-1. Abbreviations: SV: sensitive variety; MV: moderate variety; RV: drought-resistant variety.

[0066] Figure 3 Phenotypic and physiological responses of the background line (ND101) and two overexpression lines (miR399-OE) under conditions of sufficient water and drought. A shows the continuous phenotypic changes from sufficient water to continuous water loss and then to rehydration. B shows the seedling survival rate two days after rehydration. C shows the rate of detached water loss from the second leaf of maize seedlings under sufficient water conditions, continuously statistically analyzed from 0 to 6 hours. (***P<0.001, **P<0.01, *P<0.05)

[0067] Figure 4The table shows the number of stomata in the middle 1000 μm × 300 μm region of the spike ternate leaf in the background line (ND101) and the two overexpression lines (miR399-OE). A shows the phenotypic diagram of the spike ternate leaf in the background line (ND101) and the two overexpression lines (miR399-OE). B shows the number of stomata in the spike ternate leaf of the background line (ND101) and the two overexpression lines (miR399-OE), bar = Mean ± SD (n = 12). C shows the miR399 expression level in the background line (ND101) and the two overexpression lines (miR399-OE), bar = Mean ± SD (n = 8). (***P < 0.001, **P < 0.01, *P < 0.05)

[0068] Figure 5 A graph showing leaf photosynthesis, biomass, and economic yield reflecting sensitivity to drought; A: 24 different maize varieties were grown in an electric greenhouse. Drought stress treatments were administered 15 days after sowing. Plant height and ear height were measured during R1. Chlorophyll content (SPAD) was measured during R2. Photosynthetic parameters were measured during R3. Dry matter weight, yield, and yield components were measured during R6. Photosynthetic parameters under ample water and drought stress conditions (…) Figure 5 The area represents the difference between different varieties under conditions of sufficient water and drought stress (BD), and the V value is Mean±SD (n=5). E: drought resistance coefficient of net photosynthetic rate. Figure 5 Drought resistance coefficient (SPAD) of different maize varieties (FH). This dot plot represents the drought resistance coefficient of the 12th, 13th, and 14th leaves, and the bar chart represents the chlorophyll content under drought conditions. The average drought resistance coefficient of the 12th, 13th, and 14th leaves (FH) Figure 5 (I). Different maize varieties are arranged from largest to smallest according to their drought resistance coefficient. Figure 5 (J). DRC, drought resistance coefficient; PH, plant height; EH, ear height; DW, dry weight; ED, ear diameter; EL, ear length; KN, number of grains per row; TKW, thousand-grain weight. Physiological indicators, photosynthesis, biomass, and economic yield, measured under normal and drought conditions at maturity.

[0069] Figure 6 A diagram showing the classification of drought resistance of maize varieties using DRC; A: The drought resistance of different maize varieties is classified based on the genetic correlations between drought resistance selection criteria (***P<0.05, **P<0.01, *P<0.001). B: Cluster analysis is performed on different maize varieties based on the drought resistance coefficients of 12 traits using Euclidean distance as the clustering method.

[0070] Figure 7The number of stomata in a 1000μm×300μm region in the middle of the ear-leaf of 24 maize varieties was calculated. A is a schematic diagram of the stomatal sampling sites; B is the stomatal phenotype of the sampling sites of the 24 maize varieties under drought and irrigation conditions; C is the statistical number of stomata in the 24 maize varieties under drought conditions (n=6); D is the number of stomata in the 24 maize varieties under drought conditions; E is the correlation analysis between the number of stomata in the 24 maize varieties under drought conditions and the drought resistance (MFV value) of the varieties; F is the statistical number of stomata in the 24 maize varieties under irrigation conditions (n=6); and G is the correlation analysis between the number of stomata in the 24 maize varieties under irrigation conditions and the drought resistance (MFV value) of the varieties.

[0071] Figure 8 The data represent leaf water loss rate and flowering-silking interval (ASI) for different maize varieties. A: Three leaves of each type were continuously measured for 24 hours (n=3). Based on the 24-hour water loss rate, maize varieties were divided into drought-resistant (red), moderate (black), and drought-sensitive (green) types. The vertical lines represent Mean±SD. B: The three-leaf water loss rate and the membership function value showed a highly significant negative correlation. (C) Data represent the ASI of each maize variety. (D) The correlation between ASI and MFV. The values ​​are Mean±SE (n≥22).

[0072] Figure 9 The expression level of the mature miR399 sequence in the third leaf of seedlings of some varieties (a total of 8) of maize at the three-leaf-one-heart stage (12 days after sowing). The horizontal axis shows that the sensitivity of varieties to drought gradually decreases from left to right. Detailed Implementation

[0073] The present invention will now be described in further detail with reference to specific embodiments. The given embodiments are merely illustrative of the invention and not intended to limit its scope. The embodiments provided below can serve as a guide for further improvements by those skilled in the art and do not constitute a limitation on the invention in any way.

[0074] Unless otherwise specified, the experimental methods used in the following examples are conventional methods, performed according to the techniques or conditions described in the literature in this field or according to the product instructions. Unless otherwise specified, the materials and reagents used in the following examples are commercially available.

[0075] In this invention, unless otherwise stated, the scientific and technical terms used herein have the meanings commonly understood by those skilled in the art. Furthermore, the terms and laboratory procedures related to protein and nucleic acid chemistry, molecular biology, cell and tissue culture, microbiology, and immunology used herein are all widely used terms and routine procedures in their respective fields. To better understand this invention, definitions and explanations of relevant terms are provided below.

[0076] The term “gene” refers to a segment of DNA involved in the production of a polypeptide chain; it includes regions before and after the coding region (leader and tail regions) involved in the transcription / translation of the gene product and the regulation of said transcription / translation, as well as insertion sequences (introns) between individual coding regions (exons).

[0077] The terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature. Furthermore, in the description of this invention, unless otherwise stated, "a plurality of" means two or more.

[0078] The term "identity" is used to describe the percentage of identical amino acids or nucleotides between two amino acid sequences or nucleic acid sequences relative to a reference sequence, determined by conventional methods, for example, see Ausubel et al., eds. (1995), Current Protocols in Molecule & Lar Biology, Chapter 19 (Greene Publishing and Wiley-Interscience, New York); and the ALIGN program (Dayhoff (1978), Atlas of Protein Sequence and Structure 5: Suppl. 3 (National Biomedical Research Foundation, Washington, DC). There are many algorithms for aligning sequences and determining sequence identity, including the homology alignment algorithm of Needleman et al. (1970) J. Mol. Biol. 48: 443; the local homology algorithm of Smith et al. (1981) Adv. Appl. Math. 2: 482; and the local homology algorithm of Pearson et al. (1988) P… Similarity search methods are described in roc. Natl. Acad. Sci. 85: 2444; the Smith-Waterman algorithm (Meth. Mol. Biol. 70: 173-187 (1997); and the BLASTP, BLASTN, and BLASTX algorithms (see AltschμL et al. (1990) J. Mol. Biol. 215: 403-410). Computer programs utilizing these algorithms are also available, including but not limited to: ALIGN or Megalign (DNASTAR) software, or WU-BLAS. T-2 (AltschμL et al., Meth. Enzym., 266:460-480 (1996)); or GAP, BESTFIT, BLASTAltschμL et al., above, FASTA, and TFASTA, available in Genetics Computing Group (GCG) package, version 8, Madison, Wisconsin, USA; and CLUSTAL in the PC / Gene program provided by Intelligenetics, MountainView, California.

[0079] The following examples used SPSS 20.0 (SPSS, Inc., Chicago, IL, USA) for analysis of variance and correlation. The least significant difference (LSD, P < 0.05) method was used for significance analysis. Normality and homogeneity of variance tests were performed prior to the multiple comparison analysis.

[0080] The maize variety JN1205 is also known as Ji Nong 1205. In this invention, JN1205 is a drought-sensitive variety.

[0081] The corn variety FM985, also known as Fumin 985, is a moderately drought-resistant variety in this invention.

[0082] The maize variety HY189 is also known as Heyu 189. In this invention, HY189 is a drought-resistant variety.

[0083] Example 1: Screening of specific miRNAs in different resistant maize varieties

[0084] Three typical maize varieties, HY189 (drought resistant), FM985 (moderately sensitive), and JN1205 (drought sensitive), were selected to screen for key miRNAs involved in varietal differences. Seeds of maize varieties HY189 (drought resistant), FM985 (moderately sensitive), and JN1205 (drought sensitive) were germinated at 25℃ and cultured under conditions of daytime temperature between 28℃ and 30℃, nighttime temperature between 20℃ and 22℃, and full irrigation (relative humidity between 50% and 80%) until the two-leaf-one-heart stage. They were then randomly divided into two groups: a normal treatment group and a drought treatment group.

[0085] Drought Treatment Group:

[0086] Phenotypic observation and rehydration survival rate calculation:

[0087] The cells were subjected to drought treatment for 7 days (without additional watering), and cultured under conditions where daytime temperatures were between 28°C and 30°C and nighttime temperatures were between 20°C and 22°C. Phenotypes were recorded after 7 days of drought stress treatment. The drought stress phenotypes are as follows: Figure 1 As shown in Drought in section A ( Figure 1 China A; Figure 1The normal treatment group was designated as the normal treatment group; the drought treatment group was designated as the drought treatment group; JN1205 was the maize variety JN1205; FM985 was the maize variety FM985; and HY189 was the maize variety HY189. After 15 days of drought stress, a large number of drought-sensitive plants died. They were then thoroughly watered once more and cultured for 3 days under conditions where daytime temperatures were between 28℃ and 30℃ and nighttime temperatures were between 20℃ and 22℃. The rehydration survival rate of the three varieties was calculated (rehydration survival rate = number of surviving seedlings after rehydration / total number of seedlings), and the phenotype was recorded. The surviving plants gradually recovered normal growth after rehydration. Figure 1 (Drought in B represents the phenotype of three typical maize varieties after 3 days of rehydration). The three varieties showed the highest rehydration survival rates, as shown in Figure B. Figure 1 As shown in Figure D, the drought-resistant variety HY189 had the highest survival rate after rehydration, reaching 58%.

[0088] Relative moisture content calculation:

[0089] The relative water content of leaves was measured after seven days of drought treatment. First, fresh leaves were cut and weighed (FW). Then, the leaves were soaked in distilled water overnight to obtain saturated fresh weight (SW). Finally, the leaves were dried in an oven at 85℃ to constant weight (DW). The calculation formula is: RLWC(%) = (FW - DW / SW - DW) × 100%. The results showed that compared with the drought-sensitive variety JN1205, HY189 had a higher relative water content in its leaves. Figure 1 (C)

[0090] Normal treatment group:

[0091] Phenotypic observation:

[0092] The only difference between the normal treatment group and the drought-treated group in terms of phenotypic observation and rehydration survival rate calculation was the absence of drought treatment; all other procedures and tests were the same as in the drought-treated group. The phenotypes of the normal treatment group at 7 days of drought treatment (as in the drought-treated group) and at 3 days of rehydration (as in the drought-treated group) are as follows: Figure 1 The Control is shown in A and B.

[0093] Detection and calculation of in vitro water loss rate:

[0094] The third leaf of different maize varieties (JN1205, FM985, and HY189) was cut along the base of the leaf and excised under fully irrigated conditions (daytime temperature between 28℃ and 30℃, and nighttime temperature between 20℃ and 22℃) when they reached the three-leaf stage. The leaves were then weighed continuously at 2-hour intervals for 24 hours on a precision balance, with five replicates for each treatment. The calculation formula was: WL(%) = (Ti - Tn / Ti) × 100%, where Ti is the initial fresh weight and Tn is the leaf weight at the nth hour after excise. The results are as follows:Figure 1 As shown in Figure G, the water loss rate of detached leaves is significantly correlated with stomatal characteristics. Analysis indicates that HY189 exhibits a significantly lower water loss rate compared to drought-sensitive varieties, primarily due to its narrow leaf shape and lower stomatal density.

[0095] When maize in both the drought-treated and normal-treated groups grew to the three-leaf stage, the stomatal density and number of stomata were measured at the middle portion (1000 μm × 300 μm) of each leaf at the same growth date. The results showed that the drought-resistant variety had a lower stomatal density. Figure 1 E, Figure 1 In the diagram, L1 represents the first corn leaf from bottom to top, L2 represents the second corn leaf from bottom to top, and L3 represents the third corn leaf from bottom to top. Compared with the drought-sensitive variety JN1205, the stomatal density of the first, second, and third leaves of the drought-resistant variety HY189 was significantly reduced by 16%, 12%, and 9%, respectively. Calculations of the total number of stomata based on leaf area showed that the total number of stomata on the third leaf of the drought-resistant variety HY189 was significantly less than that of the other two varieties. The number of stomata in HY189, FM985, and JN1205 were 2303, 3644, and 3683, respectively. Figure 1 China F, Figure 1 In the diagram, L1 represents the first corn leaf from bottom to top, L2 represents the second corn leaf from bottom to top, and L3 represents the third corn leaf from bottom to top.

[0096] A highly conserved miRNA can simultaneously mediate the silencing of hundreds of genes. Here, UMI sequencing was performed on maize seedlings of three typical genotypes under irrigation conditions. Cluster analysis was then conducted, and the results are as follows: Figure 2 As shown in the figure (SV, MV, and RV represent drought-sensitive, moderately drought-resistant, and drought-resistant varieties, respectively). In this study, JN1205 is a drought-sensitive variety, while HY189 is a drought-resistant variety. The miRNA expression pattern heatmap was analyzed and created using Morpheus (https: / / software.broadinstitute.org / morpheus / ). The miRNA expression level was normalized using log2 (UMI read length).

[0097] The expression pattern of MiR399 varies among different varieties, with the expression level in drought-resistant varieties being significantly lower than that in drought-sensitive varieties.

[0098] As described above, a molecular marker associated with the resistant variety was discovered, zma-miR399, with the sequence 5'-TGCCAAAGGAGAGTTGCCCTG-3' (Sequence 1). In the sequence listing, Sequence 1 is replaced by T instead of U.

[0099] Example 2: MiR399 regulates maize drought resistance by controlling stomatal density.

[0100] 1. The precursor sequence of zma-miR399 was constructed into the pCUN-mGFP (NCBI GenBank: FJ905215, SYN 06-JUL-2009) vector to obtain the recombinant transgenic vector (recombinant plasmid pCUN-zma-miR399-mGFP);

[0101] The recombinant plasmid pCUN-zma-miR399-mGFP is obtained by replacing the fragment between the restriction endonuclease SpeⅠ and KpnⅠ restriction sites of the pCUN-mGFP vector with sequence 2, while keeping the other nucleotide sequences of the pCUN-mGFP vector unchanged.

[0102] Sequence 2 is as follows: AGTGCGGCTCTCCTCTGGCATGAGGGCGCGACTGAGAGGCACGAA CAGTTTCTGGCCTTCTCCTGCCAATGCCAAAGGAGAGTTGCCCTGC.

[0103] 2. The recombinant plasmid pCUN-zma-miR399-mGFP was transformed into Agrobacterium EHA105 to obtain recombinant Agrobacterium. This recombinant Agrobacterium was then used to infect the immature embryos of maize ND101 (maize ND101 is described in the literature "Amaize epimerase modulates cell wall synthesis and glycosylation during stomatal morphogenesis", where it is named B73-329) to obtain T0 generation transgenic plants. The T0 generation transgenic plants were self-crossed to obtain two independent homozygous overexpression plants, miR399. ND101 -OE1 and miR399 ND101 -OE2 (this germplasm material was created by the Crop Functional Genomics and Molecular Breeding Research Center of China Agricultural University). Pure T2 generation germplasm resources were obtained from the center and propagated at the Shangzhuang Experimental Station of China Agricultural University in the same year. At the three-leaf stage of seedlings, the overexpression of miR399 was detected at the DNA and RNA levels. Self-pollination was strictly carried out, and the harvested seeds were used for subsequent experiments.

[0104] The corn varieties ND101 and miR399 ND101 OE1 and miR399 ND101Select uniformly sized, plump OE2 seeds and place them in an Erlenmeyer flask. Pour in an appropriate amount of 3% hydrogen peroxide for sterilization for 10 minutes. After discarding the hydrogen peroxide, rinse 2-3 times with deionized water, then soak in excess deionized water for 8 hours. Place the flasks in germination boxes lined with germination paper for dark incubation for about 2 days, maintaining moisture during this period. Once the embryos have just germinated and are determined to be ready, transplant them into the culture box, dividing them into two equal parts. One half is planted with 12 background material plants (corn variety ND101), and the other half is planted with 12 transgenic material plants, i.e., divided into miR399... ND101 OE1 group and miR399 ND101 OE2 group, miR399 ND101 In the culture box of group OE1, the left half was planted with maize variety ND101 and the right half with miR399. ND101 OE1, miR399 ND101 In the OE2 group's culture box, the left half was planted with maize variety ND101, and the right half with miR399. ND101 Phenotypic photos of OE2 plants were taken. The plants were grown in a greenhouse at a temperature of 28 / 22℃ (day / night), a photoperiod of 16 / 8h (light / dark), and a humidity of 70%-80%. When the plants reached the two-leaf-one-heart stage, topdressing (a small amount dissolved in water) was applied, followed by a continuous drought treatment (without watering). Phenotypic photos were taken again when the plants reached the three-leaf-one-heart stage (recorded as before drought). A further 10-day drought was then conducted, followed by phenotypic photos during drought (recorded as during drought). Ten days later, the plants were fully watered (thoroughly). Phenotypic photos were taken 3 days after rehydration (recorded as after rehydration), and ND101 and miR399 were recorded. ND101 OE1 and miR399 ND101 Rehydration survival rate of OE2 (rehydration survival rate = number of seedlings surviving after rehydration / total number of seedlings).

[0105] In another experiment, when the plants reached the three-leaf stage, plants with uniform growth were selected, and the second leaf (the second corn leaf from the bottom up) was cut off. The original weight M0 was recorded, and the leaves were placed on a flat surface under the same light environment after detachment. The weight Mn was measured every 1, 2, 3, 4, 5, and 6 hours. The detachment water loss rate was calculated as (M0-Mn) / M0. Each line had at least 3 replicates to calculate the detachment water loss rate of the leaves. The results of the greenhouse soil culture experiment showed that miR399 ND101 The two lines of OE exhibited leaf wilting under drought conditions, indicating lower drought resistance than ND101. Figure 3 China A, Figure 3 ND101, miR399-OE-1, and miR399-OE-2 represent maize varieties ND101, miR399, and miR399, respectively. ND101 OE1 and miR399 ND101 OE2) had a significantly lower rehydration survival rate after rehydration than ND101.Figure 3 (B), and the rate of water loss in vitro is higher than that of ND101 ( Figure 3 (C), indicating that miR399 participates in the drought stress response of maize in a negative regulatory manner.

[0106] In early May, corn varieties ND101 and miR399 were... ND101 OE1 and miR399 ND101 OE2 was cultivated at the Shangzhuang Experimental Station of China Agricultural University in Beijing, China (N40°08′E116°11′). Normal irrigation management was implemented (irrigation every two weeks, with each irrigation reaching at least 80% of field capacity). Fertilization was carried out before sowing with 100 kg·ha⁻¹ of nitrogen fertilizer, 52 kg·ha⁻¹ of phosphorus fertilizer, and 100 kg·ha⁻¹ of potassium fertilizer, followed by topdressing with water-soluble fertilizer at the jointing stage. Pest and disease control and manual weeding were implemented throughout the growth period to ensure maize growth. Self-pollination was used. After reaching plant height, samples were taken from the maize to maturity for stomatal density observation. Stomatal samples were collected using the nail polish imprint method, measuring the stomata on the three leaves of the mature ear. The specific method is as follows:

[0107] Select mature maize varieties (ND101 and miR399) ND101 OE1 and miR399 ND101 For the OE2 ear, apply a layer of nail polish to the underside of the three leaves, about 2 cm from the vein. Let it sit for 20 minutes until the nail polish hardens. Then, use tweezers to remove the leaf along the edge and place it on a glass slide. Next, photograph the slide under an optical microscope (4x) and use a drawing tool. Figure 3 D selects a 1 / 4 area of ​​the field of view and uses imageJ (1.8.0) to calculate the number of stomata per unit area. The results show that miR399 ND101 OE1 and miR399 ND101 The stomatal density of OE2 spikelets was higher than that of ND101. Figure 4 A and B in the middle, Figure 4 In the text, ND101, miR399-OE-1, and miR399-OE-2 represent maize varieties ND101, miR399, and miR399, respectively. ND101 OE1 and miR399 ND101 OE2), which indicates that miR399 regulates the drought resistance of maize by adjusting stomatal density.

[0108] The maize varieties ND101 (background material) and miR399 were tested using the following methods. ND101 OE1 and miR399 ND101miR399 expression level in OE2: Total RNA was extracted from plant leaves and reverse transcribed to obtain cDNA. Using the U6 gene as an internal reference, the relative expression level of miR399 was detected by Real-time qPCR. The results showed that, compared with the transgenic recipient maize variety ND101, the expression levels of two independent miR399 cells were significantly higher. ND101 OE1 and miR399 ND101 The expression level of miRNA399 in the OE2 transgenic line was significantly increased. Figure 4 (C). Among them, the primer pair used to detect miR399:

[0109] miR399-F: 5'-GAATGCTGCCAAAGGAGAGTTGCCCTG-3';

[0110] miR399-R: 5'-AGACCGGCAACAGGATTCAATC-3'.

[0111] Primer pair used for detecting the U6 gene:

[0112] U6--F:5'-GGAACGATACAGAGAAGATTAGCA-3';

[0113] U6--R: 5'-GTGCAGGGTCCGAGGT-3'.

[0114] Experimental Example 3: Classification of Drought Sensitivity of Different Maize Varieties

[0115] Further selections of major maize varieties covering China's maize-growing belt were planted in electrically powered rainproof sheds. The schematic diagram shows the growth status and measurement time. Figure 5 (A) The specific method is as follows:

[0116] The experiment was divided into an arid zone and a normally irrigated zone. The following planting was carried out in each zone: In early May, seeds of 24 maize varieties (as shown in Table 1) were planted in an electric rainproof shed with a row length of 3m, a row spacing of 0.5m, and a plant spacing of 0.25m. There were 12 replicates for each variety, for a total of 24 plots.

[0117] Irrigate every two weeks. In areas with normal irrigation, the irrigation volume should be at least 80% of field capacity each time, while in arid areas it should be 40% of field capacity. 3 / hm 2 When the maize plants reached the flowering stage, the net photosynthetic rate (Pn), transpiration rate (Tr), intercellular CO2 concentration (Ci), and chlorophyll content of the 12th, 13th (ear leaves), and 14th (fully expanded leaves) of these 24 maize varieties (as shown in Table 1) were ranked. Figure 5 (BD, where D-* represents arid areas and W-* represents areas with normal irrigation).

[0118] Plant height (PH), ear height (EH), dry weight (DW), yield per ear, and yield components (ear diameter ED; ear length EL; number of grains per row KN; 1000-grain weight TKW) were measured during the growth to maturity stage. Each experiment was repeated 12 times, and the data were recorded in Excel 2016 (Microsoft Corp., Redmond, WA, USA). Analysis of variance and correlation were performed using SPSS 20.0 (SPSS, Inc., Chicago, IL, USA). The least significant difference (LSD) test (P < 0.05) was used for significance analysis. Normality and homogeneity of variance tests were performed before multiple comparison analysis.

[0119] The results showed that varieties such as DH710 and HY189 maintained good photosynthetic performance under drought conditions, while varieties such as JN1205 and LY99 exhibited strong photosynthetic performance under drought conditions. Figure 6 The study investigated eight traits, including plant height (PH), ear height (EH), dry weight (DW), yield per ear, and yield components (ear diameter ED; ear length EL; number of kernels per row KN; and thousand-kernel weight TKW). Different maize genotypes were sequenced using the DRCS (Diagram of the Root Canal System). Figure 5 (See Table 2). The drought resistance coefficient (DRC) of different traits shows a high degree of consistency with the genetic order of different varieties; for example, DH710 and HY189 are still ranked first, while JN1205 and LY99 are ranked last.

[0120] Net photosynthetic rate (Pn) of panicle leaves was measured using a Li6400 photosynthesis system.

[0121] Transpiration rate (Tr) of panicle leaves was detected using a Li6400 photosynthesis system.

[0122] Intercellular CO2 concentration (Ci) in spikelet leaves was detected using a Li6400 photosynthesis system.

[0123] Detection of chlorophyll content in the 12th, 13th (spike leaves) and 14th unfolded leaves of the spike: The SPAD value of the plant was measured once at the top, middle and bottom of the leaf using a handheld SPAD meter.

[0124] The length and width of leaves 4-19 were measured: leaf length and width were measured with a ruler.

[0125] Plant height (PH): The distance from the ground to the highest point of the tassel.

[0126] Ear height (EH): The distance from the ground to the base of the female ear.

[0127] Dry weight (DW): Bake at 80 degrees Celsius until the weight no longer decreases.

[0128] Yield per ear: weight of grains per ear.

[0129] DRC was significant in all cases based on 12 traits. Figure 6 (A) All traits showed highly significant positive correlations, indicating that the drought resistance coefficients of the 12 traits can be used as indicators for drought resistance selection. The drought resistance coefficient (DRC) is an important indicator for evaluating the drought resistance of different maize genotypes. It refers to the ratio of the value of a certain agronomic or physiological trait under drought conditions to the value under a fully irrigated control condition.

[0130] The formula for calculating DRC is:

[0131] DRCmn=Tmnd / Tmnww

[0132] Where DRCmn is the drought resistance coefficient of the m-th trait of the n-th maize genotype; Tmnd and Tmnww are the values ​​of the m-th trait of the n-th maize genotype under drought and sufficient irrigation treatments, respectively.

[0133] Cluster analysis of the DRCs of 12 traits showed that the 24 maize varieties were clustered into 3 groups based on the DRCs of the 12 traits. Figure 6 Group B). The first group consists of nine drought-resistant maize varieties (DH3737, HY189, DK157, DH710, ND372, XY1466, XY1225, JND935, DH518). Cluster III consists of seven drought-sensitive maize varieties (Tn9, JN1205, XY335, ZD958, DK159, ZY8911, ND108). The remaining varieties belong to the moderately sensitive variety type. Membership function value (MFV) was used as a comprehensive evaluation index for the drought resistance of maize varieties. Values ​​estimated based on 12 indicators are shown in Table 2. The minimum and maximum MFV were 0.08 (JN1205) and 0.94 (DH518), respectively. Based on the MFV value, maize varieties were divided into three levels (Ⅰ: 0-0.333; Ⅱ: 0.333-0.666; Ⅲ: 0.666-1). Of the 24 maize varieties, four (JN1205, Tn9, ZY8911, and DK159) had low MFV values ​​(0-0.333), classifying them as drought-sensitive. Ten maize varieties (LP206, XY1225, DH710, DH3737, DK517, XY1466, HY189, ND372, JND935, and DH518) had high MFV values ​​(0.666-1), indicating they are drought-resistant varieties. The remaining varieties were classified as moderately drought-resistant.

[0134] The conclusions drawn from classifying drought sensitivity using these two methods are consistent. For example, JN1205, Tn9, ZY8911, and DK159 are drought-sensitive varieties dependent on MFV (Table 2), and these maize varieties also appear in the sensitivity range dependent on DRC values. Figure 6 (B) This demonstrates that the classification of drought sensitivity among different maize varieties is reliable.

[0135] Seeds of 24 maize varieties (as shown in Table 1) were seedled indoors in rows 3m long, with a row spacing of 0.5m and a plant spacing of 0.25m. Each variety had 12 replicates, resulting in 24 plots. Irrigation was carried out every two weeks, with each irrigation reaching at least 80% of field capacity. The plants were incubated at 25°C. When the plants reached the five-leaf stage, leaf water loss rate (water loss rate of the 3rd, 4th, and 5th leaves) was measured. Leaf water loss rate is an important indicator reflecting the drought resistance of different maize varieties. Among all varieties, the water loss rate of the 3rd, 4th, and 5th leaves showed a similar trend (…). Figure 8 (A) The 24-hour water loss rates of TN9, JN1205, and ZY8911 were 77.24%, 73.49%, and 72.76%, respectively, similar to the results measured by DRC and MFV, indicating they are drought-sensitive maize varieties. The water loss rates of DH518, DK517, and HY189 were 42.15%, 57.44%, and 58.22%, respectively, indicating they are drought-resistant maize varieties. Regression analysis showed a significant negative correlation between the membership function value and the water loss rate at the three-leaf stage. Figure 8 (B)

[0136] Water loss rate of the 3rd, 4th, and 5th leaves: First, the 3rd, 4th, and 5th leaves of each corn plant were cut along the base to remove the leaves from the plant. Then, they were weighed continuously on a precision balance every 2 hours for 24 hours, with five replicates for each treatment. The calculation formula is as follows:

[0137] WL(%) = (Ti-Tn) / Ti; where Ti is the initial fresh weight and Tn is the leaf weight at the nth hour after leaf removal.

[0138] The flowering-silking interval (ASI) at the flowering stage is a key indicator of maize growth and development under drought stress. Drought stress can lead to asynchrony in ASI, ultimately resulting in reduced maize yield. Here, we use it to further examine the classification accuracy of drought sensitivity. Flowering-silking intervals were measured for the aforementioned maize varieties in arid regions.

[0139] Flowering-silking interval (ASI): The time difference between pollen shedding (male ear maturity) and silking (female ear maturity).

[0140] The results showed that under drought conditions, the ASI (Average Sequence Indication) varied greatly among different varieties from 1 to 8 days. Figure 8(C). The ASI values ​​for drought-resistant genes DK517, HY189, and DH518 were 2.04d, 2.33d, and 2.54d, respectively. The ASI values ​​for LY99, XD20, and JN1205 were 5.22d, 4.96d, and 4.83d, respectively, classifying them as drought-sensitive maize varieties. Furthermore, a highly significant negative correlation existed between ASI and MFV (R² = 0.517; P < 0.001), further validating the accuracy of previous classifications.

[0141] Table 1. Drought Resistance Coefficient (DRC) for 12 Traits

[0142]

[0143]

[0144]

[0145] Membership function (MFV) method is used to quantify the drought resistance of different maize genotypes through multiple agronomic and physiological traits. The calculation formula is as follows:

[0146]

[0147] In the formula, DRCmn is the drought resistance coefficient of the m-th trait of the nth variety (n = 24 varieties); Tmnd is the value of the m-th trait of the nth variety under drought treatment; Tmw is the value of the m-th trait under sufficient irrigation treatment. DRCmmax and DRCmmin are the maximum and minimum values ​​of the drought resistance coefficient of the m-th trait, respectively. MFVn is the average membership function value of the nth variety, and its magnitude represents the drought resistance of the variety.

[0148] Table 2. Membership function (MFV) analysis and drought resistance classification of 224 maize varieties.

[0149]

[0150]

[0151] Membership function values ​​and categories of drought resistance for the tested genotypes. Genotypes are divided into three categories based on their membership function values: I: 0-0.333; II: 0.333-0.666; III: 0.666-1. MFV (Membership Function Value); DRL (Drought Resistance Level).

[0152] Experimental Example 4: miR399 regulates drought resistance of varieties by controlling stomatal density

[0153] The experiment investigated the number of stomata in a 1000μm×300μm region in the middle of the ear leaf of 24 maize varieties under conditions of sufficient irrigation and drought stress.

[0154] The experiment was divided into an arid zone and a normally irrigated zone. The following planting methods were used in each zone: In early May, seeds of 24 maize varieties (as shown in Table 1) were planted in electrically powered rainproof greenhouses, with row lengths of 3m, row spacing of 0.5m, and plant spacing of 0.25m. Each variety had 12 replicates, for a total of 24 plots. Irrigation was carried out every two weeks. In the normally irrigated zone, the irrigation volume was at least 80% of field capacity, while in the arid zone, it was 40% of field capacity. 3 / hm 2 When the plants reach maturity, samples are taken to observe the number and density of stomata.

[0155] The number of stomata was counted using the nail polish imprint method (Takahashi et al., 2018). Plant leaves were selected, and a thin, even layer of nail polish (2cm × 1cm) was lightly applied to the underside of the leaf. (Note: the upper surface of corn leaves is hairy, making it difficult to peel off the nail polish and observe the stomatal morphology). The leaves were left to stand for 10-20 minutes (depending on the environment) until the nail polish solidified. Then, the nail polish was gently peeled off from the edge using tweezers and placed on a clean glass slide. (If the nail polish could not be spread evenly, a drop of distilled water could be added to allow it to slowly spread and prevent air bubbles.) The slide was placed under a low-power (10×) optical microscope (OLYMPUSBX 43) to find the field of view, and then photographed under a 40× eyepiece. The number of stomata within an area of ​​1000 μm × 300 μm was counted using ImageJ (1.8.0) software, and the stomatal density was calculated.

[0156] The results showed that the stomata on maize leaves were arranged in a parallel linear pattern. Figure 7 (A, B). Under sufficient water conditions, the leaves are flat and the stomata remain open. However, under drought stress, the stomatal opening decreases. Statistical results of stomatal number are shown in... Figure 7 Central D (drought) and Figure 7 In the middle E (normal watering area). Figure 7 In the text, Drought represents the arid region, while Well-watered represents the region with normal irrigation.

[0157] The results showed that with increasing drought resistance in maize varieties, the number of stomata per unit area decreased under both irrigation and drought stress conditions. For example, under drought stress, JN1205 and DH518 had 28 and 21 stomata, respectively, while under irrigation stress, the numbers were 27 and 19, respectively. Under drought and sufficient water conditions, the number of stomata was significantly negatively correlated with varietal drought resistance (MFV value), with correlation coefficients R = -0.581 (P < 0.01) and -0.489 (P < 0.05), respectively. These results indicate that maize varieties with fewer stomata exhibit stronger drought resistance.

[0158] The above-mentioned maize varieties were grown to the three-leaf stage (12 days after sowing) under normal irrigation conditions. The expression of the mature miR399 sequence in the third leaf of seedlings of ZY8911, DK159, ND108, JD50, HD188, NH101, LP206, and DK517 was detected. The specific method is as follows: Total RNA was extracted from leaves using the Trizol method. Reverse transcription was performed using the specific primer 5'-GTCGTATCCAGTGCAGGGTCCGAGGTATTCGCACTGGATACGACCAGGGC-3', with U6 used as an internal control. The U6 reverse transcription sequence is 5'-GTGCAGGGTCCGAGGTTTTGGACCATTTCTCGAT-3'. The reverse transcription product was detected by RT-PCR. The primers used for miR399 were:

[0159] miR399-F: 5'-GAATGCTGCCAAAGGAGAGTTGCCCTG-3';

[0160] miR399-R: 5'-AGACCGGCAACAGGATTCAATC-3'.

[0161] The primers used for internal reference U6 are:

[0162] F:5'-GGAACGATACAGAGAAGATTAGCA-3'

[0163] R:5'-GTGCAGGGTCCGAGGT-3'

[0164] The results are as follows Figure 9 As shown, drought resistance in maize varieties is negatively correlated with miR399 expression levels.

[0165] The present invention has been described in detail above. For those skilled in the art, the invention can be practiced in a wide range of ways with equivalent parameters, concentrations, and conditions without departing from its spirit and scope, and without requiring unnecessary experiments. Although specific embodiments have been given, it should be understood that further modifications can be made to the invention. In summary, according to the principles of the invention, this application is intended to include any changes, uses, or improvements to the invention, including changes made using conventional techniques known in the art that depart from the scope disclosed herein. Some of the essential features can be applied within the scope of the following appended claims.

Claims

1. Any of the following applications of the substance used to detect the miRNA: A1) Application in detecting or assisting in the detection of drought resistance in grasses and / or in the preparation of products for detecting or assisting in the detection of drought resistance in grasses; A2) Application in detecting or assisting in the detection of stomatal density in grasses and / or in the preparation of products for detecting or assisting in the detection of stomatal density in grasses; A3) Application in detecting or assisting in the detection of the number of stomata in grasses and / or in the preparation of products for detecting or assisting in the detection of the number of stomata in grasses; Its features are, The miRNA sequence is shown in Sequence 1; The grass species mentioned is maize.

2. A method for identifying or assisting in the identification of stomatal density in grasses, characterized in that, The method includes detecting the expression level of the miRNA described in claim 1 in the target gramineous plant, and identifying or assisting in the identification of the stomatal density of the gramineous plant based on the expression level of the miRNA in the target gramineous plant. The stomatal density of grass plants with high miRNA expression levels is greater than that of grass plants with low miRNA expression levels. The grass species mentioned is maize.

3. A method for identifying or assisting in the identification of the number of stomata in grasses, characterized in that, The method includes detecting the expression level of the miRNA described in claim 1 in the target gramineous plant, and identifying or assisting in identifying the number of stomata in the gramineous plant based on the expression level of the miRNA described in the target gramineous plant. The number of stomata in grasses with high miRNA expression levels is greater than the number of stomata in grasses with low miRNA expression levels. The grass species mentioned is maize.

4. A method for identifying or assisting in the identification of drought resistance in grasses, characterized in that, The method includes detecting the expression level of the miRNA described in claim 1 in the test gramineous plant, and identifying or assisting in identifying the drought resistance of the gramineous plant based on the expression level of the miRNA described in the test gramineous plant; The drought resistance of grass plants with high miRNA expression levels is lower than that of grass plants with low miRNA expression levels. The grass species mentioned is maize.

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