MicroRNA probe related to stomatal density in drought-resistant and water-saving corn variety as well as detection method and application thereof

Abstract

The invention discloses a pore density related MicroRNA probe in a drought-resistant and water-saving corn variety as well as a detection method and application of the pore density related MicroRNA probe. The problem to be solved and solved is to predict, regulate and control drought tolerance and stomatal density of corn. The invention specifically discloses any one of the following applications of miRNA or a substance for detecting the miRNA: A1) an application in increasing the number of stomata of the gramineous plant and / or preparing a product for increasing the number of stomata of the gramineous plant; a2) application in a product for improving the stomatal density of the gramineous plants and / or improving the stomatal density of the gramineous plants; a3) application in reducing the drought tolerance of the gramineous plants and / or preparing products for reducing the drought tolerance of the gramineous plants; a4) a product for improving the in-vitro water loss rate of the gramineous plant and / or preparing the in-vitro water loss rate of the gramineous plant, wherein the miRNA sequence is as shown in the sequence 1. The drought tolerance and stomatal density of the leaves of the corn variety to be detected can be identified by detecting the expression quantity of the miRNA, and the miRNA can be used for industrial production.

Description

Technical Field

[0001] The present invention specifically relates to a stomatal density-related MicroRNA probe in drought-resistant and water-saving corn varieties and a detection method and application thereof. Background Art

[0002] Currently, agriculture accounts for 70% of the total water use in the world. The global population has increased from 5 billion in 1990 to more than 7.5 billion at present, and is expected to increase to 9.7 billion to 10 billion by 2050. Food demand will increase by 60% by 2050, which requires more agricultural water (World Water Assessment Program). Maize is a water-intensive crop. From 1983 to 2009, drought caused a 7% loss in maize production worldwide (0.15 tons / hectare). China is the second largest maize producer in the world. Every year, maize occupies 41 million hectares of land and produces 261 million tons of maize, accounting for 23.18% of the world's grain production (National Bureau of Statistics of China, 2020). In China, about 60% of maize-growing areas face water shortage pressure, resulting in a 20-30% reduction in yield each year. Therefore, it is very important to select drought-tolerant maize varieties, but drought is a quantitative trait controlled by multiple genes, and few single genes significantly enhance the drought resistance of plants. Conventional methods of judging whether corn is drought-tolerant are mainly based on the phenotype and yield after drought stress, which is time-consuming and labor-intensive and has a great impact on the cultivation environment. As a highly conserved small molecule in terrestrial plants, miRNA can target and regulate hundreds of genes at the same time. Therefore, finding a miRNA probe technology to identify crop drought sensitivity is a new direction for drought-resistant cultivation and breeding screening of corn. Summary of the invention

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

[0004] In order to solve the above problems, the present invention provides the following applications.

[0005] Use of miRNA, a substance for increasing the expression of a gene encoding the miRNA, or a substance for increasing the activity or content of the miRNA in any of the following:

[0006] A1) Use in increasing the number of stomata in gramineous plants and / or preparing a product for increasing the number of stomata in gramineous plants;

[0007] A2) Use of the method for increasing the stomatal density of gramineous plants and / or in products for increasing the stomatal density of gramineous plants;

[0008] A3) use in reducing drought tolerance of gramineous plants and / or preparing products for reducing drought tolerance of gramineous plants;

[0009] A4) increasing the water loss rate of gramineous plants in vitro and / or preparing a product that increases the water loss rate of gramineous plants in vitro;

[0010] The miRNA is any of the following:

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

[0012] B2) RNA molecules having more than 80% identity with the nucleotides shown in B1) and having the same function as those in B1) obtained by substitution and / or deletion and / or addition of nucleotide residues of the protein described in B1);

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

[0014] In the above, the drought tolerance index may be a survival rate. The survival rate may be a rewatering survival rate. The grass plant may be a grass plant in the three-leaf one-heart stage.

[0015] In the above, the grass plant may be a three-leaf, one-heart grass plant.

[0016] In the above, the leaves may be the 12th, 13th and 14th leaves.

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

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

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

[0020] In the above, the substance that regulates the expression of the coding gene may be a substance that performs at least one of the following five types of regulation: 1) regulation at the transcription level of the gene; 2) regulation after the transcription of the gene (that is, regulation of the splicing or processing of the primary transcript of the gene); 3) regulation of the RNA transport of the gene (that is, regulation of the transport of the mRNA of the gene from the cell nucleus to the cytoplasm); 4) regulation of the translation of the gene; 5) regulation of the mRNA degradation of the gene.

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

[0022] D1) a nucleic acid molecule that increases the expression of the gene encoding the miRNA;

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

[0024] D3) 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) a recombinant microorganism containing the gene described in D2), or a recombinant microorganism containing the expression cassette described in D3), or a recombinant microorganism 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] D1) In the nucleic acid molecule, a person skilled in the art can easily mutate the nucleic acid molecule for regulating the expression of the coding gene of the RNA of the present invention by using known methods, such as directed evolution or point mutation. Those artificially modified nucleotides having 80% or more identity with the nucleic acid molecule sequence for regulating the expression of the coding gene of the RNA isolated by the present invention, and having the function of controlling the expression of the coding gene of the nucleic acid molecule for regulating the expression of the coding gene of the RNA, are all derived from the nucleotide sequence of the present invention and are equivalent to the sequence of the present invention.

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

[0032] Herein, identity refers to the identity of an amino acid sequence or a nucleotide sequence. The identity of an amino acid sequence can be determined using a homology search site on the Internet, such as the BLAST webpage on the NCBI homepage website. For example, in Advanced BLAST2.1, by using blastp as a program, setting the Expect value to 10, setting all Filters to OFF, using BLOSUM62 as a Matrix, setting Gap existence cost, Per residue gap cost and Lambda ratio to 11, 1 and 0.85 (default values) respectively and searching to calculate the identity of an amino acid sequence, the value (%) of identity can then be obtained.

[0033] In order to solve the above problems, the present invention also provides a method for cultivating grass plants with high stomatal density, high stomatal number or high in vitro water loss rate.

[0034] The method comprises increasing the expression amount of the coding gene of the miRNA in the target Gramineae plant, and / or the activity and / or content of the miRNA to obtain a Gramineae plant with high stomatal density, high stomatal number or high in vitro water loss rate, wherein the Gramineae plant with high stomatal density, high stomatal number or high in vitro water loss rate has a higher stomatal density and water loss rate than the target Gramineae plant, and / or has more stomatal numbers than the target Gramineae plant.

[0035] In order to solve the above problems, the present invention also provides a method for cultivating Gramineae plants with low drought tolerance.

[0036] The method comprises increasing the expression level of the coding gene of the miRNA in the target Gramineae plant, and / or increasing the activity and / or content of the miRNA in the Gramineae plant with low drought tolerance, wherein the drought tolerance of the Gramineae plant with low drought tolerance is lower than that of the target Gramineae plant.

[0037] In the above method, the step of increasing the expression of the gene encoding the above RNA in the Gramineae plant comprises introducing the above nucleic acid molecule or encoding gene or vector into the target plant.

[0038] In order to solve the above problems, the present invention also provides the following application.

[0039] Any of the following uses of miRNA or a substance for detecting the miRNA:

[0040] A1) Use in detecting or assisting in detecting drought tolerance of gramineous plants and / or preparing products for detecting or assisting in detecting drought tolerance of gramineous plants;

[0041] A2) Use in detecting or assisting in detecting the stomatal density of gramineous plants and / or preparing a product for detecting or assisting in detecting the stomatal density of gramineous plants;

[0042] A3) Use in detecting or assisting in detecting the number of stomata in Gramineae plants and / or preparing a product for detecting or assisting in detecting the number of stomata in Gramineae plants;

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

[0044] In the above, the drought tolerance indicators are stomatal density, stomatal number, ASI, leaf relative water content, rehydration survival rate, and leaf water loss rate.

[0045] In the above, the substance for detecting the miRNA may be a substance for detecting the expression amount of the miRNA.

[0046] In the above, the substance for detecting the miRNA may be a substance for detecting the expression amount of the miRNA.

[0047] In order to solve the above problems, the present invention also provides a product.

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

[0049] G1) detecting or assisting in detecting drought tolerance of leaves of Gramineae plants and / or preparing a product for detecting or assisting in detecting drought tolerance of leaves of Gramineae plants;

[0050] G2) Application in detecting or assisting in detecting the stomatal density of gramineous plants and / or preparing a product for detecting or assisting in detecting the stomatal density of gramineous plants;

[0051] G3) Application in detecting or assisting in detecting the number of stomata in Gramineae plants and / or preparing products for detecting or assisting in detecting the number of stomata in Gramineae plants.

[0052] In order to solve the above problems, the present invention also provides a method for identifying or assisting in identifying the stomatal density of Gramineae plants.

[0053] The method comprises detecting the expression level of the miRNA in the tested Gramineae plant, and identifying or assisting in identifying the stomatal density of the Gramineae plant according to the expression level of the miRNA in the tested Gramineae plant;

[0054] The stomatal density of the Gramineae plant with a high expression level of the miRNA is greater than the stomatal density of the Gramineae plant with a low expression level of the miRNA.

[0055] In order to solve the above problems, the present invention also provides a method for identifying or assisting in identifying the number of stomata in Gramineae plants.

[0056] The method comprises detecting the expression level of the miRNA in the tested Gramineae plant, and identifying or assisting in identifying the number of stomata of the Gramineae plant according to the expression level of the miRNA in the tested Gramineae plant;

[0057] The number of stomata of the Gramineae plant with a high expression level of the miRNA is greater than the number of stomata of the Gramineae plant with a low expression level of the miRNA.

[0058] In order to solve the above problems, the present invention also provides a method for identifying or assisting in identifying drought resistance of Gramineae plants.

[0059] The method comprises detecting the expression level of the miRNA in the tested Gramineae plant, and identifying or assisting in identifying the drought resistance of the Gramineae plant according to the expression level of the miRNA in the tested Gramineae plant;

[0060] The drought tolerance of the Gramineae plants with high expression levels of the miRNA is lower than that of the Gramineae plants with low expression levels of the miRNA.

[0061] In the above, the grass plant may be a plant of the genus Zea mays. The maize may be corn variety ZY8911, corn variety DK159, corn variety ND108, corn variety JD50, corn variety HD188, corn variety NH101, corn variety LP206, or corn variety DK517.

[0062] Beneficial Effects

[0063] The present invention discloses a stomatal density-related MicroRNA probe in drought-resistant and water-saving corn varieties and a detection method and application thereof. The problem to be solved is to predict and regulate corn drought resistance. Specifically disclosed is any of the following applications of miRNA or a substance for detecting the miRNA: A1) application in increasing the number of stomata in gramineous plants and / or preparing a product for increasing the number of stomata in gramineous plants; A2) application in increasing the stomatal density in gramineous plants and / or preparing a product for increasing the stomatal density in gramineous plants; A3) application in reducing drought resistance in gramineous plants and / or preparing a product for reducing drought resistance in gramineous plants; A4) application in increasing the in vitro water loss rate of gramineous plants and / or preparing a product for increasing the in vitro water loss rate of gramineous plants, and the miRNA sequence is shown in Sequence 1. The drought resistance and stomatal density of the leaves of the tested corn variety can also be identified by detecting the expression amount of the miRNA, which can be used for industrial production. BRIEF DESCRIPTION OF THE DRAWINGS

[0064] Figure 1Figure 1 shows the phenotypic and physiological responses of different resistant maize varieties under well-watered and drought conditions; A shows that the plants were well-watered within 10 days after germination. After drought, watering was stopped for 7 days, during which time photos were taken and samples were collected. B shows that the plants in the drought group were stopped from watering for 15 days and then re-watered for 3 days, at which time photos were taken. C shows the relative water content (RWCs) of leaves of three different maize varieties under drought and water conditions, D shows the comparison of survival rates among different maize varieties after 3 days of rehydration, E shows the average stomata of the first three leaves, the middle position of each leaf (1000μm×300μm), V value is Mean±SD (n=9), F shows the total number of stomata in the first three leaves; G shows the water loss rate of the third leaf of maize seedlings, V value is Mean±SD (n≥3), for each treatment, the bars with different letters are significantly different (P≤0.05), which verifies the accuracy of the previous classification.

[0065] Figure 2 Figure 3 is a graph of miRNAs significantly associated with varieties in three maize varieties based on full miRNA analysis; the figure shows a heat map of the expression levels of differentially expressed miRNAs in three maize genotypes (n=3), the color bar shows the log2 (UMI reads) between different genotypes, the color scale in the upper corner represents the relative gene expression level, where red, black and green represent high, medium and low levels of gene expression, respectively, the expression levels of up-regulated and down-regulated miRNAs in the three maize genotypes, up-regulated: Log2-fold change ≥1; down-regulated: Log2-fold change ≤-1, abbreviated as SV: sensitive variety; MV: medium variety; RV: drought-resistant variety.

[0066] Figure 3 The phenotypic and physiological response diagrams of the background line (ND101) and two overexpression lines (miR399-OE) under well-watered and drought conditions. A is a continuous phenotypic change diagram from well-watered to continuous water loss to rehydration. B is the survival rate of seedlings two days after rehydration. C is the in vitro water loss rate of the second leaf of corn seedlings under well-watered conditions, with continuous statistics from 0-6h. (***P<0.001, **P<0.01, *P<0.05)

[0067] Figure 4The number of stomata in the 1000μm×300μm area in the middle part of the three leaves of the ear of the background line (ND101) and the two overexpression lines (miR399-OE). A is the phenotypic diagram of the ear leaves of the background line (ND101) and the two overexpression lines (miR399-OE). B is the number of stomata in the three leaves of the ear of the background line (ND101) and the two overexpression lines (miR399-OE) bar=Mean±SD(n=12). C is the miR399 expression level diagram of 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 Leaf photosynthesis, biomass and economic yield reflect the sensitivity to drought. Figure A: 24 different maize varieties were planted in electric greenhouses. Drought stress treatment was carried out 15 days after sowing. Plant height and ear height were measured during R1. Chlorophyll content (SPAD) was measured during R2. Photosynthesis-related indices were measured during R3. Dry matter weight, yield and yield components were measured during R6. Photosynthesis parameters under well-watered and drought stress conditions ( Figure 5 BD), the size of the area represents the difference between different varieties under water-sufficient and drought-stress conditions, and the V value is Mean±SD (n=5). E: Net photosynthetic rate drought resistance coefficient. ( Figure 5 The drought resistance coefficient (SPAD) of different maize varieties in FH) is shown in the dot graph, which shows the drought resistance coefficient of the 12th, 13th, and 14th leaves, and the bar graph shows the chlorophyll content under drought conditions. The average drought resistance coefficient ( Figure 5 I). Arrange different corn varieties according to their drought resistance coefficient from large to small ( 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 kernels per row; TKW, thousand-kernel weight. Physiological indicators photosynthesis, biomass and economic yield measured under normal conditions and drought conditions at maturity.

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

[0070] Figure 7is the number of stomata in a 1000μm×300μm area in the middle of the leaf at the ear position of 24 corn varieties; A is a schematic diagram of the stomatal sampling site, B is the stomatal phenotype of the sampling site under drought and irrigation conditions of the 24 corn varieties, C is the statistical number of stomata of the 24 corn varieties under drought conditions (n=6), D is the number of stomata of the 24 corn varieties under drought conditions, E is the correlation analysis between the number of stomata of the 24 corn varieties under drought conditions and the variety drought resistance (MFV value), F is the statistical number of stomata of the 24 corn varieties under irrigation conditions (n=6), and G is the correlation analysis between the number of stomata of the 24 corn varieties under irrigation conditions and the variety drought resistance (MFV value).

[0071] Figure 8 The water loss rate of leaves and the anthesis-silking interval (ASI) of different maize varieties; A: Three leaves of each type were measured continuously for 24 hours (n=3). According to the 24-hour water loss rate, the maize varieties were divided into drought-resistant type (red), medium type (black) and drought-sensitive type (green). The vertical lines are Mean±SD. B: The water loss rate of three leaves was extremely significantly negatively correlated with the membership function value. (C) The data represent the ASI of each maize variety. (D) is the correlation between ASI and MFV. The values ​​are Mean±SE (n≥22).

[0072] Fig. 9 This is the expression level of the miR399 mature sequence in the third leaf of the seedlings of some varieties (8 in total) of corn in the three-leaf and one-heart period (12 days after sowing), and the sensitivity of the varieties to drought decreases from left to right on the horizontal axis. DETAILED DESCRIPTION

[0073] The present invention is further described in detail below in conjunction with specific embodiments, and the examples provided are only for illustrating the present invention, rather than for limiting the scope of the present invention. The examples provided below can be used as a guide for further improvements by those of ordinary skill in the art, and do not constitute a limitation of the present invention in any way.

[0074] The experimental methods in the following examples, unless otherwise specified, are all conventional methods, and are performed according to the techniques or conditions described in the literature in the field or according to the product instructions. The materials, reagents, etc. used in the following examples, unless otherwise specified, can all be obtained from commercial channels.

[0075] In the present invention, unless otherwise specified, the scientific and technical terms used herein have the meanings commonly understood by those skilled in the art. In addition, the protein and nucleic acid chemistry, molecular biology, cell and tissue culture, microbiology, immunology and laboratory operation procedures used herein are terms and routine procedures widely used in the corresponding fields. At the same time, in order to better understand the present invention, the definitions and explanations of the relevant terms are provided below.

[0076] The term "gene" refers to a segment of DNA involved in producing a polypeptide chain; it includes regions preceding and following the coding region (leader and trailer regions) that are involved in the transcription / translation of the gene product and the regulation of said transcription / translation, as well as intervening sequences (introns) between individual coding regions (exons).

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

[0078] When the term "identity" is used to describe an amino acid sequence or a nucleic acid sequence relative to a reference sequence, the percentage of identical amino acids or nucleotides between two amino acid sequences or nucleic acid sequences is determined by conventional methods, for example, see Ausubel et al., eds. (1995), Current Protocols in MolecμLar 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; the local homology algorithm of Pearson et al. (1988) P. The similarity search method of Proc. Natl. Acad. Sci. 85: 2444; Smith-Waterman algorithm (Meth. Mol. Biol. 70: 173-187 (1997); and BLASTP, BLASTN, and BLASTX algorithms (see Altsch μL et al. (1990) J. Mol. Biol. 215: 403-410). Computer programs that utilize these algorithms are also available and include, but are not limited to, ALIGN or Megalign (DNASTAR) software, or WU-BLAS T-2 (Altsch μL et al., Meth. Enzym., 266:460-480 (1996)); or GAP, BESTFIT, BLAST Altsch μL et al., supra, FASTA, and TFASTA, available in the Genetics Computing Group (GCG) package, Version 8, Madison, Wisconsin, USA; and CLUSTAL in the PC / Gene program provided by Intelligenetics, Mountain View, California.

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

[0080] Corn variety JN1205 is also known as Jilong 1205. In the present invention, JN1205 is a drought-sensitive variety.

[0081] Corn variety FM985 Corn variety FM985 is also known as Fumin 985. In the present invention, FM985 is a medium drought-resistant variety.

[0082] The corn variety HY189 is also called Heyu 189. In the present invention, HY189 is a drought-resistant variety.

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

[0084] Three typical maize varieties, HY189 (drought resistance), FM985 (moderate sensitivity) and JN1205 (drought sensitivity), were selected to screen the key miRNAs involved in variety differences. The seeds of maize varieties HY189 (drought resistance), FM985 (moderate sensitivity) and JN1205 (drought sensitivity) were germinated at 25°C, cultured at daytime temperatures between 28°C and 30°C, nighttime temperatures between 20°C and 22°C, and fully watered (relative humidity between 50% and 80%) to the two-leaf and one-heart stage, and then randomly divided into two groups, namely the normal treatment group and the drought treatment group.

[0085] Drought treatment group:

[0086] Phenotypic observation and rehydration survival rate calculation:

[0087] The drought treatment was carried out for 7 days (no additional watering), and the temperature was between 28℃ and 30℃ during the day and between 20℃ and 22℃ at night. The phenotype was recorded after 7 days of drought stress treatment. The drought stress phenotype was as follows: Figure 1 As shown in Drought in A ( Figure 1 Middle A; Figure 1Normal is the normal treatment group; drought is the drought treatment group; JN1205 is the corn variety JN1205; FM985 is the corn variety FM985; HY189 is the corn variety HY189). After 15 days of drought stress, a large number of drought-sensitive plants died. Then they were fully watered once (drenched), and cultured for 3 days under the conditions of daytime temperature between 28℃ and 30℃ and nighttime temperature 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 is the phenotype of three typical corn varieties after rehydration for 3 days. The highest survival rate of the three varieties after rehydration is as follows: Figure 1 As shown in D, the drought-resistant variety HY189 had the highest rehydration survival rate, reaching 58%.

[0088] Calculation of relative water content:

[0089] The relative water content of leaves was tested 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), and finally the leaves were dried in an oven at 85°C 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, the relative water content of leaves of HY189 was higher ( Figure 1 Middle C).

[0090] Normal treatment group:

[0091] Phenotypic observations:

[0092] The only difference between the phenotypic observation and rewatering survival rate calculation of the drought treatment group is that no drought treatment was performed. Other operations and tests were the same as the drought treatment group. The phenotypes of the normal treatment group at 7 days after drought treatment and the phenotypes of the drought treatment group at 3 days after rewatering were as follows: Figure 1 As shown in A and Control in B.

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

[0094] The third leaf of different varieties of corn (JN1205, FM985 and HY189) was cultivated under sufficient irrigation conditions (daytime temperature between 28℃ and 30℃, nighttime temperature between 20℃ and 22℃) until the three-leaf, one-heart stage. The leaves were cut open along the leaf base to separate the leaves, and then weighed continuously every 2 hours for 24 hours on a precision balance. Each treatment had five replicates. The calculation formula is: WL (%) = (Ti-Tn / Ti) × 100%, where Ti is the initial fresh weight and Tn is the leaf weight at the nth hour after the leaves were separated. The results are shown in Figure 2. Figure 1 As shown in G, the water loss rate of detached leaves was significantly correlated with stomatal characteristics. The analysis showed that the water loss rate of HY189 was significantly reduced compared with the drought-sensitive varieties, which was mainly attributed to its narrow leaf shape and lower stomatal density.

[0095] When the corn in the drought treatment group and the normal treatment group grew to three leaves and one heart, the stomatal density and number of stomata in the middle part of each leaf position (1000μm×300μm) were measured on the same growth date. The results showed that the stomatal density of drought-resistant varieties was lower ( Figure 1 Middle E, Figure 1 In E, L1 is the first corn leaf from bottom to top, L2 is the second corn leaf from bottom to top, and L3 is 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%. The total number of stomata was calculated by leaf area, and the results showed that the total number of stomata in the third leaf of the drought-resistant variety HY189 was significantly less than that of the other two varieties. The number of stomata of HY189, FM985, and JN1205 were 2303, 3644, and 3683, respectively ( Figure 1 Middle F, Figure 1 In middle E, L1 is the first corn leaf from bottom to top, L2 is the second corn leaf from bottom to top, and L3 is the third corn leaf from bottom to top).

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

[0097] The expression patterns of MiR399 were different in different varieties, and the expression level in drought-resistant varieties was significantly lower than that in drought-sensitive varieties.

[0098] As described above, a molecular marker associated with resistant varieties was found, the sequence of zma-miR399 is 5'-TGCCAAAGGAGAGTTGCCCTG-3' (sequence 1). In the sequence list, sequence 1 replaces U with T.

[0099] Example 2 MiR399 regulates drought resistance of maize by regulating 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 overexpression 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: AGTCGGCTCTCCTCTGGCATGAGGGCGCGACTGAGAGGCACGAA CAGTTTCTGGCCTTCTCCTGCCAATGCCAAAGGAGAGTTGCCCTGC.

[0103] 2. The recombinant plasmid pCUN-zma-miR399-mGFP was transformed into Agrobacterium EHA105 to obtain recombinant Agrobacterium, and then the recombinant Agrobacterium was used to infect immature embryos of maize variety ND101 (maize variety ND101 is recorded in the following document "Amaize epimerase modulates cell wall synthesis and glycosylation during stomatalmorphogenesis", and its name in the document is B73-329) to obtain T0 transgenic plants; T0 transgenic plants were self-pollinated to obtain two independent homozygous plants overexpressing 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), and obtained pure T2 generation germplasm resources from the center. It was propagated at the Shangzhuang Experimental Station of China Agricultural University that year, and the overexpression of miR399 was detected at the DNA and RNA levels at the three-leaf stage of the seedlings. Strict self-pollination was carried out, and the harvested seeds were used for subsequent experiments.

[0104] The maize varieties ND101 and miR399 ND101 OE1 and miR399 ND101Select seeds of OE2 with uniform size and full grains and put them into a conical flask, pour in an appropriate amount of 3% hydrogen peroxide for disinfection for 10 minutes, pour out the hydrogen peroxide and wash with deionized water for 2-3 times, then pour in excess deionized water and soak for 8 hours, and then put them in a germination box covered with germination paper for dark culture for about 2 days. During this period, pay attention to keep moisture. When the embryos have just germinated, plant them in the culture box and divide them into two parts, one half is planted with 12 background materials (corn variety ND101), and the other half is planted with 12 transgenic materials, that is, divided into miR399 ND101 OE1 group and miR399 ND101 OE2 group, miR399 ND101 In the OE1 group, the left half of the culture box was planted with maize variety ND101 and the right half was planted with miR399 ND101 OE1, miR399 ND101 In the OE2 group, the left half of the culture box was planted with maize variety ND101 and the right half was planted with miR399 ND101 OE2 was photographed for phenotype and planted in a greenhouse, maintained at 28 / 22°C (day / night), 16 / 8h (light / darkness), and 70%-80% humidity. Topdressing (a small amount of water dissolved) was performed when the plant had two leaves and one heart, and continuous drought treatment (no water supplementation) was performed. When the plant grew to the three-leaf and one-heart stage, phenotypic photos were taken (recorded as before drought), and drought phenotypic photos were taken after 10 days of drought (recorded as during drought). After another 10 days, the plant was watered thoroughly and rehydrated. After 3 days of rehydration, phenotypic photos were taken (recorded as after rehydration), and ND101 and miR399 were counted. ND101 OE1 and miR399 ND101 The rehydration survival rate of OE2 (rehydration survival rate = number of surviving seedlings after rehydration / total number of seedlings).

[0105] In another experiment, when the plants grew to three leaves and one heart, plants with consistent growth were selected, the second leaf (the second corn leaf from bottom to top) was cut off, the original weight M0 was recorded, and the weight Mn was measured every 1, 2, 3, 4, 5, and 6 hours after separation. The in vitro water loss rate was calculated by (M0-Mn) / M0. Each strain was set up with at least 3 replicates to calculate the in vitro water loss rate of leaves. The results of the greenhouse soil culture experiment showed that miR399 ND101 The leaves of the two OE lines wilted under drought conditions, and their drought resistance was lower than that of ND101 ( Figure 3 Middle A, Figure 3 ND101, miR399-OE-1 and miR399-OE-2 represent maize varieties ND101, miR399 ND101 OE1 and miR399 ND101 OE2), the rehydration survival rate after rehydration was significantly lower than that of ND101 ( Figure 3 B), and the in vitro water loss rate was higher than that of ND101 ( Figure 3 This indicates that miR399 participates in the drought stress response of maize in a negative regulatory manner.

[0106] In early May, the maize varieties ND101 and miR399 were introduced ND101 OE1 and miR399 ND101 OE2 was planted at Shangzhuang Experimental Station of China Agricultural University in Beijing, China (N40°08′E116°11′), with normal watering management conditions (irrigation every two weeks, with each irrigation amount being more than 80% of the field water holding capacity). Fertilization management measures included 100kg·ha-1 nitrogen fertilizer, 52kg·ha-1 phosphorus fertilizer, and 100kg·ha-1 potassium fertilizer before sowing, and topdressing with water-soluble fertilizer during the jointing period. Pest and disease control and manual weeding were carried out throughout the growth period to ensure corn growth. The pollination method was self-pollination, and after the plant height was determined, the corn grew to maturity, and samples were taken to observe the stomatal density. The stomatal samples were sampled using the nail polish blotting method to determine the stomata of the three-leaf leaves at the mature ear position. The specific method is as follows:

[0107] Select mature corn (corn varieties ND101, miR399 ND101 OE1 and miR399 ND101 OE2) Apply a layer of nail polish on the back of the leaves at about 2 cm from the middle of the three leaves near the veins at the ear position. Leave it for 20 minutes until the nail polish solidifies. Remove it along the edge with tweezers and place it on a glass slide. Then take a picture of the glass slide under an optical microscope (4 times) and use a painting to record the color of the leaves. Figure 3 D Select a 1 / 4 area field and use imageJ (1.8.0) to calculate the number of stomata per unit area. The results showed that miR399 ND101 OE1 and miR399 ND101 The stomatal density of OE2 panicle three leaves was higher than that of ND101 ( Figure 4 Among A and B, Figure 4 In the table, ND101, miR399-OE-1, and miR399-OE-2 represent maize varieties ND101, miR399 ND101 OE1 and miR399 ND101 OE2), indicating that miR399 regulates drought resistance in maize by regulating stomatal density.

[0108] The maize variety ND101 (background material) and miR399 were detected according to the following methods. ND101 OE1 and miR399 ND101miR399 expression in OE2: Total RNA was extracted from leaves of plants and reverse transcribed to obtain cDNA. The relative expression level of miR399 was detected by real time qPCR using U6 gene as internal reference gene. The results showed that compared with the transgenic recipient maize variety ND101, two independent miR399 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 is:

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

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

[0111] Primer pairs for detecting U6 gene:

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

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

[0114] Experimental Example 3: Classification of drought sensitivity of different corn varieties

[0115] Further, the main varieties covering the Chinese corn growing belt were selected and planted in an electric rainproof canopy. 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 a drought area and a normal watering area, and the following planting was carried out in each area: In early May, seeds of 24 corn varieties (as shown in Table 1) were planted in an electric rainproof awning, with a row length of 3m, a row spacing of 0.5m, and a plant spacing of 0.25m. Each variety was replicated 12 times, for a total of 24 plots.

[0117] Irrigation is carried out every two weeks. The irrigation volume for each irrigation is more than 80% of the field water holding capacity in the normal watering area and 40% of the field water holding capacity in the drought area. 3 / hm 2 When the 24 maize varieties (as shown in Table 1) grew to the flowering stage, the net photosynthetic rate (Pn), transpiration rate (Tr), intercellular CO2 concentration (Ci) of the ear leaves and the chlorophyll content of the 12th, 13th (ear leaves) and 14th expanded leaves were ranked ( Figure 5 BD, where D-* is the drought area and W-* is the normal watering area).

[0118] Plant height (PH), ear height (EH), dry weight (DW), single ear yield and yield components (ear diameter ED; ear length EL; number of grains per row KN; 1000-grain weight TKW) were tested when the plants grew to maturity. Each of the above experiments was repeated 12 times, and the data were recorded in Excel 2016 (Microsoft Corp., Redmond, WA, USA). SPSS20.0 (SPSS, Inc., Chicago, IL, USA) was used for variance analysis and correlation analysis. The least significant difference method (LSD, P<0.05) was used for significance analysis. Normality and variance homogeneity tests were performed before multiple comparison analysis.

[0119] The results showed that varieties such as DH710 and HY189 could still maintain good photosynthetic performance under drought conditions, while varieties such as JN1205 and LY99 showed strong photosynthetic performance under drought conditions ( Figure 6 E and I in the study. Eight traits were studied, including plant height (PH), ear height (EH), dry weight (DW), single ear yield and yield components (ear diameter ED; ear length EL; number of kernels per row KN; thousand-kernel weight TKW). Different maize genotypes were ranked by DRCS ( Figure 5 The drought resistance coefficients (DRC) of different traits showed high consistency in the genetic order of different varieties, such as DH710 and HY189 still ranked in the front, and JN1205 and LY99 ranked in the back.

[0120] Detection of net photosynthetic rate (Pn) of ear leaves: Detected using Li6400 photosynthetic meter.

[0121] Detection of transpiration rate (Tr) of ear leaves: Detected using Li6400 photosynthetic instrument.

[0122] Detection of intercellular CO2 concentration (Ci) of ear leaves: Detected using Li6400 photosynthesis instrument.

[0123] Detection of chlorophyll content in the expanded leaves 12, 13 (ear leaves) and 14 of the ear: Use a handheld SPAD instrument to measure once at the top, middle and bottom of the leaf blade and take the average value as the SPAD value of the plant.

[0124] The leaf length and leaf width of leaves 4-19 were measured: The leaf length and leaf width were measured using 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 ear.

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

[0128] Single ear yield: weight of grains per ear.

[0129] The DRC calculated based on the 12 traits reached a significant level in all cases ( Figure 6 A in the middle). All the traits showed extremely significant positive correlation, indicating that the drought resistance coefficients of the 12 traits can be used as indicators for drought resistance selection. Drought resistance coefficient (DRC) is an important indicator for evaluating drought resistance of different genotypes of corn. It refers to the ratio of the value of a certain agronomic or physiological trait under drought conditions to the value under sufficient irrigation control conditions.

[0130] The calculation formula of DRC is:

[0131] DRCmn=Tmnd / Tmnww

[0132] Among them, DRCmn is the drought resistance coefficient of the mth trait of the nth corn genotype; Tmnd and Tmnww are the values ​​of the mth trait of the nth corn genotype under drought and sufficient irrigation treatments, respectively.

[0133] Cluster analysis of the DRC of the 12 traits was performed. The results showed that the 24 maize varieties were clustered into three categories based on the DRC of the 12 traits: Figure 6 The first cluster consisted of nine drought-resistant maize varieties (DH3737, HY189, DK157, DH710, ND372, XY1466, XY1225, JND935, and DH518). Cluster III consisted of seven drought-sensitive maize varieties (Tn9, JN1205, XY335, ZD958, DK159, ZY8911, and ND108). The remaining varieties were classified as moderately sensitive varieties. The membership function value (MFV) was used as a comprehensive evaluation index for drought resistance of maize varieties. The values ​​estimated based on 12 indicators were (Table 2). The minimum and maximum MFVs were 0.08 (JN1205) and 0.94 (DH518), respectively. The maize varieties were divided into three levels according to the size of MFV (Ⅰ: 0-0.333; Ⅱ: 0.333-0.666; Ⅲ: 0.666-1). Among the 24 maize varieties, 4 maize varieties (JN1205, Tn9, ZY8911, DK159) had low MFV values ​​(0-0.333), belonging to the drought-sensitive type. Ten maize varieties (LP206, XY1225, DH710, DH3737, DK517, XY1466, HY189, ND372, JND935, DH518) had high MFV (0.666-1), indicating that they are drought-resistant maize varieties. The remaining varieties were classified as moderately drought-resistant varieties.

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

[0135] The seeds of 24 corn varieties (as shown in Table 1) were grown indoors at the seedling stage with a row length of 3m, a row spacing of 0.5m, and a plant spacing of 0.25m. Each variety was replicated 12 times, with a total of 24 plots. Irrigation was carried out every two weeks, and the irrigation amount was more than 80% of the field water holding capacity. When the seeds grew to five leaves and one heart at 25 degrees Celsius, the leaf water loss rate was tested (the water loss rate of the 3rd, 4th, and 5th leaves). The leaf water loss rate is an important indicator reflecting the drought resistance of different corn varieties. Among all varieties, the water loss rate of the 3rd, 4th, and 5th leaves showed a similar trend ( Figure 8 The 24-hour water loss rates of TN9, JN1205, and ZY8911 were 77.24%, 73.49%, and 72.76%, respectively, which were similar to the results of DRC and MFV, and they were drought-sensitive corn varieties. The water loss rates of DH518, DK517, and HY189 were 42.15%, 57.44%, and 58.22%, respectively, and they were drought-resistant corn varieties. Regression analysis showed that the membership function value was significantly negatively correlated with the water loss rate of the three leaves ( Figure 8 (middle 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 leaf base to separate the leaves, and then weighed continuously every 2 hours for 24 hours on a precision balance, with five replicates for each treatment. The calculation formula is:

[0137] WL (%) = (Ti-Tn) / Ti, wherein Ti is the initial fresh weight, and Tn is the weight of the leaf n hours after the leaf is separated from the body.

[0138] The anthesis-silking interval (ASI) is a key indicator of maize growth and development under drought stress when it grows to the flowering stage. Drought stress may lead to asynchrony of ASI, which ultimately leads to reduced maize yield. Here, we used it to further test the classification accuracy of drought sensitivity. In the drought area, the anthesis-silking interval of the above maize varieties was tested.

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

[0140] The results showed that under drought conditions, the ASI of different varieties varied greatly from 1d to 8d ( Figure 8Middle C). The ASI values ​​of drought-resistant genes DK517, HY189, and DH518 were 2.04d, 2.33d, and 2.54d, respectively. The ASI values ​​of LY99, XD20, and JN1205 were 5.22d, 4.96d, and 4.83d, respectively, and they were drought-sensitive maize varieties. In addition, there was a highly significant negative correlation between ASI and MFV (R2=0.517; P<0.001), which further verified the accuracy of the previous classification.

[0141] Table 1 Drought resistance coefficient (DRC) of 12 traits

[0142]

[0143]

[0144]

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

[0146]

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

[0148] Table 2 Membership function analysis (MFV) and drought resistance classification of 24 corn varieties

[0149]

[0150]

[0151] Membership function values ​​and categories of drought resistance of the tested genotypes. The genotypes were divided into three categories according to the 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 regulating stomatal density

[0153] The experiment studied the number of stomata in the 1000μm×300μm area in the middle of the leaf at the ear of 24 corn varieties under sufficient irrigation and drought stress conditions.

[0154] The experiment was divided into arid and normal watering areas, and the following planting was carried out in each area: In early May, seeds of 24 corn 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. Each variety had 12 replicates, for a total of 24 plots. Irrigation was carried out every two weeks, with the irrigation amount in the normal watering area being more than 80% of the field water holding capacity, and in the arid area being 40% of the field water holding capacity. 3 / hm 2 , grow to maturity, and take samples to observe the number and density of stomata.

[0155] The number of stomata was counted using the nail polish imprint method (SUMP method) (Takahashi et al., 2018). Select plant leaves and apply a layer of nail polish evenly on the back of the leaves (2 cm × 1 cm. The front of corn leaves is hairy, so nail polish is not easy to tear off, and the stomata morphology is not easy to observe). Let it stand for 10-20 minutes (affected by the external environment). After the nail polish solidifies, use tweezers to gently tear off the nail polish from the edge and place it on a previously cleaned slide (if the nail polish cannot be flattened, drop a drop of distilled water to let the water slowly soak and flatten the nail polish to prevent bubbles from forming). Place the slide under an optical microscope (OLYMPUSBX 43) with a low-power lens (10×) to find the field of view, and then take a picture under a 40× eyepiece. Use imageJ (1.8.0) software to count the number of stomata within an area of ​​1000 μm × 300 μm and calculate the stomatal density.

[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 conditions, the stomata opening decreases. The statistical results of the number of stomata are shown in Figure 7 Medium D (drought) and Figure 7 Middle E (normal watering area). Figure 7 In the figure, Drought refers to the drought area and Well-watered refers to the normal watering area.

[0157] The results showed that as the drought resistance of the varieties increased, the number of stomata per unit area showed a decreasing trend under irrigation and drought stress conditions. For example, under drought stress conditions, the number of stomata of JN1205 and DH518 was 28 and 21, respectively, while under irrigation conditions, the number of stomata of JN1205 and DH518 was 27 and 19, respectively. Under drought and sufficient water conditions, the number of stomata was significantly negatively correlated with the variety drought resistance (MFV value), and the correlation coefficients R were -0.581 (P < 0.01) and -0.489 (P < 0.05), respectively. The above results show that corn varieties with fewer stomata have stronger drought resistance.

[0158] The above corn varieties were grown under normal watering conditions until the three-leaf one-heart stage (12 days after sowing, that is, the three-leaf one-heart stage), and the expression of the mature sequence of miR399 in the third leaf of the seedlings of ZY8911, DK159, ND108, JD50, HD188, NH101, LP206 and DK517 was detected. The specific method is as follows: the total RNA of the leaves was extracted using the Trizol method, and the specific primer 5'-GTCGTATCCAGTGCAGGGTCCGAGGTATTCGCACTGGATACGACCAGGGC-3' was used for reverse transcription, and U6 was used as an internal reference. The reverse transcription sequence of U6 was 5'-GTGCAGGGTCCGAGGTTTTGGACCATTTCTCGAT-3', and the reverse transcription product was detected by RT-PCR. The primers used for miR399 are:

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

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

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

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

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

[0164] The results are as follows Fig. 9 As shown, the drought resistance of maize varieties was negatively correlated with the expression level of miR399.

[0165] The present invention has been described in detail above. It will be apparent to those skilled in the art that the present invention may be implemented in a wide range under equivalent parameters, concentrations and conditions without departing from the spirit and scope of the present invention and without the need for unnecessary experimentation. Although the present invention provides specific embodiments, it should be understood that further improvements may be made to the present invention. In short, according to the principles of the present invention, this application intends to include any changes, uses or improvements to the present invention, including changes made by conventional techniques known in the art that depart from the scope disclosed in this application. Applications of some of the basic features may be made within the scope of the following appended claims.

Claims

1. Use of miRNA, a substance for increasing the expression of a gene encoding the miRNA, or a substance for increasing the activity or content of the miRNA in any of the following: A1) Use in increasing the number of stomata in gramineous plants and / or preparing a product for increasing the number of stomata in gramineous plants; A2) Use of the method for increasing the stomatal density of gramineous plants and / or in products for increasing the stomatal density of gramineous plants; A3) use in reducing drought tolerance of gramineous plants and / or preparing products for reducing drought tolerance of gramineous plants; A4) increasing the water loss rate of gramineous plants in vitro and / or preparing a product that increases the water loss rate of gramineous plants in vitro; The miRNA is any of the following: B1) The nucleotide sequence is the RNA molecule shown in Sequence 1; B2) RNA molecules having more than 80% identity with the nucleotides shown in B1) and having the same function as those in B1) obtained by substitution and / or deletion and / or addition of nucleotide residues of the protein described in B1); B3) A fusion RNA molecule obtained by connecting a tag to the N-terminus or / and C-terminus of B1) or B2).

2. The use according to claim 1, characterized in that: The miRNA is derived from corn.

3. The use according to claim 1 or 2, characterized in that: The substance that increases the expression of the gene encoding the miRNA is any one of the following: D1) a nucleic acid molecule that increases the expression of the gene encoding the miRNA according to claim 1 or 2; D2) expressing the gene encoding the nucleic acid molecule described in D1); D3) an expression cassette containing the gene described in D2); D4) a recombinant vector containing the gene described in D2) or a recombinant vector containing the expression cassette described in D3); D5) a recombinant microorganism containing the gene described in D2), or a recombinant microorganism containing the expression cassette described in D3), or a recombinant microorganism containing the recombinant vector described in D4); 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); 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); 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).

4. A method for cultivating a gramineous plant with high stomatal density, high stomatal number or high in vitro water loss rate, comprising increasing the expression level of the gene encoding the miRNA described in claim 1 or 2 in the target gramineous plant, and / or the activity and / or content of the miRNA to obtain a gramineous plant with high stomatal density, high stomatal number or high in vitro water loss rate, wherein the gramineous plant with high stomatal density, high stomatal number or high in vitro water loss rate has a higher stomatal density and water loss rate than the target gramineous plant, and / or has more stomata than the target gramineous plant.

5. A method for cultivating low drought-tolerant Gramineae plants, comprising increasing the expression level of the gene encoding the miRNA described in claim 1 or 2 in the target Gramineae plants, and / or the activity and / or content of the miRNA in the Gramineae plants with low drought tolerance, wherein the drought tolerance of the low drought-tolerant Gramineae plants is lower than that of the target Gramineae plants.

6. Any of the following uses of miRNA or a substance for detecting the miRNA: A1) Use in detecting or assisting in detecting drought tolerance of gramineous plants and / or preparing products for detecting or assisting in detecting drought tolerance of gramineous plants; A2) Use in detecting or assisting in detecting the stomatal density of gramineous plants and / or preparing a product for detecting or assisting in detecting the stomatal density of gramineous plants; A3) Use in detecting or assisting in detecting the number of stomata in Gramineae plants and / or preparing a product for detecting or assisting in detecting the number of stomata in Gramineae plants; It is characterized in that The miRNA sequence is shown in Sequence 1.

7. The product, characterized in that The product contains the substance for detecting miRNA expression as claimed in claim 6, and can be any one of the following G1)-G3): G1) detecting or assisting in detecting drought tolerance of leaves of Gramineae plants and / or preparing a product for detecting or assisting in detecting drought tolerance of leaves of Gramineae plants; G2) Application in detecting or assisting in detecting the stomatal density of gramineous plants and / or preparing a product for detecting or assisting in detecting the stomatal density of gramineous plants; G3) Application in detecting or assisting in detecting the number of stomata in Gramineae plants and / or preparing products for detecting or assisting in detecting the number of stomata in Gramineae plants.

8. A method for identifying or assisting in identifying the stomatal density of a grass plant, characterized in that: The method comprises detecting the expression level of the miRNA described in claim 6 or 7 in the tested tall grass plant, and identifying or assisting in identifying the stomatal density of the grass plant according to the expression level of the miRNA in the tested grass plant; The stomatal density of the Gramineae plant with a high expression level of the miRNA is greater than the stomatal density of the Gramineae plant with a low expression level of the miRNA.

9. A method for identifying or assisting in identifying the number of stomata in Gramineae plants, characterized in that: The method comprises detecting the expression level of the miRNA described in claim 6 or 7 in the tested tall grass plant, and identifying or assisting in identifying the number of stomata of the grass plant according to the expression level of the miRNA in the tested grass plant; The number of stomata of the Gramineae plant with a high expression level of the miRNA is greater than the number of stomata of the Gramineae plant with a low expression level of the miRNA.

10. A method for identifying or assisting in identifying drought tolerance of Gramineae plants, characterized in that: The method comprises detecting the expression level of the miRNA described in claim 6 or 7 in the tested tall grass plant, and identifying or assisting in identifying the drought resistance of the grass plant according to the expression level of the miRNA in the tested grass plant; The drought tolerance of the Gramineae plants with high expression levels of the miRNA is lower than that of the Gramineae plants with low expression levels of the miRNA.

Images