Leaf form related MicroRNA probe in drought-resistant and water-saving maize variety and detection method and application thereof

Abstract

The invention discloses a leaf form related MicroRNA probe in a drought-resistant and water-saving corn variety as well as a detection method and application of the leaf form related MicroRNA probe. The problem to be solved and solved is to predict, regulate and control the drought tolerance of corn. The invention specifically discloses any one of the following applications of miRNA or a substance for detecting the miRNA: A1) detecting or assisting in detecting the width-length ratio of gramineous plant leaves and / or preparing a product for detecting or assisting in detecting the width-length ratio of the gramineous plant leaves; a2) application in detection or auxiliary detection of the leaf area of the gramineous plant and / or preparation of a product for detection or auxiliary detection of the leaf area of the gramineous plant; a3) application in detection or auxiliary detection of the drought tolerance of the gramineous plant and / or preparation of a product for detection or auxiliary detection of the drought tolerance of the gramineous plant, wherein the miRNA sequence is as shown in the sequence 1. By detecting the expression quantity of the miRNA, the breadth-length ratio and the leaf area of the leaf of the to-be-detected corn variety are identified, and the method can be used for industrial production.

Description

Technical Field

[0001] The present invention specifically relates to a MicroRNA probe related to leaf morphology 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 invention is how to provide a molecular marker related to corn drought resistance, and a method for regulating corn drought resistance, leaf width-to-length ratio and leaf area.

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

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

[0006] A1) Application in regulating the width-to-length ratio of leaves of gramineous plants and / or preparing products for regulating the width-to-length ratio of leaves of gramineous plants;

[0007] A2) Use in regulating the leaf area of ​​gramineous plants and / or preparing products for regulating the leaf area of ​​gramineous plants;

[0008] A3) Use in plant breeding and / or in the preparation of plant breeding products;

[0009] The RNA is any of the following:

[0010] B1) The nucleotide sequence is the RNA molecule shown in Sequence 1;

[0011] 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);

[0012] B3) A fusion RNA molecule obtained by connecting a tag to the N-terminus or / and C-terminus of B1) or B2).

[0013] In the above, the regulation may be knocking out or inhibiting or reducing or down-regulating, or up-regulating or enhancing or increasing.

[0014] In the above, the substance that knocks out or inhibits or reduces or down-regulates the expression of the gene encoding the RNA or the substance that knocks out or inhibits or reduces or down-regulates the activity or content of the RNA can reduce the width-to-length ratio of the leaves of the Poaceae plant.

[0015] A substance that knocks out or inhibits or reduces or down-regulates the expression of the gene encoding the RNA or a substance that knocks out or inhibits or reduces or down-regulates the activity or content of the RNA can reduce the leaf area of ​​a grass plant.

[0016] A substance that upregulates, enhances or increases the expression of the gene encoding the RNA or a substance that upregulates, enhances or increases the activity or content of the RNA can increase the width-to-length ratio of the leaves of plants in this family.

[0017] A substance that upregulates, enhances or increases the expression of the gene encoding the RNA or a substance that upregulates, enhances or increases the activity or content of the RNA can increase the leaf area of ​​plants of this family.

[0018] In the above, the leaves may be leaves in mature stage.

[0019] In the above, the blades may be blades 11-20.

[0020] 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.

[0021] In the above RNA, sequence 1 (SEQ ID No. 1) consists of 21 nucleotide residues, which is named zma-miR171f or miR171f, and its encoding gene is miR171f gene.

[0022] In the above, the breeding index may be the width-to-length ratio of leaves or the leaf area.

[0023] In the above application, the protein is derived from corn.

[0024] 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 six 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 degradation of the mRNA of the gene.

[0025] In the above application, the substance that regulates the expression of the gene encoding the protein is any one of the following:

[0026] D1) a nucleic acid molecule that regulates the expression of the gene encoding the above RNA;

[0027] D2) expressing the gene encoding the nucleic acid molecule described in D1);

[0028] D3) an expression cassette containing the gene described in D2);

[0029] D4) a recombinant vector containing the gene described in D2) or a recombinant vector containing the expression cassette described in D3);

[0030] 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);

[0031] 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);

[0032] 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);

[0033] 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).

[0034] D1) In the nucleic acid molecule, a person of ordinary skill in the art can easily adopt known methods, such as directed evolution or point mutation methods. Those artificially modified nucleotides having 80% or more identity with the nucleic acid molecule sequence for regulating the expression of the RNA coding gene isolated by the present invention, and having the function of controlling the expression of the nucleic acid molecule coding gene for the RNA coding gene, are all derived from the nucleotide sequence of the present invention and are equivalent to the sequence of the present invention.

[0035] 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.

[0036] 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.

[0037] In order to solve the above technical problems, the present invention also provides a method for cultivating grass plants with low leaf width-to-length ratio or leaf area.

[0038] The method comprises knocking out or inhibiting or reducing or down-regulating the expression level of the gene encoding the above-mentioned RNA in the target Gramineae plant, and / or the activity and / or content of the RNA to obtain a Gramineae plant with a low leaf width-to-length ratio or leaf area, wherein the Gramineae plant with a low leaf width-to-length ratio or leaf area has a leaf width-to-length ratio or leaf area lower than that of the target Gramineae plant.

[0039] In the above method, the knocking out or inhibiting or reducing or down-regulating the expression of the gene encoding the above RNA in the Poaceae plant comprises introducing a gene knockout vector with sequence 3 as the target sequence into the target plant.

[0040] In order to solve the above technical problems, the present invention also provides a method for cultivating grass plants with high leaf width-to-length ratio or leaf area.

[0041] The scheme includes upregulating or enhancing or increasing the expression level of the coding gene of the above-mentioned RNA in the target Poaceae plant, and / or the activity and / or content of the RNA obtains a Poaceae plant with a low leaf width-to-length ratio or leaf area, and the leaf width-to-length ratio or leaf area of ​​the Poaceae plant with a high leaf width-to-length ratio or leaf area is higher than that of the target Poaceae plant.

[0042] In the above method, the upregulation, enhancement or improvement of the expression of the above RNA encoding gene in the Gramineae plant comprises introducing the above nucleic acid molecule or encoding gene or vector into the target plant.

[0043] In order to solve the above technical problems, the present invention also provides the following applications.

[0044] Any of the following uses of miRNA or a substance for detecting the miRNA:

[0045] 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;

[0046] A2) detecting or assisting in detecting the width-to-length ratio of leaves of grass plants and / or preparing a product for detecting or assisting in detecting the width-to-length ratio of leaves of grass plants;

[0047] A3) Use in detecting or assisting in detecting the leaf area of ​​gramineous plants and / or preparing a product for detecting or assisting in detecting the leaf area of ​​gramineous plants;

[0048] Characterized in that the miRNA sequence is as shown in Sequence 1.

[0049] In the above, the drought tolerance index can be the width-to-length ratio of leaves, body area, ASI, in vitro water loss rate, rehydration survival rate, relative water content of leaves, net photosynthetic rate of leaves, transpiration rate of leaves, and intercellular CO2 concentration of leaves.

[0050] In the above, the substance for detecting the miRNA may be a substance for detecting the expression amount of the miRNA.

[0051] In order to solve the above technical problems, the present invention also provides a product.

[0052] The product contains the substance for detecting miRNA expression as described above, and may be any one of the following G1)-G3):

[0053] G1) 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;

[0054] G2) detecting or assisting in detecting the width-to-length ratio of leaves of grass plants and / or preparing a product for detecting or assisting in detecting the width-to-length ratio of leaves of grass plants;

[0055] G3) Use in detecting or assisting in detecting the leaf area of ​​gramineous plants and / or preparing products for detecting or assisting in detecting the leaf area of ​​gramineous plants.

[0056] In order to solve the above technical problems, the present invention also provides a method for identifying or assisting in identifying drought resistance of Gramineae plants.

[0057] The method comprises detecting the expression amount 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 of the miRNA in the Gramineae plant;

[0058] The drought tolerance of the Gramineae plants with high expression levels of the miRNA is higher or is higher than the drought tolerance of the Gramineae plants with low expression levels of the miRNA.

[0059] In order to solve the above technical problems, the present invention also provides a method for identifying or assisting in identifying the width-to-length ratio of leaves of Gramineae plants.

[0060] The method comprises detecting the expression amount of the miRNA in the tested tall grass plant, and identifying or assisting in identifying the leaf width-to-length ratio of the grass plant according to the expression of the miRNA in the tested grass plant;

[0061] The width-to-length ratio of leaves of the Gramineae plant with a high expression level of the miRNA is greater than or is candidate greater than the width-to-length ratio of leaves of the Gramineae plant with a low expression level of the miRNA.

[0062] In order to solve the above technical problems, the present invention also provides a method for identifying or assisting in identifying the leaf area of ​​Gramineae plants.

[0063] The method comprises detecting the expression amount of the miRNA in the tested Gramineae plant, and identifying or assisting in identifying the leaf area of ​​the Gramineae plant according to the expression of the miRNA in the tested Gramineae plant;

[0064] The leaf area of ​​the Gramineae plant with a high expression level of the miRNA is greater than or can be greater than the leaf area of ​​the Gramineae plant with a low expression level of the miRNA.

[0065] In the above, the grass plant may be a plant of the genus Zea. The plant of the genus Zea may be Zea. The Zea may be corn variety JN1205, corn variety FM985, corn variety HY189, corn variety TN9, corn variety ZY8911, corn variety DK159, corn variety ZD958, corn variety ND108, corn variety LY99, corn variety XY335, corn variety XD20, corn variety JK968, corn variety JD50, corn variety HD188, corn variety NH101, corn variety LP206, corn variety XY1225, corn variety DH710, corn variety DH3737, corn variety DK517, corn variety XY1466, corn variety ND372, corn variety JND935 or corn variety DH518.

[0066] Beneficial Effects

[0067] The present invention discloses a MicroRNA probe related to leaf morphology 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) in detecting or assisting in detecting the width-to-length ratio of leaves of gramineous plants and / or preparing a product for detecting or assisting in detecting the width-to-length ratio of leaves of gramineous plants; A2) in detecting or assisting in detecting the leaf area of ​​gramineous plants and / or preparing a product for detecting or assisting in detecting the leaf area of ​​gramineous plants; A3) in detecting or assisting in detecting drought resistance of gramineous plants and / or preparing a product for detecting or assisting in detecting drought resistance of gramineous plants, and the miRNA sequence is shown in Sequence 1. The width-to-length ratio and leaf area of ​​the leaves of the corn variety to be tested can be identified by detecting the expression amount of the miRNA, which can be used for industrial production. BRIEF DESCRIPTION OF THE DRAWINGS

[0068] Figure 1The phenotypic and physiological response diagrams of different resistant maize varieties under water-sufficient and drought conditions; A: Plants were fully 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: Plants in the drought group stopped watering for 15 days and then re-watered for 3 days, at which time photos were taken. C: Relative water content (RWCs) of leaves of three different maize varieties under drought and water conditions. D: Comparison of survival rates among different maize varieties after 7 days of rehydration. E: Average leaf area of ​​the first three leaves of maize seedlings. F: 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). This part mainly screened more than 50 maize varieties widely cultivated nationwide in the early stage, and then identified three maize varieties with different drought resistance types, and screened them at the seedling stage. During the three-leaf and one-heart stage, the seeds were grown in pots in a greenhouse with daytime temperatures between 28°C and 30°C, nighttime temperatures between 20°C and 22°C, and relative humidity between 50% and 80%.

[0069] Figure 2 Figure 2 shows the miRNAs significantly associated with drought in three maize varieties by full miRNA analysis; A: Systematic clustering diagram showing three maize varieties with different drought resistance: sensitive variety (SV), moderately resistant variety (MV) and resistant variety (RV); B: Principal component analysis of UMI of three maize varieties; C: Trends of marker miRNAs in three different types of maize, namely miR399 family, miR166 family, miR169 family and miR171 family; D: Heat map showing 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; E: The number and possible functions of each type of miRNAs, known miRNAs ( Figure 1 F) and novel miRNAs ( Figure 1 G) V-ENN map analysis of up-regulated or down-regulated in three maize genotypes. The three drought-resistant or non-resistant materials were tested. Before sowing, the seeds were surface sterilized in 10% H2O2 for 20 min and then rinsed with distilled water 5 times for 2 min each time. They were then soaked in distilled water for 8 hours. The seeds were grown in pots in a greenhouse with daytime temperatures between 28°C and 30°C, night temperatures between 20°C and 22°C, and relative humidity between 50% and 80%. At the fully expanded third leaf stage, the aerial parts were taken for UMI sequencing after 7 days of normal watering and 7 days of drought treatment.

[0070] Figure 3Figure 1 shows drought-specific miRNAs that are mainly involved in leaf development; A: The expression levels of up-regulated or down-regulated miRNAs in three different types of maize, the histogram shows the miRNA level, and the line graph shows the predicted target gene expression level, abbreviated as SV: sensitive variety; SV_D: sensitive variety under drought; MV: medium variety; MV_D: medium variety under drought; RV: drought-resistant variety; RV_D: drought-resistant variety under drought. B: 14 groups of published data showed that these significantly different miRNAs are mainly involved in the morphogenesis of leaves, and miRNAs are highly conserved in maize, soybean, cotton, Arabidopsis, wheat and tomato. The key miRNAs that changed significantly in UMI sequencing were analyzed.

[0071] Figure 4 Figure 2 shows leaf morphology of wild-type and mutant corn plants regulated by miR171f; A: ear leaf phenotype, B: relative expression levels of wild-type and mutant corn plants, miR171f regulates the width-to-length ratio (Figure C) and leaf area (Figure D) of corn leaves, values ​​are Mean±SD, ***P<0.001, **P<0.01, *P<0.05.

[0072] Figure 5 The diagrams show leaf water loss rate, anthesis and silking interval (ASI) and grain yield 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, and the values ​​are Mean±SE (n≥22). C: There is a significant correlation between ASI and MFV. ****P<0.001, **P<0.01. The indicators of the 24 varieties screened at maturity under normal conditions.

[0073] Figure 6 Figure 2 is a significant correlation diagram between leaf width / length ratio and membership function value; A: The leaf length and width of the 4th to 19th leaves were measured to calculate the leaf width / length ratio, B: The relationship between the membership function value and the leaf width / length ratio, the data used for regression analysis are the average values ​​of the membership function values ​​and leaf width / length ratios of the 24 genotypes, and the values ​​are the mean SD (n≥5), (*P<0.05, **P<0.01, ***P<0.001).

[0074] Figure 7The following are the phenotypes of drought process and rewatering of three corn varieties. Under the condition of sufficient water (after the corn seedlings under normal water conditions are cultivated to the three-leaf stage, watering is stopped), a drought treatment of 15 days is carried out. The phenotypes at 1d, 3d, 5d, 7d, 9d, 11d, 13d and 15d are recorded respectively. Then the recovery growth of corn is recorded three days after rewatering. The phenotypes of drought process during the screening of three varieties.

[0075] Figure 8 The diagram shows the leaf length and leaf width of different leaf positions under normal water conditions; the left bar graph shows the leaf length of the first three leaves of corn seedlings. The right bar graph shows the leaf width of the first three leaves of corn seedlings. V value is Mean±SD (n=3). For each treatment, the differences with different letters are significant (P≤005). When the three varieties were screened at the seedling stage with three leaves and one heart, the length and width of the three leaves were measured respectively.

[0076] Fig. 9 is the distribution characteristics of miRNA sequences; (SV, MV, RV represent drought-sensitive varieties, intermediate varieties, and drought-resistant varieties under normal watering conditions, respectively; SV_D, MV_D, and RV_D represent drought-sensitive varieties, intermediate varieties, and drought-resistant varieties under drought conditions, respectively)

[0077] Fig.10 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 ( Fig.10 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. ( Fig.10 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 ( Fig.10 I). Arrange different corn varieties according to their drought resistance coefficient from large to small ( Fig.10 (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.

[0078] Fig.11This is a diagram for grading drought resistance of maize varieties by DRC; A: Grading drought resistance of different maize varieties by genetic correlation between drought resistance selection criteria (***P<0.001, **P<0.01, *P<0.001). B: Cluster analysis of different maize varieties was performed based on the drought resistance coefficients of 12 traits, using Euclidean distance as the clustering method.

[0079] Fig.12 This is the expression level of the miR171f mature sequence in the third leaf of the seedlings of some varieties (10 in total) of corn in the three-leaf and one-heart period (12 days after sowing). The sensitivity of the varieties to drought decreases from left to right on the horizontal axis. DETAILED DESCRIPTION

[0080] 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.

[0081] 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.

[0082] The following examples used IBM SPSS Statistics 26 statistical software to process the data. The experimental results were expressed as mean ± standard deviation. One-way ANOVA test was used. P < 0.05 (*) indicated a significant difference, P < 0.01 (**) indicated a very significant difference, and P < 0.001 (***) indicated a very significant difference.

[0083] Corn variety JN1205 is also known as Jilong 1205. In the present invention, JN1205 is a drought-sensitive variety.

[0084] Corn variety FM985 Corn variety FM985 is also known as Fumin 985. In the present invention, FM985 is a medium drought-resistant variety.

[0085] The corn variety HY189 is also called Heyu 189. In the present invention, HY189 is a drought-resistant variety.

[0086] Example 1 UMI method to screen key miRNAs involved in drought

[0087] Before sowing, the seeds of maize varieties JN1205, FM985 and HY189 were surface sterilized in 10% H2O2 for 20 min and then rinsed with distilled water 5 times for 2 min each time. They were then soaked in distilled water for 8 hours. The seeds were grown in pots in a greenhouse with daytime temperatures between 28°C and 30°C, night temperatures between 20°C and 22°C, and relative humidity between 50% and 80%. At the fully expanded third leaf stage, the maize was randomly divided into two groups, a normal treatment group and a drought treatment group. The normal treatment group was watered for 7 days and the drought treatment group was treated with drought (no additional watering) for 7 days before the aerial parts were taken for UMI sequencing.

[0088] We performed UMI transcriptome sequencing on seedlings (at the fully expanded third leaf stage) of the three typical maize genotypes (JN1205, FM985, and HY189) (Table 4 , SV_1, SV_2, SV_3, SV_D1, SV_D2, SV_D3, MV_1, MV_2, MV_3, MV_D1, MV_D2, MV_D3, RV_1, RV_2, RV_3, RV_D1, RV_D2, and RV_D3 in Table 4 represent sensitive varieties -1, -2, -3, moderate drought-resistant varieties -1, -2, -3, drought-resistant varieties -1, -2, -3, sensitive varieties under drought -1, -2, -3, moderate drought-resistant varieties under drought -1, -2, -3, and drought-resistant varieties under drought -1, -2, -3, respectively; Fig. 9 ), a total of 201 mature and hairpin forms of maize miRNAs were identified. There are 31 new miRNAs and 170 known miRNAs (compared with miRBase database) (as shown in Table 3, SV_1, SV_2, SV_3, SV_D1, SV_D2, SV_D3, MV_1, MV_2, MV_3, MV_D1, MV_D2, MV_D3, RV_1, RV_2, RV_3, RV_D1, RV_D2 and RV_D3 in Table 3 represent the same as above;). Hierarchical cluster analysis (HCA) found that miRNA levels and types were highly correlated with maize genotypes ( Figure 2 A). Principal component analysis (PCA) showed clear differences between drought- and well-watered plants ( Figure 2 In this study, miR399j and miR166g were also up-regulated under drought conditions, with the greatest up-regulation in drought-resistant varieties.

[0089] The HCA algorithm in MeV (V4.9) software (https: / / sourceforge.net / projects / mev-tm4 / files / ) was used to perform hierarchical clustering of miRNAs under different treatment conditions of the three varieties. Principal component analysis (PCA) was performed using the website (https: / / biit.cs.ut.ee / clustvis / ). The heat map of miRNA expression patterns was analyzed and produced using Morpheus (https: / / software.broadinstitute.org / morpheus / ). Log2 (UMI read length) was used to normalize miRNA expression levels.

[0090] MiR171f is downregulated under drought conditions ( Figure 2 C, Log2(SV_D / SV) is -0.26, Log2(MV_D / MV) is -0.99, Log2(RV_D / RV) is -1.32); the SV_D is the UMI read length of miR171f in the drought treatment group corn JN1205, SV is the UMI read length of miR171f in the normal treatment group corn, the MV_D is the UMI read length of miR171f in the drought treatment group corn FM985, MV is the UMI read length of miR171f in the normal treatment group corn FM985, the RV_D is the UMI read length of miR171f in the drought treatment group corn HY189, RV is the UMI read length of miR171f in the normal treatment group corn HY189; the sequence of zma-miR171f is 5'-UUGAGCCGUGCCAAUAUCACA-3' (sequence 1). Sequence 1 in the sequence list replaces U with T.

[0091] As described above, a molecular marker related to drought resistance was found, Log2 (expression level of miR171f under drought conditions / expression level of miR171f under normal conditions). The larger the absolute value of Log2 (expression level of miR171f under drought conditions / expression level of miR171f under normal conditions), the stronger the drought resistance ability.

[0092] Cluster analysis showed that there were significant differences among different drought-sensitive varieties. The 201 miRNAs were divided into six categories according to their expression patterns: Figure 2D in 2 and E in 2, Table 4). In the first category (I), the miRNA expression levels of the three maize varieties were reduced under drought conditions. Compared with the first category, the second category (II) showed an opposite trend, and the miRNAs could control the number of stomata and leaf development. The third category (III) was the reduced expression levels of miRNAs in HY189 and JN1205, and the fourth category (IV) was the increased expression levels of miRNAs in these two genes. The miRNAs in these two categories could also regulate the development of leaves and stomata. In the fifth category (V), miRNAs were usually expressed in one or two genotypes, but not in all three genotypes. This type of miRNAs may be involved in reproductive organ development and nutrient absorption. Finally, irregular miRNAs were classified into the sixth category (VI). Overall, most of the different miRNAs were involved in leaf development.

[0093] Three typical maize varieties, HY189 (drought resistance), FM985 (moderate sensitivity) and JN1205 (drought sensitivity), were selected to screen key miRNAs involved in drought sensitivity. The seeds of maize varieties HY189 (drought resistance), FM985 (moderate sensitivity) and JN1205 (drought sensitivity) were germinated at 25°C, cultured under sufficient irrigation conditions (relative humidity between 50% and 80%) to the two-leaf and one-heart stage, and randomly divided into two groups, namely the normal treatment group and the drought treatment group.

[0094] Drought treatment group:

[0095] Drought treatment was carried out for 7 days (maintaining 40% of field capacity), and the culture was carried out under the conditions of daytime temperature between 28℃ and 30℃ and nighttime temperature between 20℃ and 22℃. The phenotype was recorded after 7 days of drought stress treatment ( Figure 1 Middle A; Figure 1 Normal 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 and cultured for 3 days under the conditions of daytime temperature between 28℃ and 30℃ and nighttime temperature between 20℃ and 22℃ (and the phenotypes of drought treatment 1d, 3d, 5d, 7d, 9d, 11d, 13d, 15d and three days after rewatering were recorded). The results are shown in the figure. Figure 7 As shown, each phenotype diagram shows corn variety HY189, corn variety FM985, and corn variety JN1205 from left to right. The survival rate was calculated, and the surviving plants gradually recovered to normal growth ( Figure 1 Middle B, 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). The drought-resistant variety HY189 has the highest rehydration survival rate, reaching 58% ( Figure 1 D), compared with the drought-sensitive variety JN1205, HY189 had a higher relative water content in leaves ( Figure 1 Middle C).

[0096] Relative water content of leaves: 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%.

[0097] Normal treatment group:

[0098] The only difference between the two groups is that no drought treatment was performed, and other operations and tests were the same as those of the drought treatment group.

[0099] When the corn in the drought treatment group and the normal treatment group grew to three leaves and one heart and the leaf area of ​​the third leaf was measured on the same growth date, the leaf area of ​​HY189 was 30.4% smaller than that of JN1205. The third leaf area of ​​JN1205, FM985 and HY189 was 47.2 cm -2 、44.2cm -2 and 32.9cm -2 ( Figure 1 Middle E). The leaf length of the three varieties did not change significantly, but the leaf width of the drought-resistant variety became narrower ( Figure 8 ), HY189 had a significantly lower water loss rate than JN1205, which was mainly due to its narrow leaf shape ( Figure 1 These results indicated that HY189 was a drought-resistant variety, FM985 was a moderately drought-resistant variety, and JN1205 was a drought-sensitive variety.

[0100] The third leaf is the third corn leaf from bottom to top.

[0101] In vitro water loss rate: Leaves of different varieties of corn at the same leaf position, cultured to two leaves and one heart under full irrigation conditions, were cut along the leaf base for leaf separation, and then weighed continuously every 2 hours for 24 hours on a precision balance, with five replicates for each treatment. 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 leaf is separated from the body.

[0102] Table 3 Counts of novel and known miRNAs in the library

[0103] name Number of known miRNAs Number of new miRNAs Number of new siRNAs SV_1 96 19 309 SV_2 95 19 408 SV_3 91 21 288 SV_D1 91 20 322 SV_D2 88 21 296 SV_D3 79 19 223 MV_1 101 23 838 MV_2 89 20 676 MV_3 102 24 773 MV_D1 89 14 333 MV_D2 94 20 552 MV_D2 107 21 683 RV_1 93 22 368 RV_2 76 19 267 RV_3 78 21 271 RV_D1 67 20 220 RV_D2 70 19 160 RV_D3 83 19 274

[0104] Table 4 Summary statistics of small RNA library high-throughput sequencing results

[0105]

[0106] Example 2 Functions of key miRNAs suggest that leaf morphology plays a key role in drought sensitivity

[0107] We performed further analysis to identify the miRNAs that were significantly altered in the three cultivars (JN1205, FM985, and HY189) under drought conditions (|log2FC| ≥ 1). Figure 3 Among the 6 known miRNAs, 9 were upregulated and 8 were downregulated under drought conditions ( Figure 2 F, Table 5). Then, the newly detected miRNAs were analyzed. In the three maize varieties, no new miRNAs were upregulated, but four miRNAs were downregulated, namely new_miR39, new_miR42, new_miR55, and new_miR57 ( Figure 2 Finally, we identified 21 key miRNAs as 9 miRNAs upregulated by drought with higher expression levels in drought-resistant genes, and 12 miRNAs downregulated by drought but with lower expression levels in drought-sensitive genes (Table 6).

[0108] Another 21 groups of published miRNA data showed that 7 key miRNAs were mainly involved in leaf morphogenesis ( Figure 3 Middle B). We chose to investigate the drought sensitivity of different maize genotypes by detecting the upregulation of miR171 expression.

[0109] Table 5 Up-regulated and down-regulated miRNAs in three maize varieties

[0110]

[0111]

[0112] Table 6 Gene information of four new miRNAs

[0113]

[0114]

[0115] Example 3 MiR171 regulates corn leaf morphology

[0116] 1. The precursor sequence of zma-miR171f (sequence 2) was constructed into the pCUN-mGFP vector to obtain a recombinant overexpression transgenic vector (recombinant plasmid pCUN-zma-miR171f-mGFP);

[0117] Sequence 2 is as follows:

[0118] TTGGTTGTTGGCTGAGAGAGTGCGATGTTGGCATGGCTCAATCAACTCGCCGGCCGCGGGTGGCTTAGCTT AATTCTGCGCATTCGATCGAGGTGCGGGCAGTGTTTAATTGATTGAGCCGTGCCAATATCACAACCTTCTCTAGC CTATA.

[0119] The recombinant plasmid pCUN-zma-miR171f-mGFP is obtained by replacing the fragment between the restriction endonuclease SpeⅠ and KpnⅠ sites of the pCUN-mGFP vector with sequence 2, while keeping the other nucleotide sequences of the pCUN-mGFP vector unchanged.

[0120] 2. The above recombinant plasmid pCUN-zma-miR171f-mGFP was transformed into Agrobacterium tumefaciens 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 stomatal morphogenesis", and its name in the document is B73-329) to obtain T0 generation transgenic plants; T0 generation transgenic plants were self-pollinated to obtain two independent homozygous plants overexpressing miR171f ND101 OE1 and miR171f ND101 OE2 (this germplasm material was created by the Crop Functional Genomics and Molecular Breeding Research Center of China Agricultural University), obtained pure T2 generation germplasm resources from the center, and propagated them at the Shangzhuang Experimental Station of China Agricultural University that year. The overexpression of miR171 was detected at the DNA and RNA levels at the three-leaf stage of the seedlings, and self-pollination was strictly carried out. The harvested seeds were used for subsequent experiments.

[0121] 3. Construction of miR171f editing vector

[0122] To generate CRISPR-Cas9 mutants of miR171f, sgRNAs for miR171f were designed and evaluated using the CRISPR online server (http: / / crispor.tefor.net / ). The sgRNAs were inserted into the pBCXUN vector and verified by Sanger sequencing. The construct pBCXUN-miR171f-sgRNA1 was transformed into the previously described inbred line ND101 by Agrobacterium (strain EHA105). Positive transgenic lines were confirmed by PCR and sequencing. Stably inherited lines were selected for further phenotypic studies. The miR171f CRISPR-Cas9 mutant was created by the Crop Functional Genomics and Molecular Breeding Research Center of China Agricultural University.

[0123] The miR171f sequence (sequence 3) was provided to the Crop Center of China Agricultural University for construction of the miR171f editing vector. The miR171f knockout vector was obtained. The miR171f knockout vector was transferred into Agrobacterium EHA105 competent cells. The Agrobacterium EHA105 / miR171f knockout vector was obtained. The Agrobacterium EHA105 / miR171f knockout vector is Agrobacterium EHA105 containing the miR171f knockout vector.

[0124] Genetic transformation of maize

[0125] The maize variety ND101 was infected with the Agrobacterium EHA105 / miR171f knockout vector prepared above to obtain T0 transgenic plants; the T0 transgenic plants were self-pollinated to obtain an independent gene-edited homozygous plant miR171f ND101Crispr .

[0126] Using the above miR171f ND101 The genomic DNA of the Crispr seedlings was used as a template for amplification and sequencing using target PCR primer F (5'-TGGTTGTTGGCTGAGAGAG-3') and target PCR primer R (5'-CATAGCAGGACGACAAAGAAC-3'), respectively.

[0127] The sequencing results showed that:

[0128] miR171f ND101 Compared with the wild-type corn variety ND101, Crispr found that miR171f in the corn genome mutated: in the two homologous chromosomes, there was a deletion mutation of 5 deoxynucleotide residues between positions 128 and 134 of sequence 3 in the sequence list, that is, the deletion between positions 12 and 16 of sequence 4 (the mature sequence of miR171f) (the sequence is 5'-CAATA-3'), and the mature region of miR171f was deleted, thereby knocking out miR171f.

[0129] Sequence 3 is as follows:

[0130] .

[0131] Sequence 4 is as follows:

[0132] UUGAGCCGUGCCAAUAUCACA.

[0133] 4. Transfect corn varieties ND101 and miR171f ND101 OE1 and miR171f ND101 OE2 and miR171f ND101 Crispr seeds were planted at 25°C and grown to the flowering stage. The width-to-length ratio and leaf area of ​​the 11th to 20th leaves were tested and the phenotype was recorded.

[0134] Leaf width-to-length ratio: leaf width / leaf length.

[0135] Leaf area: leaf width*leaf length*0.75.

[0136] Leaves 11-20 are the 11-20 corn leaves from bottom to top.

[0137] result Figure 4 As shown in A, C and D, MiR171f ND101OE1 and miR171f ND101OE2 The width-to-length ratio of leaves 11-20 increased significantly ( Figure 4 The leaf area of ​​the 12th leaf, 13th leaf (ear leaf), and 14th leaf of the transgenic miR171f corn plants also increased significantly ( Figure 4 In contrast to the overexpressing transgenic lines, miR171f ND101Crispr The width-to-length ratio and leaf area of ​​the strain were significantly lower than those of ND101, indicating that miR171f plays a key role in regulating leaf width ( Figure 4 (A).

[0138] 5. The maize variety ND101 (background material) and miR171f were detected according to the following methods ND101OE1 and miR171f ND101OE2 and miR171f ND101Crispr The expression of miR171f in the transgenic maize variety ND101 was compared with that in the transgenic maize recipient maize variety ND101. ND101OE1 and miR171f ND101OE2 The expression level of miRNA171f in the transgenic line was significantly increased, and there was a 5-base deletion in the 21-nt mature 171f region ( Figure 4 Middle B, miR171f ND101OE1 and miR171f ND101OE2 Two independent miR171f ND101OE1 and miR171f ND101OE2 Transgenic line, miR171f ND101Crispr Gene editing of homozygous plants for an independent gene miR171f ND101Crispr ). Two independent miR171f ND101OE1 and miR171f ND101OE2 The expression level of miRNA171f in the transgenic line was significantly increased. Figure 4 A and B).

[0139] The primers used for miR171f are:

[0140] F: 5'-GAATGCTTGAGCCCGTGCCAATATCAC-3'

[0141] R:5'-GTGCAGGGTCCGAGGT-3'

[0142] The primers used for the internal reference U6 are:

[0143] F:5'-GGAACGATACAGAGAAGATTAGCA-3'

[0144] R:5'-GTGCAGGGTCCGAGGT-3

[0145] Example 4 Classification of sensitivity of different corn varieties to drought

[0146] Further, the main varieties covering the Chinese corn growing belt were selected and planted in electric rainproof canopies. The schematic diagram shows the growth status and measurement time ( Fig.10 (A).

[0147] Seeds of 24 corn varieties (as shown in Table 1) were planted in an electric rainproof shed, with a row length of 3 m, a row spacing of 0.5 m, and a plant spacing of 0.25 m. Each variety was replicated 12 times, with a total of 24 plots. Irrigation was carried out every two weeks. The irrigation amount in the normal watering area was more than 80% of the field water holding capacity, and in the drought area it was 40% of the field water holding capacity. 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 ( Fig.10 BD, where D-* is the drought area and W-* is the normal watering area).

[0148] When the crops grew to maturity, 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.

[0149] 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 ( Fig.10 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 ( Fig.10 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.

[0150] To investigate the key role of leaf morphology in drought sensitivity, the leaf length and width of 24 major cultivars from the 4th to the 19th leaves were measured to calculate the leaf width / length ratio ( Figure 6 Across all maize varieties studied, there was a high correlation between MFV and leaf length ratio ( Figure 6 (B). The results showed that all 16 leaves were extremely significantly negatively correlated (P<0.05). The correlation coefficient R ranged from -0.517 to 0.809, and the 10 correlation coefficients of 12 leaves, 13 leaves (ear leaves) and 14 leaves were -0.672, -0.681 and -0.760, respectively, indicating that they were closely related to drought resistance. The leaves of drought-resistant varieties were slender.

[0151] Detection of net photosynthetic rate (Pn) of ear leaves: Detected using Li6400 photosynthetic meter.

[0152] Detection of transpiration rate (Tr) of ear leaves: Detected using Li6400 photosynthetic instrument.

[0153] Detection of intercellular CO2 concentration (Ci) of ear leaves: Detected using Li6400 photosynthesis instrument.

[0154] 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.

[0155] The leaf length and leaf width of leaves 4-19 were measured: The leaf length and leaf width were measured using a ruler.

[0156] Plant height (PH): the distance from the ground to the highest point of the tassel.

[0157] Ear height (EH): the distance from the ground to the base of the ear.

[0158] Dry weight (DW): Dry at 80 degrees Celsius until the weight no longer decreases.

[0159] Single ear yield: weight of grains per ear.

[0160] The DRC calculated based on the 12 traits reached a significant level in all cases ( Fig.11 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.

[0161] The calculation formula of DRC is:

[0162] DRCmn=Tmnd / Tmnww (Formula 2-7)

[0163] Among them, DCmn 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.

[0164] 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: Fig.11 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 1). 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.

[0165] 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 1), and these maize varieties also appear in the sensitive range that depends on DRC value ( Fig.11 (B) Thus, the classification of the sensitivity of different maize varieties to drought is reliable.

[0166] The seeds of 24 corn varieties (as shown in Table 1) were cultured indoors at 25 degrees Celsius during the seedling stage. When they grew to five leaves and one heart, 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 5The 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 5 (middle B).

[0167] When the plant grows to the flowering stage, the anthesis-silking interval (ASI) is a key indicator of maize growth and development under drought stress. 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.

[0168] The results showed that under drought conditions, the ASI of different varieties varied greatly from 1d to 8d ( Figure 5 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 ( Figure 5 (middle D).

[0169] 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:

[0170] 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.

[0171] Anthesis-silking interval (ASI): The time difference between pollen shedding (ear maturity) and silking (ear maturity).

[0172] Table 7 Drought resistance coefficient (DRC) of 12 traits

[0173]

[0174]

[0175] Genetic correlation analysis showed that the DRC of the 12 traits reached significant levels in all cases ( Figure 5The DRC of the 12 traits was highly significantly positively correlated, indicating that the drought resistance coefficients of the 12 traits can be used as indicators for drought resistance selection. The clustering results showed that the 24 maize varieties were clustered into three categories according to the DRC of the 12 traits ( Figure 5 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 1). 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), which were drought-sensitive varieties. Ten maize varieties (LP206, XY1225, DH710, DH3737, DK517, XY1466, HY189, ND372, JND935, DH518) had high MFV (0.666-1), indicating that they were drought-resistant maize varieties. The remaining varieties were classified as medium types.

[0176] The conclusions drawn from the classification of drought sensitivity using these two methods were consistent. For example, JN1205, Tn9, ZY8911, and DK159 were drought-sensitive varieties depending on MFV (Table 1), and these maize genotypes also appeared in the sensitive area depending on DRC value ( Fig.11 (B) Thus, the classification of the sensitivity of different maize varieties to drought is reliable.

[0177] Our classification of drought sensitivity is mainly focused on the reproductive growth period. Is it suitable for vegetative growth? Leaf water loss rate is an important indicator reflecting the drought resistance of different maize varieties during the vegetative growth period. In all genotypes, the water loss rate of the 3rd, 4th, and 5th leaves showed similar trends ( Figure 5The 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 5 (middle B).

[0178] Anthesis-silking interval (ASI) is a key indicator of maize growth and development under drought stress. 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. The results showed that under drought conditions, different varieties had large differences in ASI from 1d to 8d ( Figure 5 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 ( Figure 5 (middle D).

[0179] 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:

[0180]

[0181] 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.

[0182] Table 1 Membership function analysis (MFV) and drought resistance classification of 24 corn varieties

[0183]

[0184]

[0185] 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.

[0186] The above corn varieties were grown under normal watering conditions to the three-leaf one-heart stage (12 days after sowing, that is, the three-leaf one-heart stage), and the expression of the miR171f mature sequence in the third leaf of the seedlings of DH710, NH101, HD188, XD20, ZY8911, LY99, ND108, JK968, DK159 and TN9 was detected. The specific method is as follows:

[0187] The total RNA of leaves was extracted using the Trizol method, and reverse transcription was performed using the specific primer 5'-GTCGTATCCAGTGCAGGGTCCGAGGTATTCGCACTGGATACGACCAGATC-3'. U6 was used as an internal reference, and the reverse transcription sequence of U6 was 5'-GTGCAGGGTCCGAGGTTTTGGACCATTTCTCGAT-3'. The reverse transcription product was detected by RT-PCR.

[0188] The primers used for miR171f are:

[0189] F: 5'-GAATGCTTGAGCCCGTGCCAATATCAC-3'

[0190] R:5'-GTGCAGGGTCCGAGGT-3'

[0191] The primers used for the internal reference U6 are:

[0192] F:5'-GGAACGATACAGAGAAGATTAGCA-3'

[0193] R:5'-GTGCAGGGTCCGAGGT-3'

[0194] The results are as follows Fig.12 As shown, the drought resistance of maize varieties was positively correlated with the expression level of miR171f.

[0195] 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 regulating the expression of a gene encoding the miRNA, or a substance for regulating the activity or content of the miRNA in any of the following: A1) Application in regulating the width-to-length ratio of leaves of gramineous plants and / or preparing products for regulating the width-to-length ratio of leaves of gramineous plants; A2) Use in regulating the leaf area of ​​gramineous plants and / or preparing products for regulating the leaf area of ​​gramineous plants; A3) Use in plant breeding and / or in the preparation of plant breeding products; The RNA 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 shown 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 RNA is derived from maize.

3. The use according to claim 1 or 2, characterized in that: The substance that regulates the expression of the gene encoding the protein is any one of the following: D1) a nucleic acid molecule that regulates the expression of the gene encoding the RNA 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 grass plants with low leaf width-to-length ratio or leaf area, comprising knocking out or inhibiting or reducing or down-regulating the expression level of the gene encoding the miRNA described in claim 1 or 2 in the target grass plant, and / or, the activity and / or content of the miRNA obtains a grass plant with a low leaf width-to-length ratio or leaf area, wherein the grass plant with a low leaf width-to-length ratio or leaf area has a leaf width-to-length ratio or leaf area lower than that of the target grass plant.

5. A method for cultivating a grass plant with a high leaf width-to-length ratio or leaf area, comprising up-regulating or enhancing or increasing the expression level of the gene encoding the miRNA described in claim 1 or 2 in the target grass plant, and / or the activity and / or content of the miRNA to obtain a grass plant with a low leaf width-to-length ratio or leaf area, wherein the grass plant with a high leaf width-to-length ratio or leaf area has a leaf width-to-length ratio or leaf area higher than that of the target grass plant.

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) detecting or assisting in detecting the width-to-length ratio of leaves of grass plants and / or preparing a product for detecting or assisting in detecting the width-to-length ratio of leaves of grass plants; A3) Use in detecting or assisting in detecting the leaf area of ​​gramineous plants and / or preparing a product for detecting or assisting in detecting the leaf area of ​​gramineous 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) 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; G2) detecting or assisting in detecting the width-to-length ratio of leaves of grass plants and / or preparing a product for detecting or assisting in detecting the width-to-length ratio of leaves of grass plants; G3) Use in detecting or assisting in detecting the leaf area of ​​gramineous plants and / or preparing products for detecting or assisting in detecting the leaf area of ​​gramineous plants.

8. 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 of the miRNA in the tested grass plant; The drought tolerance of the Gramineae plants with high expression levels of the miRNA is higher or is higher than the drought tolerance of the Gramineae plants with low expression levels of the miRNA.

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

10. A method for identifying or assisting in identifying the leaf area of ​​a grass plant, characterized in that: The method comprises detecting the expression level of the miRNA of claim 6 or 7 in the tested tall grass plant, and identifying or assisting in identifying the leaf area of ​​the grass plant according to the expression of the miRNA in the tested grass plant; The leaf area of ​​the Gramineae plant with a high expression level of the miRNA is greater than or can be greater than the leaf area of ​​the Gramineae plant with a low expression level of the miRNA.

Images