Low-maturing-rate corn germplasm creation method, identification method and application method

Abstract

The invention relates to the technical field of agricultural breeding, in particular to a low-maturing-rate corn germplasm creation method, an identification method and an application method. Comprising the following steps: hybridizing a bravo line Mexican teosinte germplasm and a W22 corn germplasm to obtain an F1 generation; backcrossing the F1 generation and the W22 corn germplasm, and continuously backcrossing the F1 generation and the W22 corn germplasm for six generations; in the backcross process, tracking a target fragment tb1 by using an RFLP marker so as to confirm a phenotype with a low maturing rate; continuously selfing for 6 generations by taking the low setting rate as a breeding standard to obtain the corn germplasm with the low setting rate; the low setting rate is 0%-50%. The germplasm created by the invention shows a phenotype with reduced maturing rate, i.e., in a stress state, under a normal cultivation condition, and a stress response molecular mechanism can be directly explored under a non-treatment condition.

Description

Technical Field

[0001] The present invention relates to the technical field of agricultural breeding, and in particular to a method for creating, identifying and applying low-fruiting-rate corn germplasm. Background Art

[0002] Maize seed setting rate is an important agronomic shape that responds to environmental stress and is a common phenotype under a variety of environmental stresses. Recently, with the dramatic changes in climate and the implementation of high-density mechanized maize cultivation programs, the seed setting of maize varieties has decreased.

[0003] In order to improve the environmental adaptability of corn and study the molecular mechanism of environmental adaptability, corn materials need to be subjected to stress treatment. Corn plants are tall, which requires a relatively high area of ​​the treatment site. In particular, the use of forward genetics to study the molecular mechanism of environmental adaptability of corn has high requirements for the number of germplasms and the scale of treatment, resulting in high research costs and slow research progress. Therefore, it is necessary to develop a method to create corn germplasm that shows a reduced fruiting rate under non-treatment conditions to explore the molecular mechanism of corn stress response. Summary of the invention

[0004] In order to solve the above problems, the present invention provides a method for creating, identifying and applying corn germplasm with low fruit setting rate.

[0005] The present invention is achieved through the following technical solutions:

[0006] A method for creating low-fruiting rate corn germplasm comprises the following steps:

[0007] The Bravo line of Mexican teosinte germplasm was hybridized with the W22 maize germplasm to obtain the F1 generation.

[0008] The F1 generation was backcrossed with W22 maize germplasm for six consecutive generations. During the backcrossing process, the target fragment tb1 was tracked using RFLP markers to confirm the phenotype of low seed setting rate.

[0009] Using low fruit setting rate as the breeding standard, six generations of continuous self-pollination were carried out to obtain corn germplasm with low fruit setting rate.

[0010] The low fruit setting rate is 0% to 50%.

[0011] The nucleotide sequence of the target fragment tb1 is shown in SEQ ID NO.1.

[0012] The RFLP markers are NPI615, umc140, tb1, umc107, bnl15.18 and kn1.

[0013] A method for using low-fruiting rate corn germplasm to explore corn environmental adaptability, using the low-fruiting rate corn germplasm obtained by the method as material, exploring the molecular mechanism of stress response under non-treatment conditions, so as to explore corn environmental adaptability.

[0014] A method for identifying low-fruiting-rate corn germplasm, wherein the low-fruiting-rate corn germplasm refers to the low-fruiting-rate corn germplasm obtained by the method.

[0015] The identification method of low-fruiting-rate corn germplasm comprises: identifying low-fruiting-rate corn germplasm by transcriptome sequencing, whole-genome association and linkage analysis.

[0016] Preferably, the transcriptome sequencing comprises the following steps:

[0017] (1) Using the low-fruiting-rate corn germplasm as material, transcriptome sequencing was performed.

[0018] (2) Use transcriptome sequencing results to screen differentially expressed genes.

[0019] (3) GO and KEGG enrichment analysis was performed on the differentially expressed genes. When the differentially expressed genes were enriched in response to light and temperature stress, they were identified as low-fruiting rate corn germplasm.

[0020] Preferably, the whole gene association and linkage analysis comprises the following steps:

[0021] (1) Using the low-fruiting rate corn germplasm as material, whole-genome association and linkage analysis were performed to identify SNP loci that respond to adverse stress.

[0022] (2) Identify low fruit set corn germplasm by detecting stress-responsive SNP loci.

[0023] Compared with the prior art, the present invention has the following beneficial effects:

[0024] The present invention provides a method for creating corn germplasm with low seed setting rate, wherein Bravo Mexican teosinte germplasm is hybridized with W22 corn germplasm to obtain F1 generation; F1 generation is backcrossed with W22 corn germplasm, and backcrossed with W22 corn germplasm for 6 generations continuously; during the backcrossing process, RFLP markers are used to track the target fragment tb1 to confirm the phenotype of low seed setting rate; low seed setting rate is used as the breeding standard, and self-pollination is performed for 6 generations continuously to obtain corn germplasm with low seed setting rate. The creation of the germplasm is to use a high-generation backcross population of corn and its close wild species teosinte to show a phenotype of stress treatment, that is, a significant reduction in seed setting rate. Through transcriptome sequencing, association and linkage analysis, it is found that the differentially expressed genes of the material are highly responsive to light and temperature stress, and linkage and association analysis can focus on the stress response site of adverse environment. The germplasm created by the present invention shows a reduced seed setting rate under normal cultivation conditions, that is, a phenotype under stress state, and the molecular mechanism of stress response can be directly explored under non-treatment conditions. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0026] Figure 1 for phenotypic characterization of the germplasm of the present invention;

[0027] Figure 1 In the figure, A: Plant morphology: Examples of plant morphology of W22, W22×Bravo BC and W22×Blanco BC are shown, including plant height, height of the first ear position and the number of empty stalks. B: Ear traits: including ear diameter, ear length, number of row cups, number of rows of grains and fruit setting rate, with typical female ear pictures. For plant height, height of the uppermost ear, ear diameter, ear length and fruit setting rate, the Student's t test was used; for the number of row cups and number of rows of grains, the Mann–Whitney–Wilcoxon test was used. The number of measured samples (n) for each trait is indicated in each figure. The dotted line represents the comparison between the W22×Bravo BC line and W22, and the solid line represents the comparison between the W22×Bravo BC line and the W22×Blanco BC line. * indicates P<0.05, ** indicates P<0.01;

[0028] Figure 2 The differences between W22 and HD in young panicles, filaments and pollen of the present invention;

[0029] Figure 2In the figure, A: There are missing grains in the HD panicle, the scale bar is 10 cm; Figure B: The HD filaments are significantly reduced, the scale bar is 10 cm; CF: A large number of low-vitality pollen and aborted pollen appear in HD, the scale bar is 2 mm;

[0030] Figure 3 The Manhattan plot and QQ plot of the fruit set rate restoration sites within the whole genome of the present invention;

[0031] Figure 3 In the figure, A is the Manhattan graph; B is the QQ graph;

[0032] Figure 4 It is the QTL location map of the fruit setting rate restoration site of the present invention;

[0033] Figure 4 In, A:F 2:3 :By855×HD;B:F 2:3 :Zac5346×HD;

[0034] Figure 5 This is the GPS linkage analysis of F2 fruit set rate of the present invention. The horizontal axis represents 10 maize chromosomes and the corresponding position information, and the vertical axis is the Ratio value after noise reduction analysis;

[0035] Figure 5 In the middle, A: F2:K10×HD GPS noise reduction analysis, B: F2:Zheng29×HD GPS noise reduction analysis;

[0036] Figure 6 It is the volcano plot of RNA-seq differential expression of the present invention;

[0037] Figure 6 In the figure, Figure A: Ear: young spike; Figure B: Pollen: pollen; Figure C: Silk: silk. log2FoldChange<-1 indicates downregulation (blue dots), log2FoldChange>1 indicates upregulation (red dots);

[0038] Figure 7 It is the GO biological process enrichment of the present invention;

[0039] Figure 8 This is the KEGG enrichment of the present invention. DETAILED DESCRIPTION

[0040] In order to facilitate the understanding of the present invention, the present invention will be described more comprehensively below, and preferred embodiments of the present invention are provided. However, the present invention can be implemented in many different forms and is not limited to the embodiments described herein. On the contrary, the purpose of providing these embodiments is to make the understanding of the disclosure of the present invention more thorough and comprehensive.

[0041] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as those commonly understood by those skilled in the art of the present invention. The terms used in the specification of the present invention herein are only for the purpose of describing specific embodiments and are not intended to limit the present invention.

[0042] The inventive concept of the present invention is as follows:

[0043] In order to improve the environmental adaptability of corn and study the molecular mechanism of environmental adaptability, it is necessary to subject corn materials to stress treatment. Corn plants are tall, which places relatively high requirements on the area of ​​the treatment site. In particular, the use of forward genetics to study the molecular mechanism of environmental adaptability of corn has high requirements on the number of germplasms and the scale of treatment, resulting in high research costs and slow research progress. Therefore, it is necessary to create a phenotype that shows a reduced fruiting rate under non-treatment conditions, that is, a phenotype under stress state, to explore the molecular mechanism of corn stress response.

[0044] Based on this, the present invention provides a method for creating low-fruiting rate corn germplasm, comprising the following steps:

[0045] The Bravo line of Mexican teosinte germplasm was hybridized with the W22 maize germplasm to obtain the F1 generation.

[0046] The F1 generation was backcrossed with W22 maize germplasm for six consecutive generations. During the backcross process, RFLP markers were used to track the target fragment tb1 to confirm the phenotype of low fruit set rate.

[0047] Using low fruit setting rate as the breeding standard, six generations of continuous self-pollination were carried out to obtain corn germplasm with low fruit setting rate.

[0048] The low fruit setting rate is 0% to 50%.

[0049] The present invention utilizes a high-generation backcross population of W22 corn and its close wild species Bravo Mexican teosinte germplasm combination, showing a phenotype of stress treatment, that is, a significant reduction in the fruit setting rate, and uses RFLP markers to track the target fragment tb1 to confirm the phenotype of low fruit setting rate. The corn germplasm cultivated by this method shows a reduced fruit setting rate under normal cultivation conditions, that is, a phenotype under a stress state, and can directly explore the molecular mechanism of stress response under non-treatment conditions. The present invention uses Blanco teosinte germplasm and W22 corn backcross as a control group to identify the phenotype. The results show that the Blanco teosinte germplasm and W22 corn backcross do not show a phenotype of low fruit setting rate, indicating that compared with other variety breeding methods, only Bravo Mexican teosinte germplasm and W22 corn backcross can obtain a phenotype of low fruit setting rate.

[0050] The present invention also provides a method for identifying low-fruiting rate corn germplasm, which identifies low-fruiting rate corn germplasm through transcriptome sequencing, whole-genome association and linkage analysis. Through transcriptome sequencing, association and linkage analysis, it is found that the differentially expressed genes of the material are highly responsive to light and temperature stress, and linkage and association analysis can focus on the stress response sites.

[0051] The technical solution of the present invention will be further described below in conjunction with specific embodiments.

[0052] Example 1: A method for creating low-fruiting rate corn germplasm

[0053] A Bravo Mexican teosinte germplasm was hybridized with a W22 corn germplasm to obtain the F1 generation; the Bravo Mexican teosinte germplasm was collected by Beadle and Kato from Site 6, 79 kilometers south of Valle de Bravo, Mexico, and the W22 corn germplasm was from Professor Doebley's laboratory at the University of Wisconsin-Madison, USA. The F1 generation was backcrossed with the W22 corn germplasm for 6 consecutive generations. During the backcrossing process, RFLP markers NPI615, umc140, tb1, umc107, bnl15.18 and kn1 located near tb1 were used to track the target fragment tb1; with low fruiting rate as the breeding standard, it was self-pollinated for 6 consecutive generations to obtain low fruiting rate corn germplasm HD.

[0054] This low-fruiting corn germplasm HD can be used to explore the molecular mechanism of stress response under non-treated conditions, that is, under normal cultivation conditions without environmental stress treatment, in order to explore the environmental adaptability of corn.

[0055] The nucleotide sequence of the target fragment tb1 is shown in SEQ ID NO.1:

[0056]

[0057] The Bravo Mexican teosinte germplasm was disclosed in Xue, Wei et al. "Hybrid Decay: A Transgenerational Epigenetic Decline in Vigor and Viability Triggered in Backcross Populations of Teosinte with Maize." Genetics vol. 213, 1 (2019): 143-160. doi: 10.1534 / genetics.119.302378.

[0058] Experimental Example 1: Identification of Phenotype

[0059] In this example, the fruit set rate, number of grains per row, number of ear rows, ear diameter, ear length, silking period and pollen shedding period phenotypes of W22, W22×Blanco BC and W22×Bravo BC were identified and compared. W22×Blanco BC means that W22 is backcrossed with Blanco teosinte; W22×Bravo BC means that W22 is backcrossed with Bravo teosinte. Among them, W22×Blanco BC is used as a control.

[0060] It should be noted that in order to reduce the influence of other chromosome segments of Teosinte on the phenotype, the phenotype investigation started from W22×BlancoBC6 and W22×Bravo BC6, that is, W22 and Blanco Teosinte were backcrossed for 6 generations, and W22 and Bravo Teosinte were backcrossed for 6 generations. Due to the limitation of seed quantity, the investigation of some phenotypes was completed in the seventh generation, which is represented by W22×Blanco BC7 and W22×Bravo BC7.

[0061] The results are as follows Figure 1 shown. Figure 1 A in the figure represents plant morphology: examples of plant morphology of W22, W22×Bravo BC6 and W22×BlancoBC are shown, including plant height, first ear height and the proportion of empty stems. Figure 1B in the figure represents ear traits: including ear diameter, ear length, row cup number, number of rows of grains and seed setting rate, with typical female ear pictures. Student's t test was used for plant height, top ear height, ear diameter, ear length and seed setting rate; Mann-Whitney-Wilcoxon test was used for row cup number and number of rows of grains. The number of samples measured for each trait, n, is indicated in each figure. The dotted line represents the comparison between W22×BravoBC and W22, and the solid line represents the comparison between W22×BravoBC and W22×Blanco BC. * indicates P<0.05, and ** indicates P<0.01.

[0062] 2. Pollen dyeing:

[0063] TTC staining method to determine pollen vitality. Collect mature pollen from W22 and HD respectively, take a small amount and place it on a clean glass slide. Add 2 drops of 0.5% TTC solution, stir well, cover with a cover glass, and place in a 35℃ constant temperature box. After 10 minutes, examine under a microscope. Pollen stained red has strong vitality, light red is second, and colorless pollen has no vitality or is sterile.

[0064] KI staining method to determine pollen fertility. Collect mature anthers of W22 and HD corn respectively, and place them on a glass slide. Add 1 drop of distilled water, and crush the anthers with tweezers to release the pollen grains. Add 2 drops of KI solution, cover with a coverslip, and observe under a microscope. All pollen grains that are stained blue are active pollen grains containing starch, and those that are yellow-brown are poorly developed pollen grains.

[0065] The results are as follows Figure 2 As shown in the figure, there are obvious differences between W22 and HD in young panicles, filaments and pollen. Compared with W22, HD young panicles have missing grains, the scale bar is 10 cm; HD filaments are significantly reduced, the scale bar is 10 cm; the innovative germplasm has a large number of low-vitality pollen and aborted pollen, the scale bar is 2 mm.

[0066] Experimental Example 2: Genetic analysis of seed setting rate restoration loci

[0067] (1) Leaf DNA extraction:

[0068] DNA extraction by CTAB method. Heat the water bath to 65℃. Pour 350mg of the punched leaf disc into the mortar that has been previously introduced into liquid nitrogen, and grind vigorously when the liquid nitrogen is about to evaporate, repeat three times. Immediately add 900ul 2X CTAB solution evenly to the freshly ground sample powder, and wait for the sample to dissolve completely. Transfer the objects in the mortar to a 2ml centrifuge tube, cover the tube cap and heat it in a water bath, shake it once every 10min, and take it out after 30min. Add 900ul chloroform:isoamyl alcohol = 24:1, shake vigorously for 5min; centrifuge for 10min, 13000rpm. Transfer 1000ul of the aqueous phase to a new 2ml centrifuge tube, add an equal volume of isopropanol, precool at -20℃, invert for 5min, and centrifuge at 7000rpm for 5min. Pour out the liquid, use a pipette to absorb the residual liquid around the precipitate, add 1.0ml 76% ethanol / 0.2M sodium acetate, and let it stand at room temperature for 20min. Centrifuge for 5min at 7000rpm, pour out the liquid, aspirate the liquid, add 500ul 76% ethanol / 10Mm ammonium acetate, place at room temperature for 5min, centrifuge for 4min at 13000rpm, pour out the liquid, aspirate the liquid. Wait for the precipitate to be dry and transparent, but not too dry. When there are yellow-green impurities, the next step can be carried out when the impurities appear streaks. Add 500ul TE to dissolve the precipitate, flick and mix after adding, and place in a refrigerator at 4℃ overnight. Centrifuge for 10min at 13300rpm on the second day, transfer the liquid to a 1.5ml centrifuge tube. Add 3ul 10mg / ml RNA remover, shake and mix, and place at room temperature for 30min. Add an equal volume of phenol: chloroform: isoamyl alcohol = 25:24:1, shake and mix for 5min. Centrifuge at 13300rpm for 10min, transfer the aqueous phase to a new 1.5ml centrifuge tube, add an equal volume of 400ul chloroform: isoamyl alcohol 24:1, shake and mix for 5min, and centrifuge at 13300rpm for 10min. Transfer the aqueous phase to a 2ml centrifuge tube, add 35ul of 3M sodium acetate (1 / 10 of the aqueous phase volume), 2.5 times the volume of the aqueous phase, ice, pre-cooled at -20℃, anhydrous ethanol, and mix. If the DNA precipitate is obvious, centrifuge for 5min at 7000rpm, pour out the liquid, and wait for it to dry and become transparent for 20min. If it is not obvious, store it at -20℃ overnight. Add 150ul TE to dissolve the DNA precipitate, flick it, and store it in a 4° refrigerator.

[0069] (2) Whole-genome association analysis of fruit set restoration loci

[0070] The phenotypic data were obtained from 164 groups of inbred lines that were screened to restore hybrid decline from 2021 to 2024. The average value of the fruit set rate was calculated and converted according to the formula (F1:IBLs×W22-F1:IBLs×HD) / F1:IBLs×W22. The phenotype of F1:IBLs×HD was used as the phenotypic value of the fruit set rate in the whole genome association analysis. The genotype data were downloaded from the website of corn genetics and molecular breeding of Professor Yan Jianbing's laboratory. The genotype file All_imputated was downloaded from https: / / pan.baidu.com / s / 1E65xZP4ChSspGy_0Sft6wQ. The file contains information such as the name of the associated inbred line, the source of the inbred line, the name of the molecular marker, the name of the chromosome where the molecular marker is located, and the chromosome position. The original file was read. In actual operation, the file data could not be read successfully because it was too large, so it was divided into 10 Marker files according to different chromosomes. According to the presence or absence of phenotypic data, the genotype file of the corresponding inbred line was retrieved. The chromosome position, molecular marker position and base pair were selected to form a map file, and the plant fruiting rate phenotypic data were combined into a phenotype file. The whole genome association analysis was performed using the R language "statgenGWAS" package, with p = 2.0 × 10 -6 Serves as a significance threshold; uses the "CMplot" package to draw Manhattan plots and QQ, i.e., quantile-quantile plots, to statistically identify significant sites.

[0071] The Manhattan plot revealed that there were 9 significant SNP markers for fruit set rate, such as Figure 3 As shown in A. The results of the QQ plot show that most of the data are distributed along the 45-degree reference line, indicating that the data as a whole conform to the expected normal distribution. The end of the QQ plot is S-shaped, indicating that these data are extreme and outliers, which may be related signals, such as Figure 3 The specific site information of the 9 significant SNP markers for statistical fruit set rate is shown in Table 1.

[0072] Table 1 Significantly associated SNP loci for fruit setting rate

[0073] Characteristics chromosome Physical location, bp Gene frequency P-Value Replacement Effect Substitution effect standard error <![CDATA[Contribution R 2 > LOD value SET 1 138572013 0.92 1.8E-07 0.31 0.06 14 6.74 SET 1 292529539 0.93 2.5E-07 0.34 0.07 14 6.61 SET 1 290805644 0.89 5.4E-07 0.26 0.05 13 6.27 SET 1 218986570 0.27 1.8E-06 0.31 0.07 12 5.74 SET 2 233762613 0.75 4.6E-07 0.19 0.04 14 6.33 SET 5 41414718 0.93 9.9E-07 0.31 0.07 13 6.00 SET 6 107320065 0.39 8.2E-07 -0.17 0.04 13 6.09 SET 7 141885624 0.96 6.7E-07 0.40 0.08 13 6.17 SET 9 122714866 0.88 1.3E-06 0.24 0.05 13 5.89

[0074] Note: SET: fruit setting rate; R 2 : R based on likelihood ratio 2 ; LOD: LOD score for SNPs, defined as -log10(p-value).

[0075] Among the 9 significant markers, 6 marker gene frequencies were above 80%. The substitution effect of 1 marker was evaluated as negative, and the substitution effect of 7 markers was evaluated as positive, with a standard error of 0.04 to 0.08 and a contribution rate between 12% and 14%.

[0076] (3) Linkage analysis of seed setting rate restoration loci

[0077] The phenotypic data were obtained using F2:Zac546×HD and F2:By855×HD constructed in Hainan in the winter of 2021 and the corresponding F2:Zac546×HD planted in Shenyang in the summer of 2023. 2:3 Data obtained. DNA was extracted from individual plants and parents in F2: Zac546×HD and F2: By855×HD, i.e., individual plants in the F2 population constructed by the innovative germplasm HD and the restorer lines Zac546 and By855, as well as leaves of W22, Zac546 and By855 using the leaf DNA extraction method (1) to detect genotypes. Population distribution of fruit set rate in the four populations was statistically analyzed. Map and ped files were read using Tassel 5.0, and the ABH genotype function was used to convert map / ped files into ABH type files based on the genotypes of the parents. The "ABHgenotypeR" package was called using R software to fill and correct the genotype file, with maxHapLength=3, and the genotype file after filling and correction was saved. Phenotypic and genotypic data were organized using EXCEL to conform to the data format required by QTL IciMapping. The MAP function was used to calculate the genetic distance, and the parameters selected were Threshold Value = 0.30 (By REC); k-Optimality, By REC, 2-OptMAP, NN Initials = 10; Window Size = 5 (By RE C). The BIP function was used to analyze the significant region, and the parameters were Deletion for Missing Phenotype, Step = 1cM, Pin = 0.001; the ICIM-ADD method was used to calculate the LOD value, and the significance threshold was filled in with 2.5. The ADD function was used for drawing.

[0078] The results are as follows Figure 4 As shown in Figure 2, after screening, the inbred lines By855 and Zac546 (HD) had good resilience. Therefore, By855 and Zac546 were crossed with innovative germplasm to construct segregating populations. 2:3 The phenotypes of the family and the genotypes of the F2 plants were mapped using QTL IciMapping 4.2 software, with a significance threshold of LOD = 2.5. A total of 6 significant QTLs were located. In the By855 population, linkage loci were detected on chromosomes 1, 3, 5, and 9, such as Figure 4 As shown in A, the Zac546 population detected a linked locus on chromosome 2, such as Figure 4 As shown in B.

[0079] (4) Gradient pool sequencing analysis of fruit set recovery sites

[0080] The phenotypic data came from 10 F2 populations constructed in 2023 and were divided into pools according to the fruit set scoring standard. The genotypic data used the 2023 45K targeted sequencing genotyping data. Each plant in the F2:K10×HD and F2:Zheng29×HD populations was labeled and leaves were taken. When the fruits were ripe, the phenotype of the fruit set rate was investigated. According to the fruit set rate, 4 mixed pools were constructed. From the 8 mixed pools of the two inbred line populations, appropriate amounts of individual leaves were taken and mixed. DNA was extracted using the leaf DNA extraction method (1). In addition, leaf DNA of the parents K10, Zheng29, and W22 was extracted and the genotype was detected to obtain polymorphic sites.

[0081] Tassel 5.0 was used to align the parental sequences and obtain the polymorphic sites. The Linux system was used to merge the vcf files using the "bcftool" and the "vcftools" software was used to retrieve the SNP information of the polymorphic sites in the vcf files according to the polymorphic sites. The GPS command was executed using Perl software, and the pvalue and -log10 (p-value) values ​​were calculated by Ridit analysis. Further noise reduction analysis was performed, and the ratio value was calculated with a 400 kb window and a 100 kb step size. The "CMplot" package of the R language was used for drawing, or the Manhattan plot was made using the "Manhattan Plot for GWAS" plug-in of the origin software.

[0082] GPS was used to analyze the two populations F2:K10×HD and F2:Zheng29×HD. Ridit analysis and noise reduction analysis were performed on the sequencing data, and the corresponding p-value and ratio value (the ratio of the number of statistically significant variants exceeding the set threshold to the total number of variants within the defined genomic interval of 400kb) were obtained for each marker. After noise reduction, F2:K10×HD detected large ratio intervals on chromosomes 1, 2, and 9, such as Figure 5 As shown in A in the figure, it is the SNP interval with the highest proportion of significant p-values. F2: Zheng29×HD detected a large proportion of intervals on chromosomes 1, 3 and 5, as shown in Figure 5 As shown in B.

[0083] Experimental Example 3: Transcriptome Sequencing Analysis of Silks, Pollen and Spikes of Created Germplasm

[0084] (1) RNA extraction

[0085] Silks were sampled three days after silking, pollen was sampled within three days after pollination, and spikelets were sampled within six days after pollination. Each tissue of W22 and HD was sampled five times. Put a little liquid nitrogen in a mortar and then add the tissue. When the liquid nitrogen content is low, grind the tissue into fine powder until the nitrogen is exhausted. Repeat this operation until the tissue is ground into powder. Add TRI reagent, 1 ml for every 50mg-100mg tissue. TRI reagent should be frozen. Grind the sample and TRI reagent in a frozen state, and then let the sample stand to thaw. Grind again after thawing, and then transfer the sample to a new sterile 2ml tube with a sterile spatula. Label the sample number on the test tube and transfer it immediately after grinding to prevent evaporation. Grind the sample for 2 minutes, and then let the test tube stand at room temperature for 10 minutes. Place the sample in a centrifuge and centrifuge at 12000G for 10 minutes. Transfer the supernatant to a new sterile 1.5ml tube. Add 200 μl of chloroform to each sample and mix vigorously. Shake thoroughly for 5 minutes until turbid. Let the sample stand at room temperature for 15 minutes. Centrifuge the sample at 12,000G for 15 minutes at 4°C. Carefully transfer 400ul of the aqueous phase to a new sterile tube, add 200μl of isopropanol and 200μl of a mixture of 0.8M sodium citrate and 1.2M sodium chloride to each tube, mix well, and store at -20°C for 30 minutes. Centrifuge at 4°C and 12,000G for 15 minutes, add 1ml of isopropanol, cover the tube, and turn the tube upside down several times, but do not shake vigorously. Centrifuge at 7,500G for 5 minutes in a sterile centrifuge. Wash with 1ml of 70% ethanol, centrifuge at 7,500G for 5 minutes at room temperature, remove the ethanol, and air dry for 15 minutes. Dissolve the precipitate in 50μl of water, measure the concentration with 2μl of the sample, and store at -80°C when the concentration reaches the standard.

[0086] (2) Transcriptome sequencing and retrieval of differentially expressed genes

[0087] RNA quality inspection After the RNA sample is qualified, the eukaryotic mRNA is enriched with magnetic beads with Oligo (dT). Then, fragmentation buffer is added to break the mRNA into short fragments. Using mRNA as a template, a six-base random primer is used to synthesize a single-strand cDNA, and then a buffer, dNTPs, DNA polymerase I and RNase H are added to synthesize a second-strand cDNA, and then the double-stranded cDNA is purified using AMPure XP beads. The purified double-stranded cDNA is first end-repaired, A-tailed and connected to the sequencing adapter, and then the fragment size is selected using AMPure XP beads. Finally, PCR amplification is performed, and the PCR product is purified with AMPure XP beads to obtain the final sequencing library. Sequencing to the original sequencing number was commissioned to Novogene. The original reads were trimmed using the Linux system cutadapt software to remove the adapter. The index of Zm-W22-REFERENCE-NRGENE-2.0 was established using hisat2-build, and hisat2 was continued to be converted to sam format. Transcript quantification was performed using HTSeq (-a 10 to filter results with a quality lower than 10). Principal component analysis, i.e., PCA analysis, was performed using the R language plotPCA function. Differentially expressed genes were identified using the R package “DESeq2” and p values ​​< 0.05 were filtered.

[0088] The difference of 1 times was set as the significance threshold. The analysis results showed that 635 genes were differentially expressed in young ears, of which 403 genes were down-regulated and 282 genes were up-regulated. Figure 6 As shown in A; there are 38 differentially expressed genes in pollen, of which 34 genes are down-regulated and 4 genes are up-regulated, such as Figure 6 As shown in B; there are 756 differentially expressed genes in filaments, of which 190 genes are down-regulated and 566 genes are up-regulated, as shown in Figure 6 As shown in C.

[0089] (3) GO and KEGG analysis

[0090] The differentially expressed genes were analyzed by GO and KEGG on the DAVID (DAVID FunctionalAnnotation BioinformaticsMicroarrayAnalysis) website, and the R package ggplot2 was used to plot the graphs.

[0091] The results of GO analysis are as follows Figure 7 As shown, the differentially expressed genes between the innovative germplasm and its recurrent parent W22 in the panicle were enriched under light, heat, and oxidative stresses, and the differentially expressed genes in the filaments were mainly enriched in the biosynthetic pathway.

[0092] The results of KEGG enrichment are as follows Figure 8 The results show that the differentially expressed genes between the innovative germplasm and its recurrent parent W22 in the young panicles are enriched in pathways such as protein processing in the endoplasmic reticulum and photosynthesis, while the differentially expressed genes in the filaments are mainly enriched in the protein processing and metabolic processes.

[0093] The technical features of the above-described embodiments may be arbitrarily combined. To make the description concise, not all possible combinations of the technical features in the above-described embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0094] The above-mentioned embodiments only express several implementation methods of the present invention, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the invention patent. It should be pointed out that, for ordinary technicians in this field, several variations and improvements can be made without departing from the concept of the present invention, and these all belong to the protection scope of the present invention. Therefore, the protection scope of the patent of the present invention shall be subject to the attached claims.

Claims

1. A method for creating low-fruiting rate corn germplasm, characterized in that: The following steps are involved: The Bravo line of Mexican teosinte germplasm was crossed with the W22 maize germplasm to obtain the F1 generation; The F1 generation was backcrossed with W22 maize germplasm for 6 consecutive generations; During the backcrossing process, the target fragment tb1 was tracked using RFLP markers to confirm the phenotype of low seed setting; Taking low seed setting rate as the breeding standard, the corn germplasm with low seed setting rate was obtained after six consecutive self-pollination generations. The low fruit setting rate is 0% to 50%; The nucleotide sequence of the target fragment tb1 is shown in SEQ ID NO.

1.

2. The method for creating low-fruiting rate corn germplasm according to claim 1, characterized in that: The RFLP markers are NPI615, umc140, tb1, umc107, bnl15.18 and kn1.

3. A method for exploring the environmental adaptability of corn using low-fruiting rate corn germplasm, characterized in that: Using the low-fruiting-rate corn germplasm obtained by the method of claim 1 as material, the molecular mechanism of stress response is explored under non-treatment conditions to investigate the environmental adaptability of corn.

4. A method for identifying low-fruiting rate corn germplasm, characterized in that: The low-fruiting-rate corn germplasm refers to the low-fruiting-rate corn germplasm obtained by the method of claim 1; The identification method of low-fruiting-rate corn germplasm comprises: identifying low-fruiting-rate corn germplasm by transcriptome sequencing, whole-genome association and linkage analysis.

5. The method for identifying low-fruiting rate corn germplasm according to claim 4, characterized in that: The transcriptome sequencing comprises the following steps: (1) Using the low-fruiting rate corn germplasm as material, performing transcriptome sequencing; (2) Using transcriptome sequencing results to screen differentially expressed genes; (3) GO and KEGG enrichment analysis was performed on the differentially expressed genes. When the differentially expressed genes were enriched in response to light and temperature stress, they were identified as low-fruiting rate corn germplasm.

6. The method for identifying low-fruiting rate corn germplasm according to claim 4, characterized in that: The whole gene association and linkage analysis includes the following steps: (1) Using the low-fruiting rate corn germplasm as material, whole-genome association and linkage analysis were performed to identify stress-responsive SNP loci; (2) Identify low fruit set corn germplasm by detecting stress-responsive SNP loci.

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