Zm00001eb095640 gene for regulating corn ear length and application of Zm00001eb095640 gene

Abstract

The invention relates to the technical field of agricultural biology, in particular to a Zm00001eb095640 gene for regulating and controlling the ear length of corn and application of the Zm00001eb095640 gene, and particularly provides a molecular marker for the ear length of the corn, the molecular marker is the Zm00001eb095640 gene, and the nucleotide sequence of the gene is shown as SEQ ID NO.1. According to the invention, a temperate zone corn inbred line Ye107 with short ear length is used as a common male parent; and respectively hybridizing with five temperate zone and one tropical zone corn inbred line as female parents with relatively long ear length to construct a corn multi-parent group with obvious ear length difference. According to the present invention, GWAS analysis and quantitative trait site analysis are adopted to jointly locate to SNP168005869 significantly related to the ear length and located on the chromosome 2, 10.25% of the phenotypic variation of the ear length can be explained by the site, the functional gene Zm00001eb095640 for regulating and controlling the ear length can be excavated from the site, and the result of the present invention provides the technical support for the breeding of the long-ear corn variety by using the molecular marker.

Description

Technical Field

[0001] The present invention relates to the field of agricultural biotechnology, and particularly to the Zm00001eb095640 gene located on chromosome 2 of maize that regulates maize ear length and its applications. Background Art

[0002] Ear length is one of the important agronomic traits of maize and is also an important determinant of maize yield and quality. Increasing maize ear length helps to optimize yield by increasing the number of ears and grains, thereby meeting the growing food demand. Therefore, the study of maize ear length traits is of great significance. Maize is not only an important food crop worldwide but also an important source of feed and industrial raw materials. Due to its high-yield characteristics and wide adaptability, it has become a key crop in global agricultural production. However, compared with other food crops, there is a certain genetic variability in maize ear length. Therefore, breeders strive to improve its ear length performance by analyzing the relationship between different maize genotypes and ear length. In summary, increasing ear length is an important goal in maize breeding and biotechnological improvement. Exploring functional genes related to maize ear length can provide technical support for molecular marker-assisted selection of high-yield maize. Summary of the Invention

[0003] To solve the above problems, the present invention provides the Zm00001eb095640 gene that regulates maize ear length and its applications. The Zm00001eb095640 gene discovered by the present invention is a functional gene that regulates ear length, and the associated SNP can explain 10.25% of the ear length phenotypic variation.

[0004] To achieve the above object, the present invention provides the following technical solutions:

[0005] In one embodiment, the present invention provides a maize ear length molecular marker, and the molecular marker is the Zm00001eb095640 gene, and the nucleotide sequence of the gene is as shown in SEQ ID NO:1.

[0006] Furthermore, for the maize ear length molecular marker, the expression level of the Zm00001eb095640 gene is positively correlated with maize ear length.

[0007] Furthermore, for the maize ear length molecular marker, the Zm00001eb095640 gene corresponds to the 168003513-168012351st base on chromosome 2 of maize in the genomic version Zm-B73-REFERENCE-NAM-5.0, and the gene starts from the 5′ end

[0008] The base markers at positions 168003707, 168003772, 168003796, 168005202, 168005279, 168005297, 168005304, 168005311, 168005317, 168005367, 168005443, 168005475, 168005529, 168005562, 168005638, 168005657, 168005717, 168005740, 168005792, 168005869, 168006569, 168006643, 168006706, 168008342, 168008439, 168011574, 168011655 and 168011836 are AGGCACCGGACTGGGCTGACAAACGTCC, and the maize exhibits the trait of superior ear length.

[0009] In another embodiment, the present invention provides a molecular marker for maize ear length. The molecular marker is located at the SNP_168005869 locus starting from the 5′ end of chromosome 2 of the maize reference genome version Zm - B73 - REFERENCE - NAM - 5.0. The base at this locus exhibits T / C polymorphism, and when the base changes from T to C, the maize exhibits the trait of superior ear length. The molecular marker has a positive additive effect with the Zm00001eb095640 gene as shown in SEQ ID NO:1.

[0010] In another embodiment, the present invention provides the use of a product for detecting any one of the above - mentioned molecular markers in identifying or assisting in identifying the maize ear length trait. The product includes reagents, kits or gene chips, and the product detects the genotype of the molecular marker or the expression level of the Zm00001eb095640 gene.

[0011] In another embodiment, the present invention provides the use of a product for detecting any one of the above - mentioned molecular markers in identifying or assisting in identifying the maize ear length trait. The product includes products prepared by PCR, qPCR, Sanger sequencing, high - throughput sequencing, fluorescence in situ hybridization method, TaqMan probe method, ARMS - PCR method or KASP method, and the product detects the genotype of the molecular marker.

[0012] In another embodiment, the present invention provides any one of the following uses of any one of the above - mentioned molecular markers,

[0013] a) Genetic diversity analysis of ear length maize; b) Construction of molecular genetic map of ear length maize; c) Genome-wide association analysis of ear length maize; d) Variety identification of ear length maize; e) Molecular marker-assisted selection breeding of ear length maize; f) Genome-wide selection breeding of ear length maize; g) Gene editing breeding of ear length maize.

[0014] In another embodiment, the present invention provides the application of SNP locus in the gene editing breeding of ear length maize, and the application is to mutate the base of SNP_168005869 locus starting from the 5′ end on chromosome 2 of the maize reference genome version Zm-B73-REFERENCE-NAM-5.0 from T to C.

[0015] Furthermore, the gene editing breeding tool is the CRISPR / Cas9 system.

[0016] In another embodiment, the present invention provides a method for screening ear length maize. Take the maize sample to be detected and detect any one of the said molecular markers. If it conforms to the marker trait, an ear length maize variety can be obtained.

[0017] The technical effects achieved by the present invention:

[0018] The present invention provides the Zm00001eb095640 gene for regulating maize ear length and its application. The present invention uses the temperate maize inbred line Ye107 with a lower ear length as a common parent, and hybridizes it with 5 temperate and 1 tropical maize inbred lines respectively to construct a maize multi-parent population with significant ear length differences. By using GWAS analysis and QTL analysis, SNP_168005869 significantly related to ear length located on chromosome 2 was co-localized, and then the functional gene Zm00001eb095640 for regulating ear length was mined. This SNP can explain 10.25% of the ear length phenotypic variation. Haplotype analysis shows that in 789 RILs, the gene Zm00001eb095640 has 5 haplotypes (Hap1, Hap2, Hap3, Hap4 and Hap5), and the ear length of Hap3 is significantly higher than that of other haplotypes. Therefore, Hap3 of the Zm00001eb095640 gene is the haplotype type that can significantly increase ear length. The results of the present invention contribute to further studying the regulation mechanism of maize ear length and also provide technical support for breeding long-ear maize varieties. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] In order to more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following will briefly introduce the drawings required in the embodiments.

[0020] Figure 1 A pedigree diagram of a NAM population with significant ear length differences was constructed by crossing six long-ear parents with the short-ear parent Ye107;

[0021] Figure 2 Frequency distribution diagrams of ear length of NAM (Nested Association Mapping) populations under three environments;

[0022] Figure 3 (a) Three-dimensional principal component analysis (PCA) diagram; (b) Population structure diagram of the NAM population; (c) Linkage disequilibrium (LD) decay diagram;

[0023] Figure 4 Manhattan diagrams (left) and Q-Q diagrams (right) for analyzing significant SNPs of maize ear length using GWAS under different environments. (a) Significant SNPs related to maize ear length under the BLUP environment, (b) 21JH environment, (c) 22YS environment, and (d) 23YS environment.

[0024] Figure 5 Manhattan diagrams (left) and Q-Q diagrams (right) for analyzing significant SVs of maize ear length using GWAS under different environments. Among them, (a) significant SVs related to maize ear length under the BLUP environment, (b) 21JH environment, (c) 22YS environment, and (d) 23YS environment.

[0025] Figure 6 Joint GWAS analysis diagram of maize ear length using SNPs and SVs;

[0026] Figure 7 Haplotype analysis diagram of candidate gene Zm00001eb095640. (a) Location of candidate gene Zm00001eb095640 on chromosome 2. (b) Base variation distribution of different haplotypes in the region of gene Zm00001eb095640. (c) Ear lengths corresponding to five haplotypes. ** indicates P < 0.01, **** indicates P < 0.0001;

[0027] Figure 8 Analysis diagram of the dominant and additive effects of three SNPs and one SV locus;

[0028] Figure 9 Diagram of base and amino acid changes of candidate gene Zm00001eb095640; (a) Amino acid changes caused by non-synonymous SNPs. (b) Motif changes caused by amino acid changes at position 296;

[0029] Figure 10 Diagram of the positional relationship between SNPs and candidate genes;

[0030] Figure 11 Heat map of tissue-specific expression patterns of candidate genes regulating maize ear length. Specific implementation manners

[0031] To further illustrate the present invention, the Zm00001eb095640 gene for regulating maize ear length and its application provided by the present invention will be described in detail below in conjunction with the accompanying drawings and embodiments, but they should not be construed as limiting the scope of protection of the present invention.

[0032] The present invention provides the Zm00001eb095640 gene for regulating maize ear length. The nucleotide sequence of the Zm00001eb095640 gene is shown in SEQ ID NO.1, corresponding to the bases at positions 168003513 - 168012351 on chromosome 2 of maize in the genomic version Zm - B73 - REFERENCE - NAM - 5.0.

[0033] In the present invention, EL (EarLength) is a common abbreviation for maize ear length, representing the length of the maize ear.

[0034] In the present invention, SV (Structural Variation) refers to structural variations in the genome. Structural variation refers to sequence changes or position changes in the genome that exceed a certain threshold in length.

[0035] Example 1

[0036] 1.1 Plant materials

[0037] The experiments were conducted in Jinghong (100°78′E, 22°00′N) in 2021 (21JH), Yanshan in 2022 (22YS) and Yanshan in 2023 (23YS) (104.5°E, 23.6°N), and experimental fields were planted in three different environments respectively. Six multi - parental populations were obtained by single - seed descent method: RIL_R - 2 - 1 - 1, RIL_YML1218, RIL_Shen137, RIL_YML226, RIL_Chang7 - 2 and RIL_Q11; among them, the common parent Ye107 is a key elite inbred line cultivated from two lines from different heterotic groups in the Chinese breeding program. Among the six multi - parental populations, RIL_R - 2 - 1 - 1 has 111 recombinant inbred lines (RILs), RIL_YML1218 has 136 RILs, RIL_Shen137 has 117 RILs, RIL_YML226 has 132 RILs, RIL_Chang7 - 2 has 151 RILs, and RIL_Q11 has 142 RILs. Finally, 789 RILs with rich genetic variations were constructed. The parental information is shown in Table 1 for details.

[0038] Table 1 Parental information

[0039]

[0040] 1.2 Experimental design

[0041] In Yanshan in 2021, Yanshan in 2022, and Yanshan in 2023, a randomized complete block design (RCBD) was adopted at three time points and locations, with 2 replicates at each location. Each experimental plot was 3.0 m long, with a row spacing of 0.5 m and an in-plant spacing of 0.25 m. There were 14 plants in each row, and 10 plants were sampled from the middle of each row. The maize in the experimental field was cultivated according to local standard agronomic practices. The ear length was measured at the dough stage when the ear length had basically stabilized. To ensure representative sampling, at least 5 ears were measured in each row.

[0042] 1.3 Heritability analysis

[0043] After preliminary processing of the phenotypic data collected at three time points and locations, the Ime4 package in R software (v4.4.1) was used to perform a correlation analysis of ear length (EL) in different populations and environments, calculate the mean, standard deviation, skewness, kurtosis, and coefficient of variation of ear length, and conduct a normal distribution test. The broad-sense heritability (h 2 ) was calculated, and the formula is shown in Equation Ⅰ:

[0044] h = Vg / (Vg+(Ve / L)) Equation Ⅰ;

[0045] In the formula, Vg is the genetic variance, Ve is the residual variance, and L is the number of environments. h 2 can help identify phenotypic trait variations. The larger h 2 is, the stronger the genetic control of the trait and the smaller the influence of environmental factors.

[0046] 1.4 DNA extraction and genome sequencing

[0047] First, the cetyltrimethylammonium bromide (CTAB) method was used to extract genomic DNA from maize seedling leaves. Subsequently, the genomic DNA isolated from each F9 RIL was digested with the restriction enzymes PstI and MspI, and then ligated to barcode adapters with T4 ligase (New England BioLabs). A GBS DNA library was constructed according to the GBS protocol and sequenced.

[0048] All ligated samples were pooled and purified using the QIAquick PCR Purification Kit (QIAGEN, Valencia, CA, USA). Polymerase chain reaction (PCR) amplification was performed using primers matching the adapters. Finally, the PCR products were purified and quantified using the Qubit dsDNA HS Assay Kit (Life Technologies, Grand Island, NY, USA). After selecting 200 - 300 bp PCR products using the Egel system (Life Technologies), the library concentration was estimated using a Qubit 2.0 fluorometer and the Qubit dsDNA HS Assay Kit (Life Technologies). Subsequently, sequencing reads were generated using TASSEL v5.0. Prior to TASSEL analysis, 80 poly(A) bases were appended to the 3'-ends of all sequencing reads. For comparative analysis, the B73_RefGen_v5 (full name Zm - B73 - REFERENCE - NAM - 5.0) reference genome sequence was used, and analysis was performed using Sentieon software (parameters "bwamem - k 32 - M - R"). The comparison results were sorted and duplicate - removed using Samtools (using the parameter rmdup). Finally, 638469 high - quality SNPs and 138707 SVs were generated and annotated using the ANNOVAR software tool.

[0049] 1.5 Phylogenetic tree, PCA and linkage disequilibrium analysis

[0050] Phylogenetic tree analysis was performed using Tassel v5.0 software, and SNPs and SVs were used to evaluate the genetic relationships among 789 RILs. Principal component analysis (PCA) was performed using the R package 4.4.1, and the results were visualized using the scatterplot3d software package. The decay of LD was evaluated using Pop LD decay v3.42 with the original SNP data. The parameter settings for calculating the r 2 (correlation coefficient) value were set to the default values. The LD decay plot was drawn with default parameters.

[0051] 1.6 Genome - wide association analysis

[0052] The efficient mixed - model association (EMMA) analysis method in the GEMMA (Genome - wide Efficient Mixed Model Association) software package was used for GWAS. To correct for population structure, the present invention used the first three principal components (PCs) to construct the S matrix, while the kinship (K) matrix was constructed using the simple matching coefficient matrix. The genetic relationships between individuals were modeled as random effects using the K matrix. In the association analysis, the significant P - value threshold was set to p < 1×10 -6 , to control the type I error.

[0053] The present invention uses PLINK software to calculate independent markers with parameters -indeppairwise 50 50 0.2. The formula -log10(1 / number of SNPs) is used to calculate the significance threshold -log10(p)>4.5 to identify significant SNPs associated with maize EL. SNPs that meet or exceed the threshold are extracted using bedtools v1.7, and based on the Zm-B73-REFERENCE-NAM-5.0 reference genome and annotation information, candidate genes associated with maize EL are identified in the 20 kb regions upstream and downstream of the significantly associated SNPs. Based on the observation that the r 2 value shows a plateau at 20 kb in the LD decay plot, the present invention decides to screen for candidate genes associated with maize EL within the 20 kb regions upstream and downstream of the significantly associated SNPs.

[0054] 1.7 Identification and functional annotation of candidate genes

[0055] The significant SNPs identified in GWAS are compared with the QTL mapping results to identify consistent loci, and SNPs overlapping within the QTL intervals are selected to screen for candidate genes. Candidate genes are searched within a 20 kb range upstream and downstream of the significant SNPs. Candidate genes are predicted in MaizeGDB (https: / / www.maizegdb.org / ) using the maize B73_RefGen_v5 reference genome. Functional annotations of the candidate genes are obtained using the InterPro database.

[0056] 1.8 Haplotype analysis

[0057] Haploview v4.2 software is used to perform haplotype analysis on SNPs associated with EL in three environments. First, a haplotype map is constructed using high-density whole-genome SNPs, and the haplotypes of SNPs significantly associated with maize ear length are determined based on the positions of these loci and the results of LD analysis. Finally, the genes within the haplotypes are annotated to identify functionally related gene loci.

[0058] 1.9 Epistasis, dominance, and additive analysis of SNPs and SVs related to ear length

[0059] Plink software is used for epistasis analysis to identify positive epistatic interactions between loci at p<0.05. TASSEL software is used for dominance and additive effect analysis. The rr-BLUP package is used to calculate the genomic estimated breeding value (GEBV) for each sample in the population. Collectively, these analyses comprehensively evaluate the epistatic, dominance, and additive effects of SNPs and SVs related to ear length, thereby identifying significantly associated markers for subsequent gene function studies.

[0060] 2. Results

[0061] 2.1 Panicle Length Phenotypic Analysis

[0062] Phenotypic data analysis of EL showed significant differences among the six NAM populations (RIL_R-2-1-1 to RIL_Q11) ( Figure 1 ). Phenotypic data collected from the 21JH, 22YS, and 23YS environments showed that EL followed a normal distribution in all three environments ( Figure 2 ). The average broad-sense heritability (H2) of EL in the six subpopulations was approximately 80%, with the highest heritability in RIL_Chang7-2 (84.51%) and the lowest in RIL_Shen137 (74.16%) (Table 3). Analysis of variance (ANOVA) showed that the sum of squares and F value of the RIL population were significantly higher than the environmental effect, indicating that the main variation in panicle length traits could be attributed to genetic factors rather than environmental effects. Although the position effect was significant (p < 0.05), its sum of squares was relatively low, indicating a limited contribution of environmental factors to panicle length variation. The interaction between the RIL population × environment was not significant (p = 1), indicating that the panicle length performance of each RIL population remained stable at different locations, and environmental factors had the least interference with genetic effects. These results showed that genetic factors were the main contributors to panicle length variation under different environmental conditions, and environmental effects were consistent but limited, laying a foundation for subsequent genetic research (Table 2).

[0063] Statistical analysis further showed that the environment had little effect on EL in the six RIL subpopulations (Table 2). The squared partial correlation coefficients (r 2 ) of the six populations (RIL_R-2-1-1 - RIL_Q11) were 0.96, 0.93, 0.92, 0.93, 0.92, and 0.95 respectively (Table 3), indicating that most of the phenotypic variation was caused by other factors. RIL_R-2-1-1 showed positive skewness and kurtosis, indicating that the phenotypic distribution was slightly skewed and concentrated around the mean. In contrast, RIL_Q11 showed negative skewness and higher negative kurtosis, indicating a flatter distribution and a higher concentration around the mean. The highest coefficients of variation (CV) were observed in RIL_Chang7-2 and RIL_Q11, 20.99% and 21.35% respectively, indicating the highest relative phenotypic variation in these populations (Table 3). In contrast, the CVs of RIL_R-2-1-1 and RIL_YML1218 were lower (15.07% and 16.58% respectively), reflecting relatively low phenotypic variation.

[0064] Table 2 Analysis of variance (ANOVA) of EL in the NAM population under three environments

[0065]

[0066] Statistical analysis results of ear length phenotype in Table 3

[0067]

[0068]

[0069] Note: 21JH, 22YS, and 23YS represent the experiments conducted in Jinghong in 2021 and in Yanshan in 2022 and 2023, respectively. H2: Heritability. r 2 : Square of the correlation coefficient.

[0070] 2.2 Population structure, principal component analysis (PCA), and linkage disequilibrium analysis

[0071] Principal component analysis (PCA) showed that 789 RILs were divided into six clusters. The RILs of RIL_YML1218 were clustered with RIL_Shen137, probably because the common parent Ye107 was used during the development of the NAM population ( Figure 3 a). RIL_R-2-1-1, RIL_Chang7-2, and RIL_Q11 were concentrated in PC1, PC2, and PC3, indicating that most of the genetic variation in these populations could be explained by these components. In contrast, RIL_YML1218 and RIL_Shen137 showed overlap because they had a common genetic background and used Ye107 as the common parent ( Figure 3 b). The overlap observed between RIL_YML1218 (YML1218×Ye107) and RIL_Shen137 (Shen137×Ye107), as well as between RIL_Shen137 and RIL_YML226 (YML226×Ye107), further supported the genetic similarity. Population structure analysis showed significant admixture between subpopulations, especially between RIL_YML1218 and RIL_Shen137, and between RIL_YML226 and RIL_Shen137, indicating gene flow and hybridization during the development of the NAM population. The optimal number of clusters was determined to be K = 6 using the ΔK method, supporting the classification of RILs into six different subclasses.

[0072] Linkage disequilibrium (LD) analysis showed that LD decayed with the increase in the physical distance between SNPs ( Figure 3 c). LD decreased rapidly with the increase in physical distance. When r 2 was 0.1, LD decayed by approximately 20 kb. Therefore, 20 kb upstream and downstream of the SNP was selected as the standard for screening candidate genes ( Figure 3 c). The rapid decay of LD indicated high genetic diversity and frequent recombination events within the population, which are characteristics of the NAM population.

[0073] 2.3 Genome-wide association analysis of significant SNPs for ear length

[0074] A genome-wide association study (GWAS) used 638,646 high-quality SNPs and combined the mean ear lengths of the NAM population in three environments. In addition, GWAS was performed using the BLUP values of the EL of RILs in the NAM population. Based on the significance threshold of -log10(P) > 5.0, multiple significant SNPs were identified, distributed on 10 chromosomes of maize( Figure 4 ). The number of SNPs and related candidate genes varied in different environments.

[0075] 2.4 Genome-wide association analysis of significant SVs for ear length

[0076] During the variant analysis process, 138,707 structural variants (SVs) were retained after filtering and used in GWAS to identify SVs related to EL. GWAS analysis using these SVs showed that based on the threshold -log10(P) > 4.0, multiple SVs were significantly associated with EL( Figure 5 ). In addition, candidate genes located near these SVs were also identified. These SVs were distributed on chromosomes 1, 2, 4, 5, and 7.

[0077] 2.4 Joint GWAS analysis using SNPs and SVs

[0078] In addition to individual SNPs and SVs, we also performed a combined analysis of SNPs and SVs in GWAS. The SNPs identified in the 22YS environment were compared with the SVs identified in the 21JH environment because these two environments showed the largest number of significant SNPs and SVs during GWAS analysis. The analysis showed that the physical distance between SNP_168005869 on chromosome 2 and an SV (SV_168757810) was less than 1 Mb, indicating that these two variants were located in the same functional interval and were both significantly associated with EL( Figure 6 ). SNP_168005869 and SV_168757810, indicating that these variants may act synergistically to affect ear length.

[0079] Since these variants are located in close proximity, they are likely to be linked. Linkage refers to the phenomenon where genes located on the same chromosome are inherited together. This phenomenon suggests that SNPs and SVs jointly regulate the expression or function of EL-related genes, ultimately affecting the EL of maize.

[0080] 2.6 Identification of candidate genes related to ear length

[0081] Through the combined analysis of SNP-GWAS and SV-GWAS, the candidate gene Zm00001eb095640 regulating maize ear length (EL) was identified. Among them, SNP-GWAS was used to locate SNP_168005869 on chromosome 2 in the whole environment (21JH, 22YS, 23YS, BLUP), and this locus could explain 10.25% of the ear length phenotypic variation. One candidate gene Zm00001eb095640 was identified using SNP_168005869, and the positional relationship between SNP_168005869 and the candidate gene Zm00001eb095640 is as Figure 10 shown.

[0082] 2.7 Haplotype analysis of candidate genes

[0083] Haplotype analysis was performed on the candidate gene Zm00001eb095640 determined by co-localization analysis ( Figure 7 a). The bases at positions 168003707, 168003772, 168003796, 168005202, 168005279, 168005297, 168005304, 168005311, 168005317, 168005367, 168005443, 168005475, 168005529, 168005562, 168005638, 168005657, 168005717, 168005740, 168005792, 168005869, 168006569, 168006643, 168006706, 168008342, 168008439, 168011574, 168011655, 168011836 of the Zm00001eb095640 gene showed five haplotypes ( Figure 7 b, Figure 7 c):

[0084] Hap1: GAACAGCGAATCAGATACGCACCCGTTC;

[0085] Hap2: AGGCGCGAAACTGAACTGATAAACGTCC;

[0086] Hap3: AGGCACCGGACTGGGCTGACAAACGTCC;

[0087] Hap4: GAACAGCGAATGAGATACGCACCCGTCC;

[0088] Hap5: GAAAGCGAGGCTGGGCTGACGCATTTCA. Among 789 RILs, the ear length of the families with Hap3 was significantly longer than that of the families with other haplotypes, and thus it was considered as a favorable haplotype of Zm00001eb095640.

[0089] 2.8 Additive effect analysis of significant loci

[0090] This study found that SNP_168005869 near the candidate gene Zm00001eb095640 showed a strong positive additive effect on ear length ( Figure 8 ). This indicates that SNP_168005869 plays a major positive regulatory role in increasing ear length.

[0091] 2.9 Nucleotide variation and expression analysis of candidate genes

[0092] The candidate gene Zm00001eb095640 was analyzed to compare the variation of the candidate gene among 6 parents.

[0093] SNP_168005869 in the R-2-1-1 population caused the base to change from T to C ( Figure 9 a), resulting in the amino acid at position 296 in the CDS region changing from leucine (L) to serine (S) ( Figure 9 b). Since leucine is hydrophobic and serine is hydrophilic, this non-synonymous mutation will change the structure and function of the protein. In the present invention, the function of Zm00001eb095640 in R-2-1-1 was changed due to the SNP_168005869 mutation, resulting in the longest ear length after maturity ( Figure 1 ; Table 1).

[0094] The public database Ensembl Plants was used to analyze the expression of the candidate gene in various tissues of maize. The expression levels of the gene Zm00001eb095640 were significantly different in different tissues and developmental stages ( Figure 11 ). In the pericarp, the expression level was 66, indicating that this gene plays an important role in the process of grain development. At the same time, the expression level of this gene in mature pollen was 40, which was related to the process of pollen development and pollination. In contrast, the expression levels in tissues such as leaves and roots were relatively low. For example, the expression level at the leaf base was only 10 and at the leaf tip was 30, indicating that this gene mainly plays a role in tissues related to plant reproduction and has little impact on the vegetative growth of the plant. Overall, Zm00001eb095640 can indirectly affect the ear length of maize by regulating processes such as pollen development, ovule development, and grain filling. The high expression in the pericarp especially indicates that this gene plays a role in grain development, nutrient supply, and water regulation, thus affecting the formation of ear length.

[0095] Although the above embodiments have described the present invention in detail, they are only some embodiments of the present invention, rather than all embodiments. People can also obtain other embodiments based on these embodiments without creative efforts, and these embodiments all fall within the protection scope of the present invention.

Claims

1. A molecular marker for corn ear length, characterized in that: The molecular marker is the Zm00001eb095640 gene, and the nucleotide sequence of the gene is shown in SEQ ID NO:

1.

2. The corn ear length molecular marker according to claim 1, characterized in that: The expression level of Zm00001eb095640 gene was positively correlated with corn ear length.

3. The corn ear length molecular marker according to claim 1, characterized in that: The Zm00001eb095640 gene corresponds to bases 168003513-168012351 on chromosome 2 of maize in the genome version Zm-B73-REFERENCE-NAM-5.

0. 168003707、168003772、168003796、168005202、168005279、168005297、168005304、168005311、168005317、168005367、168005443、168005475、168005529、168005562、168005638、168005657、1680 The base markers at positions 05717, 168005740, 168005792, 168005869, 168006569, 168006643, 168006706, 168008342, 168008439, 168011574, 168011655 and 168011836 are AGGCACCGGACTGGGCTGACAAACGTCC, and corn shows a dominant trait of ear length.

4. A molecular marker for corn ear length, characterized in that: The molecular marker is located at the SNP_168005869 site on chromosome 2 starting from the 5′ end of the corn reference genome version Zm-B73-REFERENCE-NAM-5.

0. The base at the site presents a T / C polymorphism. When the base at the site changes from T to C, the corn presents an ear length advantage trait. The molecular marker has a positive additive effect with the Zm00001eb095640 gene shown in SEQ ID NO:

1.

5. Use of a product for detecting the molecular markers of any one of claims 1 to 4 in identifying or assisting in identifying the length trait of corn cobs, characterized in that: The products include reagents, kits or gene chips.

6. Use of a product for detecting the molecular markers of any one of claims 1 to 4 in identifying or assisting in identifying the length trait of corn cobs, characterized in that: The products include products prepared by PCR, qPCR, Sanger sequencing, high-throughput sequencing, fluorescence in situ hybridization, TaqMan probe method, ARMS-PCR method or KASP method.

7. Any of the following uses of the molecular marker according to any one of claims 1 to 4, a) Genetic diversity analysis of ear length maize; b) Construction of molecular genetic map of ear length maize; c) Whole genome association analysis of ear length maize; d) Identification of ear length maize varieties; e) Molecular marker-assisted selection breeding of ear length maize; f) Whole genome selection breeding of ear length maize; g) Gene editing breeding of ear length maize.

8. Application of SNP loci in ear length corn gene editing breeding, characterized in that: The application is to mutate the base of the SNP_168005869 site on chromosome 2 starting from the 5′ end of the corn reference genome version Zm-B73-REFERENCE-NAM-5.0 from T to C.

9. The use according to claim 8, characterized in that: The gene editing breeding tool is the CRISPR / Cas9 system.

10. A method for screening corn with long ears, characterized in that: A corn sample to be tested is taken, and the molecular marker described in any one of claims 2 to 4 is tested. If the test result meets the marker trait, a corn variety with a long ear is obtained.

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