Molecular markers associated with ear diameter on chromosome 1 of maize and uses thereof

Abstract

The present application relates to the field of corn molecular marker assisted breeding, and specifically discloses a corn chromosome 1 related molecular marker and application thereof, and corn ear thickness molecular marker, the molecular marker is Zm00001eb032370 gene with the sequence shown as SEQ ID NO:1, the present application uses GWAS analysis to be located to the SNP_181125354 on chromosome 1 significantly related to ear thickness in multiple environments, and further excavates the functional gene Zm00001eb032370 for regulating ear thickness, SNP_181125354 can explain 6.15% of the ear thickness phenotype variation, and the generation interval can be shortened through molecular marker breeding, the breeding process is greatly accelerated, the selection accuracy is improved, and the cost is saved.

Description

Technical Field

[0001] This invention relates to the field of marker-assisted breeding of maize, specifically to a molecular marker on maize chromosome 1 that is associated with maize ear diameter and its application. Background Technology

[0002] The yield per maize plant is closely related to inflorescence development, especially the optimization of ear traits, which plays a decisive role in increasing yield. Studies have shown that ear diameter, as an important component of ear traits, has a significant impact on maize yield per plant. A thicker ear can accommodate more rows of kernels or larger kernel diameters, thus directly increasing yield. Therefore, optimizing ear diameter is considered a key breakthrough for improving maize yield and a key direction for future maize breeding.

[0003] The expression of crop traits depends not only on the function of individual genes but also on the interactions between genes. The contribution of genes to traits may vary under different environmental conditions. This invention aims to identify novel genes and SNPs related to ear diameter in a multi-parental population of tropical maize using whole-genome sequencing (WGS) technology and haplotype analysis to screen for tag SNPs. This reduces redundant testing costs during GS or MAS breeding processes while preserving the integrity of genetic information, ultimately providing innovative genetic resources and precise improvement strategies for significantly increasing maize yield per plant, thereby promoting the optimization and efficiency of maize production. Summary of the Invention

[0004] To address the shortcomings of existing technologies, this invention provides a molecular marker on chromosome 1 of maize that is associated with ear thickness and its application. This invention uses whole-genome sequencing (WGS) technology to perform genome-wide association analysis (GWAS) on a multi-parent population of tropical maize to identify the functional gene Zm00001eb032370 that is closely associated with ear thickness, providing a new technical solution for marker-assisted selection of maize germplasm with thicker ears.

[0005] To achieve the above objectives, the present invention provides the following technical solution: A crude molecular marker for maize ears, wherein the molecular marker is the gene Zm00001eb032370 with the sequence shown in SEQ ID NO:1.

[0006] The expression level of the Zm00001eb032370 gene is positively correlated with the diameter of maize ears.

[0007] Furthermore, the gene, starting from the 5' end, contains the following positions: 181114303, 181114391, 181114395, 181114424, 181114426, 181114432, 181114591, 181114593, 181114632, 181114635, 181114652, 181114669, 181114672, 181115212, 181115221, 181115371, 181115372, 181115384, 181115433. 181115439, 181115450, 181115458, 181115476, 181115485, 181115535, 181115544, 181115569, 181115586, 181115587, 181115855, 181115857, 181115875, 181115879, 181115917, 181115936, 181115945, 181115957, 181115959, 181115961, 181116033, 181116044, 181116070, 181116128 181116133, 181116175, 181116253, 181116324, 181116469, 181116473, 181116526, 181116549, 181116569, 181116659, 181116694, 181116801, 181116923, 181117253, 181117327, 181117354, 181117448, 181117485, 181117689, 181117692, 181117769, When the bases at positions 181118174, 181118180, 181118210, 181118218, 181118287, 181118398, 181118403, and 181118418 are respectively TATTCTGCGACCGCTTCGTCTACACGATCGCTGACTCGTCTTCAGGGGTAAGCCCGACAGGCAACACCCCGC, maize exhibits the dominant trait of thick ears.

[0008] Furthermore, the present invention provides products for detecting the molecular markers, the products comprising kits, reagents, or gene chips. The products detect the genotype or expression level of the molecular markers.

[0009] Furthermore, the present invention provides products for detecting the molecular marker genotype, the products including those prepared using PCR, qPCR, Sanger sequencing, high-throughput sequencing, fluorescence in situ hybridization, TaqMan probe method, ARMS-PCR method or KASP method.

[0010] The application of the product in identifying or assisting in the identification of corn ear thickness.

[0011] Furthermore, the present invention provides the application of the molecular marker in any of the following: a) Genetic diversity analysis of maize with thick ears; b) Construction of molecular genetic map of maize with thick ears; c) Genome-wide association analysis of maize with thick ears; d) Identification or auxiliary identification of maize varieties with thick ears; e) Molecular marker-assisted selection breeding of maize with thick ears or high yield; f) Genome-wide selection breeding of maize with thick ears.

[0012] Furthermore, the present invention provides a method for screening maize germplasm with thick ears, wherein a maize sample to be tested is taken, the molecular marker is detected, and germplasm that matches the molecular marker genotype is screened, which is maize germplasm with thick ears.

[0013] Furthermore, the present invention provides a method for screening high-yield maize germplasm, which involves taking a maize sample to be tested, detecting the molecular markers, and screening germplasm that matches the molecular marker genotypes, which are then identified as high-yield maize germplasm.

[0014] The term "molecular marker-assisted selection (MAS)" is a breeding technique that uses molecular markers of a target trait to select offspring lines in order to obtain superior individual plants containing the target gene.

[0015] The term "Genomic Selection (GS)" is a modern breeding technique that uses whole-genome marker information for genetic evaluation and selection. It aims to accelerate the breeding process and improve selection efficiency by predicting the breeding value or phenotypic performance of individuals through high-density molecular markers. The term "GS-MAS" refers to a breeding strategy that combines genomic selection (GS) with marker-assisted selection (MAS). GS-MAS uses high-density marker information and phenotypes covering the entire genome to estimate the breeding value of an individual, while also associating major and minor genes. By using breeding values, it can predict and select for complex traits (low heritability, difficult to determine, etc.) at an early stage, thereby shortening the generation interval, accelerating the breeding process, improving selection accuracy, and saving costs.

[0016] The technical effects achieved by this invention are as follows: This invention constructs a multi-parental maize population with significant differences in ear diameter by crossing the temperate maize inbred line Ye107 (with a smaller ear diameter) with six tropical and subtropical maize inbred lines (with a larger ear diameter). GWAS analysis located the SNP_181125354 on chromosome 1, which is significantly associated with ear diameter. Furthermore, the functional gene Zm00001eb032370, which regulates ear diameter, was identified. SNP_181125354 can explain 6.15% of the phenotypic variation in ear diameter. Haplotype analysis showed that among 1107 RILs (recombinant inbred lines), Zm00001eb032370 had 12 haplotypes (Hap1, Hap2, ..., Hap12), among which Hap12 had significantly higher ear diameter than the other 11 haplotypes. Therefore, Hap12 of the Zm00001eb032370 gene is a haplotype that significantly increases ear diameter. The results of this invention help to further study the regulatory mechanism of maize ear diameter and also provide a theoretical basis for developing maize varieties with larger ear diameters. Attached Figure Description

[0017] Figure 1 The following is a population structure diagram of 1107 RILs in an embodiment of the present invention; wherein: (a) principal component analysis; (b) unrooted tree; (c) Bayesian clustering diagram of 1107 RILs when K=6; (d) LD decay diagram; Figure 2 The following is a GWAS analysis diagram of panicle diameter in an embodiment of the present invention; wherein: (a) GWAS results based on the mean panicle diameter phenotype in Yanshan in 2022; (b) GWAS results based on the mean panicle diameter phenotype in Yanshan in 2023; (c) GWAS results based on the mean panicle diameter phenotype in Jinghong in 2024; (d) GWAS results based on the BLUP value of panicle diameter; Figure 3 This is a schematic diagram illustrating the relationship between significant SNPs and candidate genes in an embodiment of the present invention; Figure 4 Candidate gene LD block analysis diagram; Figure 5 A schematic diagram of mutation sites that form different haplotypes in the Zm00001eb032370 gene; Figure 6 Differences between different haplotypes in subgroups are shown, where A represents the percentage of difference and B is a box plot of differences.

[0018] Figure 7 Figure showing the expression levels of the Zm00001eb032370 gene in different tissues. Detailed Implementation

[0019] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the embodiments of the present invention. For the purchased goods in the test methods, if no specific conditions are specified, they shall be carried out according to conventional conditions or conditions recommended by the manufacturer. If the manufacturers of the reagents or instruments used are not specified, they can be conventional products that can be purchased from the market.

[0020] The gene sequence of Zm00001eb032370 marked in this invention is shown in SEQ ID NO: 1, corresponding to positions 181114266-181118468 on chromosome 1 from the 5' end of the reference genome version Zm-B73-REFERENCE-NAM-5.0. Example 1

[0021] 1. Method

[0022] 1.1 Plant Materials and Experimental Design This invention uses the excellent temperate backbone maize inbred line Ye107 as the common male parent, and crosses it with six tropical and subtropical maize inbred lines with relatively thick ears (CML312, CML395, YML46, YML32, NK40-1, and YML1218) to form six F1 hybrid combinations. These combinations are then continuously self-pollinated to F9 using the single-seed propagation method, constructing a multi-parent population containing 1107 recombinant inbred lines. The number of recombinant inbred lines in each subpopulation (pop1-pop6) is 142, 148, 303, 178, 200, and 136, respectively (Table 1).

[0023] The experiments were conducted in Yanshan County, Yunnan Province, China in 2022 and 2023, and in Jinghong City, Yunnan Province, China in 2024. The experiments followed a completely randomized block design, with each location replicated three times. The planting pattern was set as follows: row length 3m, row spacing 0.70m, 14 plants per row, and 2 rows per plot. Planting was managed according to local standard agronomic practices. After the ears matured, nine ears were randomly selected from each row to record their diameter, and the average diameter was taken to determine the average ear diameter.

[0024] Table 1. Detailed information about the parents

[0025] 1.2 Phenotypic Data Analysis First, Excel 2019 was used to preprocess the phenotypic data. SPSS 26.0 was used to assess whether the phenotypic data conformed to a normal distribution and to calculate basic statistics to help visually understand the central tendency and dispersion of the data. R4.3.2 was used to create heatmaps to assess the correlation between phenotypic data under different subgroups and environmental conditions. The aov() function was used to perform a two-way ANOVA to assess whether the influence of subgroups and environment on the phenotypic data was statistically significant. The lme4 software package was used to calculate the generalized heritability, with the formula H = Vg / (Vg + (Ve / L)), where Vg represents the genetic variance, Ve is the residual variance, and L is the environmental number.

[0026] 1.3 Whole genome sequencing 1.3.1 Sample Collection and DNA Extraction Healthy leaves were sampled during the seedling to jointing stage of maize. The collected leaf samples were immediately frozen in liquid nitrogen to prevent tissue and DNA degradation. Leaf DNA was extracted using the Tiangen Plant Genomic DNA Extraction Kit (Tiangen Biotech Co., Ltd., Beijing, China). The extracted DNA samples were quality controlled using agarose gel electrophoresis to confirm concentration (above 100 ng / μl) and purity (A260 / A280 ratio should generally be between 1.8 and 2.0) to ensure the extracted DNA was suitable for subsequent whole-genome sequencing.

[0027] 1.3.2 Library Construction and Sequencing DNA fragmentation was performed using a Vibra-Cell series ultrasonic fragmentation system (Sonics & Materials, Inc., Connecticut, America), and the fragmented DNA samples were subjected to gel electrophoresis to assess quality (ideally, the DNA fragment size should be between 200-500 bp). End repair was performed using T4 DNA polymerase (Thermo Fisher Scientific Inc., Waltham, Massachusetts, America), ligating short DNA adapters to both ends of the DNA fragments. To ensure library quality, exonuclease I enzyme (Thermo Fisher Scientific Inc., Waltham, Massachusetts, America) was used to remove DNA fragments without adapter ligations. DNA fragments of 200-500 bp in length (including portions of the adapter sequence) were selected using the AgencourtAMPureXP magnetic bead method. PCR amplification was performed on the library to increase the number of target DNA fragments. Finally, the concentration of the library was quantified using Qubit, typically targeting a concentration between 10-20 nM. Bioanalyzer (Agilent Technologies, Santa Clara, California, America) was used to detect the size distribution of the library, with fragment sizes typically ranging from 200 to 500 bp.

[0028] All samples were sequenced using the Illumina NovaSeq 6000 platform (Illumina, Inc., San Diego, California, America). The sequencing mode was paired-end sequencing, the sequencing depth was 5×, and the sequencing results were stored in FASTQ format. The quality of the sequencing data was evaluated using FastQC (Babraham Institute, Bioinformatics Group, Cambridge, United Kingdom). The evaluation criteria were: (1) Q-score ≥ 20, (2) GC content of the genome was 40% to 60%, (3) repetitive sequence ratio was less than 30%, (4) N content was less than 1-2%, and (5) read length was consistent with the expected length.

[0029] 1.4 Group Stratification Analysis 1.4.1 Principal Component Analysis To assess population genetic structure and control for the impact of population stratification on GWAS results, we performed principal component analysis (PCA) using GCTA software. First, genotypic data were standardized, and a genetic similarity matrix between samples was calculated. Then, the first few principal components were extracted based on this matrix; these principal components characterize the population structure.

[0030] 1.4.2 Construction of Unrooted Trees To further analyze the genetic relationships among subpopulations, we constructed an unrooted tree using MEGA (Molecular Evolutionary Genetics Analysis) software to assess the genetic distance and phylogenetic relationships between subpopulations. During the construction process, we used the Neighbor-Joining (NJ) method, which efficiently and accurately reflects the genetic differentiation of a population by minimizing the sum of genetic distances between samples.

[0031] 1.4.3 Population genetic structure analysis We used ADMIXTURE software for population stratification analysis. This method infers the contribution proportion of different subpopulations to each individual's genome by assuming that each individual is a mixture of components from multiple subpopulations. We first selected and set the expected subpopulation size (K value) based on our research objectives. By trying different K values ​​and selecting the optimal K value through cross-validation, we avoided overfitting or underfitting. We analyzed the population structure under different K values ​​and determined the genetic background of the samples based on the population stratification pattern.

[0032] 1.4.4 Chaining Imbalance Analysis We used PopLDdecay software to assess the genetic linkage disequilibrium (LD) in the population. The purpose of LD analysis is to measure the degree of linkage disequilibrium between SNPs, i.e., whether the genotypes of a pair of markers are independently inherited. In particular, the r² value is often used to represent the degree of LD between SNPs; the higher the r² value, the stronger the linkage and the closer the genetic association between the two SNPs. We used PopLDdecay software to calculate the r² values ​​between different SNP markers and further analyzed the LD decay at different genetic distances. We used the Plot_OnePop.pl script included with PopLDdecay to generate visualizations of LD decay. These graphs clearly show the LD structure at different locations in the population, identify high-LD regions in the genome, and further help determine marker selection and the location of genetic regions for GWAS.

[0033] 1.5 Genome-wide association analysis Genetic sweep genomic analysis (GWS) of maize ear thickness was performed using a mixed linear model (MLM) in GEMMA software. In the model, population genetic structure was treated as a fixed effect, while individual kinship was treated as a random effect to correct for the influence of population structure and kinship on trait performance. Bonferroni correction was used for multiple comparisons to reduce false positives and false negatives. M represents the number of SNPs used in the GWAS analysis. The p-value of each individual SNP was compared to the significance level after Bonferroni correction. If the p-value was less than p, the SNP was considered statistically significant. Furthermore, FDR correction was used to reduce errors from multiple comparisons to ensure the reliability and accuracy of the results. Generally, a p-value less than 5 × 10⁻⁸ was considered significant. For the identified significant SNPs, functional annotation was performed using the ANNOVAR tool to determine the location, region, and mutation type of the variant site in the genome. In addition, Manhattan plots and QQ plots were generated using PLINK software to visualize the association analysis results. The Manhattan plots assess the strength of the association between SNPs and traits, while the QQ plots assess the degree of deviation of the p-value distribution from the expected value.

[0034] 1.6 Candidate Gene Haplotype Analysis Haploview v4.2 software was used to perform haplotype analysis on candidate genes. For each gene, we analyzed the frequency distribution, phenotypic differences, and statistical significance of different haplotypes. Based on frequency distribution considerations, box plots only show haplotypes with high frequency in the sample. Haplotypes with low frequency (≤1%) were not shown separately; these low-frequency haplotypes had little statistical impact on the final results and did not affect the interpretation of the main conclusions.

[0035] 2. Results 2.1 Analysis of Maize Ear Coarseness Phenotype Data The results showed that pop4 consistently exhibited high and stable panicle diameter in all environments, while pop1 showed the lowest average panicle diameter (Table 2). Statistical analysis of the panicle diameter phenotypic data of the six subgroups is shown in Table 2 below. The coefficient of variation (CV%) of panicle diameter varied significantly among the six subgroups in each environment, indicating significant differences in panicle diameter among the subgroups. The absolute values ​​of skewness and kurtosis of panicle diameter in different environments were generally less than 1. The broad-sense heritability of panicle row number in the six subgroups ranged from 70.15% to 97.28%, indicating a strong genetic influence on this trait. The consistency of phenotypic variation across different environments highlights the reliability of the phenotypic data used for subsequent analysis. Significant differences in panicle diameter were observed among the subgroups due to the influence of genetic and environmental factors. This variability provides a solid foundation for further GWAS analysis and identification of important loci associated with panicle diameter.

[0036] Table 2. Analysis of spikelet diameter phenotypic data

[0037] Note: 22YS refers to Yanshan in 2022, 23YS refers to Yanshan in 2023, and 24JH refers to Jinghong in 2024. 2.2 Group Stratification Analysis By observing the 3D PCA plot, the clustering distribution of the samples is relatively clear, and the data can be roughly divided into 6 clusters, each representing a potential subgroup. Although most subgroups form a clear clustered structure in 3D space, there are overlapping regions between some clusters. For example, there is significant overlap between pop3 and pop6, which may indicate that these two subgroups have high similarity in the main feature dimensions. Figure 1 a).

[0038] In rootless tree analysis, although there is some degree of confounding between different clusters, the overall data can still be clearly divided into 6 main clusters ( Figure 1 b). This overlap may indicate that these clusters are relatively close in the feature space, reflecting their similarity on certain key features.

[0039] In the population structure analysis, when K=6, the data were clearly divided into 6 subgroups. Although some overlap still exists between certain samples, these 6 subgroups are generally well-defined. Figure 1 c). This overlap indicates that there may be overlapping areas between different subgroups, with some samples sharing similar characteristics, making their affiliation within certain subgroups unclear. Overall, despite the overlap, these subgroups still reflect the main structural characteristics of the population relatively well.

[0040] LD attenuation in MPP was evaluated using 16,223,980 valid SNPs. The LD attenuation plot shows that LD decreases rapidly with increasing physical distance between markers. When the r² value decreases to 0.24, the physical distance at which LD attenuation occurs is approximately 10 kb. Figure 1 d).

[0041] 2.3 Genome-wide association analysis of spikelet thickness trait This invention used 16,223,980 valid SNPs for GWAS analysis of maize ear diameter. The results showed that multiple significant SNPs associated with maize ear diameter were identified on all 10 chromosomes across all environments. Figure 2Notably, we consistently identified a significant SNP associated with maize ear diameter across all environments (22YS, 23YS, 24JH, BLUP): 1_181125354, which explained 6.15% of the ear diameter phenotypic variation. Gene screening within the relevant significant SNP and its upstream and downstream 10kb range revealed a consistent gene, Zm00001eb032370, across multiple environments. Figure 3 Based on the existing functional annotations (Table 3), and after assessing the trait relevance, this invention considers this to be a candidate gene worthy of further study.

[0042] Table 3 Candidate genes co-localized by GWAS

[0043] 2.4 Candidate gene haplotype analysis like Figure 4 , 5 6. Haplotype analysis of Zm00001eb032370 (the gene sequence of Zm00001eb032370 is shown in SEQ ID NO:1, corresponding to positions 181114266-181118468 of reference genome version Zm-B73-REFERENCE-NAM-5.0) revealed 12 distinct haplotypes (Hap1, Hap2, ..., Hap12) among 1107 RILs. The box plot only shows the 8 haplotypes with the highest frequencies in the sample. These haplotypes exhibited different frequency distributions in the different populations studied. Hap12 showed the highest phenotypic value and had a wide frequency distribution in pop4. Furthermore, there were significant differences between Hap12 and Hap1 and Hap3 (P<0.05, P<0.01). Therefore, we conclude that Hap12 is the dominant haplotype regulating maize ear diameter.

[0044] The specific haplotype loci, using Zm-B73-REFERENCE-NAM-5.0 as the reference genome, are as follows on chromosome 1 of the genome version, viewed from left to right starting at the 5' end: 181114303(REF:T / ALT:C) 181114391(REF:A / ALT:C) 181114395(REF:T / ALT:C)181114424(REF:T / ALT:G) 181114426(REF:C / ALT:T) 181114432(REF:T / ALT:G) 181114591(REF:G / ALT:A) 181114593(REF:C / ALT:A) 181114632(REF:G / ALT:T)181114635(REF:A / ALT:C) 181114652(REF:T / ALT:C) 181114669(REF:C / ALT:T)181114672(REF:G / ALT:A) 181115212(REF:C / ALT:T) 181115221(REF:T / ALT:A)181115371(REF:T / ALT:A) 181115372(REF:C / ALT:A) 181115384(REF:G / ALT:A) 181115433(REF:T / ALT:G) 181115439(REF:C / ALT:T) 181115450(REF:T / ALT:A)181115458(REF:A / ALT:G) 181115476(REF:C / ALT:T) 181115485(REF:A / ALT:G)181115535(REF:C / ALT:A) 181115544(REF:G / ALT:A) 181115569(REF:A / ALT:C)181115586(REF:T / ALT:C) 181115587(REF:C / ALT:A) 181115855(REF:G / ALT:A) 181115857(REF:C / ALT:G) 181115875(REF:T / ALT:C) 181115879(REF:G / ALT:A)181115917(REF:A / ALT:T) 181115936(REF:C / ALT:T) 181115945(REF:T / ALT:A) 181115957(REF:C / ALT:T) 181115959(REF:G / ALT:A) 181115961(REF:T / ALT:C)181116033(REF:C / ALT:T) 181116044(REF:T / ALT:C) 181116070(REF:T / ALT:G) 181116128(REF:C / ALT:G) 181116133(REF:A / ALT:C) 181116175(REF:G / ALT:A)181116253(REF:G / ALT:A) 181116324(REF:G / ALT:A) 181116469(REF:G / ALT:A)181116473(REF:T / ALT:A) 181116526(REF:A / ALT:G) 181116549(REF:A / ALT:G)181116569(REF:G / ALT:T) 181116659(REF:C / ALT:T) 181116694(REF:T / ALT:C) 181116801(REF:C / ALT:T) 181116923(REF:T / ALT:G) 181117253(REF:A / ALT:G)181117327(REF:C / ALT:G) 181117354(REF:C / ALT:A) 181117448(REF:G / ALT:A)181117485(REF:G / ALT:T) 181117689(REF:C / ALT:G) 181117692(REF:G / ALT:A)181117769(REF:A / ALT:C) 181118174(REF:C / ALT:T) 181118180(REF:G / ALT:A)181118210(REF:C / ALT:A) 181118218(REF:T / ALT:C) 181118287(REF:C / ALT:T)181118398(REF:T / ALT:C) 181118403(REF:G / ALT:T) 181118418(REF:T / ALT:C) Hap1:TCCGTGGCGCTCGTAAAAGTAGTACACCCGGCATCTCGTTCTGCAGGGAGGTTTTGACCGTGGACGCTCTTT Hap2:TATTCTGCGACCGCTTCGTCTACACGATCGCTGACTCGTCTTCAGGGGAGGTTTTGGCCAGGGACGCTCTTT Hap3:TATTCTGCTCTTGTTTCAGCTATACGATAAGTGATATGCTCTGCAGGGAGGTTTTGAGCGTCGCTGATTCGT Hap4:TATTCTGCGACCGCTTCGTCTACACGATGCTGACTCGTCTTCAGGGGTAAGCTCTACCGGCGACGCTCTGT Hap5:TATTCTGCGACCGCTTCGTCTACACGATGCTGACTCGTCTTCAGGGGAGGTTTTGGCCGGGGACGCTCTTT Hap6:CATTCTGAGCTCGTAAAAGTAGTGAACCCGGCATCTCATTTGCAGAAAAGAGCCCGACAGGCAATGATCCGC Hap7:CATTCTGCGATCGCTTCGTCTACACGATCGCTGACTCGTCTTCAGGGGTAAGCTCTACCGGCGACGCTCTTT Hap8:TATTCTACGCTCACTTCGTCTACACGATCGCTGACTCGTCTTCAGGGGTAAGCTTGGCCAGGGACGCTCTTT Hap9:TATTCTGCGATCGCTTCGTCTACACGATCGCTGACTCGTCTTCAGGGGTAAGCTCTACCGGCGACGCTCTGT Hap10:TATTCTGCGACCGCTTCGTCTACACGATGCTGACTCGTCTTCAGGGGTAAGCTCTACCGTGGACGCTCTGT Hap11:TATTCTGCGACCGCTTCGTCTACACGATGCTGACTCGTCTTCAGGGGTGGTTTTGGCCAGGGACGCTCTTT Hap12:TATTCTGCGACCGCTTCGTCTACACGATGCTGACTCGTCTTCAGGGGTAAGCCCGACAGGCAACACCCGC The expression of candidate gene Zm00001eb032370 in various maize tissues was analyzed. Figure 7 The results showed that the gene was highly expressed in the maize ear primordia, suggesting that it is related to the development of maize ear diameter.

[0045] In summary, the Zm00001eb032370 gene, as a functional marker for maize ear coarseness, can be used to develop allele-specific markers. Molecular markers can directly detect crop genotypes, accurately identify the presence or absence of target genes or traits, avoid the blindness and uncertainty of traditional selection, and ensure the accuracy of offspring selection. It can be applied in breeding for genetic resource identification, MAS (Magnetic Analytic Hierarchy Process), genetic map construction, linkage mapping, and GS-MAS (Graduate-Growth Syndrome-Mass Analysis). MAS can rapidly and accurately identify crop genotypes, avoiding the tediousness, time-consuming nature, and screening difficulties of traditional selection, greatly improving selection efficiency and accelerating the breeding process.

[0046] The above embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit it. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. The application of products that detect SNP molecular marker genotypes in marker-assisted selection breeding of maize ears and thick maize, characterized by: The specific SNP molecular marker sites are based on the Zm-B73-REFERENCE-NAM-5.0 genome as a reference. These sites are located on chromosome 1 of the genome version, starting from the 5′ end: 181114303, 181114391, 181114395, 181114424, 181114426, 181114432, 181114591, 181114593, 181114632, 181114635, 181114652, 181114669, 181114672, 181... 115212, 181115221, 181115371, 181115372, 181115384, 181115433, 181115439, 181115450, 181115458, 181115476, 181115485, 181115535, 181115544, 181115569, 181115586, 181115587, 181115855, 181115857, 181115875, 181115879, 1 81115917, 181115936, 181115945, 181115957, 181115959, 181115961, 181116033, 181116044, 181116070, 181116128, 181116133, 181116175, 181116253, 181116324, 181116469, 181116473, 181116526, 181116549, 181116569, 18111665 The bases at positions 9, 181116694, 181116801, 181116923, 181117253, 181117327, 181117354, 181117448, 181117485, 181117689, 181117692, 181117769, 181118174, 181118180, 181118210, 181118218, 181118287, 181118398, 181118403, and 181118418 appear sequentially. When TATTCTGCGACCGCTTCGTCTACACGATCGCTGACTCGTCTTCA GGGGTAAGCCCGACAGGCAACACCCCGC is used, the maize exhibits the dominant trait of thick ears; the maize in question is the offspring of maize variety Ye107 hybridized with CML312, CML395, YML46, YML32, NK40-1, or YML1218, respectively.

2. The application according to claim 1, characterized in that, The products include kits, reagents, or gene chips.

3. The application according to claim 1, characterized in that, The products include those prepared using high-throughput sequencing, fluorescence in situ hybridization, TaqMan probe method, ARMS-PCR method, or KASP method.

4. A method for screening maize germplasm with thick ears, characterized in that, Take a maize sample to be tested, detect the SNP molecular markers as described in claim 1, and screen for germplasm that meets the molecular marker genotypes of claim 1 and exhibits the dominant trait of thick ears. This germplasm is maize germplasm with thick ears. The maize is the offspring of maize variety Ye107 and CML312, CML395, YML46, YML32, NK40-1 or YML1218 respectively.

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