Molecular markers associated with ear diameter and their application

Abstract

The present application relates to the field of agricultural biotechnology, and specifically discloses a kind of corn ear roughness related molecular marker and its application.The present application provides the application of corn ear roughness molecular marker in ear roughness corn molecular marker assisted breeding, the molecular marker is Zm00001d020000 gene, the nucleotide sequence of the Zm00001d020000 gene is as shown in SEQ ID NO:1, the expression amount of the gene is positively correlated with the corn ear roughness trait, multiple SNP sites related to ear roughness are screened out by GWAS analysis, and simultaneously, QTL point analysis is used to be commonly positioned to SNP_84054216 located on the 7th chromosome, and the marker gene Zm00001d020000 for regulating ear roughness is excavated from the site, and the results of the present application provide technical support for molecular marker breeding of rough ear corn varieties.

Description

Technical Field

[0001] This invention relates to the field of agricultural biotechnology, specifically providing a molecular marker related to maize ear diameter and its application. Background Technology

[0002] Ear diameter is one of the important agronomic traits of maize and a crucial determinant of its yield and quality. Improving ear diameter helps optimize yield by increasing ear number and kernel number, thereby meeting the growing food demand. Therefore, research on maize ear diameter is of great significance. Maize is not only an important food crop worldwide but also a vital source of feed and industrial raw materials. Its high yield and wide adaptability make it a key crop in global agricultural production. However, compared to other food crops, maize ear diameter exhibits certain genetic variability. Therefore, breeders strive to improve ear diameter performance by analyzing the relationship between different maize genotypes and ear diameter. In summary, improving ear diameter is an important goal of maize breeding and biotechnology improvement. Identifying marker genes related to maize ear diameter can provide technical support for molecular marker-assisted selection of high-yielding maize. Summary of the Invention

[0003] To address the aforementioned problems, this invention provides molecular markers for regulating maize ear diameter and their applications. Furthermore, the gene Zm00001d020000 discovered in this invention is a marker gene for regulating ear diameter, and its associated SNPs exhibit high positive additive and dominant effects.

[0004] To achieve the above objectives, the present invention provides the following technical solution:

[0005] This invention provides the application of a molecular marker for ear diameter in marker-assisted breeding of maize with large ear diameter, wherein the molecular marker is... Zm00001d020000 Genes, the ones mentioned Zm00001d020000 The nucleotide sequence of the gene is shown in SEQ ID NO: 1. The expression level of the gene is positively correlated with the corn ear thickness trait.

[0006] Furthermore, this invention provides the application of molecular markers for ear thickness in marker-assisted breeding of maize with thick ears. The molecular markers are combinations of SNP loci, including alleles T at position 38900012 and A at position 158922707 on chromosome 5; allele T at position 84054216 on chromosome 7; and allele C at position 84060078 or T at position 84060181. When one or more of the SNP loci show the corresponding bases, the maize variety is identified as having the dominant ear thickness trait. The genomic version corresponding to the loci is Zm-B73-REFERENCE-NAM-4.0.

[0007] Furthermore, this invention provides the application of maize ear-thickness molecular markers in whole-genome selection breeding of maize with thick ears. The molecular markers are combinations of SNP loci, including locus 158942707 on maize chromosome 5 starting from the 5' end and locus 84054216 on maize chromosome 7 starting from the 5' end. The genomic version corresponding to these loci is Zm-B73-REFERENCE-NAM-4.0.

[0008] Furthermore, the present invention provides the application of a product for detecting molecular markers in the aforementioned application in molecular marker-assisted breeding of maize ears, wherein the product detects the expression level of the molecular markers.

[0009] Furthermore, the present invention provides the application of a product that detects the molecular markers in the aforementioned application in molecular marker-assisted breeding of coarse-ear maize, wherein the product detects the genotype of the molecular markers.

[0010] Furthermore, the application is for screening or assisting in the screening of maize varieties with the dominant trait of ear diameter.

[0011] Furthermore, the product includes reagents or kits.

[0012] Furthermore, the products include those prepared using PCR, qPCR, Sanger sequencing, high-throughput sequencing, fluorescence in situ hybridization, TaqMan probe method, ARMS-PCR method, or KASP method.

[0013] Furthermore, the present invention provides a method for screening maize with the dominant ear diameter trait, characterized in that a maize sample to be tested is taken, and the molecular markers in the application are detected. If the markers match, a maize variety with the dominant ear diameter trait is obtained.

[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.

[0016] The technical effects achieved by this invention are as follows:

[0017] This invention utilizes the temperate maize inbred line Ye107, which has a small ear diameter, as a common parent. It was crossed with four tropical maize inbred lines to construct a multi-parental maize population with significant differences in ear diameter. GWAS and QTL analyses jointly located SNP 7_84054216, significantly associated with ear diameter, on chromosome 7, and SNP 5_158942707 on chromosome 5. Furthermore, functional genes Zm00001d020000 and Zm00001d016356, which regulate ear diameter, were identified. SNP 7_84054216 showed an additive effect of 0.20 and a dominant effect of 0.25. Haplotype analysis of gene Zm00001d020000 revealed HAP-1 (CT) and HAP-2 (CC). Analysis showed that in all study settings, the frequency of HAP-1 was significantly higher than that of HAP-2 in the study population NK40-1. Specifically, the HAP-1 haplotype had a high frequency in the population and was positively correlated with increased ear diameter, while the HAP-2 haplotype had a relatively low frequency and showed a smaller effect. Furthermore, statistical analysis revealed that individuals carrying HAP-1 (CT) had significantly larger average ear diameters than those carrying HAP-2 (CC), suggesting that HAP-1 may have a significant genetic contribution to the improvement of ear diameter. This result supports the role of HAP-1 as a beneficial haplotype, potentially influencing ear diameter development by regulating genes related to cell growth and development.

[0018] This invention, by analyzing and screening tag SNP loci, facilitates further research into the regulatory mechanisms of maize ear diameter. In GS or MAS breeding processes, it reduces redundant detection costs while preserving the integrity of genetic information, aiming to provide innovative genetic resources and precise improvement strategies for significantly increasing maize yield per plant, thereby promoting the optimization and efficiency of maize production. Specifically, this invention also conducted genome-wide selection on the research population to further corroborate the reliability of the discovered loci and screened for potentially superior breeding materials with thicker ears using Genetic Potential Prediction (GEBV). Attached Figure Description

[0019] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the accompanying drawings used in the embodiments will be briefly described below.

[0020] Figure 1. A pedigree of a NAM population with significant differences in ear diameter was constructed by crossing four coarse-eared parents with parent Ye107.

[0021] Figure 2. Phenotypic variation and correlation analysis of spikelet diameter for four populations under three environments. (a) Distribution of spikelet diameter phenotype for the four populations (population 1, population 2, population 3, and population 4) under three environments (Dehong, Baoshan, and Yanshan). Each box plot represents spikelet diameter data for a specific population under a given environment. The midline of the box represents the median, while the upper and lower edges of the box correspond to the third and first quartiles, respectively. Outliers exceeding the normal distribution range are displayed as individual points. (b) Pearson correlation coefficients of spikelet diameter phenotype for the four populations (population 1, population 2, population 3, and population 4) under three environments (Dehong, Baoshan, and Yanshan). Each subplot corresponds to one population, and the matrix within the subplot shows the correlation between different environments.

[0022] Figure 3. Heatmap of marker density for 10 maize chromosomes;

[0023] Figure 4. Evolutionary tree of the four populations;

[0024] Figure 5. Principal component analysis of the four groups;

[0025] Figure 6. LD decay of the four populations;

[0026] Figure 7. Manhattan plot (left) and QQ plot (right) of maize ear diameter significant SNPs analyzed by GWAS under different environments, (a) BLUP, (b) Baoshan environment, (c) Dehong environment, (d) Yanshan environment, showing SNPs related to ear diameter;

[0027] Figure 8. Significant QTLs associated with spikelet diameter (4 QTLs co-localize with SNP7_84054216 identified by GWAS).

[0028] Figure 9 Significant QTLs associated with spikelet diameter were identified (one QTL co-localized with SNP5_158942707 identified by GWAS).

[0029] Figure 10 The relative positions of SNPs and gene Zm00001d020000;

[0030] Figure 11 The haplotype of gene Zm00001d020000;

[0031] Figure 12 (a) Location of gene Zm00001d020000 in four environments; (b) Distribution of the two haplotypes in NK40-1; (c) Differences in the expression of the two haplotypes in different environments;

[0032] Figure 13 Changes in amino acid sequence;

[0033] Figure 14 Expression of gene Zm00001d020000 in different populations and tissues;

[0034] Figure 15 Based on the comprehensive GEBV assessment results, (a) Dehong environment, (b) Baoshan environment, and (c) Yanshan environment, Venn diagrams were plotted using the common breeding sample results of the 13 models. The number of intersections represents the number of samples jointly selected by the 13 models. (d) Materials selected in all three environments.

[0035] Figure 16 (a) Genes associated with two SNPs in the same region on chromosome 7, (b) Genes associated with two SNPs in the same region on chromosome 5. Detailed Implementation

[0036] To further illustrate the present invention, the present invention will be described in detail below with reference to the accompanying drawings and embodiments, but these should not be construed as limiting the scope of protection of the present invention.

[0037] This invention provides a method for regulating the diameter of maize ears. Zm00001d020000 Gene, Zm00001d020000 The nucleotide sequence of the gene is shown in SEQ ID NO.1, corresponding to bases 84056033-84060419 on chromosome 7 of maize in genome version Zm-B73-REFERENCE-NAM-4.0.

[0038] In this invention, ear diameter (ED) is a common abbreviation for corn ear diameter, which represents the cross-sectional diameter of the corn ear.

[0039] The molecular marker sites and base information provided by this invention are shown in Table 1 below. The corresponding genome versions are Zm-B73-REFERENCE-NAM-4.0, calculated from the 5' end of chromosomes 5 and 7, respectively.

[0040] Table 1. Location of molecular marker sites and base composition

[0041] Example 1

[0042] 1.1 Plant materials

[0043] Four tropical maize inbred lines, CML444, YML46, YML32, and NK40-1, were selected as female parents in the experiment. These four female parents were crossed with the superior temperate maize inbred line Ye107 (male parent) to obtain the first generation (F1). The F1 generation (FI) was continuously self-pollinated generation by generation until the F7 generation, finally constructing four multi-parent populations. Figure 1The populations, namely Group 1 (CML444 × Ye107), Group 2 (YML46 × Ye107), Group 3 (YML32 × Ye107), and Group 4 (NK40 - 1 × Ye107), experienced inbreeding depression and other environmental stresses during the self-pollination process. Some inbred lines failed to survive, resulting in a NAM (Nested Association Mapping) population containing 858 F7 RILs used to locate genes affecting ear diameter (ED). Parental information is detailed in Table 2.

[0044] Table 2 Parental Information

[0045]

[0046] 1.2 Experimental Design

[0047] Four recombinant inbred lines (RILs) were constructed: population 1 (CML444 × Ye107), population 2 (YML46 × Ye107), population 3 (YML32 × Ye107), and population 4 (NK40 - 1 × Ye107). These lines were planted in Baoshan City, Yanshan County, and Dehong Prefecture, Yunnan Province. A Latin square design was used, with rows 4m long, 14 plants per row, and a plant spacing of 25cm. Three replicates were employed, and standard field management was implemented. Sampling was conducted near maturity (generally the milk or waxy stage) during the maize growing season, when ear diameter had stabilized. Approximately 10 ears per row were measured to ensure sample representativeness, and the measurement process avoided damaging the kernels. The maize ears were laid flat on a level work surface, and ear diameter was measured using vernier calipers from the base to the tip, recorded to the nearest millimeter (mm).

[0048] 1.3 Heritability Analysis

[0049] After preliminary processing of the phenotypic data collected at three time locations, statistical analysis was performed on the phenotypic data using Excel-2021 and IBM SPSS Statistics 20. The mean, minimum, maximum, standard deviation (SD), coefficient of variation (CV), skewness, and kurtosis were calculated. Kurtosis and skewness were used to assess the normality of the frequency distribution and to calculate the generalized heritability of ED.

[0050] 1.4. DNA Extraction and Genome Sequencing

[0051] During the reproductive period, genomic DNA was extracted from leaves of RILs in the NAM population using the cetyltrimethylammonium bromide (CTAB) method. The genomic DNA was then digested with PstI and MspI restriction endonucleases. Next, barcode-bearing adapters were ligated to the digested DNA fragments using T4 DNA ligase. All samples were purified using a QIAquick PCR purification kit (QIAGEN, Valencia, CA, USA). Subsequently, polymerase chain reaction (PCR) was used to amplify primers complementary to the adapters, and the PCR products were purified and quantified using the Qubit dsDNA HS Assay Kit (Life Technologies, GrandIsland, NY, USA). PCR products of 200–300 bp were screened for library construction, and fragment selection was performed using the Egel system (Life Technologies). The concentration of each library was then determined using a Qubit 2.0 fluorometer and the Qubit dsDNA HS Assay Kit (Life Technologies). Template preparation and library sequencing were performed using the Ion PI HiQ Chef Kit (Thermo Fisher, USA). Sequencing was conducted using a P1v3 chip on an Ion Proton sequencer (Life Technologies, software version 5.10.1). The Ion Proton system generated variable-length sequencing reads. After sequencing, the raw data underwent quality control, removing adapter sequences and low-quality reads (sequences with a base quality value Q≤5 exceeding 50%). Sequencing data from four RIL subgroups were cleaned, and the obtained high-quality sequences were analyzed using TASSELv5.0 software. The reference genome for alignment was the maize B73_V4 genome (full name Zm-B73-REFERENCE-NAM-4.0), and sequence alignment was performed using BWA software with the alignment parameters set as: mem -t 4 -k 32 -M -R. The alignment results were converted to SAM / BAM files using SAMtools, and SNP detection was performed using Genome Analysis Toolkit (GATK) software. SNP filtering was performed using PLINK v1.9 software with parameters -geno 0.2 and -maf 0.05, removing sites with a deletion rate exceeding 10% and a minimum allele frequency (MAF) below 5%. SNP annotation was performed using ANNOVAR software.

[0052] 1.5 Phylogenetic Tree, Population Structure, and Linkage Disequilibrium Analysis

[0053] Genetic differentiation among populations was analyzed by constructing phylogenetic trees. The genetic distance matrix among 858 RILs in the NAM population was calculated using TreeBeST software (version: Treebest-1.9.2) based on a filtered SNP dataset. Subsequently, a phylogenetic tree was constructed using the neighbor-joining method, and support values ​​were obtained through 1000 bootstrap iterations. Population structure inference was performed using Admixture software with default parameters. Admixture inferred the ancestral composition of individuals using maximum likelihood estimation based on the SNP genotyping dataset. The optimal number of clusters was determined by the cross-validation error rate (CV error), where the K value corresponds to the minimum CV error, representing the optimal number of clusters. The linkage disequilibrium (LD) degree (r²) between paired markers was calculated using PopLDdecay software (v3.40). LD decay curves were plotted using the built-in script Plot_OnePop.pl. LD decay describes the process of linkage disequilibrium decreasing over time or generations. The r² value ranges from 0 to 1, with a value closer to 1 indicating a higher degree of linkage disequilibrium between the two sites. LD decay analysis helps determine the minimum number of markers required for GWAS and to evaluate the detection efficiency and accuracy of GWAS.

[0054] 1.6 GWAS and QTL

[0055] Genome-wide association study (GWAS) of ED was conducted using a mixed linear model (MLM) implemented in EMMAX. During GWAS analysis, individual kinship and population stratification are major factors leading to false positives. The MLM model considers population structure and individual kinship, reducing false positives during GWAS. This study used an MLM model for marker-trait association, with population structure as a fixed effect and individual kinship as a random effect to mitigate the influence of these factors. The mixed linear model analysis was performed using the following formula:

[0056]

[0057] y represents the phenotypic trait, X represents the indicator matrix of the fixed effects, α represents the estimated parameters of the fixed effects, Z represents the indicator matrix of the SNP, β represents the effect of the SNP, W represents the indicator matrix of the random effects, μ represents the predicted random individuals, and e represents the random residuals, which follow the pattern e ~ (0, δe 2).

[0058] Both the QQ plot and the Manhattan plot were generated using R software (v4.3.3). Independent labels were calculated using PLINK (parameters: -indep-pair-wise 50 5 0.2). A significance threshold of -log10(P) > 4.5, calculated using the formula −log10(1 / total number of SNPs) and adjusted for Bonferroni, was used to identify significant SNPs.

[0059] Linkage analysis was performed to determine whether significant SNPs identified by GWAS overlapped and lay within QTL intervals identified by QTL mapping. Linkage analysis was performed on four populations, totaling 858 RILs. Genetic linkage maps for the four populations were constructed using JoinMap v4. QTLs associated with ED were identified using Composite Interval Mapping (CIM) with Windows QTL Cartographer v2.0. The LOD threshold was set based on a 1000-permutation test with a significance level of P ≤ 0.05. QTLs with an LOD threshold ≥ 2.5 were considered significant. The partial correlation coefficient (r) was used to determine the significance level of the RILs. 2 The square is used to calculate the percentage of phenotypic variance explained (PVE) for a single QTL.

[0060] 1.7 Identification and Functional Annotation of Candidate Genes

[0061] Candidate genes associated with spikelet diameter (ED) were identified and annotated using the B73_V4 reference genome. Candidate genes identified by QTL and GWAS were compared with previous studies in public databases such as NCBI, Maize GDB, InterPro, and UniProt.

[0062] 1.8 Haplotype Analysis

[0063] Upstream and downstream 20 kb regions of important loci were screened to identify candidate genes. Haploview v4.2 software was used to analyze important SNPs / candidate genes to identify dominant haplotypes. Subsequently, haplotypes were classified according to their corresponding phenotypes, and box plots were generated.

[0064] 1.9 Genome-wide selection

[0065] The implementation of genomic selection requires, first, the construction of a reference cohort to establish a genomic prediction equation. Individuals in the reference cohort possess both phenotypes and marker genotypes, and the genetic effects of the markers on traits are estimated using a mathematical model. Secondly, a candidate cohort is needed, where individuals only provide marker genotypes. The genomic estimated breeding value (GEBV) for each individual in the candidate cohort is obtained by summing the marker effects. Then, superior individuals are selected for breeding based on the GEBV. The models used in this study for estimating breeding values ​​include gBLUP, rrBLUP, Bayes A (BA), Bayes B (BB), Bayes C (BC), Bayesian Lasso (BL), Bayes Ridge Regression (BRR), RKHS (Reproducing Kernel Hilbert Space), Random Forest, Lasso Regression, Ridge Regression, SVR, and LightGBM.

[0066] 2. Results

[0067] 2.1 Phenotypic Analysis of Ear Thickness

[0068] After collecting and statistically analyzing the spike diameter ED phenotypic data of four multiparental populations under three different environments, the results are shown in Table 3. Figure 2 In the three environments, the absolute values ​​of skewness and kurtosis of ED in different populations were all less than 1, showing a normal distribution, consistent with the genetic characteristics of quantitative traits. We had four populations (population 1, population 2, population 3, and population 4). To compare whether there were significant differences in ear diameter among different populations in different locations, we used ANOVA (analysis of variance). The results showed that there were significant differences in ear diameter among different populations in the three environments of Dehong, Baoshan, and Yanshan (p < 0.00001). We used correlation analysis to explore the relationship between ear diameter phenotypes of the same population in different environments. We calculated the Pearson correlation coefficients between different environments (Dehong, Baoshan, and Yanshan) to assess their linear relationship. The results showed that r was greater than 0.7 for all four populations in different environments, which means that the ear diameter phenotypes of the same population measured in different environments are consistent and show a positive correlation.

[0069] Table 3. Phenotypic statistical analysis of spikelet diameter

[0070]

[0071] Note: Dehong, Baoshan, and Yanshan represent the experiments conducted in Dehong in 2018, Baoshan in 2019, and Yanshan in 2021, respectively.

[0072] 2.2 Population structure, principal component analysis (PCA), and linkage disequilibrium analysis

[0073] Phylogenetic tree and principal component analysis (PCA) showed that the 858 RILs were divided into four populations, consistent with the experimental design. The mixing observed in these four populations may be due to gene introgression or hybridization during the breeding process. Figure 4 , Figure 5 ); Figure 3 A heatmap showing the marker density of the 10 maize chromosomes is displayed. The number of SNPs on chromosomes 1 through 10 are 81417, 66909, 66084, 75031, 57271, 47553, 52316, 49743, 44543, and 43284, respectively; the original SNP dataset for each multiparent population was used for linkage disequilibrium (LD) decay analysis. Figure 6 We calculated the LD decay for the four populations and found that at r 2 The value plateaued at a physical distance of 20 kb from the threshold, with a value of 0.2. Therefore, we subsequently screened genes 20 kb upstream and downstream of the significantly relevant SNPs.

[0074] 2.3 Genome-wide association analysis of spikelet diameter

[0075] In this study, the ED phenotypic data of the multiparental population in all three environments followed a normal distribution, making them suitable for GWAS analysis. We used a mixed linear model (MLM) to perform GWAS on ED in different environments, setting the threshold to −log10p > 4.5. Figure 7 Fifteen SNPs with high heterogeneity across multiple environments were identified. In particular, the PVE (Phenotypic Variation Explained) of SNP5-38900012 (Ref / Alt=C / T) on chromosome 5 was found to be greater than 10%.

[0076] 2.4 QTL mapping of the ear population

[0077] To identify QTLs associated with end-stage renal disease (ED), QTL mapping was performed on four multiparental populations (population 1, population 2, population 3, and population 4) in three different environments. Best linear unbiased prediction (BLUP) was also performed on ED in all environments, filtering out SNP markers with a deletion rate greater than 10% and sites with a minimum allele frequency less than 5%. The LOD threshold was set to ≥2.5. The results are shown below:

[0078] A total of 14 significant QTLs were detected in populations 1, 3, and 4 across three environments and BLUP (Table 4). These QTLs with a LOD ≥ 2.5 were considered significantly associated with ear diameter (ED). These 14 QTLs were distributed on chromosomes 1, 2, 3, 4, 5, and 7. Among these QTLs, qED7-3 had the highest LOD of 4.3, originating from the Dehong environment of population 4. This QTL explained up to 10.8% of the phenotypic effect, with an additive effect of 18.6%, which was positive. In addition, qED7-2 had a phenotypic explanation of 10.1% and an additive effect of 17.2%. Given the high phenotypic explanation and additive effect of these two QTLs, we believe that these two QTLs may affect ear diameter.

[0079] Table 4 Significant QTLs related to spikelet diameter

[0080]

[0081] 2.5 Joint Analysis of GWAS and QTL

[0082] The combined analysis of QTL and GWAS results, used to obtain more accurate genetic loci and candidate genes, showed that the SNP 7-84054216 on chromosome 7 identified by GWAS was located within the intervals qED7-1, qED7-2, qED7-3, and qED7-4 in population 4 (NK40-1 population) (Table 5). Figure 8 They co-localize; in addition, the SNP 5-158942707 on chromosome 5 identified by GWAS is located within the qED5-1 interval of population 1 (CML444 population) (Table 5, Figure 9 Co-location also exists. Notably, SNP7-84054216 exhibits a high positive additive and dominant effect, meaning that individuals carrying this SNP or QTL will perform better in the trait. Based on linkage disequilibrium (LD) decay analysis, candidate genes within 20 kb upstream and downstream of tSNPs were screened. Comparing genes identified by GWAS with those obtained from QTL mapping, we found that gene Zm00001d020000 was consistently identified, therefore we believe this gene is associated with ear diameter.

[0083] Table 5. Candidate genes identified by combined GWAS and QTL mapping analysis

[0084]

[0085] 2.6 genes Zm00001d020000

[0086] We first determine the location of gene Zm00001d020000 in order to perform haplotype analysis. Figure 10 The study identified BLUP and two haplotypes significantly associated with maize ear diameter in three environments: HAP-1 (CT) and HAP-2 (CC). These haplotypes are located at loci 84060078 and 84060181 on maize chromosome 7, starting from the 5' end. Figure 11 Taking the NK40-1 population as an example, analysis showed that the frequency of HAP-1 in the NK40-1 population was significantly higher than that of HAP-2 in all study environments. Specifically, the higher distribution frequency of the HAP-1 haplotype in the population increased the ear diameter, indicating a positive correlation between the distribution frequency of the HAP-1 haplotype and ear diameter. Furthermore, statistical analysis revealed that individuals carrying HAP-1 (CT) had a significantly larger average ear diameter than those carrying HAP-2 (CC), suggesting that HAP-1 may have a significant genetic contribution to the improvement of ear diameter. This result supports the role of HAP-1 as a favorable haplotype, potentially influencing ear diameter development by regulating genes related to cell growth and development. Figure 12 ).

[0087] Statistical analysis showed that, among the four populations, individuals with SNP sites marked in Table 1, namely SNP5_38900012, SNP5_158942707, SNP7_84054216, SNP7_84060078, and SNP7_84060181, when their bases were T, A, T, C, and T respectively, had significantly higher average ear diameters than individuals with other base types.

[0088] From the phenotypic data, we found significant differences in ear diameter among different families in population 1 (NK40-1). To investigate whether a mutation occurred in the gene Zm00001d020000 in NK40-1, further research revealed a non-synonymous variant in the nucleotide sequence of the conserved domain of Zm00001d020000 (base 64 of the Zm00001d020000 gene changed from T to A). This variant altered the amino acid sequence at position 19 (from valine to aspartic acid), leading to a change in motif (…). Figure 13 Therefore, it is speculated that the function of the gene Zm00001d020000 in NK40-1 is altered by an SNP mutation, subsequently affecting spike diameter. To further verify whether the gene Zm00001d020000 is expressed in spike development, we analyzed the expression profiles of Zm00001d020000 in multiple tissues across four populations. Figure 14The results showed that the expression level of this gene reached a relatively high level after standardization in population 4 (the population where the gene was co-located). In particular, the average ear diameter of individuals with higher gene expression levels was significantly higher than that of individuals with lower expression levels. In addition, we found that the expression of Zm00001d020000 was also relatively high in the ear tissues of other populations, which further corroborates the finding that this gene affects the ear diameter of maize.

[0089] 2.7 Genome-wide selection

[0090] To further explore the genetic mechanisms behind ear diameter and improve the efficiency of genetic improvement, we integrated whole-genome data using the GS method, explored the genotype-phenotype relationship related to ear diameter in multi-parent populations, and screened potential superior breeding materials using genetic potential prediction (GEBV). While estimating GEBV, the effect values ​​of SNP loci were also estimated. Based on the GEBV ranking, the top 20% with the highest GEBV were selected as breeding samples. From this 20%, 13 models were further selected to jointly screen individuals, yielding the comprehensive GEBV evaluation results (Figure 15). In the Dehong environment, the highest number of individuals screened was 163, indicating high stability of GEBV prediction in this environment. In contrast, the GEBV prediction results in the Yanshan environment were more dispersed, with only 71 individuals showing common characteristics, indicating a significant influence of the environment on GEBV prediction. Furthermore, we found that 45 individuals were selected in the Baoshan, Dehong, and Yanshan environments, representing the most robust candidate breeding materials. These individuals showed consistent GEBV rankings across different environments, indicating strong genetic potential and broad adaptability. Furthermore, their large spike diameter and SNP effect values ​​make them suitable as a core breeding population. While estimating the effect values ​​of SNP loci, we ranked all SNP effect values ​​and found that SNP7-84054329 on chromosome 7 ranked highly (top 5%) among all SNPs. This finding is associated with the previously co-located SNP7-84054216, both belonging to the same region (chromosome 7, 84034216-84074221). The candidate gene Zm00001d020000 associated with this region is considered to influence spike diameter. Figure 16 (a). Additionally, SNP5_158942627 on chromosome 5 was also detected in GS, while SNP5_158942707, located 80 bp away, was previously co-identified. The candidate gene Zm00001d016356 associated with this region is also considered to affect spike diameter. Figure 16 (b)).

[0091] Although the above embodiments have provided a detailed description of the present invention, they are only some embodiments of the present invention, and not all embodiments. People can obtain other embodiments based on these embodiments without creative effort, and these embodiments all fall within the protection scope of the present invention.

Claims

1. The application of products containing molecular markers for maize ear diameter in marker-assisted breeding of maize with thicker ears, characterized in that, The molecular marker is a combination of SNP sites, including alleles C at position 84060078 and T at position 84060181 on chromosome 7. When the SNP site shows the corresponding base, it is identified as a maize variety with the dominant ear diameter trait. The genome version corresponding to the site is Zm-B73-REFERENCE-NAM-4.

0. The maize is a tropical maize inbred line CML444, YML46, YML32 or NK40-1, or the maize is the offspring of a cross between a tropical maize inbred line CML444, YML46, YML32 or NK40-1 and a maize inbred line Ye107.

2. The application according to claim 1, characterized in that, The product detects the genotype of the molecular marker.

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

4. The application according to claim 2, 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.

5. A method for screening maize with the dominant trait of ear diameter, characterized in that, Take a maize sample to be tested and detect the molecular markers in the application described in claim 1. If the markers are matched, obtain a maize variety with the dominant ear diameter trait. The maize is a tropical maize inbred line CML444, YML46, YML32 or NK40-1, or the maize is a hybrid offspring of a tropical maize inbred line CML444, YML46, YML32 or NK40-1 and a maize inbred line Ye107, respectively.

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