Molecular marker Zm00001eb181850 gene related to corn leukoderma resistance and application of molecular marker Zm00001eb181850 gene

Abstract

The invention belongs to the technical field of molecular genetic breeding, and particularly relates to a molecular marker Zm00001eb181850 gene related to corn leukoderma resistance and application thereof, the invention provides a molecular marker related to the corn leukoderma resistance, the gene sequence of the molecular marker is shown as SEQ ID NO: 1 and / or SEQ ID NO: 2, and the molecular marker Zm00001eb181850 gene is shown as SEQ ID NO: 1 and / or SEQ ID NO: 2. Researches prove that corn white spot resistance QTL qMWS4-1 and qMWS4-5 intervals and resistance SNP: 4-118983592 have co-localization, the corn white spot resistance QTL has a high phenotypic interpretation rate, the associated gene Zm00001eb181850 (SEQ ID NO: 2) is highly expressed in corn leaves, it is proved that the associated gene Zm00001eb181850 (SEQ ID NO: 2) is associated with the corn leaf spot, the corn white spot resistance is a quantitative character jointly regulated by multiple genes, and the corn leaf spot resistance QTL has a good application prospect. According to the technical scheme provided by the invention, a new method is provided for cultivating a new variety of leukoderma-resistant corn by utilizing a modern molecular breeding technology.

Description

Technical Field

[0001] The invention belongs to the technical field of molecular genetic breeding, and specifically relates to a SNP: 4-118983592 site located on corn chromosome 4 and related to corn white spot resistance, and application of a site-associated functional gene Zm00001eb181850. Background Art

[0002] Corn (Zea mays L.), as one of the important food crops, directly affects the development of animal husbandry. In recent years, corn white spot disease caused by Pantoea ananatis is a leaf disease that seriously affects corn production. In the early stage of corn white spot disease, lesions appear on the base leaves, and then quickly spread to the upper part of the plant. In the later stage of the disease, a chlorotic appearance appears, which affects the plant carbon cycle and photosynthesis. If some leaves are infected before the corn filling stage, the net photosynthetic rate can drop by 40%, which in turn leads to the premature end of the reproductive maturity stage, and ultimately leads to corn ear deformity and low seed yield, which seriously reduces the yield and quality of corn.

[0003] At present, the prevention and control of white spot disease mainly focuses on measures such as optimizing field farming systems and the use of agricultural chemicals. Studies in recent years have shown that white spot disease resistance depends largely on its genetic factors. Therefore, genetically cultivating white spot disease-resistant varieties is the most economical and effective way to control the disease. However, since white spot disease is a newly erupted corn disease in my country, the functional genes related to white spot disease resistance have not yet been cloned. Based on whole genome association analysis and QTL positioning, the present invention uses tropical corn inbred lines (YML32, TRL418, CML171, TML139, YML226, NK40-1) as resistant parents, hybridizes with temperate susceptible excellent inbred line Ye107, and selects 6 F9 recombinant inbred lines (RIL) after 9 consecutive generations of single-grain transmission self-pollination. These RILs were planted in Yanshan County, Yunnan Province for three consecutive years to carry out phenotypic identification. Combined with the high-quality SNPs of the RIL population, the functional genes significantly related to corn white spot disease resistance were identified through GWAS analysis and linkage analysis. Summary of the invention

[0004] The main purpose of the present invention is to provide corn white spot resistance-related QTL qMWS4-1 and qMWS4-5 sites located on chromosome 8 of corn, SNP: 4-118983592 site on chromosome 4, and site-associated gene Zm00001eb181850 to assist in improving corn white spot resistance, thereby avoiding complicated and time-consuming resistance screening process, shortening breeding years, and improving the efficiency of molecular genetic breeding of corn white spot resistance.

[0005] The present invention specifically provides the following technical solutions:

[0006] In one aspect, the present invention provides molecular markers associated with corn white spot resistance, wherein the molecular marker gene sequence is shown in SEQ ID NO:1 and / or SEQ ID NO:2.

[0007] Furthermore, the molecular marker, such as the sequence shown in SEQ ID NO:1, presents T / C polymorphism at the 201st base from the 5′ end; the sequence shown in SEQ ID NO:2 corresponds to the corn Chr4:119014763-119023372 sequence, and presents G / T polymorphism at the 119022188th base from the 5′ end, and / or the expression level of the gene or its translated protein shown in SEQ ID NO:2 is positively correlated with corn white spot resistance.

[0008] In another aspect, the present invention provides a molecular marker associated with corn white spot resistance, wherein the molecular marker is a SNP site, including 119015573, 119015605, 119015666, 119015689, 119015754, 119015775, 119016626, 119018991, 119019227, 119019236, 119019440, 119019442, 119019443, 119019444, 119019445, 119019446, 119019447, 119019448, 119019449, 119019440, 119019441, 119019443, 119019444, 119019447, 119019448, 119019449 ...0, 119019441, 119019442, 119019443, 119019443, 119019443, 119019443, 119019443, 119019443, 119019443, 119019443, 11901944 At least one of the SNP sites 9019567, 119019601, 119019635, 119019878, 119020288, 119020495, 119020805, 119021016, 119021024, 119021932, 119022096, 119022608, and 119022763, and the reference genome version where the SNP site is located is Zm-B73-REFERENCE-NAM-5.0.

[0009] Furthermore, the present invention provides any of the following applications of any of the molecular markers:

[0010] a) Genetic diversity analysis of maize resistant to white spot disease; b) Construction of molecular genetic map of maize resistant to white spot disease; c) Whole genome association analysis of maize resistant to white spot disease; d) Identification of maize varieties resistant to white spot disease; e) Molecular marker-assisted selection breeding of maize resistant to white spot disease; f) Whole genome selection breeding of maize resistant to white spot disease.

[0011] Furthermore, the present invention provides a product for detecting any of the molecular markers, the product comprising a reagent, a kit or a gene chip, the product detecting the genotype of the molecular marker, or detecting the expression level of the sequence shown in SEQ ID NO: 2 or its translated protein.

[0012] Furthermore, the present invention provides products for detecting any of the molecular markers, including products prepared by PCR, qPCR, Sanger sequencing, high-throughput sequencing, fluorescence in situ hybridization, TaqMan probe method, ARMS-PCR method or KASP method, and the product detects the genotype of the molecular marker, or detects the expression level of the sequence shown in SEQ ID NO: 2 or its translated protein.

[0013] Furthermore, the present invention provides any of the following applications of the product:

[0014] a) Genetic diversity analysis of white spot disease resistant maize; b) Construction of molecular genetic map of white spot disease resistant maize; c) Whole genome association analysis of white spot disease resistant maize; d) Identification or auxiliary identification of white spot disease resistant maize varieties; e) Molecular marker-assisted selection breeding of white spot disease resistant maize; f) Whole genome selection breeding of white spot disease resistant maize.

[0015] On the other hand, the present invention provides a method for screening corn with resistance to white spot disease. A corn sample to be tested is taken, and the gene sequence shown in SEQ ID NO:1 is detected. When the base at the 201st position from the 5′ end of the sequence shown in SEQ ID NO:1 is C, a corn variety with resistance to white spot disease is obtained.

[0016] On the other hand, the present invention provides a method for screening corn with resistance to white spot disease. A corn sample to be tested is taken, and the expression level or genotype of the gene sequence shown in SEQ ID NO:2 is detected. When the sequence shown in SEQ ID NO:2 or its translated protein is overexpressed and / or the base at position 119022188 from the 5′ end presents T, it is judged as a corn variety with resistance to white spot disease.

[0017] On the other hand, the present invention provides a method for screening corn with resistance to white spot disease. A corn sample to be tested is taken, and the genotype of the molecular marker is detected. When the SNP sites of the molecular marker are presented in sequence as: CTCGCGGTGCTTAACCATGTGCCAA, it is judged to be a corn variety with resistance to white spot disease.

[0018] The technical effects achieved by the present invention are:

[0019] Through multi-point experiments over many years, the present invention co-localizes the white spot disease resistance QTL qMWS4-1 and qMWS4-5 intervals and the resistance SNP: 4-118983592 and its associated gene Zm00001eb181850 on chromosome 8 of maize. The site can be located in different environments through QTL linkage analysis and GWAS association analysis. The white spot disease resistance QTL qMWS4-1 and qMWS4-5 overlap, which can explain 15.05% of the phenotypic variation; the QTL interval contains the consistent resistance site SNP: 4-118983592 (i.e., the 201bp site from the 5′ end of the sequence shown in SEQ ID NO: 1). The SNP: 4-118983592 site can explain 8.84% of the resistance phenotypic variation. Its associated candidate functional gene Zm00001eb181850 (SEQ ID NO: 2) mainly encodes a leucine-rich repeat sequence (LRR), which plays an important regulatory role in plant stress response, plant growth and development, and signal transduction. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] Figure 1 Leaf images of corn with different grades of white spot disease; HR: highly resistant to white spot disease, R: resistant to white spot disease, M: moderately resistant to white spot disease, S: sensitive to white spot disease, HS: highly susceptible to white spot disease.

[0021] Figure 2 Correlation heat map of white spot disease resistance in six populations; describes the correlation of the overall performance of RILs in six populations under different environments. The narrower the circle and the redder the color, the stronger the correlation.

[0022] Figure 3 Figure 2 shows the SNP density and LD decay diagrams; (a) Chromosome-specific SNP density within 1Mb intervals, the ordinate represents the chromosome, the abscissa represents the position on each chromosome, and the redder the corresponding position, the more variant sites there are. (b) The change of genome-wide LD decay (r2) of all chromosomes in 941 maize RILs with physical distance (Kb).

[0023] Figure 4 Co-localization map of white spot disease resistance QTL qMWS4-1 and qMWS4-5 and resistance locus SNP: 4-118983592;

[0024] Figure 5 The seven haplotypes of the candidate gene Zm00001eb181850 for white spot disease resistance are shown;

[0025] Figure 6Analysis of the candidate gene Zm00001eb181850 for white spot disease resistance; (a) Overall differences in the resistance levels of 7 haplotypes to maize white spot disease, * indicates p<0.05, **** indicates p<0.0001; (b) The relative positions of Zm00001eb181850 and SNP:4-118983592, and the base variation and amino acid variation in the parents TRL418 and TML139; (c) The expression level of the Zm00001eb181850 gene in different tissues of maize, the red box indicates the expression of the Zm00001eb181850 gene in leaves. DETAILED DESCRIPTION

[0026] In order to make the purpose, technical solutions and advantages of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below in combination with the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0027] The invention is based on genome-wide association analysis and QTL positioning, uses tropical white spot disease resistant corn inbred lines (YML32, TRL418, CML171, TML139, YML226, NK40-1) as resistant parents, hybridizes with temperate susceptible excellent inbred line Ye107, and selects 6 F9 recombinant inbred lines (RILs) through 9 consecutive generations of single seed self-pollination. These RILs are planted in Yanshan County, Yunnan Province for three consecutive years to carry out phenotypic identification, and combined with the high-quality SNP: 4-118983592 of the RIL population (i.e., the 201 bp site from the 5′ end of the sequence shown in SEQ ID NO: 1), the functional gene Zm00001eb181850 (SEQ ID NO: 2) significantly related to corn white spot disease resistance is identified through GWAS analysis and linkage analysis, and the resistance gene can be subsequently applied to corn white spot disease resistance breeding by molecular breeding.

[0028] Example 1

[0029] 1. Experimental Materials and Design

[0030] In this experiment, six tropical maize inbred lines (YML32, TRL418, CML171, TML139, YML226, and NK40-1) with wide genetic variation and resistance to white spot disease were selected as female parents, and Ye107, an excellent temperate maize inbred line susceptible to white spot disease, was used as a common parent for hybridization (the pedigree, heterotic groups, ecological groups, and related resistance levels of the seven parents are detailed in Table 1). Through the single-seed transmission method, nine consecutive generations of self-pollination were performed to produce six recombinant inbred line (RIL) populations: pop1 (YML32×Ye107), pop2 (TRL418× The RIL lines were selected from the following 100 RIL lines: Ye107, pop3 (CML171×Ye107), pop4 (TML139×Ye107), pop5 (YML226×Ye107), and pop6 (NK40-1×Ye107). Initially, each population contained 200 RIL lines, but due to environmental selection, inbreeding depression, and other factors, 904 RIL lines were finally available for this study (pop1: 145; pop2: 141; pop3: 147; pop4: 160; pop5: 152; pop6: 159). These RIL lines were planted in Yanshan County, Yunnan Province (23°19'-23°59'N, 103°35'-104°45'E) in 2021, 2022, and 2023. The experimental design adopted a completely randomized block design, with 14 plants per row, a row length of 4 m, and a plant spacing of 25 cm. Standard farmland management was followed.

[0031] Table 1. Pedigrees, ecotypes and white spot resistance of the seven parents used in the experiment

[0032]

[0033] 2. Disease grade score

[0034] Phenotypic identification of white spot disease was conducted on RILs from a multi-parent population in Yanshan County (YS), Yunnan Province, China in 2021, 2022, and 2023. Maize white spot disease outbreaks occur from early August to late September each year, when maize is in the grain filling to maturity stage, which is suitable for resistance assessment. The disease severity grading of white spot disease follows the symptom recognition criteria outlined in the Maize Pest and Disease Manual, and the average disease severity of a single plot is evaluated on a scale of 1 to 9, such as Figure 1 , as shown in Table 2.

[0035] Table 2. Classification standards for corn white spot disease

[0036]

[0037]

[0038] 3. Phenotypic Identification and Statistical Analysis

[0039] Descriptive analyses of phenotypic data were performed using SPSS (SPSS Statistics) and ORIGIN (Origin 2022) software. Mean, minimum, maximum, standard deviation (SD), coefficient of variation (CV), skewness, and kurtosis were calculated. Frequency distribution of phenotypic data was performed using SPSS software. Kurtosis and skewness were used to assess the normality of the frequency distribution. Broad-sense heritability was calculated following the method outlined by Knapp et al.

[0040] 4. Whole-genome resequencing

[0041] DNA was extracted from maize seedling leaves using a modified CTAB method and subjected to whole-genome resequencing. DNA libraries were prepared according to standard procedures and sequenced using Illumina Hi Seq TM The filtered reads were then aligned to the maize reference genome B73_RefGen_v5 (full name: Zm-B73-REFERENCE-NAM-5.0) to identify SNP markers, which were annotated using SNPeff software.

[0042] 5. Population structure analysis and LD decay

[0043] The distance matrix was calculated using TreeBeST (version: Treebest-1.9.2) software, and the phylogenetic tree was constructed based on this distance matrix using the neighbor-joining method (NJ). To ensure accuracy, the bootstrap values ​​were calculated up to 1000 times. PCA analysis was performed using GCTA. After obtaining the PCA results, the values ​​of the first two PCs were used to display the samples involved in the analysis in two dimensions. PopLDdecay software was used to calculate the degree of linkage disequilibrium (r 2 ) and used the software's own script Plot_OnePop.pl to plot LD decay.

[0044] 6. Genome-wide association analysis

[0045] A genome-wide association analysis was performed using GEMMA software (http: / / www.xzlab.org / software.html) based on 6,390,967 high-quality SNP analyses. The analysis used a mixed linear model (MLM) for GWAS for phenotypes and best linear unbiased estimates (BLUPs) for all environments. A significance threshold of -log10(p)>5 was used to identify significant SNPs associated with corn white spot resistance, and bedtools v1.7 was used to extract SNP sites that reached or exceeded the threshold. Based on the B73_RefGen_v5 (full name: Zm-B73-REFERENCE-NAM-5.0) reference genome and annotation information, candidate genes associated with corn white spot resistance were screened within a 50 kb interval upstream and downstream of the significant SNPs.

[0046] 7 Construction of genetic linkage map

[0047] The linkage map was constructed using JoinMap4.0 software, and the LOD threshold was determined using 1000 random permutation tests. If the LOD threshold was ≥2.5, the QTL was considered significant. The linkage group was defined according to the standard of LOD critical value ≥2.5, and the genetic linkage map was constructed using qualified SNP markers. The offspring genotyping was filtered based on 0.8 completeness and 0.001 partial separation to obtain six population markers, and then bins were drawn based on population markers every 15 markers without linkage to obtain the final population markers, and the bin markers of each population were sorted using Joinmap4.0, and the genetic distance (cM) between markers was calculated using the Kosambi function.

[0048] 8QTL positioning analysis

[0049] QTL mapping was performed using the composite interval mapping (CIM) method in Windows QTL Cartographer 2.0. The phenotypic data of white spot disease were integrated into a high-density genetic linkage map, SNP markers with a missing rate ≥ 0.2 and sites with a minor allele frequency lower than 0.05 were excluded, and 0.21 cM was used to identify parental polymorphic QTLs. The threshold was determined using 1000 random permutations with a 95% confidence interval. The LOD threshold associated with the flanking markers was set to 2.5 to identify QTLs controlling MWS.

[0050] 9 Candidate gene analysis

[0051] Haploview v4.2 software was used to perform haplotype analysis of candidate genes. The corresponding gene sequences were extracted from the reference genome B73_RefGen_v5 according to the candidate gene IDs and compared with the parental lines TRL418 and TML139. The corresponding coding regions and amino acid variation information were extracted, and the functional gene motifs were predicted using MEME online software (https: / / meme-suite.org / meme / tools / meme).

[0052] Results Analysis

[0053] 1 Phenotypic data analysis

[0054] The white spot disease resistance phenotypic data of six RIL groups in Yanshan were collected for three years, and descriptive statistical analysis was performed. The results showed that the coefficient of variation of the six RIL groups in Yanshan was between 0.25-0.79, indicating that there were differences between the samples. At the same time, the average disease level of white spot disease in the six RIL groups was between 2.9 and 5.81, and the absolute values ​​of the skewness and kurtosis coefficients of the six groups in three years were close to 1, indicating that the white spot disease resistance phenotypes of the test groups in the three-year resistance identification were in line with the normal distribution and met the quantitative trait characteristics. Further analysis showed that the heritability of the severity of white spot disease in each RIL group ranged from 76.47-98.79%, and there was a strong correlation between the resistance phenotypes of the same group under different environments (0.46-0.98) ( Figure 2 ), indicating that the RIL lines have strong consistency in resistance to white spot disease in different environments. The phenotypic identification results show that corn white spot disease resistance has a high heritability and corn white spot disease resistance is mainly determined by genes.

[0055] 2SNP density and LD decay

[0056] Through whole genome resequencing, a total of 6,390,967 high-quality SNPs were identified in the whole genome. These SNPs were evenly distributed on the 10 chromosomes of maize ( Figure 3 a) The numbers of SNPs identified on chromosomes 1 to 10 are as follows: 1,354,402, 699,661, 716,354, 880,880, 668,865, 485,243, 563,392, 545,220, 472,482, and 462,679. The highest number of SNPs was on chromosome 1, and the lowest was on chromosome 10. The 6,390,967 SNPs identified were used to assess linkage disequilibrium (LD) decay in the association mapping population. Figure 3 As shown in b, when r 2 When the decline rate tends to be flat, the physical distance is about 50kb. Therefore, we selected the 50kb range upstream and downstream of the significant SNP site as the standard for screening candidate genes.

[0057] 3 Group structure analysis

[0058] We used TreeBeST to perform population phylogenetic tree analysis, dividing 941 RIL lines into 6 subgroups. We then used GCTA to perform principal component analysis (PCA), which also divided the 941 RIL lines into 6 subgroups, which matched the 6 RIL populations we assembled. The analysis found that there were some mixed or overlapping families, which may be due to the common parent Ye107 in the 6 subgroups and the gene introgression during the breeding process. Therefore, the possibility that population structure will lead to false positives in GWAS needs to be considered in subsequent analyses.

[0059] 4. Genome-wide association analysis

[0060] The software GEMMA (http: / / www.xzlab.org / software.html) was used to conduct GWAS analysis on the white spot disease resistance phenotype data of 941 RIL lines in the multi-parent population in Yanshan for three years and 6390967 high-quality SNPs obtained by whole genome resequencing. The mixed linear model (MLM) was used to correct the population structure and individual kinship at the same time, and a total of multiple SNPs were identified. Among the significant SNPs located, the consistent significant SNP that can be co-located in three or more environments is: 4-118983592. Since artificial populations may cause false positives in GWAS analysis results, in order to improve the accuracy of identification, QTL analysis will be used to further identify candidate sites.

[0061] 5. QTL Mapping

[0062] The white spot disease resistance phenotypes of each population under different environments were combined with the constructed high-density genetic map to locate the QTL of maize white spot disease resistance loci. The positioning results were compared with the results of GWAS analysis. Finally, under the BLUP and 22YS environments, the white spot disease resistance QTL intervals qMWS4-1 and qMWS4-5 were identified from the TML139×Ye107 population. These two resistance QTLs overlapped and could explain -15.05% of the phenotypic variation. This QTL interval included the consistent resistance loci SNPs of the above three environments (21YS, 23YS, BLUP): 4-118983592 ( Figure 4 ). SNP: 4-118983592 can explain 8.84% of the resistance phenotypic variation ( Figure 4 ).

[0063] 6. Candidate gene mining

[0064] In this study, the B73_RefGen_v5 reference genome was used to screen the 50Kb region upstream and downstream of the significant locus SNP: 4-118983592 in the qMWS4-4 interval, and the candidate genes were annotated and functionally predicted using databases such as MaizeGDB, InterPro, UniProt and NCBI, and the candidate functional gene Zm00001eb181850 (Chr4: 119014763-119023372) was identified. SNP: 4-118983592 was co-located in 21YS, 23YS and BLUP, and the SNP explained a total of 8.84%% of the phenotypic variation, and the locus was included in the consistent QTL qMWS4-1 and qMWS4-5 intervals ( Figure 4 ), indicating that the SNP in the interval of qMWS4-1 and qMWS4-5 is a molecular marker with high credibility. Its associated gene Zm00001eb181850 encodes a leucine-rich repeat (LRR) family protein. The domain of LRR is evolutionarily conserved in many proteins related to innate immunity of plants and animals. In different plants, LRR-RLK can act as a receptor for signal recognition to participate in the signal transduction process, which plays an important regulatory role in plant stress response, plant growth and development, and signal transduction.

[0065] 7. Candidate Gene Analysis

[0066] In order to clarify the correlation between the selected candidate functional gene Zm00001eb181850 and the resistance to corn white spot disease, Zm00001eb181850 was analyzed and it was found that the 119015573, 119015605, 119015666, 119015689 、119015754、119015775、119016626、119018991、119019227、119019236、119019440、119019442、119019567、119019601、119019635、119019878、119020288、119020495、119020805、 Mutations occurred at bases 119021016, 119021024, 119021932, 119022096, 119022608, and 119022763, resulting in 7 major haplotypes in the study population (Hap1: CTCGCGGTGCTTAACCATGTGCTGC; Hap2: TGACTTATACCGGTTTGCAGTTTGC, Hap3: CTCGCGGTGCTTAACCATGTGCCGC, Hap4: TGACTTATACCGGTTTGCAGTTCAC, Hap5: TGACTTACACCGGTTTGCAGTTCAA, Hap6: TGACTTATATCGGTTTGCAGTTTGC, Hap7: CTCGCGGTGCTTAACCATGTGCCAA) Figure 5 ),

[0067] Among them, plants with haplotype Hap7 (genotype: CTCGCGGTGCTTAACCATGTGCCAA) showed better resistance to corn white spot disease ( Figure 6 a). By comparing the sequences of the gene in the resistant materials TRL418 and TML139, a specific G / T mutation was found in the 119022188th base of TRL418 and TML139, which caused the corresponding amino acid sequences of the resistant materials TRL418 and TML139 to mutate from glutamine to histidine, respectively ( Figure 6 b), the mutation of these amino acids changes the motif of the protein. By studying the expression of this gene in different stages and tissues of corn, it was found that the expression level of Zm00001eb181850 in leaves was higher than that in other tissues ( Figure 6 c), further proving that this gene is closely related to resistance to corn leaf diseases and can be used as a molecular marker for breeding corn with white spot disease resistance.

[0068] Although the present invention has been described in detail above with general descriptions and specific embodiments, it is obvious to those skilled in the art that some modifications or improvements may be made thereto based on the present invention. Therefore, these modifications or improvements made without departing from the spirit of the present invention all fall within the scope of protection claimed by the present invention.

Claims

1. A molecular marker associated with corn white spot disease resistance, characterized in that: The molecular marker gene sequence is shown in SEQ ID NO: 1 and / or SEQ ID NO:

2.

2. The molecular marker according to claim 1, characterized in that As shown in SEQ ID NO:1, the base at position 201 from the 5′ end presents a T / C polymorphism; as shown in SEQ ID NO:2, the sequence corresponds to the corn Chr4:119014763-119023372 sequence, and the base at position 119022188 from the 5′ end presents a G / T polymorphism, and / or as shown in SEQ ID NO:2, the expression level of the gene or its translated protein is positively correlated with the resistance to corn white spot disease.

3. A molecular marker associated with corn white spot disease resistance, characterized in that: The molecular markers are SNP sites, including 119015573, 119015605, 119015666, 119015689, 119015754, 119015775, 119016626, 119018991, 119019227, 119019236, 119019440, 119019442, 119019567, 119019 At least one of the SNP sites 601, 119019635, 119019878, 119020288, 119020495, 119020805, 119021016, 119021024, 119021932, 119022096, 119022608, and 119022763, and the reference genome version where the SNP site is located is Zm-B73-REFERENCE-NAM-5.

0.

4. Any of the following uses of the molecular marker according to any one of claims 1 to 3, a) Genetic diversity analysis of maize resistant to white spot disease; b) Construction of molecular genetic map of maize resistant to white spot disease; c) Whole genome association analysis of maize resistant to white spot disease; d) Identification of maize varieties resistant to white spot disease; e) Molecular marker-assisted selection breeding of maize resistant to white spot disease; f) Whole genome selection breeding of maize resistant to white spot disease.

5. A method for detecting a product labeled with a molecule according to any one of claims 1 to 3, characterized in that: The product includes a reagent, a kit or a gene chip, and the product detects the genotype of the molecular marker, or detects the expression level of the sequence shown in SEQ ID NO: 2 or its translated protein.

6. A method for detecting a product labeled with a molecule according to any one of claims 1 to 3, 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, and the products detect the genotype of the molecular marker, or detect the expression level of the sequence shown in SEQ ID NO: 2 or its translated protein.

7. Any of the following uses of the product according to claim 5 or 6, a) Genetic diversity analysis of white spot disease resistant maize; b) Construction of molecular genetic map of white spot disease resistant maize; c) Whole genome association analysis of white spot disease resistant maize; d) Identification or auxiliary identification of white spot disease resistant maize varieties; e) Molecular marker-assisted selection breeding of white spot disease resistant maize; f) Whole genome selection breeding of white spot disease resistant maize.

8. A method for screening corn resistant to white spot disease, characterized in that: A corn sample to be tested is taken, and the gene sequence shown in SEQ ID NO: 1 is tested. When the base at the 201st position from the 5′ end of the sequence shown in SEQ ID NO: 1 is C, a corn variety with white spot disease resistance is obtained.

9. A method for screening corn resistant to white spot disease, characterized in that: Take a corn sample to be tested and detect the expression level or genotype of the gene sequence shown in SEQ ID NO:

2. When the sequence shown in SEQ ID NO: 2 or its translated protein is overexpressed and / or the base at position 119022188 from the 5′ end is T, it is judged to be a corn variety with white spot disease resistance.

10. A method for screening corn resistant to white spot disease, characterized in that: Take a corn sample to be tested and detect the molecular marker genotype according to claim 3. When the SNP sites of the molecular marker are sequentially presented as: CTCGCGGTGCTTAACCATGTGCCAA, it is judged to be a corn variety with white spot disease resistance.

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