Molecular markers associated with white spot disease resistance on maize chromosome 2 and their application

Abstract

The present invention belongs to the technical field of molecular marker-assisted breeding, and specifically discloses a molecular marker associated with white spot disease resistance on maize chromosome 2 and its application. The present invention provides a molecular marker gene associated with maize white spot disease resistance, wherein the gene sequence is shown in SEQ ID NO: 1 and / or SEQ ID NO: 2. Through years of multi-point experiments, the present invention co-localizes SNP: 2-212792117 and its downstream gene Zm00001eb107230 on maize chromosome 2. The SNP can be located under multiple different environments and can explain 20.39% of phenotypic variation. The associated candidate functional gene mainly encodes a Remorin family protein, which has been confirmed to be related to maize resistance and can be used as a molecular marker for maize white spot disease resistance.

Description

Technical Field

[0001] The present invention belongs to the technical field of molecular marker-assisted breeding, and specifically relates to an application of a molecular marker site SNP: 2-212792117 related to white spot disease resistance on maize chromosome 2 and a candidate functional gene Zm00001eb107230 associated therewith in improving maize white spot disease resistance. Background Art

[0002] Maize (Zea mays L.), as a key food crop, directly impacts global food security and the development of animal husbandry. In recent years, maize white spot blight, caused by Pantoea ananatis, is a foliar disease that severely impacts maize production. First reported in India in 1965, the disease became prevalent in Brazil and the United States during the 1980s and 1990s. Severe cases of white spot blight have reportedly reduced maize yields by over 60% in Brazil. Since mid-July 2020, white spot blight has erupted in my country's southwestern maize ecosystem, particularly in Yunnan, resulting in widespread corn yield losses of 10% to 50% in some areas. This has severely impacted maize production and caused a significant drop in farmers' incomes. Since 2023, the disease has spread to the main maize-producing regions in northern China and has now become a nationwide maize disease. In the early stages of the disease, lesions appear on the base of the leaves, rapidly spreading to the upper part of the plant. In the later stages of the disease, the leaves become chlorotic, impacting plant carbon cycling and photosynthesis. If some leaves are infected before the corn filling stage, the net photosynthetic rate may drop sharply by 40%, leading to the premature end of the reproductive maturity stage, and ultimately causing the corn ears to be deformed and the seed rate to be low, seriously reducing the yield and quality of corn.

[0003] Currently, prevention and control of white spot disease primarily focuses on optimizing field tillage systems and the use of agricultural chemicals. Recent research has shown that resistance to white spot disease is largely dependent on genetic factors. Therefore, breeding genetically resistant varieties to white spot disease is the most cost-effective approach to controlling the disease. However, because white spot disease is a relatively new corn disease in my country, the functional genes associated with white spot disease resistance have yet to be cloned. Summary of the Invention

[0004] The main purpose of the present invention is to provide a molecular marker related to white spot disease resistance on maize chromosome 2 and its application, and to provide a new method for breeding new maize varieties resistant to white spot disease using modern molecular breeding technology.

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

[0006] On the one hand, the present invention provides a molecular marker associated with resistance to corn white spot disease, and the molecular marker gene sequence is shown in SEQ ID NO:1 and / or SEQ ID NO:2; the sequence shown in SEQ ID NO:1 presents an A / T polymorphism at base 201 from the 5′ end; the sequence shown in SEQ ID NO:2 corresponds to the corn Chr2:212799375-212800757 sequence, and the bases at positions 212800221, 212800219 or 212800217 from the 5′ end present C / G, A / G, or C / G polymorphisms.

[0007] On the other hand, the present invention provides a molecular marker associated with resistance to corn white spot disease, characterized in that the molecular marker is a SNP site, including at least one of the sites 212792117, 212800397, 212800429, 212800459, 212800221, 212800219 or 212800217 located on chromosome 2 of corn, and the reference genome version where the SNP site is located is Zm-B73-REFERENCE-NAM-5.0.

[0008] Furthermore, the present invention provides any of the following applications of the molecular marker:

[0009] a) Genetic diversity analysis of white spot disease-resistant maize; b) Construction of molecular genetic map of white spot disease-resistant maize; c) Genome-wide association analysis of white spot disease-resistant maize; d) 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.

[0010] In another aspect, the present invention provides products for detecting the molecular markers, comprising reagents, kits, or gene chips, which detect the genotype of the molecular markers. In some embodiments, the gene chip comprises a liquid-phase chip or a solid-phase chip; in more specific embodiments, the kit comprises nucleic acid extraction and purification reagents for extracting DNA from a sample, such as a lysis buffer, a deproteinization buffer, and a rinse buffer; PCR reaction reagents, including primers, probes, dNTPs (deoxynucleotide triphosphates), and a DNA polymerase for amplifying specific genes; and fluorescently labeled probes, such as fluorescently labeled probes used for real-time detection of gene mutations in fluorescent PCR technology.

[0011] On the other hand, the present invention provides products for detecting 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 products detect the genotype of the molecular markers.

[0012] Furthermore, the present invention provides any of the following applications of the product:

[0013] a) Genetic diversity analysis of white spot disease-resistant maize; b) Construction of a molecular genetic map of white spot disease-resistant maize; c) Genome-wide association analysis of white spot disease-resistant maize; d) Identification or assisted 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.

[0014] 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. If the base at the 201 bp position from the 5′ end of the sequence shown in SEQ ID NO: 1 is T, the corn variety is judged to be resistant to white spot disease.

[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: 2 is detected. If the sequence shown in SEQ ID NO: 2 corresponds to the corn Chr2: 212799375-212800757 sequence, and the bases at positions 212800221, 212800219 or 212800217 from the 5′ end are all G, it is judged to be a corn variety with resistance to white spot disease.

[0016] In another aspect, the present invention provides a method for screening corn for white spot disease resistance, wherein a corn sample to be tested is taken and a SNP site is detected, wherein the SNP site includes at least one of sites 212792117, 212800397, 212800429, 212800459, 212800221, 12800219, or 212800217 located on chromosome 2 of corn, and the reference genome version of the SNP site is Zm-B73-REFERENCE-NAM-5.0. When the bases of the SNP site are T, A, G, T, G, G, and G, respectively, the corn variety is judged to be resistant to white spot disease. In some embodiments, a liquid-phase gene chip is prepared using the SNP sites provided by the present invention, and multiple site detection is performed using high-throughput genotyping technology to identify or assist in identifying corn white spot disease resistance.

[0017] The present invention confirms through research that SNP: 2-212792117 on maize chromosome 2 (i.e., the 201bp position from the 5′ end of the sequence shown in SEQ ID NO: 1) and its downstream gene Zm00001eb107230 (SEQ ID NO: 2) have strong resistance to maize white spot disease. Maize white spot disease resistance is a quantitative trait regulated by multiple genes. The technical solution provided by the present invention provides a new method for breeding new maize varieties resistant to white spot disease using modern molecular breeding technology, thereby assisting in improving maize white spot disease resistance. This can avoid the complicated and time-consuming resistance screening process, shorten the breeding period, and improve the efficiency of molecular breeding for maize resistance to white spot disease. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] Figure 1 Images of leaves with different grades of white spot disease on corn; HR: highly resistant to white spot disease, R: resistant to white spot disease, M: moderately resistant to white spot disease, S: susceptible to white spot disease, HS: highly susceptible to white spot disease.

[0019] Figure 2 Correlation heat map of white spot disease resistance in six populations; describes the correlation of the overall performance of the six RIL populations under different environments. The narrower the circle and the redder the color, the stronger the correlation.

[0020] Figure 3 .SNP density plot and LD decay plot; (a) Chromosome-specific SNP density within 1 Mb 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 as a function of physical distance (Kb).

[0021] Figure 4 .Population structure diagram; different colors indicate different subpopulations: yellow: YML32×Ye107 (pop1); purple: YML418×Ye107 (pop2); green: CML171×Ye107 (pop3); blue: TML139×Ye107 (pop4); brown: CML226×Ye107 (pop5); orange: NK40-1×Ye107 (pop6).

[0022] Figure 5 .Manhattan plot and QQ plot; Manhattan plot (left) and QQ plot (right) of YS21(a), YS22(b), YS23(c), and BLUP(d) show SNPs associated with MWS resistance. Each point in the left plot represents a SNP, the black line represents the threshold of <1×10-5, and different colors represent different chromosomes. The red line in the right plot is the trend line that the ideal QQ plot should correspond to in each case.

[0023] Figure 6Identification diagram of the candidate gene Zm00001eb107230 for white spot disease resistance; (a) LD block of the candidate gene; (b) Schematic diagram of the mutation sites that form different haplotypes in the Zm00001eb107230 gene; (c) Overall differences in the resistance levels of the five haplotypes to MWS, * indicates p < 0.05, **** indicates p < 0.0001; (d) Relative positions of Zm00001eb107230 and SNPs, as well as base and amino acid variations in the resistant parent TML139. DETAILED DESCRIPTION

[0024] To make the objectives, technical solutions, and advantages of the present invention more clear, 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. 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 making creative efforts shall fall within the scope of protection of the present invention.

[0025] The present invention is based on genome-wide association analysis, using tropical maize inbred lines (YML32, TRL418, CML171, TML139, YML226, NK40-1) as resistant parents, hybridized with the temperate susceptible elite inbred line Ye107, and bred through nine consecutive generations of single-seed self-pollination to produce six F9 recombinant inbred lines (RILs). These RILs were planted in Yanshan County, Yunnan Province for three consecutive years to carry out phenotypic identification of white spot disease resistance. Combined with high-quality single nucleotide polymorphisms (SNPs) from the RIL population, GWAS analysis identified SNPs that were consistently significantly associated with maize white spot disease resistance in multiple environments: 2-212792117 molecular markers and the functional gene Zm00001eb107230. This resistance gene can subsequently be applied to maize white spot disease resistance breeding using molecular breeding.

[0026] The utility of the molecular markers provided by the present invention is fully illustrated by the following examples:

[0027] Example 1

[0028] 1. Experimental Materials and Design

[0029] In the present invention, 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 the excellent temperate maize inbred line Ye107 susceptible to white spot disease was used as the common parent for hybridization (the pedigrees, heterotic groups, ecological groups, and related resistance levels of the seven parents are detailed in Table 1). By single-seed descent, nine consecutive generations of self-pollination were performed to produce six recombinant inbred line (RIL) populations: pop1 (YML32×Ye107), pop2 (TRL418×Ye107), and pop3 (TRL418×Ye107). 07), pop3 (CML171×Ye107), pop4 (TML139×Ye107), pop5 (YML226×Ye107) and pop6 (NK40-1×Ye107). Initially, each population contained 200 recombinant inbred (RIL) lines, but due to environmental selection, inbreeding depression and other factors, the final number of RIL lines available for this study was 904 (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 experiment adopted a completely randomized block design with 14 plants per row, 4 m row length, and 25 cm plant spacing, following standard farmland management.

[0030] Table 1. Pedigrees, ecotypes, and white spot disease resistance of the seven parents used in the experiment

[0031]

[0032] 2. Disease grade score

[0033] In 2021, 2022, and 2023, RILs from a multi-parent population were evaluated for resistance to white spot disease in Yanshan County, Yunnan Province, China. White spot disease outbreaks occur from early August to late September each year, when corn is in the grain filling to maturity stage, making it suitable for resistance assessment. The severity of white spot disease was graded according to the symptom identification criteria outlined in the Maize Pest and Disease Manual, with the average severity of disease in individual plots evaluated on a scale of 1 to 9, e.g. Figure 1 , as shown in Table 2.

[0034] Table 2. Classification criteria for corn white spot disease

[0035]

[0036]

[0037] 3. Phenotypic Identification and Statistical Analysis

[0038] Descriptive analyses of phenotypic data were performed using SPSS Statistics and ORIGIN (Origin 2022) software. Mean, minimum, maximum, standard deviation (SD), coefficient of variation (CV), skewness, and kurtosis were calculated. Frequency distributions of phenotypic data were analyzed using SPSS software. Kurtosis and skewness were used to assess the normality of the frequency distribution. Broad-sense heritability was calculated according to the method outlined by Knapp et al.

[0039] 4. Whole-genome resequencing

[0040] 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 then annotated using the SNPeff software.

[0041] 5. Population structure analysis and LD decay

[0042] The distance matrix was calculated using TreeBeST (version: Treebest-1.9.2) software, and a phylogenetic tree was constructed based on this distance matrix using the neighbor-joining method (NJ). To ensure accuracy, 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 perform a two-dimensional display of the samples involved in the analysis. The degree of linkage disequilibrium (r) between each pair of markers was calculated using PopLDdecay software. 2 ) and used the software's own script Plot_OnePop.pl to plot LD decay.

[0043] 6. Genome-wide Association Analysis

[0044] A genome-wide association study (GEMMA) was performed using 6,390,967 high-quality single-nucleotide polymorphisms (SNPs) analyzed using GEMMA software (http: / / www.xzlab.org / software.html). This analysis employed a mixed linear model (MLM) for GWAS, targeting phenotypes and best unbiased linear estimates (BLUPs) across all environments. A significance threshold of -log10(p)>5 was used to identify significant SNPs associated with maize white spot resistance. Bedtools v1.7 was used to extract SNPs that met or exceeded the threshold. Candidate genes associated with maize white spot resistance were identified within a 50 kb interval upstream and downstream of the significant SNPs, based on the B73_RefGen_v5 reference genome and annotation information.

[0045] 7. Epistasis analysis of resistance-related SNP loci

[0046] Linear regression analysis was performed using PLINK software using the formula y = u + gi + gj + gigj, where y represents the white spot disease resistance score, gi and gj represent the main effects associated with marker i and marker j, respectively, and gigj represents the interaction effect between alleles of marker i and marker j. Significant epistasis was observed at p < 0.05.

[0047] 8 Candidate gene analysis

[0048] 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 most resistant parent, 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).

[0049] (2) Experimental results

[0050] 1. Phenotypic Data Analysis

[0051] The white spot disease resistance phenotypic data of six RIL groups were collected for three years in Yanshan, and descriptive statistical analysis was performed (Table 3). 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 plants of the six RIL groups was between 2.90-5.81, 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 the quantitative trait characteristics. Further analysis showed that the heritability of the severity of white spot disease of each RIL group ranged from 76.47-98.79%, and there was a strong correlation (0.46-0.98) between the resistance phenotypes of the same group under different environments (Table 3, Figure 2 ), indicating that the RIL lines had strong consistency in resistance to white spot disease under different environments. The phenotypic identification results showed that corn white spot disease resistance has a high heritability and is mainly determined by genes.

[0052] Table 3. Descriptive statistics of white spot disease resistance of six RIL subpopulations

[0053]

[0054]

[0055] Note: MWS phenotypic statistical analysis of 6 RIL populations in 2021, 2022, and 2023. 21YS, 22YS, and 23YS represent the experiments conducted in Yanshan in 2021, 2022, and 2023, respectively.

[0056] 2SNP density and LD decay

[0057] Through whole genome resequencing, a total of 6,390,967 high-quality SNPs were identified throughout the genome. These SNPs were evenly distributed on the 10 chromosomes of maize ( Figure 3 a) The number of SNPs identified on chromosomes 1 to 10 is 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 is on chromosome 1, and the lowest is on chromosome 10. The 6,390,967 identified SNPs 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.

[0058] 3. Group structure analysis

[0059] We used TreeBeST to perform a phylogenetic tree analysis, dividing the 941 RIL lines into six subgroups. We then used GCTA to perform a principal component analysis (PCA), which also divided the 941 RIL lines into six subgroups, which were consistent with the six RIL populations we assembled. The appearance of some mixed or overlapping families in the figure may be due to the common parent Ye107 in the six subgroups and the introgression of genes during the breeding process ( Figure 4 Therefore, the possibility that population structure may lead to false positives in GWAS needs to be considered in subsequent analyses.

[0060] 4. Genome-wide Association Analysis

[0061] We used GEMMA (http: / / www.xzlab.org / software.html) software to conduct GWAS analysis on the white spot disease resistance phenotypic 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. Mixed linear model (MLM) was used to correct for both population structure and individual kinship, and a total of 679 SNPs were identified. Among them, 109 significant SNPs ( Figure 5 b), explaining 0.06%-7.17% of the phenotypic variance; in the GWAS analysis of 22YS, 183 significant SNPs were identified ( Figure 5 c), explaining 0.18%-6.76% of the phenotypic variance; in the GWAS analysis of 23YS, 204 significant SNPs were identified ( Figure 5 d), explaining 0.19%-7.41% of the phenotypic variance; 183 significant SNPs were identified in the GWAS analysis of BLUP ( Figure 5 a), explaining 0.27%-7.24% of the phenotypic variance. These significant SNPs are distributed on all ten chromosomes of maize.

[0062] Since artificial populations may cause false positives in GWAS analysis results, SNPs need to be cross-validated using multiple results from multiple environments. By comparing the three-year GWAS analysis results of Yanshan (YS), multiple consistent and significant SNPs that co-located in all environments were identified. Epistasis analysis was performed on the co-located SNP sites, and the results showed that SNP: 2-212792117 and SNP: 8-149695036 showed the most significant epistatic interaction, with a STAT value of 9.066, indicating that the epistatic effect has a greater impact on resistance to corn white spot disease.

[0063] 5. Candidate gene mining

[0064] This study used the B73_RefGen_v5 reference genome to screen for a significant locus (SNP) 2-212792117 within a 50 kb region upstream and downstream that was consistent across multiple environments and had a high effect size. The candidate genes were annotated and functionally predicted using databases such as MaizeGDB, InterPro, UniProt, and NCBI. Ultimately, SNP 2-212792117 was used to identify the candidate functional gene Zm00001eb107230 (Chr2:212799375-212800757, NCBI Gene ID: 100192691) on chromosome 2, which is associated with white spot disease resistance. SNP 2-212792117 and Zm00001eb107230 were co-located on chromosomes 21YS, 22YS, 23YS, and BLUP, explaining 20.39% of the phenotypic variation. Epistasis analysis showed that this SNP exhibited a significant epistatic effect with SNP:8-149695036 on chromosome 8, and its epistatic effect was significantly associated with resistance to white spot disease. The candidate functional gene Zm00001eb107230, associated with SNP:2-212792117, is located 7790 bp downstream of SNP:2-212792117 and primarily encodes a Remorin family protein. Remorin proteins are a family of plant-specific oligomeric filamentous proteins that are associated with the plasma membrane / membrane rafts and localized in membrane microdomains. They participate in regulating numerous biological processes, including plant metabolism, cell cycle and growth and development, hormone signaling, and pathogen perception. As a new member of the signal transduction cascade, they participate in plant innate immune signal transduction.

[0065] 6. Candidate Gene Analysis

[0066] In order to clarify whether the candidate functional gene Zm00001eb107230 is related to the resistance to corn white spot, Zm00001eb107230 was analyzed and it was found that the Zm00001eb107230 gene had mutations at bases 212800397, 212800429 and 212800459 on maize chromosome 2 ( Figure 6 a, 6b), showed five major haplotypes (CAT, AGT, CGG, AGG and CGT) in the experimental population, among which the plants with haplotype AGT showed better resistance to corn white spot disease ( Figure 6c). By comparing the sequence of this gene in the resistant material TML139, three specific C / G, A / G, and C / G mutations were found at positions 212800221, 212800219, and 212800217 of the Zm00001eb107230 gene of TML139, resulting in changes in the corresponding amino acid sequence of the resistant material TML139 from alanine to asparagine and from glycine to glutamic acid, respectively ( Figure 6 d).

[0067] Although the present invention has been described in detail above using general descriptions and specific embodiments, it will be apparent to those skilled in the art that modifications and improvements may be made based on the present invention. Therefore, such modifications and improvements, which do not depart from the spirit of the present invention, are intended to be within the scope of protection claimed herein.

Claims

1. Application of a reagent for detecting molecular markers associated with corn white spot disease resistance in molecular marker-assisted selection breeding of white spot disease-resistant corn, characterized in that: The molecular markers are SNP sites, including sites 212792117, 212800397, 212800429 and 212800459 located on corn chromosome 2. The reference genome version of the SNP sites is Zm-B73-REFERENCE-NAM-5.

0. When the bases of the SNP sites are T, A, G and T respectively, it is judged to be a corn variety with white spot disease resistance.

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