Molecular markers associated with white spot disease resistance on maize chromosome 8 and their application

Abstract

The present invention belongs to the technical field of molecular marker-assisted breeding, and specifically relates to molecular markers associated with white spot disease resistance on maize chromosome 8 and their applications. The molecular marker gene sequence located on maize chromosome 8 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: 8-149153434 and its associated gene Zm00001eb358700 (SEQ ID NO: 2) on maize chromosome 8. The SNP can be located under multiple different environments and can explain 22.5% of phenotypic variation. This site 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:8-149153434 associated with white spot disease resistance on maize chromosome 8 and a candidate functional gene Zm00001eb358700 associated therewith in improving maize white spot disease resistance. Existing technology

[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] 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. Research in recent years has shown that white spot disease resistance depends largely on its genetic factors. Therefore, breeding varieties resistant to white spot disease from a genetic perspective is the most economical and effective way to control the disease. However, since white spot disease is a newly emerging corn disease in my country, functional genes related to white spot disease resistance have not yet been cloned. Based on whole-genome association analysis and QTL mapping, the present invention utilizes tropical corn inbred lines (YML32, TRL418, CML171, TML139, YML226, NK40-1) as resistant parents, hybridizes them with the temperate susceptible excellent inbred line Ye107, and after 9 consecutive generations of single-seed self-pollination, 6 F9 recombinant inbred lines (RILs) were selected. These RILs were planted in Yanshan County, Yunnan Province for three consecutive years to carry out phenotypic identification of corn white spot disease resistance. Combined with the high-quality SNPs of the RIL population, GWAS analysis identified resistance SNP molecular markers and functional genes significantly associated with corn white spot disease resistance. Summary of the Invention

[0004] The main purpose of the present invention is to provide a molecular marker site SNP: 8-149153434 on maize chromosome 8 related to white spot disease resistance and its associated candidate functional gene Zm00001eb358700 for improving maize white spot disease resistance. Specifically, the present invention provides the following technical solutions:

[0005] In one aspect, the present invention provides a molecular marker 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.

[0006] Furthermore, the molecular marker, as shown in SEQ ID NO: 1, presents a T / A polymorphism at the 201st base from the 5′ end; the sequence shown in SEQ ID NO: 2 corresponds to the corn Chr8: 149156241-149158195 sequence, and presents an A / T polymorphism at the 149156930th base from the 5′ end, and the expression level of the gene shown in SEQ ID NO: 2 or its translated protein is positively correlated with corn white spot resistance.

[0007] On the other hand, the present invention provides molecular markers associated with resistance to corn white spot disease, which are SNP sites, including at least one of sites 149153434, 149156506, 149157812, 149157853, 149157932, 149157959 or 149156930 located on chromosome 8 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 any of the molecular markers:

[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 a product for detecting any of the aforementioned molecular markers, the product comprising a reagent, a kit, or a gene chip, the product detecting the genotype of the aforementioned molecular marker, or detecting the expression level of the sequence shown in SEQ ID NO: 2 or its translated protein. In some embodiments, the gene chip comprises a liquid phase chip or a solid phase chip; in some 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, a rinse buffer, etc.; PCR reaction reagents: including primers, probes, dNTPs (deoxynucleotide triphosphates), DNA polymerase, etc. for amplifying specific genes; and fluorescently labeled probes: fluorescently labeled probes used for real-time detection of gene mutations in fluorescent PCR technology, etc.

[0011] In another aspect, the present invention provides a product for detecting any of the molecular markers, including products prepared using 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.

[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] In another aspect, 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 A, a corn variety with resistance to white spot disease is obtained.

[0015] On the other hand, the present invention provides a method for screening corn with white spot disease resistance. 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 149156930 from the 5′ end is T, a corn variety with white spot disease resistance is obtained. The expression level of the gene shown in SEQ ID NO: 2 or its translated protein is positively correlated with the resistance to corn white spot disease.

[0016] On the other hand, the present invention provides a method for screening corn for white spot disease resistance, taking a corn sample to be tested and detecting SNP sites, wherein the SNP sites include at least one of sites 149153434, 149156506, 149157812, 149157853, 149157932, 149157959 or 149156930 located on chromosome 8 of corn, and the reference genome version of the SNP sites is Zm-B73-REFERENCE-NAM-5.0. When the bases of the SNP sites are A, C, C, A, C, C and T respectively, the corn variety is judged to have white spot disease resistance. In a specific embodiment, the SNP sites provided by the present invention are used to prepare a liquid gene chip, and multiple site detections are performed using high-throughput genotyping technology to identify or assist in identifying corn white spot disease resistance.

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

[0018] Through years of multi-site experiments, this study co-localized SNP 8-149153434 and its associated gene, Zm00001eb358700 (Chr8:149156241-149158195, NCBI Gene ID: 103636099), on maize chromosome 8. This SNP was consistently located across multiple environments, explaining 22.5% of phenotypic variation and exhibiting the highest dominance. The associated candidate functional gene primarily encodes heat stress transcription factor C-1a of the HSF family, which has been shown to be associated with maize resistance. This locus can be used as a molecular marker for maize white spot resistance.

[0019] This study confirms that SNP 8-149153434 on maize chromosome 8 and its associated gene, Zm00001eb358700, confer strong resistance to corn white spot disease. Corn white spot disease resistance is a quantitative trait regulated by multiple genes. The technical solution provided by this study offers a novel method for cultivating new corn varieties resistant to white spot disease using modern molecular breeding techniques. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] 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.

[0021] 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.

[0022] Figure 3SNP density and LD decay plots; (a) Chromosome-specific SNP density within 1 Mb intervals. The ordinate represents chromosomes, and the abscissa represents positions on each chromosome. Redder positions indicate more variant sites. (b) Genome-wide LD decay (r²) across all chromosomes in 941 maize RILs as a function of physical distance (kb).

[0023] Figure 4 Manhattan plots and QQ plots; Manhattan plots (left) and QQ plots (right) for YS21 (a), YS22 (b), YS23 (c), and BLUP (d) show SNPs associated with MWS resistance. Each dot in the left panel represents a SNP, and the black line represents the threshold of <1×10⁻⁵. Different colors represent different chromosomes. The red line in the right panel represents the trend line corresponding to the ideal QQ plot in each case.

[0024] Figure 5 .Boxplots of SNP additive and dominant effects;

[0025] Figure 6 Identification diagram of the candidate gene Zm00001eb358700 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 Zm00001eb358700 gene.

[0026] Figure 7 . Overall difference of resistance levels of seven haplotypes to corn white spot disease, * indicates p < 0.05, **** indicates p < 0.0001;

[0027] Figure 8 .(a) The relative positions of Zm00001eb358700 and SNP, as well as the base variation and amino acid variation diagram in the parent TML139; (b) The expression level diagram of the Zm00001eb358700 gene in different tissues of corn at different stages. The red boxes represent leaves at different stages, which shows that its expression level is high in the leaves of corn at different stages. DETAILED DESCRIPTION

[0028] 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.

[0029] Based on genome-wide association analysis, the present invention uses tropical maize inbred lines (YML32, TRL418, CML171, TML139, YML226, NK40-1) as resistant parents, hybridizes them with the temperate susceptible elite inbred line Ye107, and selects six F9 recombinant inbred lines (RILs) after nine consecutive generations of single-seed self-pollination. These RILs were planted in Yanshan County, Yunnan Province for three consecutive years to carry out white spot disease resistance phenotypic identification. Combined with the high-quality SNPs of the RIL population, GWAS analysis identified a molecular marker SNP: 8-149153434 (i.e., the 201bp position from the 5′ end of the sequence shown in SEQ ID NO: 1) that was significantly associated with corn white spot disease resistance in multiple environments and its associated gene Zm00001eb358700 (Chr8: 149156241-149158195, NCBI gene ID number: 103636099). Molecular breeding can be used to subsequently apply this resistance gene to corn white spot disease resistance breeding.

[0030] The utility of the molecular markers provided by the present invention is fully illustrated by the following examples:

[0031] Example 1

[0032] (1) Experimental methods

[0033] 1. Experimental Materials and Design

[0034] 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. They were hybridized with the excellent temperate maize inbred line Ye107 susceptible to white spot disease as the common parent (the pedigrees, 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 used to generate six recombinant inbred line (RIL) populations: pop1 (YML32×Ye107), pop2 (TRL418× Initially, each population contained 200 RILs. However, due to environmental selection, inbreeding depression, and other factors, a total of 904 RILs were used for this study (pop1: 145; pop2: 141; pop3: 147; pop4: 160; pop5: 152; and pop6: 159). These RILs were planted in Yanshan County, Yunnan Province (23°19'-23°59'N, 103°35'-104°45'E) in 2021, 2022, and 2023. A complete randomized block design was used, with 14 plants per row, 4 m in length, and 25 cm plant spacing. Standard farmland management was followed.

[0035] Table 1. Pedigrees, ecotypes, and white spot disease resistance of the seven parents used in the experiment

[0036]

[0037]

[0038] 2. Disease grade score

[0039] In 2021, 2022, and 2023, RILs from a multi-parent population were evaluated for white spot disease resistance in Yanshan County (YS), 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.

[0040] Table 2. Classification criteria for corn white spot disease

[0041]

[0042] 3. Phenotypic Identification and Statistical Analysis

[0043] 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 methods outlined by Knapp et al.

[0044] 4. Whole-genome resequencing

[0045] 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.

[0046] 5. Population structure analysis and LD decay

[0047] 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.

[0048] 6. Genome-wide Association Analysis

[0049] 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 across all environments and best unbiased linear estimates (BLUPs). 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 this threshold. Based on the B73_RefGen_v5 reference genome and annotation information, candidate genes associated with maize white spot resistance were identified within a 50 kb interval upstream and downstream of the significant SNPs.

[0050] 7. Analysis of additive and dominant effects of resistance-related SNPs

[0051] Mixed linear model (MLM) analysis was performed using Tassel software, and corrections were made using kinship and PCA matrices to calculate the additive and dominant effects of SNPs.

[0052] 8. Candidate Gene Analysis

[0053] 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).

[0054] (2) Experimental results

[0055] 1. Phenotypic Data Analysis

[0056] The white spot disease resistance phenotypic data of six RIL groups were collected for three years in Yanshan, 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 2.90-5.81, 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% to 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 had strong consistency in resistance to white spot disease under different environments. The phenotypic identification results showed that the resistance to corn white spot disease has a high heritability and is mainly determined by genes.

[0057] 2SNP density and LD decay

[0058] 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. A total of 6,390,967 SNPs were identified 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 range of 50kb upstream and downstream of the significant SNP site as the standard for screening candidate genes.

[0059] 3. Group structure analysis

[0060] Phylogenetic tree analysis using TreeBeST divided the 941 RIL lines into six subgroups. Principal component analysis (PCA) using GCTA also divided the 941 RIL lines into six subgroups, which were consistent with the six RIL populations we assembled. During the analysis, some admixture or overlapping family lines were discovered. This may be due to the common parent, Ye107, among the six subgroups and gene introgression during breeding. Therefore, the possibility that population structure may lead to false positives in GWAS should be considered in subsequent analyses.

[0061] 4. Genome-wide Association Analysis

[0062] GEMMA (http: / / www.xzlab.org / software.html) software was used to conduct GWAS analysis on the white spot disease resistance phenotypic data of 941 RIL lines in the multi-parent population in the three-year Yanshan period 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 multiple SNPs were identified. Since artificial populations may cause false positives in GWAS analysis results, it is necessary to cross-validate SNPs using multiple results in multiple environments. By comparing the GWAS analysis results of the three-year Yanshan period, a total of multiple consistent significant SNPs that were co-located in all environments were identified ( Figure 4 ), the present invention conducted additive and dominant effect analysis on four co-located SNP sites with large effect values ​​related to corn white spot disease resistance, and found that the SNP with the largest phenotypic contribution rate: 8-149153434 had the largest dominant effect ( Figure 5 ), indicating that this SNP has a significant effect on improving corn white spot disease resistance.

[0063] 5. Candidate gene mining

[0064] This study used the B73_RefGen_v5 reference genome to screen the 50Kb region upstream and downstream of the SNP: 8-149153434 with the largest effect value and the largest dominant effect. The candidate genes were annotated and functionally predicted using databases such as MaizeGDB, InterPro, UniProt, and NCBI. Finally, the candidate functional gene Zm00001eb358700 associated with the SNP: 8-149153434 on chromosome 8 was identified. Both SNP: 8-149153434 and gene Zm00001eb358700 were co-located in 21YS, 22YS, 23YS, and BLUP. This SNP explained a total of 22.5% of the phenotypic variation and had the largest dominant effect among the four significant SNPs with the highest effect values ​​( Figure 5 、 Figure 6 a), indicating that this SNP has a strong effect on white spot resistance. The Zm00001eb358700 gene primarily encodes heat stress transcription factor C-1a, a member of the HSF family. HSF transcription factors regulate the expression of jasmonic acid, abscisic acid, indole-3-acetic acid, and other plant hormones. Under certain conditions, these hormones mediate activation of stress conditions, enhancing plant stress tolerance.

[0065] 6. Candidate Gene Analysis

[0066] In order to clarify whether the candidate functional gene Zm00001eb358700 was related to the resistance to corn white spot, Zm00001eb358700 was analyzed. It was found that Zm00001eb358700 had mutations at sites 149156506, 149157812, 149157853, 149157932, and 149157959 on chromosome 8 of corn, resulting in a total of seven major haplotypes of gene Zm00001eb358700: CCGAT (Hap1), TTGAT (Hap2), TCACC (Hap3), CCACC (Hap4), CTGAT (Hap5), CTGCT (Hap6), and TTGCT (Hap7). Among them, plants with haplotype CCACC (Hap4) showed better resistance to corn white spot. Figure 6b. Figure 7 By comparing the sequence of this gene in the resistant material TML139, a specific A / T mutation was found at position 149156930 of the Zm00001eb358700 gene of TML139, which caused the corresponding amino acid sequence of the resistant material TML139 to mutate from threonine to serine ( Figure 8 a), mutations in these amino acids change the protein motif. By studying the expression of this gene RNA in different stages and tissues of corn, it was found that Zm00001eb358700 in leaves remained at a high level ( Figure 8 b), further proving that this gene is closely related to resistance to maize leaf diseases.

[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 product 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 149156506, 149157812, 149157853, 149157932 and 149157959 located on corn chromosome 8. The reference genome version of the SNP sites is Zm-B73-REFERENCE-NAM-5.

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

2. The use according to claim 1, characterized in that The product includes a reagent, a kit or a gene chip, and the product detects the genotype of the molecular marker.

3. A method for screening corn resistant to white spot disease, characterized in that: A corn sample to be tested was taken to detect the SNP site genotype. The SNP sites included sites 149156506, 149157812, 149157853, 149157932 and 149157959 located on corn chromosome 8. The reference genome version of the SNP sites was Zm-B73-REFERENCE-NAM-5.

0. When the bases of the SNP sites were C, C, A, C and C respectively, it was judged to be a corn variety with white spot disease resistance.

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