KASP molecular marker for wheat scab resistance QTL Qfhb.sdau-1BL and its application

Abstract

The present application relates to KASP molecular marker of wheat scab resistance QTL Qfhb.sdau-1BL and application thereof, and belongs to the technical field of wheat scab resistance molecular marker.The present application locates a new QTL site of wheat scab resistance on 1BL (401-406Mb) chromosome by BSR-Seq analysis, and names it as Qfhb.sdau-1BL.A KASP molecular marker is developed from the above QTL interval, and is named as KASP-QFhb.sdau-1B.15, with a physical position of 406306877.The above KASP molecular marker has high correlation with scab resistance, and the site can be applied to molecular marker assisted selection breeding.Therefore, the present application mines a new scab resistance gene, and can provide a new gene resource for cultivation of new wheat varieties with scab resistance.

Description

Technical Field

[0001] This invention relates to QTLs for resistance to wheat scab. Qfhb.sdau-1BL The KASP molecular marker and its application belong to the field of molecular marker technology for wheat resistance to Fusarium head blight. Background Technology

[0002] Wheat is an important food crop, providing humans with approximately 21% of the calories and 20% of the protein in their diet. my country is the world's largest producer and consumer of wheat, with its annual output accounting for about 17% of global production. Wheat production is of great significance for ensuring domestic food security and stabilizing international grain prices. Fungal diseases can cause wheat yield losses of 15% to 20% annually, with Fusarium head blight being particularly severe.

[0003] Fusarium head blight is a widespread fungal disease caused by Fusarium graminearum (Fusarium graminearum). Fusarium graminearum Fusarium head blight is the most important pathogen. Its occurrence leads to shriveled grains, reduced grain weight, and consequently lower wheat yield. More importantly, Fusarium head blight causes toxin contamination, among which deoxynivalenol (DON) is the most common Fusarium toxin found in infected wheat and its products.

[0004] Based on its manifestations, wheat Fusarium head blight resistance can be divided into five categories: Type I (resistance to invasion), Type II (resistance to spreading), Type III (resistance to kernel infection), Type IV (tolerance against FHB and trichothecenes), and Type V (resistance to trichothecene accumulation). Extensive research has been conducted both domestically and internationally on the genetics of Fusarium head blight resistance, identifying over 400 quantitative trait loci (QTLs) for resistance, distributed across all wheat chromosomes and concentrated in 44 chromosomal regions. Among these, resistance genes... Fhb1 - Fhb7 It has been formally named. Located on the short arm of chromosome 3B. Fhb1 It exhibits the strongest and most stable resistance. This gene, which provides resistance to Fusarium head blight extension (Type II), was first discovered in the Chinese wheat variety Sumai 3. Fhb1 This gene originates from a local Taiwanese wheat variety. Several local varieties in the middle and lower reaches of the Yangtze River in my country contain this gene, such as Wangshuibai, Baisanyuehuang, and Huangfangzhu.

[0005] Chinese patent document CN112941232A (application number 202110473947.4) discloses a molecular marker related to wheat Fusarium head blight resistance and its application. Genotype data were obtained using a high-throughput gene chip of wheat (Wheat55K), and a relatively stable locus related to Fusarium head blight resistance, QFhb-6B-YM4, was obtained. The enhancing gene is derived from Yangmai 4, that is, the gene that increases Fusarium head blight resistance and reduces the rate of diseased spikelets comes from Yangmai 4. The QTL peak position is on chromosome 6B at 33.60 cM-34.00 cM, corresponding to the marker interval AX109482211-AX111634185, which is 0.4 cM apart. The position is relatively fine, and the phenotypic contribution rate reaches 11.35%-13.09%. Further, SNP markers were preliminarily screened from QTL intervals based on marker homology. SNP markers with high specificity and the highest correlation with Fusarium head blight resistance were selected for KASP marker transformation. The AX111634185 marker at 27.97 Mb on 6B was found to have the best genomic specificity and the most significant correlation with Fusarium head blight resistance.

[0006] Zhu Zhanwang (“Locating wheat Fusarium head blight resistance genes and developing molecular markers using genome-wide linkage and association analysis”, China Excellent Doctoral and Master's Dissertations Full-text Database (Doctoral) Agricultural Science and Technology Series, 2021) identified Fusarium head blight resistance in a natural population composed of 240 domestic wheat varieties (lines) under four environments. Genotyping was performed using a 90K SNP chip, and genome-wide association study (GWAS) was performed using a mixed linear model with TASSEL software. In addition, Fusarium head blight resistance was identified in a doubled haploid (DH) population of Yangmai 16 / Zhongmai 895 containing 174 families under five environments. Genotyping was performed using a 660K SNP chip, and QTL mapping was performed using IciMapping software. Five relatively stable resistance loci for Fusarium head blight were identified in the natural population, located at 1AS, 2DL, 5AS, 5AL, and 7DS, explaining 5.6%, 10.3%, 5.0%, 5.4%, and 5.6% of the phenotypic variation, respectively. Among these, loci 5AS, 5AL, and 7DS may be novel resistance loci. Seven stable QTLs for Fusarium head blight resistance were detected in the Yangmai 16 / Zhongmai 895 population. QFhb.caas-4AS , QFhb.caas-5AL and QFhb.caas-6BS This could be a new site. QFhb.caas-4BS and QFhb.caas-4DS They should be dwarf stalk sites respectively. Rht-B1 and Rht-D1 And it was associated with anther extrusion (AE). A method was developed... FHB-1AS-STS , FHB-5AS-KASP , FHB-5AL-CAPS , InDel_AX-89588684 and KASP_ AX-110917097 Five PCR markers linked to anti-Fusarium graminearum loci.

[0007] Discovering more QTL sites for wheat resistance to Fusarium head blight and developing them into linked molecular markers for use in breeding is crucial for marker-assisted selection of wheat with varying degrees of resistance to Fusarium head blight. Summary of the Invention

[0008] To address the shortcomings of existing technologies, this invention provides a wheat scab resistance QTL. Qfhb.sdau-1BL KASP molecular markers and their applications.

[0009] The technical solution of the present invention is as follows:

[0010] A wheat scab resistance QTL Qfhb.sdau-1BL KASP molecular markers, the QTL Qfhb.sdau-1BL Located on chromosome 1BL, specifically at positions 401-406 Mb; the KASP molecular marker is KASP-QFhb.sdau-1B.15 The specific location is 406306877, and the KASP molecular marker is... KASP-QFhb.sdau-1B.15 The SNP site base variation is an A / G variation, and wheat materials containing the GG base have better resistance to Fusarium head blight than wheat materials containing the AA base.

[0011] A wheat scab resistance QTL Qfhb.sdau-1BL Primers for the KASP molecular marker, comprising two forward primers with nucleotide sequences as shown in SEQ ID NO.1 and SEQ ID NO.2, and a reverse universal primer with a nucleotide sequence as shown in SEQ ID NO.3.

[0012] According to a preferred embodiment of the present invention, different fluorescent detection sequences are added before the two forward primer sequences.

[0013] More preferably, the fluorescence detection sequences are FAM sequence and HEX sequence.

[0014] A wheat scab resistance QTL Qfhb.sdau-1BL The genotyping method involves extracting wheat genomic DNA, performing PCR amplification using primers shown in SEQ ID NO.1, SEQ ID NO.2, and SEQ ID NO.3, and determining the genotype after fluorescence detection.

[0015] A wheat scab resistance QTL Qfhb.sdau-1BL The product is a genotyping product, including detection materials based on the KASP molecular marker.

[0016] According to a preferred embodiment of the present invention, the detection substance comprises primers with the above-mentioned KASP molecular marker.

[0017] The above-mentioned wheat scab resistance QTLs Qfhb.sdau-1BL The application of KASP molecularly labeled detection substances in any of the following:

[0018] (1) To identify or assist in the identification of wheat resistance to Fusarium head blight;

[0019] (2) To prepare products for identification or to assist in the identification of wheat resistance to Fusarium head blight;

[0020] (3) Compare the resistance of wheat grains to Fusarium head blight;

[0021] (4) Select or screen wheat strains or varieties with relatively strong resistance to Fusarium head blight;

[0022] (5) Select or screen wheat lines or varieties with relatively weak resistance to Fusarium head blight;

[0023] (6) Prepare products for screening or comparing the strength of wheat resistance to Fusarium head blight.

[0024] According to a preferred embodiment of the present invention, the detection substance for the KASP molecular marker includes the primers for the aforementioned KASP molecular marker.

[0025] Beneficial effects:

[0026] Pooled transcriptome sequencing (BSR-Seq) is a highly efficient sequencing method combining cluster separation analysis (BSA) and RNA sequencing (RNA-Seq). It can effectively identify significantly differentially expressed loci and predict candidate genes. This invention utilizes BSR-Seq analysis to locate a novel QTL site for wheat resistance to Fusarium head blight on chromosome 1BL (401-406Mb), named... Qfhb.sdau- 1BL KASP molecular markers were developed by screening the above QTL intervals and named... KASP-QFhb.sdau-1B.15 The physical location is 406306877. The aforementioned KASP molecular marker is highly correlated with Fusarium head blight resistance, and this locus can be applied to marker-assisted selection breeding. Therefore, this invention has uncovered a new Fusarium head blight resistance gene, which can provide new gene resources for the breeding of new Fusarium head blight resistant wheat varieties. Attached Figure Description

[0027] Figure 1 A bar chart showing the chromosome distribution of SNP / Indel loci numbers.

[0028] Figure 2The image shows a Manhattan plot of the Δ (SNP-index) chromosome distribution. In the plot, the scatter plot represents the original values, the black curve represents the fitted values, the blue curve represents the 95% confidence interval boundary, and the red curve represents the 99% confidence interval boundary.

[0029] Figure 3 For ED 2 The Manhattan plot shows the chromosome distribution. In the plot, the scatter plot represents the original values, the black curve represents the fitted values, the blue curve represents the 95% confidence interval boundary, and the red curve represents the 99% confidence interval boundary.

[0030] Figure 4 The image shows a Manhattan plot of the Δ (SNP-index) distribution of chromosome 1B. In the plot, the scatter plot represents the original values, the black curve represents the fitted values, the blue curve represents the 95% confidence interval boundary, and the red curve represents the 99% confidence interval boundary.

[0031] Figure 5 ED of chromosome 1B 2 The distribution is shown in the Manhattan plot. In the plot, the scatter plot represents the original values, the black curve represents the fitted values, the blue curve represents the 95% confidence interval boundary, and the red curve represents the 99% confidence interval boundary.

[0032] Figure 6 KASP molecular marker KASP-QFhb.sdau-1B.15 The genotyping results are shown in the figure. In the figure, R represents the individual genotype consistent with the parent Nankang 1 (disease resistant), S represents the individual genotype consistent with the parent Shannong 102 (disease susceptible), and NTC is the negative control.

[0033] Figure 7 KASP molecular marker KASP-QFhb.sdau-1B.15 The genotyping results are shown in the figure. In the figure, R represents the Fusarium head blight resistant strain, S represents the Fusarium head blight susceptible strain, and NTC represents the negative control. Detailed Implementation

[0034] The technical solution of the present invention will be further described below with reference to the embodiments, but the scope of protection of the present invention is not limited thereto. Unless otherwise specified, the reagents and medicines involved in the embodiments are all commercially available products; unless otherwise specified, the experimental operations and steps involved in the embodiments are all conventional operations in the art.

[0035] Biomaterials involved in the embodiments:

[0036] The disease-resistant parent, Nankang 1, and the susceptible parent, Shannong 102, can be obtained from Shandong Agricultural University. The F4 generation population material constructed by crossing Nankang 1 with Shannong 102 consists of 426 lines.

[0037] Fusarium graminearum can be purchased from ordinary commercial channels.

[0038] Example 1 Sample Screening

[0039] Using the F4 generation population constructed from the cross between Nankang 1 and Shannong 102 as samples, wheat was planted in a greenhouse from September 2020 to January 2021 and from March to June 2021. Wheat grains were placed in seedling trays filled with a mixed substrate (nutrient soil: vermiculite: ordinary soil = 1:1:1, by mass). After germination at room temperature for 2 days, the seedlings were placed in a 4℃ light incubator for approximately 35 days of vernalization. The light incubator settings during vernalization are shown in Table 1. After vernalization, the seedlings were transplanted to pots in the greenhouse of Shandong Agricultural University and managed under standard care until maturity.

[0040] Table 1. Vernalization conditions in a light incubator

[0041]

[0042] The population material of Nankang No. 1 × Shannong No. 102 F5:6 generation, planted in greenhouse flowerpots in March 2021, was used. Normal plants at the early flowering stage of wheat were selected, and five ears of wheat of the same line were randomly chosen. Two florets in the middle of each ear were inoculated. A 20 μL suspension of Fusarium graminearum spores (1 μL containing 50 spores) was injected using a microsyringe. The mixture was sprayed with water, bagged, and kept moist for 3 days. After 3 days, the resealable bag was removed.

[0043] The disease incidence was investigated 7 days, 14 days, and 21 days after inoculation, and the number of diseased spikelets was recorded.

[0044] Diseased spikelet rate (DSR) = (Number of infected spikelets / Total number of spikelets per spikelet) × 100%

[0045] The length of the diseased spike rachis (DRL) was measured 21 days after inoculation.

[0046] Resistance gene effect = (Average diseased spikelet rate of materials carrying resistance genes - Average diseased spikelet rate of materials not carrying resistance genes) / Average diseased spikelet rate of materials not carrying resistance genes

[0047] The severity of disease in inoculated wheat materials was investigated, and the classification was based on the People's Republic of China Agricultural Industry Standard (Technical Specification for Evaluation of Wheat Disease and Pest Resistance NY / T 1443.4-2007): Grading of Severity of Wheat Resistance to Fusarium Head Blight and Evaluation Standards, as shown in Tables 2 and 3.

[0048] Table 2. Grading of Fusarium head blight severity and symptom description under single-flower drip inoculation conditions.

[0049]

[0050] Table 3 Evaluation criteria for Fusarium head blight resistance under single-flower drip inoculation conditions.

[0051]

[0052] Phenotypic identification was used to screen 20 highly resistant and 20 highly susceptible strains from the F5:6 generation population of Nankang 1 × Shannong 102. Equal amounts of ear tissue from the highly resistant and highly susceptible strains were mixed to construct two pools for RNA extraction and analysis.

[0053] Example 2 Sequencing Analysis

[0054] The entire process of BSR sequencing sample RNA extraction and quality testing, cDNA library construction and quality control, transcriptome sequencing, sequencing results and data analysis was carried out by Guangzhou Gediao Biotechnology Co., Ltd.

[0055] 1. RNA extraction and quality control

[0056] (1) Sample preparation: Take 20 highly resistant lines and 20 highly susceptible lines respectively. Take equal amounts of ear tissue from each line and mix them well. Construct two pools for RNA extraction: one for disease resistance and one for disease susceptibility. In addition, extract RNA from the ear tissue of the disease-resistant parent Nankang 1 and the disease-susceptible parent Shannong 102.

[0057] (2) Take an appropriate amount of wheat ear tissue, grind it thoroughly in liquid nitrogen environment, transfer it to a 1.5 mL centrifuge tube, add 1 mL of Trizol reagent, mix thoroughly, and place at room temperature for 10 min to allow for complete lysis;

[0058] (3) Add 200µL of chloroform, shake well to mix, centrifuge at 4℃ and 12000r / min for 10min;

[0059] (4) Take the supernatant, add an equal volume of phenol:chloroform mixture (25:24, v / v), shake well, centrifuge at 4℃, centrifuge at 12000r / min for 10min;

[0060] (5) Take the supernatant, add an equal volume of chloroform, shake well, centrifuge at 4℃, and centrifuge at 12000r / min for 10min;

[0061] (6) Take the supernatant, add an equal volume of isopropanol, let stand at -20℃ for 1 h, centrifuge at 4℃, and centrifuge at 12000 r / min for 10 min;

[0062] (7) Discard the supernatant, add 1 mL of 75% ethanol, wash the precipitate, centrifuge at 4°C, centrifuge at 8000 r / min for 5 min, discard the supernatant, and repeat twice;

[0063] (8) Place in a fume hood to dry for 2-4 minutes;

[0064] (9) Add 20~50μL RNase-Free Water, dissolve at room temperature for 10min, mix well and then centrifuge briefly;

[0065] (10) The RNA was quality checked by agarose gel electrophoresis, a nanodrop 2000 micro spectrophotometer, and an Agilent 2100. Store at -80℃.

[0066] 2. Construction and quality control of cDNA libraries

[0067] (1) Prepare the first-strand reaction buffer and random primer mixture (2×) (Table 4):

[0068] Table 4. First-chain reaction buffer (Buffer) and random primer mixture (2×)

[0069]

[0070] (2) Isolation of mRNA, fragmentation and addition of primers: eukaryotic mRNA was enriched with magnetic beads with Oligo (dT); 17 µL of the pre-prepared first-strand reaction buffer and random primer mixture (2×) was added to the tube, and the sample was incubated at 95 °C for 15 min to elute the mRNA from the magnetic beads.

[0071] (3) First-strand cDNA synthesis:

[0072] a. Add cDNA first-strand synthesis reagent to the mixture of fragmented and primer-added mRNA. The synthesis system is as follows:

[0073] Table 5 cDNA First-Strand Synthesis System

[0074]

[0075] b. Place the cDNA first-strand synthesis system in a preheated PCR instrument for reaction (overheating temperature: 105℃), synthesis conditions: 25℃ for 10 min, 42℃ for 15 min, 70℃ for 15 min, 4℃.

[0076] c. Immediately begin the second-chain synthesis reaction.

[0077] (4) cDNA second-strand synthesis:

[0078] Add the reagents listed in the table below to the above cDNA first-strand synthesis reaction solution (20 µL) to synthesize the cDNA second strand.

[0079] Table 6. Reagents required for cDNA second-strand synthesis

[0080]

[0081] (5) Preparation of cDNA library fragment ends:

[0082] a. Mix the following reagents in a sterile tube:

[0083] Table 7. Reagents required for cDNA library fragment end preparation

[0084]

[0085] b. Place the mixed reagents into a PCR instrument for reaction (heating temperature 75℃), reaction conditions: 20℃ for 30 min, 65℃ for 30 min, 4℃.

[0086] c. Proceed immediately with the connector connection procedure.

[0087] (6) Connect the connectors:

[0088] a. Add the reagents in the table below directly to the end-of-phase reaction solution (65 μL) from the previous step (Note: Dilute NEBNext Adaptor with Tris-HCl).

[0089] Table 8. Reagents required for connector connection

[0090]

[0091] b. Place in a PCR instrument, 20℃, for 15 min. Close the heat seal.

[0092] (7) Purify the ligation reaction solution

[0093] The reaction solution was diluted with water to 100 μL, purified using AMPure XP Beads, washed with 80% ethanol, eluted with ddH2O, and the eluent was used for the next reaction.

[0094] (8) PCR library amplification

[0095] a. The amplification system for PCR library amplification is shown in the table below:

[0096] Table 9 PCR library amplification system

[0097]

[0098] b. PCR cycling conditions: 98℃ for 30s; 98℃ for 10s, 65℃ for 75s, 12 cycles; 65℃ for 5s.

[0099] (9) Purify the PCR products using AMPure XP Beads (1.0×).

[0100] (10) Document Quality Inspection

[0101] The reagent kit used is the DNA 1000 assay kit (Agilent Technologies, 5067-1504). The DNA 1000 assay kit can detect sample fragments ranging from 25 to 1000 bp in size and 0.1 to 50 ng / µL in concentration.

[0102] The sequencing libraries were analyzed using an Agilent 2100 Bioanalyzer (Agilent, Santa Clara, CA), and library quantification was performed using real-time PCR.

[0103] 3. Illumina sequencing

[0104] Sequencing was performed on a Novaseq 6000 sequencer using the PE150 sequencing strategy.

[0105] 4. Data quality control

[0106] To ensure data quality and reduce interference from invalid data, the raw data was filtered. The raw sequences were processed using FASTP (version 0.18.0) (Chen... et al. (2018) Quality control was performed to filter low-quality data and obtain high-quality sequences (clean reads).

[0107] The reads filter conditions are as follows:

[0108] (1) Reads containing adapters;

[0109] (2) Reads containing ≥10% of unknown nucleotides (N);

[0110] (3) Reads that are all A bases;

[0111] (4) Low-quality reads (more than 50% of the reads have a quality value of Q≤20).

[0112] After the data is filtered, the composition and mass distribution of the bases are analyzed to visually demonstrate the data quality.

[0113] The results showed that 76,162,892, 62,759,864 and 74,168,292, 63,300,060 original sequences were generated from the resistant parent, susceptible parent, and resistant-susceptible pools, respectively. After filtering, 75,748,704, 62,419,952 and 73,748,806, 62,946,928 high-quality sequences were obtained, accounting for 99.43-99.46% of the total. Other invalid sequences accounted for a small percentage (Table 10).

[0114] Table 10 Data Filtering Statistics Table

[0115]

[0116] Note: The percentages are based on the proportion of the original sequence.

[0117] The anti-parent, susceptible, and anti-susceptible pools produced 11,424,433,800, 9,413,979,600, and 11,125,243,800, 9,495,009,000 bp of raw bases, respectively. After filtration, 11,322,396,712, 9,331,792,559, and 11,025,171,867, 9,414,154,647 bp of high-quality bases were obtained. The GC content after filtration was 51.56-52.02%, the sequencing quality ≥Q20 was 97.85-98.02%, and ≥Q30 was 94.09-94.55%, indicating good sequencing quality that met the requirements for subsequent analysis (Table 11).

[0118] Table 11 Base Information Statistics Table

[0119]

[0120] 5. Sequence alignment analysis

[0121] To eliminate the influence of residual rRNA, the short read alignment tool bowtie2 (Langmead et al., 2012) was used to align high-quality sequences (clean reads) to a wheat ribosome database. Reads that were aligned to ribosomes were removed, and the remaining unmapped reads were termed valid sequences. The alignment software HISAT2 (Daehwan) was used. et al. (2015) The effective sequences were aligned to the Chinese Spring reference genome (IWGSC_RefSeq_v2.1), the alignment rate and the chromosome distribution of the sequences were statistically analyzed, and the uniquely aligned sequences were analyzed.

[0122] Comparative analysis showed that 62,840,849, 51,567,191 and 63,774,745, 52,458,768 sequences from the resistant parent, susceptible parent, and resistant-susceptible pool were uniquely aligned to the reference genome, respectively. The proportions of these sequences varied between 82.83% and 86.71% across the four samples (Table 12).

[0123] Table 12 Comparison Reference Statistics

[0124]

[0125] Note: The number of reads after filtering ribosomes is called the effective sequence.

[0126] 6. Genomic variation detection

[0127] For uniquely mapped reads, chromosome sorting and repetitive sequence removal were performed on the alignment results using the variant detection software GATK (version 3.4-46) (DePristo). et al SNP detection was performed using ANNOVAR (version 2) (Wang, 2011), and ANNOVAR (version 2) was used. et al. (2010) Functional annotations were added to the detected Variant.

[0128] To minimize background noise, SNP / Indel sites were filtered according to the following criteria, and sites meeting the following conditions were used for subsequent BSA analysis:

[0129] (1) When both parents exist, there must be differences between the parents and the segregation pattern must conform to the population type (the segregation pattern of the markers retained in the F1 population is nn×np, lm×ll, hk×hk, and the segregation pattern of the markers retained in other populations is aa×bb).

[0130] (2) When the parents are present, the sequencing depth of (both) parents must be greater than or equal to the given threshold. The threshold used in this analysis is 5×.

[0131] (3) Neither offspring pool is missing;

[0132] (4) The sequencing depth of each progeny pool should be greater than 10× and less than 500×;

[0133] (5) At least one offspring pool has an SNP-index greater than 0.3;

[0134] (6) At least one offspring pool has an SNP-index less than 0.7.

[0135] SNP and Indel variant detection was performed using the GATK4 software, and the data were statistically analyzed, yielding a total of 725,683 loci, including 692,717 SNP loci and 32,966 Indel loci (Table 13). To minimize background noise, SNP / Indel loci were filtered according to standards, resulting in 30,289 SNP / Indel loci, of which 30,109 were located on 21 chromosomes, accounting for 99.40% (Table 14). Figure 1 The number of SNP sites detected in the D genome is less than that in the A and B genomes. The B genome has the most SNP sites, with 15,172. The most are found in 5B and 1B, with 3,256 and 3,214 respectively. The fewest are found in 3D and 4D, with 188 and 131 respectively.

[0136] Table 13 Statistical results of SNP / Indel loci number

[0137]

[0138] Table 14 Statistics of the number of tags before and after filtering

[0139]

[0140] 7. BSA Analysis Method Based on SNP-index

[0141] Parental segregating SNPs will be screened from the population as molecular markers for subsequent QTL mapping using BSA (QTL-seq). Sliding window analysis will be used to calculate the frequency distribution of SNPs in the progeny samples, which is the progeny SNP-index. To reduce interference from windows with fewer than 10 SNPs in the sliding window analysis, the number of SNPs in each window across the entire genome will be counted first. The proportion of windows with ≥10 SNPs will be calculated, and a window size of 400kb (>95%) will be selected as the analysis parameter. Based on the SNP density distribution, with a window size of 400kb and a sliding step of 20kb, the frequency distribution of SNPs in the pooled samples will be calculated, which is the progeny SNP-index. A Manhattan plot will be used to visually represent the distribution of the pooled SNP-index on the chromosome. The mean SNP index for each window's SNP marker locus will be calculated, and a fitted curve will be plotted. The difference between the two pooled SNP-index values ​​will be calculated as Δ(SNP-index). The calculation process involved 1000 permutation tests to obtain the 95% and 99% confidence intervals (Δ(SNP index)) for each locus and window. Across the entire genome, peak regions exceeding the 95% confidence interval were selected as candidate regions, and SNPs / InDels within these candidate regions were annotated to screen for potential candidate functional mutations.

[0142] The SNP-index is calculated as follows:

[0143] The SNP-index of a specific locus is calculated as ρ(recessive) / (ρ(dominant) + ρ(recessive)).

[0144] ρ represents the depth of the locus in the mixed pool. When dominance and recessiveness can be clearly determined, Δ (SNP-index) has a clear directionality. A positive value indicates that the proportion of recessive alleles (or mutant alleles) in the recessive pool is higher than that in the dominant pool, which is usually the direction we are interested in. A negative value indicates that the proportion of recessive alleles (or mutant alleles) in the dominant pool is higher than that in the recessive pool.

[0145] 8. BSA Analysis Method Based on ED Method

[0146] The Euclidean Distance (ED) algorithm uses sequencing data to identify markers with significant differences between two pools. The calculation formula is shown below; a larger ED value indicates a greater difference in the marker between the two pools.

[0147] The formula for calculating the Euclidean distance is as follows:

[0148]

[0149] Where mut and wt represent recessive / mutant pools and dominant / wild-type pools, respectively, and A, C, G, and T represent the coverage depth of each allele. In order to widen the gap between the small and large values ​​and thus eliminate background noise, the original ED values ​​are usually exponentialized. The ED values ​​mentioned in this article refer to the results after exponentiation.

[0150] BSA analysis results based on SNP-index and ED method:

[0151] To reduce background noise, the calculated Δ(SNP-index) and ED method results were fitted using a sliding window method. The window size used in the sliding window was 2000kb, and the step size was 20kb. A window with 10 or more SNPs was considered a valid window; if the number of SNPs was insufficient, the results of that window were merged into the next window. The statistics of the number of valid sliding windows for SNP-index and ED results are shown in Table 15.

[0152] Table 15 Statistics on the number of effective sliding windows for SNP-index and ED method related indicators

[0153]

[0154] To visually represent the distribution of Δ (SNP-index) and the square of the original ED on the chromosome, a Manhattan plot is used to illustrate it. Figure 2 and Figure 3 The SNP-index (Δ) was filtered based on whether the fitted peak value within the sliding window was ≥0.55 or ≤-0.55, resulting in 32 valid windows. For ED... 2 Screening was performed using a sliding window fitting peak value ≥0.6 as a criterion, resulting in 42 valid windows. Combining two analysis methods, a new candidate QTL region was identified, located on chromosome 1BL, specifically 1BL (401-406 Mb). Figures 4-5 ), named Qfhb.sdau-1BL There is one SNP site in this QTL region, with a physical location of 406306877, which shows an A / G base mutation and is named [name missing]. KASP-QFhb.sdau-1B.15 Furthermore, within the candidate QTL region located on chromosome 3B, there are 395 SNP / Indel loci at a 95% confidence interval. Analysis indicates that this QTL region contains a major gene for resistance to Fusarium head blight. Fhb1 This also verified the results of the molecular markers.

[0155] Example 3: KASP primer design and genotyping detection

[0156] To further verify the relationship between the sites detected by BSR-Seq and wheat scab resistance, SNP sites on 1BL were selected, and KASP primers were designed using the sequences at both ends of these sites. The results were validated in parents and populations. Based on the physical location of the SNP sites, the sequences 100 bp before and after the SNP sites were obtained from the Wheat Research Consortium multi-omics data website (http: / / 202.194.139.32 / #). The locations and sequences of the SNP sites are detailed in Table 16, and the nucleotide sequences of the SNP sequences are shown in SEQ ID NO.4.

[0157] Table 16 SNP molecular marker sequences and base variations

[0158]

[0159] KASP primers were designed for the SNP molecular marker sequences using the Polymarker website (http: / / polymarker.tgac.ac.uk / ) (Table 17). After primer design, a fluorescence detection sequence was added before the two forward primer sequences:

[0160] FAM sequence: GAAGGTGACCAAGTTCATGCT,

[0161] HEX sequence: GAAGGTCGGAGTCAACGGATT.

[0162] The primers were sent to Qingdao Sangon Biotech Co., Ltd. for synthesis.

[0163] Table 17 KASP Primer Sequences

[0164]

[0165] The specific experimental procedures for genotyping testing are as follows:

[0166] (1) Primer dissolution and mixing: Dilute each primer to 100 μM with ultrapure water and mix the primers according to the volume ratio of upstream primer 1: upstream primer 2: downstream primer: ultrapure water / buffer solution = 6: 6: 15: 13;

[0167] (2) Preparation of PCR system: The total volume of the amplification system is 10.0825 μL. The specific sample addition is shown in Table 18, and the PCR amplification program is shown in Table 19.

[0168] Table 18 PCR Amplification System

[0169]

[0170] Table 19 PCR Amplification Procedure

[0171]

[0172] (3) Fluorescence detection: The fluorescence signal was detected by the real-time fluorescence quantitative PCR system to determine the genotype of each strain, and the genotyping results were exported by Launch Kluster Caller software;

[0173] (4) Phenotypic test: The correlation between the genotyping data and the greenhouse phenotypic identification results in spring 2021 was analyzed using SPSS software (version 26) to determine the association between SNP sites and wheat scab resistance and to test the reliability of the localization interval.

[0174] The results showed that the QTLs derived from Fusarium head blight resistance... Qfhb.sdau-1BL KASP molecular markers in the interval KASP- QFhb.sdau-1B.15 The classification results were good (Table 20). Figure 6 Correlation analysis between KASP test results and phenotypic traits revealed highly significant differences in phenotypic traits among different genotypes in the population. P< 0.01). KASP molecular marker. KASP- QFhb.sdau-1B.15 The SNP site base variation was an A / G variation, with wheat materials containing the GG base showing better resistance to Fusarium head blight than those containing the AA base (Table 21). The genotyping results fully demonstrate the reliability of this KASP molecular marker and its high correlation with Fusarium head blight resistance, suggesting that this KASP molecular marker can be applied to marker-assisted selection breeding.

[0175] Table 20 Correlation Tests of KASP Primers

[0176]

[0177] Note: **At the 0.01 level (two-tailed), the correlation is significant.

[0178] Table 21. Base types of SNP base variations in disease-resistant and disease-susceptible materials

[0179]

[0180] Example 4: Label Verification

[0181] Experimental materials: Twenty wheat varieties from our research group were planted in the agronomic experimental field of Shandong Agricultural University from 2022 to 2023. Each variety was planted in four rows, with a row length of 1.2 meters and a row width of 25 cm, and 40 grains per row; three replicates were performed. The flowering period was closely monitored after heading; single-floret drip identification was performed on spikelets that had just begun to flower. The identification methods and resistance investigation and evaluation methods were the same as in Example 1.

[0182] Table 22 Disease Resistance Survey of Wheat Varieties

[0183]

[0184] Based on the survey of Fusarium head blight resistance after single-flower drip irrigation (Table 22), it was found that KASP-QFhb.sdau-1B.15 The molecular marker typing is consistent with the Fusarium head blight phenotype. Figure 7 Therefore, this KASP molecular marker can be used for molecular-assisted selection of wheat varieties resistant to Fusarium head blight.

Claims

1. A wheat scab resistance QTL Qfhb.sdau-1BL The KASP molecular marker, characterized by, The QTL Qfhb.sdau-1BL Located on chromosome 1BL, specifically at position 401-406Mb; the nucleotide sequence of the KASP molecular marker is shown in SEQ ID NO.4, and the 101st nucleotide of the KASP molecular marker nucleotide sequence is its SNP site. The base variation at the SNP site is an A / G variation. Wheat materials containing the GG base have better resistance to Fusarium head blight than wheat materials containing the AA base.

2. A wheat scab resistance QTL as described in claim 1 Qfhb.sdau-1BL Amplification primers for the KASP molecular marker, characterized in that, The amplification primers include two forward primers with nucleotide sequences as shown in SEQ ID NO.1 and SEQ ID NO.2, and one reverse universal primer with a nucleotide sequence as shown in SEQ ID NO.

3.

3. The amplification primers for the KASP molecular marker as described in claim 2, characterized in that, Different fluorescence detection sequences are added before the two forward primer sequences.

4. The amplification primers for the KASP molecular marker as described in claim 3, characterized in that, The fluorescence detection sequences are the FAM sequence and the HEX sequence, respectively.

5. A wheat scab resistance QTL based on claim 1 Qfhb.sdau-1BL The KASP molecular marker-based genotyping method is characterized by, Wheat genomic DNA was extracted and PCR amplified using primers shown in SEQ ID NO.1, SEQ ID NO.2, and SEQ ID NO.

3. Genotyping was determined after fluorescence detection. Wheat materials with GG bases at the SNP sites of the KASP molecular marker showed better resistance to Fusarium head blight than wheat materials with AA bases.

6. A wheat scab resistance QTL based on claim 1 Qfhb.sdau-1BL The KASP molecular marker genotyping product is characterized by, Amplification primers for the KASP molecular marker as described in claim 1.

7. The genotyping product as described in claim 6, characterized in that, The amplification primers include the amplification primers of the KASP molecular marker as described in any one of claims 2 to 4.

8. The wheat scab resistance QTL as described in claim 1 Qfhb.sdau-1BL The application of KASP molecularly labeled detection substances in any of the following: (1) To identify or assist in the identification of wheat resistance to Fusarium head blight; (2) To prepare products for identification or to assist in the identification of wheat resistance to Fusarium head blight; (3) Compare the resistance of wheat grains to Fusarium head blight; (4) Select or screen wheat lines or varieties with relatively strong resistance to Fusarium head blight; (5) Prepare products for screening or comparing the resistance of wheat to Fusarium head blight; The detection substance includes the amplification primers for the KASP molecular marker as described in claim 1.

9. The application as described in claim 8, characterized in that, The amplification primers for the KASP molecular marker include the amplification primers for the KASP molecular marker as described in any one of claims 2 to 4.

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