Wheat yield kasp molecular marker, primer and application thereof

Abstract

This invention belongs to the field of wheat germplasm resource identification technology, specifically involving KASP molecular markers for wheat yield, primers, and their applications. This invention identified six multi-environmentally stable MTAs in a hotspot region of chromosome 4D (16.15–19.70 Mb). Haplotype analysis further showed that allelic variations at these loci were highly significantly correlated with plant height and spikelet length phenotypes. Therefore, this invention successfully developed three KASP markers that can be used for breeding. K‑4D_16159705 , K‑4D_ 16388958 and K‑4D_17341225 Materials carrying superior allelic variations all exhibited reduced plant height, shortened internode length below the ear, and increased thousand-grain weight.

Description

Technical Field

[0001] This invention belongs to the field of wheat germplasm resource identification technology, specifically involving KASP molecular markers for wheat yield, primers, and their applications. Background Technology

[0002] wheat( Triticum aestivum Wheat (L.) is one of my country's staple crops, and extreme drought can lead to reduced wheat yields. Therefore, in-depth analysis of the genetic basis of key agronomic traits in wheat under drought stress and the cultivation of drought-resistant, high-yielding, and stable-yielding new wheat varieties are of great significance to ensuring national food security.

[0003] Plant height and its key component, the sub-ear node, directly affect wheat yield and drought response, making them crucial traits for high-yield breeding and drought-resistant genetic improvement. Plant height directly determines lodging resistance, canopy structure, and grain yield. Under normal irrigation conditions, appropriately reducing plant height can enhance stem lodging resistance, optimize light use efficiency, and improve water use efficiency, thereby effectively increasing wheat yield. However, under drought stress, excessively low wheat plant height leads to a significant reduction in biomass and an imbalance in source-sink relationships, resulting in yield reduction. Therefore, maintaining a reasonable wheat plant height under drought conditions is key to minimizing yield loss. The sub-ear node, the stem portion from the base of the ear to the petiole of the flag leaf, contributes the most to plant height and is a key trait controlling wheat plant height. It is also an important nutrient supply organ for ear development, and its length is closely related to yield traits. The length of the lower internode is also significantly associated with drought resistance. Under drought stress, drought-resistant varieties accumulate more soluble carbohydrates in the lower internode and transport them to the grains, thus compensating for wheat grain yield loss. Simultaneously, by regulating plant physiological metabolism, they improve water use efficiency, thereby reducing the damage to normal growth and development caused by drought stress. Therefore, identifying new regulatory sites for plant height and lower internode length is of great significance for improving wheat yield under drought conditions.

[0004] Studies have shown that plant height and the lower internode are typical quantitative traits, and their development is significantly influenced by multi-gene regulation and environmental interactions. To date, 27 dwarfing genes have been identified and named through quantitative trait locus (QTL) mapping analysis and genome-wide association study (GWAS). Rht-B1b ( Rht1 ), Rht-D1b ( Rht2 ) is a major dwarf gene that is widely used in breeding. Rht1 and Rht2The gene encodes the DELLA protein in the gibberellin signaling pathway. Mutant alleles of this gene are insensitive to gibberellin and remain stable, leading to dwarfing of wheat and increased harvest index. However, varieties carrying this gene exhibit negative effects such as low nitrogen use efficiency and low yields in dryland cultivation. Several alternatives have been identified. Rht1 / 2 Furthermore, there are no genes for plant height with significant negative effects. This has been confirmed by Kroupin et al. Ppd-D1a Genes indirectly reduce plant height and increase thousand-seed weight by shortening the vegetative growth period. Zhang et al. found that genes located on chromosome 2DS... Rht8 The gene reduces plant height by decreasing sensitivity to brassinolide, and it is proposed that... Rht8 and Ppd-D1a It can synergistically regulate plant height and significantly increase the number of fertile spikelets, thereby ensuring stable yield under drought stress. Liu et al. cloned a key gene that specifically regulates the elongation of the lower internode using GWAS analysis. TaPL1 Its excellent allelic variation ( TaPL1-K These genes can achieve multiple beneficial effects, such as shortening the lower internode, reducing plant height, and increasing thousand-grain weight. However, most of these genes are concentrated on wheat plant height and its effects on other agronomic traits. The functions of most genetic loci under extreme drought stress and complex field conditions have not yet been verified, and there is still a shortage of superior plant height gene resources in dryland wheat breeding.

[0005] With the widespread adoption of high-throughput genotyping technology and the continuous improvement of reference genomes, QTL mapping and GWAS analysis have become the main strategies for elucidating complex quantitative traits in wheat. Compared to traditional QTL mapping based on parental cross populations, GWAS can directly utilize the rich genetic variation and historically accumulated linkage disequilibrium in natural populations to effectively mine trait-associated loci across the entire genome using high throughput and high resolution, and effectively resolve marker-trait association (MTA) loci in multiple environments. Currently, GWAS analysis has identified several genes and loci related to traits such as wheat plant height, yield, and thousand-grain weight, such as... TaF-box-7A , TaBSK2-1A , QPh.nwafu-4B.3 and QTkw.nwafu-6A They also analyzed the relevant genetic mechanisms.

[0006] Although GWAS research has made a series of important advances in the genetic analysis of wheat yield traits and the discovery of key genes, there are still problems such as insufficient primer specificity, non-specific amplification and false positives due to the complexity of the wheat allohexaploid genome, as well as the low detection rate of some superior alleles. Its gene discovery and functional mechanism research in wheat yield regulation are still relatively lagging behind, and its application potential in breeding has not yet been fully demonstrated.

[0007] Therefore, plant height and its key component, the pre-ear node, are crucial traits for high-yield breeding and drought resistance genetic improvement in wheat, and their stable formation ability is a key factor affecting yield resilience. Developing functional molecular markers targeting plant height and pre-ear node traits is of great significance for promoting yield genetic improvement and provides important theoretical support for high-yield and stable wheat breeding. Summary of the Invention

[0008] To address the aforementioned technical problems, this invention provides KASP molecular markers for wheat yield, primers, and their applications.

[0009] KASP molecular markers for wheat yield, the molecular markers being based on 4D_16159705 Molecular markers based on sites 4D_16388958 Molecular markers at sites or based on 4D_17341225 Molecular markers at the site; based on 4D_16159705 The nucleotide sequence of the molecular marker at the site is shown in SEQ ID NO.1. The degenerate base R at position 6 of the nucleotide sequence is an SNP site with polymorphism A or G. When the polymorphism is A, the haplotype of wheat is HapⅠ, and when the polymorphism is G, the haplotype of wheat is HapⅡ. based on 4D_16388958 The nucleotide sequence of the molecular marker at the site is shown in SEQ ID NO.2. The degenerate base S at position 6 of the nucleotide sequence is an SNP site with a polymorphism of C or G. When the polymorphism is C, the haplotype of wheat is HapⅠ, and when the polymorphism is G, the haplotype of wheat is HapⅡ. based on 4D_17341225 The nucleotide sequence of the molecular marker at the site is shown in SEQ ID NO.3. The degenerate base M at position 6 of the nucleotide sequence is an SNP site with polymorphism C or A. When the polymorphism is C, the haplotype of wheat is HapⅠ, and when the polymorphism is A, the haplotype of wheat is HapⅡ. Wheat yields of haplotype HapⅠ are lower than those of haplotype HapⅡ.

[0010] This invention identified six environmentally stable MTAs in a hotspot region of chromosome 4D, ranging from 16.15 to 19.70 Mb. These six SNP markers can be divided into two haplotypes in the tested materials: HapⅠ and HapⅡ. The genotypes of the six SNPs in haplotype HapⅠ are AA, CC, CC, TT, CC, and GG, while the genotypes of haplotype HapⅡ are GG, GG, AA, CC, GG, and AA. Haplotype analysis showed that the allelic variations at these loci were significantly correlated with plant height, length of internode below the spike, and yield. High-throughput genotyping was performed on 373 wheat natural population varieties (lines), and the two haplotypes were successfully distinguished based on the genotyping results of the molecular markers.

[0011] A specific primer for amplifying the molecular marker, based on 4D_16159705 The primers for the site include upstream primers as shown in SEQ ID NO.4 and SEQ ID NO.5, and downstream primers as shown in SEQ ID NO.6; based on 4D_16388958 The primers for the site include upstream primers as shown in SEQ ID NO.7 and SEQ ID NO.8, and downstream primers as shown in SEQ ID NO.9; based on 4D_17341225 The primers for the site include upstream primers as shown in SEQ ID NO.10 and SEQ ID NO.11, and downstream primers as shown in SEQ ID NO.12.

[0012] A kit for detecting wheat yield traits, the kit comprising any one of the specific primers described herein.

[0013] The application of the molecular marker, the specific primer, or the kit in identifying wheat yield.

[0014] Preferably, the steps for determining wheat yield are as follows: (1) Extract genomic DNA from the wheat to be tested; (2) Using the extracted DNA as a template, amplification is performed using the specific primers described in claim 4 to obtain the amplification product; (3) Identify the amplification products 4D_16159705 , 4D_16388958 or 4D_17341225 The genotype at the locus is used to determine the yield of the wheat being tested.

[0015] Preferably, the wheat yield refers to the thousand-grain weight of wheat.

[0016] The application of the molecular marker, the specific primer, or the kit in wheat breeding or wheat-assisted breeding, wherein the wheat-assisted breeding is for cultivating high-yielding wheat.

[0017] The application of the molecular marker, the specific primer, or the kit in identifying wheat plant type traits, wherein the plant type trait refers to the plant height or the length of the internode below the ear of wheat; The plant height of wheat with haplotype HapⅠ is shorter than that of wheat with haplotype HapⅡ, and the length of the lower internode of wheat with haplotype HapⅠ is shorter than that of wheat with haplotype HapⅡ.

[0018] Compared with the prior art, the beneficial effects of the present invention are as follows: In this invention, six environmentally stable MTAs were identified in the hotspot region of chromosome 4D, ranging from 16.15 to 19.70 Mb. Haplotype analysis further showed that allelic variations at these loci were highly significantly correlated with plant height and length of the lower internode. P< 0.001). Therefore, this invention has successfully developed three KASP markers that can be used for breeding. K-4D_16159705 , K-4D 16388958 and K-4D_17341225 Materials carrying superior allelic variations all exhibited reduced plant height and shortened internode length below the spike, providing key technical support for molecular marker-assisted selection for improving plant architecture in dryland wheat. Attached Figure Description

[0019] Figure 1 Monthly and total rainfall during different environmental periods for the natural wheat population and the KASP validation population are given, where A represents monthly rainfall and B represents total rainfall.

[0020] Figure 2 The phenotypic frequency distribution of PH and PL in natural wheat populations under different environmental conditions.

[0021] Figure 3 Heatmaps showing the correlation between pH and PL in natural wheat populations under different environmental conditions and the correlation between different traits (SL: spike length, GNS: yield, TKW: thousand-grain weight).

[0022] Figure 4 The distribution of high-quality SNPs on 21 chromosomes of a natural wheat population.

[0023] Figure 5 For different subgroup germplasm types and varietal sources.

[0024] Figure 6 The structural analysis of 215 natural wheat populations is presented. In this analysis, A represents the CV error value obtained through ADMIXTURE analysis; B represents the phenotypic differences between groups PH and PL; and C represents the population structure of the 215 natural wheat populations.

[0025] Figure 7 The LD decay curves of natural wheat population materials at the whole genome level are shown.

[0026] Figure 8 Manhattan plot and QQ plot for GWAS analysis of pH and PL in different environments.

[0027] Figure 9 LD Block analysis of significant SNPs associated with PH and PL.

[0028] Figure 10Haplotype analysis of PH, PL, and TKW-related SNP sites.

[0029] Figure 11 For the molecular marker validation results, A is... K-4D_16159705 , K-4D_16388958 and K-4D_17341225 Genotyping; B is the significance test of PH and PL phenotypic traits.

[0030] Figure 12 for K-4D_16388958 The distribution frequency of two haplotypes in different years of varieties bred in major wheat-growing areas of my country was marked. Detailed Implementation

[0031] The specific embodiments of the present invention are described in detail below, but it should be understood that the scope of protection of the present invention is not limited to the specific embodiments. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without inventive effort are within the scope of protection of the present invention. Unless otherwise specified, the experimental methods described in the embodiments of the present invention are conventional methods.

[0032] 1. Wheat materials and field trials This invention collected 215 wheat natural populations (lines) (Table 1) for GWAS analysis, including 8 local varieties, 13 bred lines, and 194 modern bred varieties. Simultaneously, a natural population consisting of 373 wheat varieties (lines) (Table 2) was selected for KASP molecular marker validation. All materials were sourced from different arid and semi-arid wheat-growing regions both domestically and internationally, reflecting the genetic diversity of germplasm resources.

[0033] Table 1: Variety names and sources of 215 natural wheat populations Table 2: Variety names and sources of 373 wheat KASP validation population materials 215 natural wheat varieties (lines) were planted in Wujiachuan Wheat Experiment Station (E1) (35° 11′ N, 105° 19′ E) in Tongwei County, Gansu Province in 2020-2021, in Nanhu Wheat Experiment Station (E2) (35°34′ N, 105° 96′ E) in Zhuanglang County in 2022-2023, and in Zhongliang Wheat Experiment Station (E3) (34° 58′ N, 105° 72′ E) and Nanhu Wheat Experiment Station (E4) in Zhuanglang County in 2023-2024.

[0034] The 373 natural wheat populations used for KASP molecular marker validation were planted at the Zhuanglang County Nanhu Wheat Experimental Station in 2023-2024, and at the Zhuanglang County Nanhu Wheat Experimental Station and Ningxian County Hesheng Wheat Experimental Station (35°24′ N, 105°50′ E) in 2024-2025, respectively. These environments were designated E5, E6, and E7. These areas are located in the southern part of the Loess Plateau, a continuous loess hilly and gully region, and all have a typical temperate semi-arid monsoon climate. During the experiment, the planting environment relied entirely on natural rainfall, and no artificial irrigation was applied throughout the entire growth period. Data from local meteorological stations (or designated monitoring points) showed that rainfall in each environment during the wheat growing season ranged from 225.2 (E4) to 303.5 (E2) mm. Figure 1 ).

[0035] Each material was planted in 4 rows, 1m long, with a row spacing of 20cm, and 20 seeds were sown per row. Field management followed local wheat production practices. At wheat maturity, the main stems of 5 wheat plants were randomly selected for plant height (PH) and peduncle length (PL). After harvesting the grains, they were air-dried, and the thousand-grain weight (TKW) of different varieties (lines) was measured. The phenotypic mean values ​​of the above traits under different drought conditions were calculated.

[0036] DNA was extracted from young leaves of 215 wheat natural populations and 373 wheat KASP molecular marker verification natural population varieties (lines) using the CTAB method. After concentration detection, the DNA was homogenized to a uniform concentration of 15 ng / μL and stored at -20℃ for later use. The DNA was then used for genotyping on a 100K SNP microarray and for KASP molecular marker verification.

[0037] 2. Phenotypic Data Analysis Using "in R" lme4 "The Mixed Linear Model (MLM) of the package, combined with..." lsmeans The package calculates the best linear unbiased estimates (BLUEs) of cross-environment phenotypic data using genotype and environment as random factors (v4.4.1). BLUEs for PH and PL are treated as independent environments for further analysis. The package uses R's " ggplot2 The software package was used for visualization, generating histograms of phenotypic distributions for PH and PL. The CorrelationPlot v1.31 tool in Origin 2024 (https: / / www.originlab.com / FileExchange / details.aspx?fid=574) was used to analyze the correlation between PH and PL in different environments. One-way ANOVA was performed using IBM SPSS Statistics (v29.0.2.0) (https: / / www.ibm.com / cn-zh / products / spss-statistics) to calculate the generalized heritability of each trait using phenotypic data for each variety under different environments. h² B The formula for calculating heritability follows Toker's method.

[0038] 3. SNP genotyping Genotyping of 215 wheat natural populations was performed using a 100K SNP liquid phase chip (Borde Biotechnology Co., Ltd.). Quality control of the genotypic data was performed using PLINK software, removing markers with SNP deletion rates ≥20%; discarding markers with deletion rates ≥5%; and screening out markers with minor allele frequencies ≤2%.

[0039] 4. Linkage Disequilibrium (LD) and Population Structure Analysis Use PopLDdecay to calculate the pairwise squared correlation coefficient between SNPs. r ²), and specified the parameter "-MaxDist50000" to test LD decay. In order to evaluate the population structure of 215 natural wheat population materials, the cross-validation error at K values ​​(K=2-15) was calculated using ADMIXTURE software (v1.3.0) to evaluate the population clustering results and thus determine the optimal number of clusters (K).

[0040] 5. Genome-wide association analysis GWAS analysis was performed using phenotypic data and best linear unbiased estimates (BLUEs) from 215 natural wheat populations. Associations between traits and polymorphic markers were analyzed using... GAPIT-R v3.4The MLM model in the software package was statistically analyzed. The first three principal components of the MLM model were used as fixed factors, and the kinship matrix as a random factor, balancing statistical power and mixed effects while ensuring computational efficiency. The significance threshold for MTA was set to [value missing]. -log 10 ( p SNP markers detected in two or more environments are considered multi-environment stable MTAs. Important MTAs are BLAST-aligned in the Wheat Omics v2.1 database (https: / / wheatomics.sdau.edu.cn) for functional annotation. R is used for this purpose. CMplot The software package (https: / / github.com / YinLiLin / CMplot) plots Manhattan plots and QQ plots to visualize the distribution of saliency markers and evaluate the results of association analysis.

[0041] 6. Haplotype analysis LDBlock analysis was performed using Haploview (https: / / sourceforge.net / projects / haploview / ) to identify haplotypes by analyzing genotype-phenotype differences at marker loci in different populations, thus characterizing genetic variation among varieties (lines).

[0042] 7. KASP marker development and genotyping For the selected SNP marker sites, KASP primers were designed according to the FLU-ARMS for KASP technical manual (https: / / www.goodbtk.com / newsitem / 173442) (Table 3), and the primer specificity was verified on the wheat multi-omics website (http: / / wheatomics.sdau.edu.cn / blast / blast.html). The primers were synthesized by Sangon Biotech (Shanghai) Co., Ltd. Simultaneously, a natural population consisting of 373 wheat accessions (lines) was used for KASP molecular marker verification. Genotyping was performed using a high-throughput fully automated genotyping system (GeneMatrix Pro, Chengdu Hancheng Guangyi), and the results were visualized by identifying the FAM / HEX fluorescent markers of the products. The results were analyzed based on the images.

[0043] Table 3: KASP molecular marker names and primer sequences result 1. Phenotypic statistical analysis of plant height and lower internode length Statistical analysis of pH and PL values ​​in 215 natural wheat populations under four different drought conditions (Table 4) showed that pH ranged from 41.87 to 139.38 cm, with an average of 79.77 cm and a coefficient of variation (CV) of 17.74% to 20.90%. PL ranged from 12.67 to 53.47 cm, with an average of 29.67 cm and a CV between 18.82% and 23.78%. The phenotypic data for pH and PL showed a clear continuous trend under different drought conditions, making them suitable for GWAS analysis of pH and PL. Figure 2 ).

[0044] Analysis of variance showed that genotype, environment, and the interaction between genotype and environment had a significant impact on the PH and PL traits (Table 5), and the broad-sense heritability of PH and PL was [not specified]. h² B The correlation coefficients were 0.61 and 0.67, respectively, indicating that genetic factors play a major role in the genetic regulation of pH and PL traits, but both are influenced by the environment to some extent. The correlation coefficients between pH and PL in natural wheat populations ranged from 0.48 to 0.95 and 0.50 to 0.90, respectively, and the correlation between pH and PL reached a highly significant level across multiple different drought environments. P< 0.001). This indicates that although the PH and PL phenotypes are dominated by genetic factors, they are still affected by drought conditions. Furthermore, there is a significant positive correlation between PH and PL traits, with a correlation coefficient of 0.83, while the correlation coefficient with thousand-grain weight ranges from -0.26 to -0.31, showing a significant negative correlation. Figure 3 ).

[0045] Table 4: Phenotypic variation analysis of PH and PL in natural wheat populations under different environmental conditions Table 5: Analysis of variance of pH and PL in natural wheat populations ***Significance level P <0.001.

[0046] 2. SNP marker statistical analysis Genotype data obtained from 100K SNP microarray analysis were screened, removing SNP markers with SNP deletion rates ≥20%, sample deletion rates ≥5%, and MAF ≤5%, resulting in 104,254 high-quality SNP markers for GWAS analysis (Table 6). Among these, subgenomes A, B, and D contained 37,776 (36.23%), 36,362 (34.88%), and 30,098 (28.87%) polymorphic SNP markers, respectively. The distribution of polymorphic SNP markers differed significantly among different wheat chromosomes, with chromosome 2A showing the highest number of detected polymorphic SNP markers (6,349) and chromosome 4D showing the lowest (3,492). The total physical map length was 14,221.99 Mb, with genome lengths of A, B, and D being 4,973.86 Mb, 5,247.57 Mb, and 4,000.56 Mb, respectively. The average marker density across the entire chromosome set was 0.14 Mb / SNP, with densities of 0.13 Mb / SNP, 0.14 Mb / SNP, and 0.13 Mb / SNP on subgenomes A, B, and D, respectively. Among the 21 chromosomes, chromosome 1B had the highest marker density at 0.19 Mb / SNP, while chromosome 1A had the lowest density at only 0.12 Mb / SNP. Figure 4 ).

[0047] Table 6: Statistical analysis of 100K SNP chip genotyping markers in natural wheat populations 3. Group Structure Analysis The population structure of 215 natural wheat varieties was analyzed using ADMIXTURE. Based on the K-CV plot, the curve trend slowed down when K=7; therefore, the population was divided into 7 subgroups, namely Groups I-VII. Figure 6 A, Figure 6(C) Group I contains 9 varieties, all of which are bred varieties. They mainly come from Beijing and Henan. Group II contains 18 wheat varieties, including 14 bred varieties and 4 high-generation lines, mainly from Gansu. Group III contains 45 materials, including 41 bred varieties and 4 local varieties, mainly from Shanxi, Gansu, and Beijing. Group IV contains 46 wheat materials, including 39 bred varieties, 2 local varieties, and 4 high-generation lines, mainly from Gansu. Group V contains 43 wheat materials, including 39 bred varieties, 3 high-generation lines, and 1 local variety, mainly from Gansu and Beijing. Group VI contains 22 wheat materials, all of which are bred varieties, mainly from Beijing. Group VII contains 32 wheat materials, including 30 bred varieties, 1 local variety, and 1 high-generation line, mainly from Shanxi and Shaanxi provinces. Figure 5 Statistical analysis of the PH and PL phenotypic traits among different subgroups (Table 7) showed significant differences between the two phenotypes among different subgroups. Figure 6 B).

[0048] Table 7: Maximum and minimum values ​​of PH and PL for different subgroups 4. Chain Imbalance Analysis Using 104,236 high-quality polymorphic SNPs after quality control, genome-wide and subgenome-wide linkage disequilibrium (LD) decay analyses were performed on natural wheat populations. Figure 7 As shown, the whole-genome LD decay distance is approximately 3.41 Mb. At the subgenome level, the LD decay distances for subgenomes A, B, and D are 3.39 Mb, 4.16 Mb, and 0.66 Mb, respectively. Among these, subgenome D exhibits a shorter LD decay distance compared to subgenomes A and B, indicating that subgenome D in this population is more conserved.

[0049] 5. Genome-wide association analysis GWAS analysis was performed using an MLM statistical model, combined with PH and PL phenotypic data, BLUE values, and 104,236 SNP markers from natural wheat populations under different drought conditions. A total of 145 MTAs significantly associated with PH and PL traits were identified, of which 116 were associated with PH and 29 with PL. Among these MTAs, 15 loci were repeatedly detected in two or more environments, and 6 loci were detected in three or more environments. The contribution rates of these loci to phenotypic variation ranged from 1.31% to 30.11%. These multi-environmentally stable loci were distributed on wheat chromosomes 2D and 4D, with 14 loci on chromosome 4D and 1 on chromosome 2D. Further analysis revealed that these stable loci were repeatedly identified in different environments as 28 multi-environment MTA loci significantly associated with PH and 16 multi-environment MTA loci significantly associated with PL.

[0050] A total of 28 multi-environmental MTA loci significantly associated with the pH trait were repeatedly identified, distributed across 9 wheat chromosomes (2A, 2D, 3A, 3B, 4A, 4D, 6D, 7A, and 7D). The contribution rate of these loci to pH phenotypic variation was [not specified in the original text]. R 2 The percentage ranges from 9.13% to 30.11%. Figure 8 Of these, four MTAs were stably expressed in both environments: 4D_15879510 , 4D_16159705 , 4D_16388958 , 4D_19865285 There are four MTAs that are stably expressed in the four environments, namely: 4D_17341225 , 4D_18178735 , 4D_ 18951612 and 4D_19694829 .

[0051] A total of 16 multi-environmental MTA loci significantly associated with the PL trait were repeatedly identified, distributed across 7 wheat chromosomes (1D, 2D, 3D, 4A, 5A, and 6D). Their contribution to PL phenotypic variation was (…). R 2 The percentage ranges from 1.31% to 3.59%. Figure 8 Of these, one MTA was stably expressed in both environments. 2D_497267374 Six MTAs were stably expressed in the three environments, namely: 4D_16159705 , 4D_16388958 , 4D_17341225 , 4D_18178735 , 4D_18951612 and 4D_19694829 .

[0052] 6. MTA hotspot area verification and KASP tag development Linkage disequilibrium analysis was performed on six multi-environmentally stable SNP markers on chromosome 4D that were significantly associated with both PH and PL. Figure 9 Six SNPs were located within the LD Block confidence interval (2.50 Mb) and were considered high-confidence SNP markers stably associated with the PH and PL traits. Further analysis of these six SNP markers within the interval... 4D_16159705 , 4D_16388958 , 4D_ 17341225 , 4D_18178735 , 4D_18951612 and 4D_19694829 ( R 2 Haplotype analysis was performed on samples with a plurality of 1.64% - 30.11%. Figure 10 The results showed that these six SNP markers could be divided into two haplotypes in the tested materials: HapⅠ and HapⅡ. The genotypes of the six SNPs in the HapⅠ haplotype were AA, CC, CC, TT, CC, and GG, while the corresponding genotypes in the HapⅡ haplotype were GG, GG, AA, CC, GG, and AA. Phenotypic analysis showed that the mean pH of the HapⅠ population was 83.98 cm, significantly higher than that of the HapⅡ population (65.63 cm); the mean PL of the HapⅠ population was 31.31 cm, significantly higher than that of the HapⅡ population (24.37 cm); and the mean TKW of the HapⅠ population was 40.83 g, significantly lower than that of the HapⅡ population (42.72 g). Analysis showed that the varieties with the above six allelic variations were highly significant with respect to the pH, PL, and TKW traits. P <0.001) correlation.

[0053] against 4D_16159705 , 4D_16388958 , 4D_17341225 , 4D_18178735 , 4D_18951612 and 4D_ 19694829 KASP molecular markers were developed at the locus, and high-throughput genotyping was performed on 373 wheat natural population varieties (lines) using these markers. K-4D_16159705 , K-4D_16388958 and K-4D_17341225 The typing results of these three markers successfully distinguished two haplotypes ( Figure 11 Association analysis showed that allelic variants carrying the G / G, G / G, and A / A homozygous genotypes (HapⅡ) had shorter pH, shorter PL, and higher TKW, and the phenotypic associations were highly significant. P< 0.001). Analysis shows that the Hap II population has undergone positive selection in the wheat breeding process in my country. Figure 12This indicates that the G / G, G / G, and A / A allelic variants carried by the HapII population are dominant allelic variants that regulate PH, PL, and TKW. The developed KASP marker can be used for the precise identification of these superior variants and for molecular marker-assisted selection breeding.

[0054] Molecular markers K-4D_16159705 The nucleotide sequence is as follows: ACCTGRTGTGC, denoted as SEQ ID NO.1. The degenerate base R at position 6 of the nucleotide sequence is an SNP site with a polymorphism of A or G.

[0055] Molecular markers K-4D_16388958 The nucleotide sequence, such as AATCTSTGATG, is denoted as SEQ ID NO.2. The degenerate base S at position 6 of the nucleotide sequence is an SNP site with a polymorphism of C or G.

[0056] Molecular markers K-4D_17341225 The nucleotide sequence, such as GGCGAMGAATA, is denoted as SEQ ID NO.3. The degenerate base M at position 6 of the nucleotide sequence is an SNP site with a polymorphism of C or A.

[0057] It should be noted that when numerical ranges are mentioned in the claims of this invention, it should be understood that the two endpoints of each numerical range and any value between the two endpoints can be selected. To avoid redundancy, the present invention describes preferred embodiments.

[0058] Although preferred embodiments of the invention have been described, those skilled in the art, upon learning the basic inventive concept, can make other changes and modifications to these embodiments. Therefore, the appended claims are intended to be interpreted as including both the preferred embodiments and all changes and modifications falling within the scope of the invention.

[0059] Obviously, those skilled in the art can make various modifications and variations to this invention without departing from its spirit and scope. Therefore, if these modifications and variations fall within the scope of the claims of this invention and their equivalents, this invention also intends to include these modifications and variations.

Claims

1. KASP molecular marker for wheat yield, characterized by, The molecular marker is based on 4D_16159705 Molecular markers based on sites 4D_16388958 Molecular markers at sites or based on 4D_17341225 Molecular markers at the site; based on 4D_16159705 The nucleotide sequence of the molecular marker at the site is shown in SEQ ID NO.

1. The degenerate base R at position 6 of the nucleotide sequence is an SNP site with polymorphism A or G. When the polymorphism is A, the haplotype of wheat is HapⅠ, and when the polymorphism is G, the haplotype of wheat is HapⅡ. based on 4D_16388958 The nucleotide sequence of the molecular marker at the site is shown in SEQ ID NO.

2. The degenerate base S at position 6 of the nucleotide sequence is an SNP site with a polymorphism of C or G. When the polymorphism is C, the haplotype of wheat is HapⅠ, and when the polymorphism is G, the haplotype of wheat is HapⅡ. based on 4D_17341225 The nucleotide sequence of the molecular marker at the site is shown in SEQ ID NO.

3. The degenerate base M at position 6 of the nucleotide sequence is an SNP site with polymorphism C or A. When the polymorphism is C, the haplotype of wheat is HapⅠ, and when the polymorphism is A, the haplotype of wheat is HapⅡ. Wheat yields of haplotype HapⅠ are lower than those of haplotype HapⅡ.

2. A specific primer for amplifying the molecular marker of claim 1, characterized in that, based on 4D_16159705 The primers for the site include upstream primers as shown in SEQ ID NO.4 and SEQ ID NO.5, and downstream primers as shown in SEQ ID NO.6; based on 4D_16388958 The primers for the site include upstream primers as shown in SEQ ID NO.7 and SEQ ID NO.8, and downstream primers as shown in SEQ ID NO.9; based on 4D_17341225 The primers for the site include upstream primers as shown in SEQ ID NO.10 and SEQ ID NO.11, and downstream primers as shown in SEQ ID NO.

12.

3. A reagent kit for detecting wheat yield traits, characterized in that, The kit includes the specific primers as described in any one of claims 3.

4. The use of the molecular marker of claim 1, the specific primer of claim 2, or the kit of claim 3 in identifying wheat yield.

5. The application according to claim 4, characterized in that, The steps for determining wheat yield are as follows: (1) Extract genomic DNA from the wheat to be tested; (2) Using the extracted DNA as a template, amplification is performed using the specific primers described in claim 4 to obtain the amplification product; (3) Identify the amplification products 4D_16159705 , 4D_16388958 or 4D_17341225 The genotype at the locus is used to determine the yield of the wheat being tested.

6. The application according to claim 6, characterized in that, The wheat yield refers to the weight of 1,000 grains of wheat.

7. The application of the molecular marker of claim 1, the specific primer of claim 2, or the kit of claim 3 in wheat breeding or assisted wheat breeding, characterized in that, The aforementioned assisted wheat breeding aims to cultivate high-yielding wheat.

8. The application of the molecular marker of claim 1, the specific primer of claim 2, or the kit of claim 3 in identifying wheat plant type traits, characterized in that, The plant type trait refers to the plant height or the length of the internode below the ear of wheat; The plant height of wheat with haplotype HapⅠ is shorter than that of wheat with haplotype HapⅡ, and the length of the lower internode of wheat with haplotype HapⅠ is shorter than that of wheat with haplotype HapⅡ.

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