A c04 chromosome major-effect qtl site of brassica napus early flowering stage and flowering duration trait, snp molecular marker and application thereof

Abstract

This invention relates to a major QTL locus on chromosome C04 for the traits of initial flowering time and flowering duration in Brassica napus. It is tightly linked to a first SNP marker located at base 36757914, which is either A or C, and this mutation leads to polymorphism. It is also tightly linked to a second SNP marker located at base 37139204, which is either A or G, and this mutation leads to polymorphism. Furthermore, it is tightly linked to a third SNP marker located at base 36798469, which is either A or G, and this mutation leads to polymorphism. Preferably, the third SNP marker contributes 11.09% and 9.81% to the initial flowering time and flowering duration traits of Brassica napus, respectively. Related SNP markers and their applications are also provided. The major QTL locus on chromosome C04 of this invention has a high contribution rate to the initial flowering time and flowering duration traits of Brassica napus, exhibiting high genetic contribution and stability.

Description

Technical Field

[0001] This invention relates to the fields of molecular biology and rapeseed breeding technology, and in particular to a major QTL locus on chromosome C04, a SNP molecular marker for the traits of initial flowering period and flowering duration in Brassica napus, and their application. Background Technology

[0002] Increased rapeseed yield primarily comes from three approaches: increasing yield per unit area, increasing seed oil content, and expanding planting area. Among these, increasing yield and oil content are currently the top priorities in breeding efforts. However, key traits such as yield, oil content, and quality are complex quantitative traits, controlled by multiple genes and highly susceptible to environmental factors, making it difficult for traditional breeding methods to achieve significant breakthroughs in the short term. In recent years, the development of molecular breeding technology, especially the organic combination of quantitative genetics and molecular marker-assisted selection (MAS), has provided more efficient and precise means for rapeseed breeding.

[0003] Flowering period is one of the important phenological factors affecting rapeseed yield. The initial flowering stage, as a key phenological node, determines the degree of phenological compatibility between rapeseed and the regional environment, directly affecting the risk of late spring frost damage, the ability to avoid sclerotinia stem rot, and the efficiency of later temperature and light resource utilization, thus significantly impacting pollination, seed setting, and grain maturation. In the Yangtze River basin, spring temperatures fluctuate frequently. An early initial flowering stage easily leads to low-temperature freezing damage to flower buds and pistils. Furthermore, if it coincides with the peak release of ascospores from sclerotinia stem rot fungi, it significantly increases the risk of disease infection. Appropriately delaying the initial flowering stage can avoid these stresses, ensuring sufficient light and accumulated temperature for subsequent silique development. The duration of flowering regulates the internal nutrient distribution pattern of the plant. During the flowering stage, there is significant competition between flower buds and young siliques for resources; abnormal flowering duration interferes with silique formation. An excessively long flowering period prolongs the disease infection window and exacerbates sclerotinia stem rot under high humidity conditions, while an excessively short flowering period results in insufficient effective pollination time; both are detrimental to yield formation. Extensive genetic analysis and cultivation trials have confirmed that flowering time does not directly determine yield, but rather indirectly regulates yield performance through environmental adaptation, disease occurrence, and photosynthetic product allocation. It is a key indirect trait in rapeseed yield formation, and synergistic optimization of initial flowering time and flowering duration is necessary in variety breeding. However, these two traits are quantitative traits controlled by multiple genes and are significantly influenced by the environment, making direct selection difficult in the absence of molecular markers. Summary of the Invention

[0004] To address the shortcomings of existing technologies, this invention proposes a major-effect QTL locus, SNP molecular marker, and their application that contribute significantly to the traits of initial flowering time and flowering duration in Brassica napus. The major-effect QTL locus for the flowering time trait in Brassica napus is located between bases 36757914 and 37139204 on chromosome C04 of Brassica napus. It can be used for map-based cloning and marker-assisted selection, significantly improving breeding efficiency and making it suitable for large-scale application.

[0005] Plant traits are divided into qualitative traits and quantitative traits. Qualitative traits are either one or the other, such as whether the petals are red or white, or whether they have thorns or not. They are controlled by a single gene and have clear boundaries. Quantitative traits, on the other hand, are traits that vary continuously and cannot be simply divided into a few categories.

[0006] In this invention, the initial flowering period (number of days between early and late flowering) and flowering duration (number of days the flower is open) of Brassica napus do not simply fall into two categories, "early" and "late," but rather exhibit a continuous gradient of days. This is regulated by multiple genes and the environment, thus classifying it as a typical quantitative trait, typically located using QTLs (quantitative trait loci). Major-effect QTLs refer to single loci with high genetic contribution rates that can significantly alter the initial flowering period and flowering duration; they are key segments determining flowering characteristics. The loci screened in this invention are major-effect QTLs.

[0007] Tight linkage means that the probability of genetic recombination between a molecular marker and a target QTL site is low. In a population, the genotype of this molecular marker can be used to indicate whether an individual carries the major QTL site.

[0008] The first aspect of this invention provides a major-effect QTL-linked SNP molecular marker for the traits of initial flowering time and flowering duration in Brassica napus, wherein the SNP molecular marker comprises a combination selected from a first SNP molecular marker, a second SNP molecular marker, and a third SNP molecular marker, wherein...

[0009] The first, second, and third SNP molecular markers are located between bases 36757914 and 37139204 on chromosome C04 of Brassica napus.

[0010] Furthermore, the first SNP molecular marker is located at the 36757914th base of the C04 chromosome of Brassica napus, and the base at this site is either C or A. This mutation leads to polymorphism.

[0011] Furthermore, the second SNP molecular marker is located at base 37139204 on chromosome C04 of Brassica napus, and the base at this site is either G or A, indicating a single nucleotide polymorphism.

[0012] Furthermore, the third SNP molecular marker is located at base 36798469 on chromosome C04 of Brassica napus, and the base at this site is either A or G, indicating a single nucleotide polymorphism.

[0013] Secondly, the present invention provides primers or probes for detecting SNP molecular markers linked to major QTL sites of the initial flowering period and flowering duration traits of Brassica napus as described in any one of the claims.

[0014] Furthermore, the primers for the major QTL-linked SNP molecular markers of the initial flowering stage and flowering duration traits in Brassica napus include a combination of primers selected from the first SNP molecular marker, the second SNP molecular marker, and the third SNP molecular marker, wherein:

[0015] The primers for the first SNP molecular marker were designed based on a DNA fragment consisting of 400 bp upstream and downstream of the 36757914th base on chromosome C04 of Brassica napus, the sequence of which is shown in SEQ ID No. 1.

[0016] The primers for the second SNP molecular marker were designed based on a DNA fragment with a sequence of 400 bp upstream and downstream of the 37139204th base on chromosome C04 of Brassica napus, the sequence of which is shown in SEQ ID No. 2.

[0017] The primers for the third SNP molecular marker were designed based on a DNA fragment with a sequence of 400 bp upstream and downstream of the 36798469th base on chromosome C04 of Brassica napus, the sequence of which is shown in SEQ ID No. 3.

[0018] Thirdly, the present invention provides a Brassica napus SNP chip containing primers or probes for SNP molecular markers linked to major QTL sites of the initial flowering period and flowering duration traits of Brassica napus.

[0019] Fourthly, the present invention provides a kit containing primers or probes for SNP molecular markers linked to major QTL sites for the initial flowering period and flowering duration traits of Brassica napus.

[0020] Fifthly, the present invention provides a breeding method for Brassica napus, comprising the following steps: using the Brassica napus SNP molecular marker, the primers or probes, the SNP chip or the kit to detect the rapeseed DNA to be tested, thereby selecting suitable rapeseed for breeding.

[0021] Sixthly, the present invention provides the application of any one of the following in molecular marker-assisted breeding for detecting the initial flowering period and flowering duration of Brassica napus and predicting the initial flowering period and flowering duration of Brassica napus: the SNP molecular marker of Brassica napus, the primer or probe, the SNP chip or the kit.

[0022] In summary, compared with the prior art, the present invention achieves the following technical effects:

[0023] (1) This invention utilizes genome-wide association analysis to locate a QTL interval on chromosome C04 of Brassica napus that is significantly associated with the initial flowering period and flowering duration, defined between bases 36757914 and 37139204. The contribution rates of this QTL to the initial flowering period and flowering duration are 11.09% and 9.81%, respectively, showing high genetic contribution and stability.

[0024] (2) The SNP molecular markers constructed in this invention can accurately predict the flowering period in the early stage of plant growth, which can significantly shorten the breeding cycle. At the same time, since the flowering period is greatly affected by environmental factors such as light and temperature, the use of molecular markers to assist selection can improve the selection accuracy and avoid environmental interference.

[0025] The SNP molecular markers disclosed in this invention enable marker-assisted selection, which is simple, highly efficient, and can predict the flowering period of Brassica napus. The selection target is clear and unaffected by environmental factors. Individual Brassica napus plants with suitable flowering periods can be identified early in the growth cycle, eliminating other plants. In summary, the major-effect QTL loci of this invention contribute significantly to the flowering period trait of Brassica napus, playing a crucial role in its regulation. They can be used for map-based cloning and marker-assisted selection, making them suitable for large-scale application. Attached Figure Description

[0026] To more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings used in the embodiments will be briefly introduced below. It should be understood that the following drawings only show some embodiments of the present invention and should not be regarded as a limitation on the scope. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.

[0027] Figure 1 This is a schematic diagram showing the phenotypic distribution results of the initial flowering stage traits of Brassica napus according to the present invention.

[0028] Figure 2 This is a schematic diagram showing the phenotypic distribution results of flowering duration of Brassica napus according to the present invention.

[0029] Figure 3This is a Manhattan diagram of the genome-wide association analysis of the initial flowering trait of Brassica napus in this invention.

[0030] Figure 4 This is a schematic diagram illustrating the allelic analysis of the peak SNP molecular markers of the major QTL sites of the initial flowering stage of Brassica napus in this invention.

[0031] Figure 5 This is a Manhattan plot of the genome-wide association analysis of flowering duration in Brassica napus according to the present invention.

[0032] Figure 6 This is a schematic diagram illustrating allelic analysis using peak SNP molecular markers of major QTL sites related to the flowering duration of Brassica napus in this invention. Detailed Implementation

[0033] Example 1: Identification of the initial flowering phenotype in a Brassica napus-type associated population

[0034] (1) The natural population used in this study consisted of 278 purebred rapeseed lines. Each line was obtained through multiple generations of self-pollination. The genotypes within the lines tended to be homozygous, and there was rich genetic variation among the lines. Field planting was carried out for a total of three years at the Yangluo Experimental Base in Wuhan and the Experimental Base of Yangzhou Academy of Agricultural Sciences to complete the multi-year, multi-location phenotypic survey of the traits of initial flowering period and flowering duration.

[0035] (2) Direct seeding was adopted, with a row spacing of 33 cm and a plant spacing of 15 cm. Each plot had 4 rows, and three replicates were randomly designed. Protective rows were planted around the perimeter of the experimental plots.

[0036] (3) Initial flowering period: the number of days from the date when 25% of the plants in the whole area begin to flower, minus the planting date; flowering duration: the number of days from the end of flowering period minus the initial flowering period.

[0037] (4) The best linear unbiased prediction (BLUP) method was used to integrate multi-year multi-location phenotypic data to obtain the breeding values ​​of initial flowering period and flowering duration as the phenotypic values ​​of initial flowering period and flowering duration.

[0038] The phenotypic values ​​of all environments for the 278 materials were averaged, and the results are summarized in Tables 1-1 to 1-6 (flowering time phenotypic values ​​of locus chrC04_36798469), Tables 2-1 to 2-6 (flowering time phenotypic values ​​of locus chrC04_36757914), and Tables 3-1 to 3-6 (flowering time phenotypic values ​​of locus chrC04_37139204).

[0039] Table 1-1 Flowering period phenotypic values ​​(days) of locus chrC04_36798469 in 278 materials

[0040]

[0041] Table 1-2 Flowering period phenotypic values ​​(days) of locus chrC04_36798469 in 278 materials

[0042]

[0043] Table 1-3 Flowering period phenotypic values ​​(days) of locus chrC04_36798469 in 278 materials.

[0044]

[0045] Table 1-4 Flowering period phenotypic values ​​(days) of locus chrC04_36798469 in 278 materials.

[0046]

[0047] Table 1-5 Flowering period phenotypic values ​​(days) of locus chrC04_36798469 in 278 materials.

[0048] Table 1-6 Flowering period phenotypic values ​​(days) of locus chrC04_36798469 in 278 materials

[0049]

[0050] Table 2-1 Flowering period phenotypic values ​​(days) of locus chrC04_36757914 in 278 materials

[0051]

[0052] Table 2-2 Flowering period phenotypic values ​​(days) of locus chrC04_36757914 in 278 materials

[0053]

[0054] Table 2-3 Flowering period phenotypic values ​​(days) of locus chrC04_36757914 in 278 materials

[0055]

[0056] Table 2-4 Flowering period phenotypic values ​​(days) of locus chrC04_36757914 in 278 materials

[0057]

[0058] Table 2-5 Flowering period phenotypic values ​​(days) of locus chrC04_36757914 in 278 materials.

[0059]

[0060] Table 2-6 Flowering period phenotypic values ​​(days) of locus chrC04_36757914 in 278 materials

[0061]

[0062] Table 3-1 Flowering period phenotypic values ​​(days) of locus chrC04_37139204 in 278 materials

[0063]

[0064] Table 3-2 Flowering period phenotypic values ​​(days) of locus chrC04_37139204 in 278 materials

[0065]

[0066] Table 3-3 Flowering period phenotypic values ​​(days) of locus chrC04_37139204 in 278 materials

[0067]

[0068] Table 3-4 Flowering period phenotypic values ​​(days) of locus chrC04_37139204 in 278 materials

[0069]

[0070] Table 3-5 Flowering period phenotypic values ​​(days) of locus chrC04_37139204 in 278 materials.

[0071]

[0072] Table 3-6 Flowering period phenotypic values ​​(days) of locus chrC04_37139204 in 278 materials

[0073]

[0074] The rapeseed natural population used in this study exhibited rich phenotypic variation in flowering time. The initial flowering period ranged from 134 to 171 days, with an average of 159 days and a coefficient of variation of 3.75%, indicating that the overall flowering time of the population was relatively concentrated and the difference in initial flowering time between individuals was small. The flowering duration ranged from 22 to 48 days, with an average of 27 days and a coefficient of variation of 13.19%, indicating that the duration of flowering varied greatly among different materials, and that this trait has higher genetic diversity. The coefficient of variation was calculated as: Coefficient of variation = Sample standard deviation ÷ Sample mean × 100%. This value is used to compare the degree of variation between different traits; the larger the value, the greater the difference between materials within the population and the richer the phenotypic variation. The distribution results of these two flowering time traits showed a continuous and normal distribution, proving that the initial flowering period and flowering duration are quantitative traits and that major gene loci exist. Figure 1 and Figure 2 As shown.

[0075] Example 2: Obtaining a high-quality SNP dataset for a related population

[0076] Total DNA was extracted from leaves using the CTAB method. Total DNA was extracted from leaves of each material in the associated population. The specific method was as follows:

[0077] Young leaves were rinsed in 10% ethanol; then 0.1–0.2 g of leaves were cut and placed in a mortar, and rapidly ground into powder using liquid nitrogen, and transferred to a 2 mL centrifuge tube; 700 μL of preheated DNA extraction buffer was added; after mixing, the mixture was placed in a 65°C water bath for 1 hour, mixing every 10–15 minutes; 700 μL of a mixture of phenol, chloroform, and isoamyl alcohol in a volume ratio of 25:24:1 was added, and the mixture was gently inverted and mixed for 10 minutes; the mixture was centrifuged at 10,000 × g for 15 minutes at room temperature; the supernatant was transferred to a new 2 mL centrifuge tube; an equal volume of the mixture (chloroform and isoamyl alcohol in a volume ratio of 24:1) was added, the mixture was inverted and mixed, and allowed to stand for 5 minutes; the mixture was then centrifuged at 10,000 × g for 15 minutes, and the supernatant was transferred to a new centrifuge tube; two volumes of anhydrous ethanol were added, the mixture was mixed, and the mixture was allowed to stand at -20°C for 1 hour, and then centrifuged at 10000 × g for 15 minutes. Centrifuge at 10,000×g for 10 min, discard the supernatant; add 500 μL of pre-cooled 75% ethanol to wash the precipitate, discard the supernatant; after washing the precipitate twice, air dry; add 100 μL of RNase A solution, incubate at 37℃ for 1 h, then at 4℃ overnight; extract the DNA solution again with an equal volume of mixed buffer (chloroform:isoamyl alcohol = 24:1), invert and mix, incubate for 10 min, centrifuge at 10,000×g for 15 or 20 min to remove RNase A, collect the supernatant (about 60 μL), centrifuge again for 1 min; detect the DNA concentration, quality and integrity using agarose gel electrophoresis (0.8%) and UV spectrophotometer; determine that the absorbance 260 / 280 ratio of all DNA samples is between 1.8 and 2.0. Then transport the DNA samples to the sequencing company (BGI Genomics Co., Ltd.) on dry ice, with a sequencing depth of approximately 7× for each material.

[0078] The raw sequencing data obtained from deep sequencing were quality assessed using FastQC (v0.11.9) software to remove sequencing adapter contamination, excessively short sequences, and low-quality reads, resulting in high-quality clean sequencing data. The clean data was then aligned to the *Brassica napus* Darmor-bzh V5 reference genome (genome download source: http: / / brassicadb.cn / # / Download / ) using BWA mem (v0.7.17) software. Based on the alignment results, population single nucleotide polymorphism (SNP) variant detection was performed using GATK4 (v4.2.6.1) software. Finally, the raw SNP markers obtained were subjected to quality control screening. The screening criteria were set as follows: minimum allele frequency (MAF) ≥ 0.05, genotype deletion rate ≤ 0.1, and locus heterozygosity ≤ 0.1, ultimately obtaining a high-quality population SNP dataset suitable for subsequent association analysis.

[0079] Example 3 Genome-wide association analysis

[0080] This embodiment conducts genome-wide association analysis (GWAS) based on a high-quality SNP variant dataset after quality control. Plink software was used to standardize the VCF-formatted SNP data to obtain genotype files suitable for EMMAX analysis. Subsequently, the preprocessed phenotypic data for initial flowering time and flowering duration, along with the standardized SNP genotype data, were imported into EMMAX software to complete the GWAS, obtaining the association p-values ​​(P-values) for each SNP locus corresponding to the two flowering time traits. Figure 3 and Figure 5 Furthermore, the significant SNP screening threshold was set to a p-value less than 7.5 × 10⁻⁶. -7 SNP sites that meet this threshold are identified as trait-significantly associated sites, and the SNP with the smallest P value within a single QTL interval is defined as the peak SNP.

[0081] Association analysis revealed 15 significantly associated SNP loci for the initial flowering stage trait, including 2 significant loci on chromosome A02, 12 significant loci on chromosome C04, and 1 significant locus on chromosome C06. For the flowering duration trait, 33 significantly associated SNP loci were detected, including 6 significant loci on chromosome A02, 1 significant locus on chromosome A09, and 26 significant loci on chromosome C04. Trait co-location analysis revealed an overlapping key QTL region on chromosome C04 for the two flowering traits: initial flowering time and flowering duration. The physical location of this region is 36757914 bp to 37139204 bp. Core significant SNPs within this region include chrC04_36757914 (C / A) and chrC04_37139204 (G / A), with the peak SNP being chrC04_36798469 (A / G). The phenotypic contribution rate (PVE) was used to quantify the explanatory power of each significant SNP for the target trait. The PVE for each SNP was calculated using the following formula:

[0082]

[0083] In the PVE calculation formula, β represents the effect value of the variant site, MAF represents the minor allele frequency of the site, se represents the standard error of the effect value of the site, and N represents the sample size of the experimental population.

[0084] Contribution analysis showed that the overlapping QTL interval contributed 11.09% and 9.81% to the phenotypic variation in the initial flowering period and flowering duration of Brassica napus, respectively, and belonged to the major genetic locus regulating the flowering period trait. Based on the genotype of the peak SNP chrC04_36798469 (A / G), the experimental natural population was divided into groups. The results of the significance test for phenotypic differences between groups showed significant differences in the initial flowering period and flowering duration between the two groups, with the p-value for the difference in initial flowering period between groups being 4.3 × 10⁻⁶. -8 The difference in flowering duration between groups was p-valued at 0.0012, as shown in the results. Figure 4 , Figure 6 As shown.

[0085] Flanking SNPs mark the left and right ends of a QTL interval, defining the physical start and end points of the QTL, and are not necessarily significant peak sites. Peak SNPs are the SNPs within the QTL interval that have the smallest P-value and the highest phenotypic contribution rate in GWAS analysis, and are the most core associated sites.

[0086] The analysis revealed a boundary SNP for the flowering trait, denoted as chrC04_36757914 (C / A). The corresponding flowering phenotype groupings were as follows: when the SNP at the position of chrC04_36757914 was C (among 217 materials), the average initial flowering period was 159.53 days, and the average flowering duration was 26.38 days; when it was A (among 40 materials), the average initial flowering period was 154.16 days, and the average flowering duration was 29.55 days. The contribution rates of this boundary SNP to the initial flowering period and flowering duration were 8.89% and 8.12%, respectively.

[0087] Another boundary SNP for the flowering trait is chrC04_37139204 (G / A). The corresponding flowering phenotype groupings are as follows: when the SNP at the position of chrC04_37139204 is G (in 217 materials), the average initial flowering period is 159.38 days and the flowering duration is 26.49 days; when it is A (in 40 materials), the average initial flowering period is 150.71 days and the flowering duration is 31.01 days. The contribution rates of this boundary SNP to the initial flowering period and flowering duration are 9.63% and 9.59%, respectively.

[0088] The peak SNP for the flowering trait is labeled as chrC04_36798469 (A / G), corresponding to the following phenotypic groupings: when the SNP at the position of chrC04_36798469 is A (out of 217 materials), the average initial flowering period is 159.77 days and the flowering duration is 26.28 days; when it is G (out of 40 materials), the average initial flowering period is 153.33 days and the flowering duration is 29.58 days. The contribution rates of this peak SNP to the initial flowering period and flowering duration are 11.09% and 9.81%, respectively.

[0089] by Figure 4 The average initial flowering period of 153.32 days for the GG type, as shown in the box plot, serves as the dividing line. The GG type is early-flowering, meaning a short initial flowering period, while the AA type is late-flowering, meaning a long initial flowering period. Statistical data from Tables 1-1 to 1-6 show that 15 GG type materials meet the short initial flowering period requirement, with an accuracy rate of 37.5%; 199 AA type materials meet the long initial flowering period requirement, with an accuracy rate of 91.7%. Using the average flowering duration of 29.58 days for the GG type as the dividing line, the GG type has a long flowering duration, while the AA type has a short flowering duration. Statistical data from Tables 1-1 to 1-6 show that 15 GG type materials meet the long flowering duration requirement, with an accuracy rate of 37.5%; 200 AA type materials meet the short flowering duration requirement, with an accuracy rate of 92.2%.

[0090] The complete genome sequence of rapeseed (Brassica oleracea var. nana) has been published (Darmor-bzh, http: / / brassicadb.cn / # / Download / ). The 400bp sequences before and after chrC04_36757914 (C / A) (801bp in total) are shown in SEQ ID NO:1, the 400bp sequences before and after chrC04_37139204 (G / A) (801bp in total) are shown in SEQ ID NO:2, and the 400bp sequences before and after chrC04_36798469 (A / G) (801bp in total) are shown in SEQ ID NO:3.

[0091] SEQ ID NO.1

[0092] CTTTATTTTATTATTTTATTATTTATTATTTTATTTTTATTTATTTAATAATGATTATTA

[0093] TATATATATATATATAGATAACAAAGACATAAGAGTATTTTGCCACTTAATGAACAATGT

[0094] ATTTTTGAAAATATCCATTTAGTGGCGGTAAAGATGAAAAGTGGTACCAAATTTTTCCAT

[0095] TAAATAAAGTAATCAAAAGTGATAGCAAATAAATGGCCATCCATATATTGATTTATATAC

[0096] ATTGAAATTTGAAATTTAGCCTAGGAAGAAGCACATATTCAAAATGATAGAAAAGTCACT

[0097] CGATTGATCTCAAAGAAGTAAACTACCAAACAATAATTTGCGGTGTCACGTCGATGGAAC

[0098] TTGAAACAACATATTTTGGGGACAAGATGGTTTTACATGA M ATGAGTACTGATGAGAGTA

[0099] AAAAATATATAACGAAACCTCTCATCTTTGCATGCATAATGCCAAGCTCTGATCTGAGCA

[0100] GACTGAGCTGTATAATATATGAAGATTCTTCAATAACTAGATGTGGTGTTTGTTATTGTT

[0101] AGGAATTGATGAAGATAATGCGGAAGTTGGATATGCACAATCGAGTTTGTTTATGTAAGT

[0102] TTTAAGGAACCGAAGTTTGTTGATTTAATCACACGAAAGCACAGCATATTGAAGCAGATG

[0103] GAAAGATGTAGATTTGTATTAGTTATTTAGAGTTGGATTTTATGTAAGGATGTTTACGAA

[0104] GAAAACAAGTCATTTTTAGTTTGTTTACATATTTGAGTACAAGAGATCTGTGAAATCAAT

[0105] TAAAAGCCCATCGGCTTTTAT, M=A or C

[0106] SEQ ID NO.2

[0107] ACAATATGAACACTAACCACAAAACTTGAAAACTCCAATTCAAAGAAACCTAAATCTAC

[0108] ATTCCATAATTGACTCAGCCGTAACCAATCTATATTCCTAAATAACTAAATCTATATTCC

[0109] ACCTTGATTCTAGCAAAAATCGATCGCATACCAATGATGAAAGATCTAGAAAACGATGTA

[0110] ATATCAGGTTTAATAACAGAAAAATAAAATCAAAAGGTGAGAGAGGATACCCCCATT

[0111] GAACAGCGAGGGACTCGTAGTCCCAATAATCCTTGGGTTTTATGACGTTGACATCGGCGT

[0112] AAACCCTAGCCTTCGACGGCGCACCGGCACGCCGGATGGATTTACCGATCTTCTGCGCCA

[0113] GCGTTTCCGATTTATTCACGCGGGGTTGTTGTTGTTGCTG R CGGTAGAGAGAGGCGAATC

[0114] CACGGAGAAAGGAGAGGAGGCTCTTCTTCGCCCGAGGGGAGGAGGAAGACGAAGAGATGG

[0115] AGAGGAGGAAGGAGAAGCGGAGGTCGTTGGCGGCTGAAGCGTTGCAAAGAGAGGAGATTG

[0116] TGAATCCGATAGGCCTAAAGGCCATTTAACATTTTAATTAAAATCTCTTAAGGAAAT

[0117] GAAATACAGGGTAACGACTTGCTTCTCTTTTTTTTTTGGACCTCTTTGTAAACTTTCT

[0118] ATATGATCTCCCGACGTTGGTAGTGTCTGTACTCCTTTTTCTTTTCTTCCAAATTTTGGA

[0119] AGATATAGGTCAATGTGTTATAAACATATACTCAAGATCGGCCTGCAAAGATGGTCAGTT

[0120] TGAATACAATTTAGTTTCAGT, R=G or A

[0121] SEQ ID NO.3

[0122] TAAAGAATGAACTTTGTTCCGCGTTTTTGAGCAATCGATAAATCAATTTTACCACTCAAA

[0123] TTTACTTTTAGACAGCTTTTCCATATCAAATAATAAAATAAAAAAAAAATCCTGTTCATT

[0124] ATTTAAAAGATTCATGATAAAAGTTTACAATTCCTTCGGATCCAAAACATAATCATATAA

[0125] TATCAGCATCATTTCACGCGTCACTCGATCATATCAATTCTAAAAGATTCAATATTTTTT

[0126] TATGAAGCATATTAATTAGTAATAATGACAATGTCTTGTTTAAGTTTTGTTTTTTTTCTT

[0127] TTGAGAATTTGTCTTATAATTGTAATGTCTTGTTGAAGTTGTTAAATAAAACAGAGGTCG

[0128] ATTAACAAATTGAGTAGGGTCCAAAAGGCAGAAAAATCCA R CTTACCCATCTAAGTTTTG

[0129] CTTTGCTTGTAATATTATGGTTTATCGGGATGTCTCTCGTTACTTTCTTCAGTGCATAGC

[0130] AGTGTTTGAAATATTTACATGTATATCGGGACTGTGTTTCACAGTTTTGAAGTTTACTTA

[0131] CACTTACCGCCGATAAGGCAAGTCGCGGCTCTTACGTGCAATAACACTAAGTAAAATAAC

[0132] ACAAATTTGAAGAAACAAAGGAATAAGCCACTGGTTGATAATGTGGAGTGACTCTTAAG

[0133] TGCAATAATACTAAGTAAAGAAAACACAAATTTGAAGAAACATACCAAGAAGATAAGAAA

[0134] ATGAACTCATAAACGTTCTTGTATCTAAGAACAGAGTGACTGCAGTTTATTAAATCTTCA

[0135] AAATCAGACTACTCGCAGGAG, R= A or G

[0136] Those skilled in the art can design specific primers or probes for detecting SNP sites based on known sequences using conventional methods. These primers or probes can also be labeled with fluorescent groups, such as FAM, HEX, VIC, ROX, etc., and quenching groups, such as BHQ1 or TAMRA, using conventional techniques. This allows for the detection of the genotype of the aforementioned SNP sites using conventional methods such as sequencing or PCR. Consequently, the timing and duration of flowering in Brassica napus can be determined, and the timing and duration of flowering in Brassica napus can be predicted. This enables effective selection of the timing and duration of flowering in Brassica napus, accelerating the breeding process of Brassica napus during its growth period.

[0137] The present invention also provides a primer or probe comprising primers or probes for amplifying or detecting the SNP molecular marker.

[0138] In some embodiments, the primers are designed based on any of the following DNA fragments:

[0139] (1) A DNA fragment with 400 bp before and after the 36757914th base of the chromosome of Brassica napus, the nucleotide sequence of which is shown in SEQ ID NO.1;

[0140] (2) A DNA fragment with 400 bp before and after the 37139204th base on chromosome C04 of Brassica napus, the nucleotide sequence of which is shown in SEQ ID NO.2;

[0141] (3) A DNA fragment with 400 bp before and after the 36798469th base of chromosome C04 of Brassica napus, the nucleotide sequence of which is shown in SEQ ID NO.3.

[0142] In some implementations, the primers are any one of the following groups:

[0143] (1) The primers for the first SNP molecular marker were designed based on the fragment of SEQ ID NO.1, and the primer sequences are shown in SEQ ID NO.4~5;

[0144] (2) The primers for the second SNP molecular marker were designed based on the fragment of SEQ ID NO.2, and the primer sequences are shown in SEQ ID NO.6~7;

[0145] (3) The primers for the third SNP molecular marker were designed based on the fragment of SEQ ID NO.3, and the primer sequences are shown in SEQ ID NO.8-9.

[0146] SEQ ID NO.4

[0147] TGGCGGTAAAGATGAAAAGTGGTACC

[0148] SEQ ID NO.5

[0149] TGCTTCAATATGCTGTGCTTTCGTGT

[0150] SEQ ID NO.6

[0151] TTCCATAATTGACTCAGCCGTAACCA

[0152] SEQ ID NO.7

[0153] CCATCTTTGCAGGCCGATCTTGA

[0154] SEQ ID NO.8

[0155] ATGAACTTTGTTCCGCGTTTTTGAGC

[0156] SEQ ID NO.9

[0157] CTCCTGCGAGTAGTCTGATTTTGAAGA

[0158] Preferably, the primers or probes are labeled with fluorescent groups, including FAM, HEX, VIC, and ROX.

[0159] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. An application of an SNP molecular marker in detecting the traits of initial flowering time and flowering duration in Brassica napus, characterized in that, Using Darmor-bzh V5 as the reference genome, the SNP molecular marker is located at the 36798469th base on chromosome C04 of Brassica napus. The base at this site is either A or G, and there is a single nucleotide polymorphism. Homozygous plants with the base site A have a long initial flowering period and a short flowering time; homozygous plants with the base site G have a short initial flowering period and a long flowering time.

2. An application of the SNP molecular marker primers described in claim 1 in detecting the traits of initial flowering stage and flowering duration in Brassica napus, wherein, The primers for the SNP molecular marker were designed based on a DNA fragment with a sequence of 400 bp upstream and downstream of the 36798469th base on chromosome C04 of Brassica napus, the sequence of which is shown in SEQ ID No.

3.

3. A kit for detecting the initial flowering stage and flowering duration of Brassica napus, characterized in that: The kit contains primers for detecting the SNP molecular marker described in claim 1.

4. A chip for detecting the initial flowering stage and flowering duration of Brassica napus, characterized in that, The chip contains primers for detecting the SNP molecular marker described in claim 1.

5. A method for detecting the initial flowering stage and flowering duration of Brassica napus using the SNP molecular markers described in claim 1, characterized in that, The method includes the following steps: using the SNP molecular marker of Brassica napus as described in claim 1, the kit as described in claim 3, and the chip as described in claim 4 to detect the DNA of the rapeseed to be tested, wherein the homozygous plants with base site A have the trait of long initial flowering period and short flowering time; and the homozygous plants with base site G have the trait of short initial flowering period and long flowering time, thereby selecting suitable rapeseed for breeding.

6. The application of any one of the molecular markers described in claim 1, the primers described in claim 2, the kit described in claim 3, or the chip described in claim 4 in molecular marker-assisted breeding for detecting the initial flowering period and flowering duration of Brassica napus and predicting the initial flowering period and flowering duration of Brassica napus, wherein the homozygous plants with base site A have a long initial flowering period and a short flowering time; and the homozygous plants with base site G have a short initial flowering period and a long flowering time.

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