A SNP marker, primer set, detection method and application for assisting in the selection of leaf number in Brassica napus.

Abstract

This invention discloses an SNP marker, primer set, detection method, and application for assisting in the selection of leaf number in Brassica napus, relating to the fields of biology and rapeseed breeding technology. The SNP marker is located at 9283404 bp on chromosome A02 of Brassica napus, with the bases at this site being either the T allele or the C allele, where the T allele is associated with the multi-leaf trait. The SNP marker provided by this invention solves the technical problem of the lack of effective molecular markers closely linked to the leaf number trait in Brassica napus in existing technologies, which prevents rapid and accurate screening of this trait in the early stages of breeding, thus limiting the breeding efficiency of high-efficiency, ideal plant type rapeseed varieties.

Description

Technical Field

[0001] This invention relates to the fields of biology and rapeseed breeding technology, and in particular to an SNP marker, primer set, detection method, and application technology for assisting in the selection of leaf number in Brassica napus. Background Technology

[0002] Currently, although existing research has conducted gene mapping and cloning on traits such as leaf shape (e.g., lobed leaves), leaf color, and photosynthetic efficiency in rapeseed (e.g., the lobed leaf gene located on chromosome A10 and the leaf-rolling gene on chromosome A05), and developed corresponding molecular markers, and although current research has clearly recognized that rapeseed leaves are a key "source" organ, and their quantitative traits directly determine photosynthetic capture efficiency and significantly affect silique number, grain weight, and final yield, and that there is a huge gap between the actual and theoretical yields of rapeseed in my country that urgently needs to be overcome, current technical means are still focused on gene mining for traits such as leaf shape and leaf color. The genetic analysis of leaf quantity, a core agronomic trait, is still lacking. This results in a lack of molecular tools for early and precise screening of superior traits with multiple leaves in breeding, which seriously restricts the breeding process of improving light efficiency and yield through plant type improvement. Summary of the Invention

[0003] In view of this, the main objective of this invention is to propose an SNP marker, primer set, detection method and application for assisting in the selection of the number of leaves in Brassica napus. This aims to solve the technical problem that the lack of effective molecular markers closely linked to the leaf number trait in Brassica napus in the prior art makes it impossible to quickly and accurately screen this trait in the early stages of breeding, thereby restricting the breeding efficiency of high light efficiency and ideal plant type rapeseed varieties.

[0004] Firstly, this invention provides a SNP marker for assisting in the selection of leaf number in Brassica napus, located at 9283404 bp on chromosome A02 of Brassica napus. The bases at this site are either T or C alleles, with the T allele associated with the multi-leaf trait. By employing the above technical solution, this invention, for the first time, discovers and provides a direct association between this specific SNP site and the leaf number trait in Brassica napus, providing a core target for marker-assisted breeding and solving the technical problem of lacking key genetic markers for controlling leaf number in existing technologies.

[0005] Secondly, the present invention provides a primer set for detecting the SNP markers provided above, comprising a first primer, a second primer, and a third primer;

[0006] The nucleotide sequence of the first primer is shown in SEQ ID NO: 16;

[0007] The nucleotide sequence of the second primer is shown in SEQ ID NO: 17;

[0008] The nucleotide sequence of the third primer is shown in SEQ ID NO: 18. By employing the above technical solution, this invention provides a set of primers with high specificity and sensitivity, capable of accurately and efficiently detecting the genotype of target SNP sites, thus providing a key tool for high-throughput molecular detection.

[0009] Thirdly, the present invention provides a method for detecting genotypes related to the number of leaves in Brassica napus, comprising the following steps:

[0010] S1. Extract genomic DNA from rapeseed samples;

[0011] S2. Using genomic DNA as a template, perform PCR amplification using the primer set provided in this invention;

[0012] S3. Detect the amplification products to determine the genotype of the SNP marker provided by this invention.

[0013] By adopting the above-mentioned technical solution, this invention establishes a rapid and accurate genotype detection method, which can realize early prediction and screening of leaf number traits in the seedling stage, and greatly improve breeding efficiency.

[0014] In some embodiments of the present invention, step S3 includes the following steps:

[0015] S3.1 Determine the genotype of the SNP marker by detecting the fluorescence signal of the PCR amplification product; if a FAM fluorescence signal is generated, the genotype is a T allele homozygote; if a HEX fluorescence signal is generated, the genotype is a C allele homozygote; if both FAM and HEX fluorescence signals are generated, the genotype is a heterozygote.

[0016] In some embodiments of the present invention, the PCR amplification in step S2 is performed using KASP amplification.

[0017] In some embodiments of the present invention, the conditions for KASP amplification include: pre-denaturation at 94℃-96℃ for 10-15 minutes; denaturation at 94℃-96℃ for 20-45 seconds, followed by annealing at 65-57℃ for 45-60 seconds, for a total of 8-12 cycles; and denaturation at 94℃-96℃ for 20-45 seconds, followed by annealing at 55-57℃ for 45-60 seconds, for a total of 32-36 cycles.

[0018] Fourthly, the present invention provides a method for breeding rapeseed varieties with ideal leaf number traits, comprising the following steps:

[0019] S1. Extract genomic DNA from rapeseed samples;

[0020] S2. Using genomic DNA as a template, perform PCR amplification using the primer set provided in this invention;

[0021] S3. Detect the amplification products to determine the genotype of the SNP marker provided by this invention;

[0022] S4. Select plants with the genotype TT for the SNP marker as breeding parents or for screening; the ideal leaf number trait is the multi-leaf trait. This invention, by employing the above technical solution, combines molecular marker detection with breeding selection, achieving precise and efficient selection of superior leaf number traits, significantly shortening the breeding cycle and improving selection accuracy.

[0023] Fifthly, this invention provides an application of an SNP marker for assisting in the selection of leaf number in Brassica napus in marker-assisted breeding of Brassica napus. By employing the above technical solution, this invention expands the application of this SNP marker in rapeseed genetic improvement, providing a new technical means for the breeding of high-yielding, high-light-efficiency rapeseed varieties.

[0024] Sixthly, this invention provides the application of a primer set for detecting the SNP markers provided by this invention in the preparation of a kit for assisting in the selection of leaf count in Brassica napus. By employing the above technical solution, this invention provides core components for the development of commercial breeding kits, promoting the industrial application of molecular breeding technology.

[0025] Seventhly, this invention provides a kit for assisting in the selection of leaf count in Brassica napus, comprising the primer set provided by this invention. By employing the above technical solutions, this invention provides an integrated and standardized detection tool, facilitating rapid promotion and application in breeding practices and lowering the technical barriers to use. Attached Figure Description

[0026] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on the structures shown in these drawings without creative effort.

[0027] Figure 1 The image shows the final number of leaves of two plants (2116C and ZH18) on the 69th day after sowing in Example 1 of this invention; the image visually demonstrates the significant difference in the number of leaves between the two parents in the later stages of growth.

[0028] Figure 2 This is a graph showing the number of fully expanded leaves of two plants (2116C and ZH18) on the 69th day after sowing in Example 1 of the present invention; the vertical axis represents the number of leaves, and the green and yellow lines correspond to the dynamic changes in the number of leaves of the 2116C (more leaves) and ZH18 (fewer leaves) lines, respectively.

[0029] Figure 3 This is a graph showing the number of leaves visible during the rosette stage in Example 1 of the present invention; where the horizontal axis represents the number of days after sowing, the vertical axis represents the number of leaves, and the green and yellow lines correspond to the growth trends of the number of leaves during the rosette stage for the 2116C and ZH18 lines, respectively.

[0030] Figure 4 This is a frequency distribution diagram of leaf number in the F2 population during 2021–2022 and 2022–2023 in Example 1 of the present invention; it shows the frequency distribution of the leaf number trait in the F2 population, reflecting the genetic characteristics of its quantitative trait;

[0031] Figure 5 This is the QTL localization map of extreme leaf number pools based on BSA sequencing in Example 1 of the present invention; wherein, Figure 5 Figure (A) shows the QTL mapping results for the number of leaves during the rosette stage; Figure 5 Figure (B) in the figure shows the QTL mapping results of the number of leaves at the budding stage;

[0032] Figure 6 This is a graph showing the ΔSNP-index results based on chromosome A02 of the ZS11 v0 reference genome in Example 1 of the present invention; where the red, blue and green lines correspond to confidence thresholds of 0.99, 0.95 and 0.90, respectively, and are used to locate candidate intervals related to the number of leaves;

[0033] Figure 7 This is a graph showing the ΔSNP-index results based on chromosome A02 of the Darmor-bzh V10 reference genome in Example 1 of this invention; the red, blue, and green lines correspond to confidence thresholds of 0.99, 0.95, and 0.90, respectively, further verifying the reliability of the candidate intervals.

[0034] Figure 8 This is a KASP-labeled population phenotyping diagram from Embodiment 1 of the present invention; wherein, Figure 8 Figure (A) shows the LOD values ​​in the QTL mapping of the F2 population; Figure 8 Figure (B) shows the results of genotyping the F2 population using the LN.A02-9283404 marker;

[0035] Figure 9 This is the KASP marker verification diagram in Embodiment 2 of the present invention; Figure 9 Figure (A) shows the typing results in the remaining heterozygous progeny lines (154 lines);

[0036] Figure 9 Figure (B) shows the phenotypic comparison results of different genotypes (TT, TC, CC) of the marker LN.A02-9283404. One-way ANOVA showed that the differences in leaf number among the genotypes were significant (p<0.01).

[0037] The realization of the objective, functional features and advantages of the present invention will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. Detailed Implementation

[0038] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below. Where specific conditions are not specified in the embodiments, conventional conditions or conditions recommended by the manufacturer shall apply. Where the manufacturers of reagents or instruments are not specified, they are all conventional products that can be purchased commercially. Furthermore, the meaning of "and / or" throughout the text includes three parallel solutions; for example, "A and / or B" includes solution A, or solution B, or a solution where both A and B are satisfied simultaneously. In addition, the technical solutions of the various embodiments can be combined with each other, but this must be based on the ability of those skilled in the art to implement them. When the combination of technical solutions is contradictory or cannot be implemented, it should be considered that such a combination of technical solutions does not exist and is not within the scope of protection claimed by the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0039] Unless otherwise specified, all raw materials used in this invention are commercially available.

[0040] Currently, although existing research has conducted gene mapping and cloning on traits such as leaf shape (e.g., lobed leaves), leaf color, and photosynthetic efficiency in rapeseed (e.g., the lobed leaf gene located on chromosome A10 and the leaf-rolling gene on chromosome A05), and developed corresponding molecular markers, and although current research has clearly recognized that rapeseed leaves are a key "source" organ, and their quantitative traits directly determine photosynthetic capture efficiency and significantly affect silique number, grain weight, and final yield, and that there is a huge gap between the actual and theoretical yields of rapeseed in my country that urgently needs to be overcome, current technical means are still focused on gene mining for traits such as leaf shape and leaf color. The genetic analysis of leaf quantity, a core agronomic trait, is still lacking. This results in a lack of molecular tools for early and precise screening of superior traits with multiple leaves in breeding, which seriously restricts the breeding process of improving light efficiency and yield through plant type improvement.

[0041] In view of this, the main objective of this invention is to propose an SNP marker, primer set, detection method and application for assisting in the selection of the number of leaves in Brassica napus. This aims to solve the technical problem that the lack of effective molecular markers closely linked to the leaf number trait in Brassica napus in the prior art makes it impossible to quickly and accurately screen this trait in the early stages of breeding, thereby restricting the breeding efficiency of high light efficiency and ideal plant type rapeseed varieties.

[0042] Firstly, this invention provides a SNP marker (SNP molecular marker) for assisting in the selection of leaf number in Brassica napus, located at 9283404 bp on chromosome A02 of Brassica napus. The bases at this locus are either T or C alleles, with the T allele associated with the multi-leaf trait. By employing the above technical solution, this invention, for the first time, discovers and provides a direct association between this specific SNP locus and the leaf number trait in Brassica napus, providing a core target for marker-assisted breeding and solving the technical problem of lacking key genetic markers for controlling leaf number in existing technologies.

[0043] Secondly, the present invention provides a primer set for detecting the above-mentioned SNP marker, comprising a first primer, a second primer, and a third primer;

[0044] The nucleotide sequence of the first primer is shown in SEQ ID NO: 16;

[0045] The nucleotide sequence of the second primer is shown in SEQ ID NO: 17;

[0046] The nucleotide sequence of the third primer is shown in SEQ ID NO: 18. By employing the above technical solution, this invention provides a set of primers with high specificity and sensitivity, capable of accurately and efficiently detecting the genotype of target SNP sites, thus providing a key tool for high-throughput molecular detection.

[0047] Thirdly, the present invention provides a method for detecting genotypes related to the number of leaves in Brassica napus, comprising the following steps:

[0048] S1. Extract genomic DNA from rapeseed samples;

[0049] S2. Using genomic DNA as a template, perform PCR amplification using the primer set provided in this invention;

[0050] S3. Detect the amplification products to determine the genotype of the SNP marker provided by this invention. This invention, by employing the above technical solution, establishes a rapid and accurate genotype detection method, enabling early prediction and screening of leaf number traits during the seedling stage, significantly improving breeding efficiency.

[0051] In some embodiments of the present invention, step S3 includes the following steps:

[0052] S3.1 Determine the genotype of the above SNP marker by detecting the fluorescence signal of the PCR amplification product; wherein, if a FAM fluorescence signal is generated, the genotype is a T allele homozygote; if a HEX fluorescence signal is generated, the genotype is a C allele homozygote; if both FAM and HEX fluorescence signals are generated, the genotype is a heterozygote.

[0053] In some embodiments of the present invention, the PCR amplification in step S2 is performed using KASP amplification.

[0054] In some embodiments of the present invention, the reaction conditions for KASP amplification include: pre-denaturation at 94℃-96℃ for 10-15 minutes; denaturation at 94℃-96℃ for 20-45 seconds, followed by annealing at 65-57℃ for 45-60 seconds, for a total of 8-12 cycles; and denaturation at 94℃-96℃ for 20-45 seconds, followed by annealing at 55-57℃ for 45-60 seconds, for a total of 32-36 cycles.

[0055] Fourthly, the present invention provides a method for breeding rapeseed varieties with ideal leaf number traits, comprising the following steps:

[0056] S1. Extract genomic DNA from rapeseed samples;

[0057] S2. Using genomic DNA as a template, perform PCR amplification using the primer set provided in this invention;

[0058] S3. Detect the amplification products to determine the genotype of the SNP marker provided by this invention;

[0059] S4. Select plants with the genotype TT for the SNP marker as breeding parents or for screening; the ideal leaf number trait is the multi-leaf trait. This invention, by employing the above technical solution, combines molecular marker detection with breeding selection, achieving precise and efficient selection of superior leaf number traits, significantly shortening the breeding cycle and improving selection accuracy.

[0060] Fifthly, this invention provides an application of an SNP marker for assisting in the selection of leaf number in Brassica napus in marker-assisted breeding of Brassica napus. By employing the above technical solution, this invention expands the application of this SNP marker in rapeseed genetic improvement, providing a new technical means for the breeding of high-yielding, high-light-efficiency rapeseed varieties.

[0061] Sixthly, this invention provides the application of a primer set for detecting the SNP markers provided by this invention in the preparation of a kit for assisting in the selection of leaf count in Brassica napus. By employing the above technical solution, this invention provides core components for the development of commercial breeding kits, promoting the industrial application of molecular breeding technology.

[0062] Seventhly, this invention provides a kit for assisting in the selection of leaf count in Brassica napus, comprising the primer set provided by this invention. By employing the above technical solutions, this invention provides an integrated and standardized detection tool, facilitating rapid promotion and application in breeding practices and lowering the technical barriers to use.

[0063] The technical solution of the present invention will be further described in detail below with reference to specific embodiments and accompanying drawings. It should be understood that the following embodiments are only used to explain the present invention and are not intended to limit the present invention.

[0064] The first sequence is LN.A02-9283404Ra, and its nucleotide sequence is shown in SEQ ID NO: 16. The specific sequence is as follows:

[0065] GAAGGTGACCAAGTTCATGCTGGATGATGAATAACAGAAAAGAGGA;

[0066] The second sequence is LN.A02-9283404Rg, and its nucleotide sequence is shown in SEQ ID NO: 17. The specific sequence is as follows:

[0067] GAAGGTCGGAGTCAACGGATTGGATGATGAATAACAGAAAAGAGGG;

[0068] The third sequence is LN.A02-9283404F, and its nucleotide sequence is shown in SEQ ID NO: 18. The specific sequence is: ATCGAGTCACTCTTCCCATTAGG.

[0069] In this invention, SEQ ID NO: 16 (LN.A02-9283404Ra, reverse primer, FAM, corresponding to T allele).

[0070] SEQ ID NO: 17 (LN.A02-9283404Rg, reverse primer, HEX, corresponding C allele).

[0071] SEQ ID NO: 18 (LN.A02-9283404F, common forward primer).

[0072] When screening rapeseed germplasm resources using KASP markers, PCR amplification was performed using the above primers; wherein, the first sequence (SEQ ID NO: 16) was labeled with FAM fluorescence to detect the T allele associated with the multi-leaf trait; the second sequence (SEQ ID NO: 17) was labeled with HEX fluorescence to detect the C allele.

[0073] The third sequence is the common forward primer, whose nucleotide sequence is shown in SEQ ID NO: 18, specifically: ATCGAGTCACTCTTCCCATTAGG. This primer works in conjunction with two allele-specific reverse primers in the KASP reaction system to amplify DNA fragments containing the target SNP site. It does not carry a fluorescent label itself and is a key component in ensuring the specificity and efficiency of the PCR reaction.

[0074] In the KASP detection system: the first sequence (SEQ ID NO: 16, allele T-specific primer) is labeled with FAM fluorescence.

[0075] The second sequence (SEQ ID NO: 17, allele C-specific primer) is labeled with HEX fluorescence.

[0076] The third sequence (SEQ ID NO: 18, common forward primer) is not fluorescently labeled and is a universal primer. The three sets of primers together constitute a complete KASP genotyping system, which achieves SNP genotyping through fluorescence signal recognition.

[0077] Example 1:

[0078] (1) Materials and methods:

[0079] (1.1) Plant materials and field trials:

[0080] This experiment used Brassica napus inbred lines 2116C (multi-leaved) and ZH18 (sparse-leaved).

[0081] Before winter, 2116C has 6-8 more leaves than ZH18, and 13-15 more leaves during bolting, showing a significant difference in leaf number between the two parents. The F1 and F2 populations were prepared by hybridization of the multi-leaved material 2116C (P1) and the few-leaved material ZH18 (P2).

[0082] In late September 2020, parental materials P1, P2, and F1 were planted in the specimen area of ​​Northwest A&F University (34°28′N, 108°07′E). Parental materials were bagged and self-pollinated for seed retention. The two parents were crossbred to produce F1. F1 was bagged and self-pollinated to construct the F2 population.

[0083] In September 2021, P1, P2, F1, and F2 materials were planted in the specimen area of ​​Northwest A&F University. A randomized block design was adopted, with each parent and F1 material planted in 5 rows with about 80 plants, and the F2 population was sown in 40 rows to construct a population of 600 individual plants.

[0084] In September 2022, P1, P2, F1, and F2 materials were planted in the specimen area of ​​Northwest A&F University. The F2 population was sown in 15 rows to construct a population of 225 individual plants. Compound fertilizer was applied as base fertilizer once throughout the entire growth period. After sowing, seedlings were thinned at the 3-5 leaf stage and finalized at the 5-leaf stage. Weeding and cultivation were carried out before winter when the seedlings had 8-9 leaves. Winter irrigation was carried out in early December. The remaining field management was carried out according to conventional methods.

[0085] Leaves from both parents and the F2 generation were collected in November 2021. F2 samples were previously labeled with corresponding numbers. After collection, 0.2 g of each sample was weighed for DNA extraction. DNA was extracted using the cetyltrimethylammonium bromide (CTAB) method, with the following steps: 0.5 g of plant tissue was placed in a centrifuge tube, steel beads and liquid nitrogen were added, and the mixture was thoroughly ground by vortexing at 60 Hz / second; 660 μL of CTAB extraction buffer was added, and the mixture was incubated in a 65°C water bath for 30 minutes, gently inverting and mixing every 10 minutes; an equal volume of phenol / chloroform / isoamyl alcohol mixture was added, and the mixture was gently inverted and shaken for 5 minutes, followed by centrifugation to collect the supernatant; two volumes of anhydrous ethanol were added to the supernatant, and the mixture was centrifuged at 12000 rpm for 10 minutes, the supernatant was discarded, and the mixture was allowed to dry at room temperature for 1 h before dissolving the DNA in 100 μL of ddH2O. The concentration and quality of DNA were detected using a nucleic acid concentration analyzer in preparation for the amplification of polymorphic primers in F2. Finally, the concentration was diluted to 50 ng / μL with ddH2O and stored at -20℃ for genome resequencing or genotyping.

[0086] (1.2) Characteristic Investigation:

[0087] From October 2020 to March 2021, the number of leaves for P1 and P2 was recorded to determine the time when the difference in the number of leaves was the greatest at different growth stages of rapeseed.

[0088] The leaf number of the P1, P2, F1 and F2 populations was investigated during the periods from October 2021 to March 2022 and from October 2022 to March 2023, when the differences in leaf number between the parents were greatest.

[0089] In May 2022, at maturity, the number of branches, biomass, and grain yield of the F2 population were investigated.

[0090] From October 2022 to March 2024, the number of leaves in P1, P2, F1, F2, and BC1F1 populations was investigated. Ten individual plants were randomly selected from the P1, P2, and F1 populations to investigate and record phenotypic traits. Individual plants in the F2 and BC1F1 populations were tagged, and the number of leaves on each individual plant was investigated.

[0091] (1.3) Analysis of the quantitative trait inheritance model of major gene + polygene:

[0092] In the 2021-2022 and 2022-2023 planting seasons, researchers used the G4F2 (P1, P2, F1 and F2) of the SEA v2.0.1 R software package

[48] to perform genetic analysis on four populations: ZH18, 2116C, F1 and F2. According to the Akaike Information Content Criterion (AIC), the four candidate models with the lowest AIC values ​​were selected from 24 candidate models. Subsequently, the goodness-of-fit test was performed on each candidate model, and the module with the smallest p value (p<0.05) was finally selected as the optimal model.

[0093] (1.4) Construction of genetic population pools and whole-genome resequencing analysis:

[0094] In March 2022, 30 plants from each of the F2 population with extreme leaf numbers were selected (the F2 population was sorted by leaf number at the budding stage, and the 30 plants with the most and 30 plants with the fewest leaves were selected). These plants, along with their parents, were used to construct four extreme mixed pools. Four DNA samples were sent to BMI for BSA resequencing analysis, which included: sample quality testing; after passing the quality test, the genome was fragmented into small fragments (approximately 350 bp), purified, and subjected to PCR testing before DNA library construction. After library quality testing, sequencing was performed using the Illumila platform.

[0095] Raw sequencing reads were filtered using FASTP software to obtain net data for subsequent analysis. Burrows-Wheeler-Alignment software was used to align reads to the reference genome ZS11 v0. Duplicate reads were sorted and removed using SAMtools software. SNP and InDel variant detection were performed using the HaplotypeCaller algorithm in GATK software, and variant annotation was analyzed using SnpEff software with default parameters.

[0096] (1.5) SNP-Index Calculation and Initial Location:

[0097] Before conducting the association analysis, the inventors screened SNP variants using specific criteria, including:

[0098] (I) Multiple genotypes exist;

[0099] (II) Coverage in the pooled sample pool is less than 4-fold;

[0100] (III) Homozygous and consistent variation exists between two pooled samples or two parents; inconsistency exists between pooled samples with the same trait and the parents. SNP-index is an association analysis method used to discover significant differences in genotype frequencies between pooled samples, where ∆SNP-index = SNP-index (B1) —SNP-index (B2). The DISTANCE / SNPNUM method was used for analysis (window size 1 Mb, step size 200 Kb), 1000 permutation tests were performed, and a confidence level of 95% was selected as the threshold for screening candidate regions. Gene sequences within the localization intervals were obtained from the ZS11 v0 genome, and gene function annotation was performed by BLAST alignment against NR database, Pfam database, KOG / COG database, Swiss-Prot database, KEGG database, GO database, etc.

[0101] (1.6) KASP marker primer design and genotyping:

[0102] A homozygous SNP between two parents was selected, with no other SNPs within 20 bp upstream and 40 bp downstream of the selected SNP. Based on the reference genome ZS11 v0, the bases at the SNP were counted towards the 5' end until the Tm value of the primer sequence was approximately 60°C. The SNP base was used as the last base at the 3' end of primer F. Using the reference genome ZS11 v0, the left primer F was fixed using PrimerPremier 5, and the right primer R was obtained via BLAST, with the product size kept as small as possible (less than 60 bp). The primer sequences were then aligned to the entire genome to ensure primer specificity.

[0103] The designed allele-specific primers were supplemented with adapter sequences FAM: GAAGGTGACCAAGTTCATGCT and HEX: GAAGGTCGGAGTCAACGGATT, respectively. The primers were then purified using ULTRPAGE for PCR. The DNA template concentration was uniformly diluted to 50 ng / μL. The PCR amplification reaction system is shown in Table 1.

[0104] Table 1

[0105]

[0106] The DNA solutions in Table 1: (The DNA in the DNA solutions is the DNA extracted using CTAB; you can extract the DNA based on your own experimental materials). In Table 1, 2x represents a multiple of 2; 1x represents a multiple of 1.

[0107] The PCR amplification reaction program employed a temperature gradient "Touchdown PCR" strategy. Based on the primer Tm temperature (-60℃), the annealing temperature was set to 65-57℃ (-0.8℃ / cycle) to further reduce non-specific primer amplification, thereby significantly improving the quality and reliability of the PCR reaction. The PCR amplification reaction conditions are shown in Table 2.

[0108] Table 2

[0109]

[0110] After PCR, the fluorescence signal was read using a TECAN Infinite M1000 microplate reader, and then the converted fluorescence signal was analyzed using the online software snpdecoder (http: / / www.snpway.com / snpdecoder / ), outputting the FAM / HEX color results. The primer information used in the PCR reaction is shown in Table 3.

[0111] Table 3

[0112]

[0113] 2. Experimental Results:

[0114] (2.1) Differences in leaf number among the parents of Brassica napus:

[0115] Two high-generation inbred lines, 2116C and ZH18, with significant differences in leaf appearance were selected from 104 core materials of Brassica napus breeding.

[0116] Among them, 2116C has a fast leaf emergence speed, while ZH18 has a slow leaf emergence speed.

[0117] During the entire pre-winter growth period from October 2020 to March 2021, ZH18 had about 8 leaves, while 2116C had about 14 leaves, showing a significant difference.

[0118] See the diagram for the number of fully expanded leaves of each plant. Figures 1 to 3 ;

[0119] in, Figure 1 The image shows the final number of leaves of two plants (2116C and ZH18) on the 69th day after sowing in Example 1 of this invention; the image visually demonstrates the significant difference in the number of leaves between the two parents in the later stages of growth.

[0120] Figure 2This is a graph showing the number of fully expanded leaves of two plants (2116C and ZH18) on the 69th day after sowing in Example 1 of the present invention; the vertical axis represents the number of leaves, and the green and yellow lines correspond to the dynamic changes in the number of leaves of the 2116C (more leaves) and ZH18 (fewer leaves) lines, respectively.

[0121] Figure 3 This is a graph showing the number of leaves visible during the rosette stage in Example 1 of the present invention; where the horizontal axis represents the number of days after sowing, the vertical axis represents the number of leaves, and the green and yellow lines correspond to the growth trends of the number of leaves during the rosette stage for the 2116C and ZH18 lines, respectively.

[0122] (2.2) Analysis of the genetic characteristics of leaf number in the 116C×ZH18 F2 population:

[0123] Based on the above investigation, a genetic population was constructed using 2116C and ZH18 as parents. For ease of study, the inventors investigated the number of fully expanded leaves 54 days after sowing. According to the phenotypic results of the 2021-2022 and 2022-2023 sowing seasons, the average number of fully expanded leaves at the rosette stage for the ZH18 line was 5.3 and 7.5, respectively; for the 2116C line, it was 12.2 and 13.6; for the F1 generation, it was 9.6 and 10.1; and for the F2 population, it was 8.1 and 9.1. Therefore, the number of leaves at the rosette stage in rapeseed exhibits quantitative trait inheritance characteristics. The average number of branches for ZH18 was 5.3 and 7.7, for 2116C it was 13.7 and 13.5, respectively; the average number of branches for the F1 generation was between that of the parents; and the average number of branches for the F2 population was 6.5 and 7, respectively. Over the two years, the parental line ZH18 had approximately 5-7 branches, while 2116C had around 13 branches, indicating that the branching number trait is relatively stable in different environments and is less affected by environmental factors. Correlation analysis based on the F2 population showed a highly significant correlation between the number of leaves at the rosette stage and the number of primary branches, biomass, and grain yield, suggesting a possible intrinsic positive correlation among them.

[0124] To study the genetic characteristics of rapeseed leaf number, the inventors used leaf number data from the ZH18, 2116C, F1, and F2 generations during the 2021-2022 and 2022-2023 growing seasons to predict the genetic model. Based on the minimum Akaike information criterion (AIC), the optimal model for rosette leaf number was determined to be either one major gene with allelic dominance (1MG-EAD) or two major genes with allelic dominance (2MG-EAD). The optimal genetic models for the number of primary branches and main branches were 2MG-EAD and 2MG-EAD. In the fitness test, the 2MG-EAD model, which had a higher number of significant p-values ​​(p<0.05), was selected as the optimal genetic model. Based on this model, the inventors predicted the genetic parameters of leaf emergence rate-related traits, which were mainly regulated by two highly heritable dominant genes with negative allelic dominance effects, with a heritability exceeding 86.4%. See the frequency distribution maps of leaf number for F2 population in 2021-2022 and 2022-2023. Figure 4 ;

[0125] Figure 4 This is a frequency distribution diagram of leaf number in the F2 population during 2021–2022 and 2022–2023 in Example 1 of the present invention; it shows the frequency distribution of the leaf number trait in the F2 population, reflecting the genetic characteristics of its quantitative trait;

[0126] The correlations among leaf number, primary branch number, biomass, and grain yield in the F2 population are shown in Table 4.

[0127] Table 4

[0128]

[0129] (2.3) Whole genome resequencing and BSA analysis based on ZH18, 2116C and their progeny pools:

[0130] After ranking the number of leaves in the rosette stage of 600 F2 populations, 30 plants with the most leaves and 30 plants with the fewest leaves were selected. Among them, the material with an extremely high number of leaves had 13-23 leaves, while the material with an extremely low number of leaves had 4-7 leaves, with an average difference of about 3 times.

[0131] The parents were sequenced at a depth of 20X, and the progeny pools were sequenced at a depth of 30X.

[0132] The resequencing data of the four samples were aligned to the ZS11 v0 genome with an alignment rate of over 99.4%, an average 1X coverage of over 89.8%, and an average 5X coverage of over 85.0%.

[0133] A total of 518,330 high-quality SNPs were obtained between P1, P2, B1, and B2. Figure 7When the confidence interval is 0.95, significant signals were located at positions 9,045,489-9,478,410 bp and 13,517,525-13,661,121 bp on chromosome A02 using SNP-index.

[0134] For the Darmor-bzh V10 genome, the alignment rate was above 99.2%, the average 1X coverage was above 89.8%, and the average 5X coverage was above 85.4%. A total of 765,950 SNPs were obtained across P1, P2, B1, and B2. At a confidence interval of 0.95, significant signals were located on chromosome A02 at 9,066,916–9,477,102 bp and 13,609,227–13,728,641 bp using the SNP-index.

[0135] The candidate regions located by the two reference genomes showed collinearity. Overall, the inventors identified a candidate gene controlling the number of rapeseed leaves within a 0.57 Mb region on chromosome A02.

[0136] See the BSA sequencing-based QTL mapping for extreme leaf number mixing. Figures 5 to 7 .

[0137] in, Figure 5 This is the QTL localization map of extreme leaf number pools based on BSA sequencing in Example 1 of the present invention; wherein, Figure 5 Figure (A) shows the QTL mapping results for the number of leaves during the rosette stage; Figure 5 Figure (B) in the figure shows the QTL mapping results of the number of leaves at the budding stage;

[0138] Figure 6 This is a graph showing the ΔSNP-index results based on chromosome A02 of the ZS11 v0 reference genome in Example 1 of the present invention; where the red, blue and green lines correspond to confidence thresholds of 0.99, 0.95 and 0.90, respectively, and are used to locate candidate intervals related to the number of leaves;

[0139] Figure 7 This is a graph showing the ΔSNP-index results based on chromosome A02 of the Darmor-bzh V10 reference genome in Example 1 of this invention; the red, blue, and green lines correspond to confidence thresholds of 0.99, 0.95, and 0.90, respectively, further verifying the reliability of the candidate intervals.

[0140] (2.4) KASP tag development:

[0141] To further validate the two regions on chromosome A02, the inventors used the ZS11 V0 reference genome as the primary source and screened for parental homozygosity and inter-parental differences, as well as for pooled mutation frequencies and SNP sites (SNPs with a QUAL value ≥ 500, with preference given to SNPs with a ΔSNP-index peak) for marker development. One molecular marker (LN.A02-9104606 and LN.A02-13510278) was designed on each side of the 9,045,489-13,661,121 bp region on chromosome A02 to indicate parental differences. The results showed that the candidate genes were intermediate between the two parental groups. A binary search approach was used to design LN.A02-9530301 and LN.A02-9377316 markers to screen 190 extreme lines from 600 F2 cells. QTL mapping was performed using QTL Icimapping (v4.2) software, and candidate genes were identified as lying between the LN.A02-9104606 and LN.A02-9377316 markers, which are only 0.5 cM apart, approximately 270 kb.

[0142] Analysis of 882 SNPs within this interval revealed a peak ΔSNP-index at 9283404 bp. Two sets of KASP primers were developed targeting this site: LN.A02-9283404.1 was designed based on the genomic "+" strand sequence, and LN.A02-9283404.2 was designed based on the genomic "-" strand sequence. After primer synthesis, genotyping between parents was performed using PCR (PCR reaction conditions and parameters are shown in Tables 1 to 3). The results showed that primers LN.A02-9283404Ft, LN.A02-9283404Fc, and LN.A02-9283404R did not bind specifically and could not distinguish between parental and offspring genotypes. The primer sets LN.A02-9283404F, LN.A02-9283404Ra, and LN.A02-9283404Rg (sixth primer set) showed differences between the parental and offspring populations. The variant site T showed FAM fluorescence, and the variant site C showed HEX fluorescence, which can be used for subsequent genotyping of larger offspring populations. The PCR product sizes in this step are shown in Table 5 below.

[0143] Table 5

[0144]

[0145] Results Analysis: During the development process, the inventors designed and tested multiple sets of primers (as shown in Table 3). Among them, the sixth primer set (LN.A02-9283404Ra / Rg / F) showed the best specificity and genotyping effect, and is the preferred solution of the present invention.

[0146] Typing of 190 extreme lines from 600 F2 generations using parental lines showed that the marker LN.A02-9283404 had the highest LOD value (LOD>3.5), the strongest linkage, and a phenotypic contribution of approximately 10.93%. Three genes related to leaf development, age, and cell cycle pathways were found near the LN.A02-9283404 marker, which may be functional genes related to leaf number.

[0147] See the KASP marker population genotyping diagram. Figure 8 ; Figure 8 This is a KASP-labeled population phenotyping diagram from Embodiment 1 of the present invention; wherein, Figure 8 Figure (A) shows the LOD values ​​in the QTL mapping of the F2 population; Figure 8 Figure (B) shows the results of genotyping the F2 population using the LN.A02-9283404 marker;

[0148] Table 6

[0149]

[0150] Example 2:

[0151] The following is an evaluation of the validity of the molecular marker LN.A02-9283404 based on genetic population:

[0152] Ten F2 heterozygous plants with the LN.A02-9283404 locus were screened using this marker, and segregating populations were constructed by self-pollination. The number of leaves on each of the 154 plants in the segregating population was investigated, and DNA was extracted using the CTAB method for candidate marker validation. PCR amplification and genotyping were performed using primers with the LN.A02-9283404 marker (PCR reaction conditions and parameters are shown in Tables 1 and 2). Among the 154 plants, the genotype distribution ratio of the LN.A02-9283404 marker was approximately FAM:FAMHEX:HEX = 1:2:1. The number of leaves differed significantly among plants with different fluorescence levels (p < 0.01), with FAM and FAMHEX fluorescence indicating more leaves and HEX fluorescence indicating fewer leaves. One recombinant plantlet selected from LN.A02-9283404 (recombination exchange rate 1 / 154 = 0.65%) showed co-segregation with the candidate gene for leaf number. This marker can be applied to leaf number screening in Brassica napus, providing a new method for rapeseed plant type breeding and high light efficiency breeding.

[0153] Figure 9 This is the KASP marker verification diagram in Embodiment 2 of the present invention; Figure 9 Figure (A) shows the typing results in the remaining heterozygous progeny lines (154 lines); Figure 9Figure (B) shows the phenotypic comparison results of different genotypes (TT, TC, CC) of the marker LN.A02-9283404. One-way ANOVA showed that the differences in leaf number among the genotypes were significant (p<0.01).

[0154] The results showed that genotyping and leaf number association analysis of the segregating population of Brassica napus using the LN.A02-9283404 marker revealed a significant correlation between different genotypes of the marker and the leaf number trait, effectively distinguishing between multi-leaf and sparse-leaf types. Furthermore, the marker was highly linked to candidate genes regulating leaf number, exhibiting good co-segregation characteristics. These results fully validate the reliability and effectiveness of this marker in leaf number-assisted selection of Brassica napus, providing a solid foundation for its application in rapeseed plant architecture improvement and high-light-efficiency breeding.

[0155] The above are merely preferred embodiments of the present invention and do not limit the patent scope of the present invention. Various modifications and variations can be made to the present invention by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the patent protection scope of the present invention.

Claims

1. Use of a reagent for a SNP marker that detects the number of leaf of Brassica napus for assisted selection of the number of leaf of Brassica napus at rosette stage, characterized in that, The SNP marker is located at 9283404bp of chromosome A02 of Brassica napus genome, the reference genome version of the Brassica napus genome is ZS11 v0, the base of the SNP marker is T allele or C allele, wherein the plant with genotype TT of the SNP marker is associated with the leaf number trait, and the Brassica napus is a progeny population taking 2116C and ZH18 as parents.

2. Use according to claim 1, said reagents comprising a primer set for detecting a SNP marker for assisting selection of leaf number in Brassica napus, characterized in that, The primer set comprises a first primer, a second primer and a third primer; The nucleotide sequence of the first primer is shown in SEQ ID NO: 16; The nucleotide sequence of the second primer is shown in SEQ ID NO: 17; The nucleotide sequence of the third primer is shown in SEQ ID NO:

18.

3. A method for breeding Brassica napus having the trait of desirable leaf number, characterized in that, The method comprises the following steps: S1, extracting genomic DNA of a Brassica napus sample; S2, using the primer set of claim 2 to perform PCR amplification with the genomic DNA as a template; S3, detecting the amplification product to determine the genotype of the SNP marker of claim 1; S4, selecting a plant with genotype TT of the SNP marker as a breeding parent or for screening; wherein the ideal leaf number trait is a leaf number trait, the Brassica napus is a rosette stage Brassica napus, and the rosette stage Brassica napus is a progeny population taking 2116C and ZH18 as parents.

4. Use of a primer set for detecting the SNP marker of claim 1 in the preparation of a kit for assisting the selection of the number of rosette leaves of Brassica napus L. characterized in that, The primer set is used for detecting an SNP marker for assisting selection of leaf number of Brassica napus, and the primer set comprises a first primer, a second primer and a third primer, wherein the Brassica napus is a progeny population taking 2116C and ZH18 as parents; The nucleotide sequence of the first primer is shown in SEQ ID NO: 16; The nucleotide sequence of the second primer is shown in SEQ ID NO: 17; The nucleotide sequence of the third primer is shown in SEQ ID NO: 18.

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