Gene for assisting breeding of low-palmitic-acid rape, molecular marker and application

Abstract

The invention belongs to the technical field of rape breeding and molecular biology, and particularly relates to a gene for assisting low-palmitic-acid rape breeding, a molecular marker and application. The invention firstly provides a gene and / or a gene composition for reducing the content of palmitic acid in rape seeds, wherein the gene composition comprises any one or more of the following genes: BnaA08. DAP, BnaA08. PAA1, BnaAO8. DUF106 and BnaC03. DAP. The invention also provides a method for preparing the gene composition for reducing the content of palmitic acid in the rape seeds, and the gene composition comprises any one or more of the following genes: BnaA08. DAP, BnaA08. PAA1, BnaAO8. DUF106 and BnaC03. DAP. Based on the gene and / or the gene composition, four low-SPAC haplotypes are identified, and a molecular marker for assisting low-palmitic acid breeding is developed at the same time. The invention is of great significance to molecular breeding of brassica napus.

Description

Technical Field

[0001] The invention belongs to the technical field of rapeseed breeding and molecular biology, and in particular relates to a gene and a molecular marker for assisting low-palmitic acid rapeseed breeding and an application thereof. Background Art

[0002] Brassica napus is the second largest oil crop in the world after soybeans. The fatty acid composition of rapeseed oil is divided into saturated fatty acids and unsaturated fatty acids, among which unsaturated fatty acids include oleic acid, linoleic acid, linolenic acid and erucic acid, and saturated fatty acids are mainly palmitic acid and stearic acid. Long-term consumption of edible oil with high palmitic acid content will increase the level of low-density lipoprotein cholesterol in the blood, thereby increasing the risk of cardiovascular disease. Therefore, reducing the content of saturated fatty acids in rapeseed oil, especially palmitic acid, can effectively improve the quality of rapeseed oil, which is of great significance to improving human health and increasing farmers' income.

[0003] Existing studies have confirmed that breeding efficiency can be greatly improved by mining candidate genes that affect target traits and using genetic engineering technology. For example, 1) Zheng H et al. reported in "GmWRI1c increases palmitic acid content to regulate seed oil content and nodulation in soybean (Glycine max)" that overexpression of Arabidopsis WRI1 homologous gene GmWRI1c can significantly increase the palmitic acid content in soybean seeds. 2) Wang Z et al. reported in "Overexpression of Soybean GmWRI1a Stably Increases the Seed Oil Content in Soybean" that overexpression of another homologous gene of soybean WRI1 GmWRI1a reduced the palmitic acid content in seeds from 15% to 8%, while increasing the seed oil content from 22% to 31%. 3) Rajcan I et al. reported in "Reduced palmitic acid content in soybean as a result of mutation in FATB1a" that knocking out the FATB1A gene can reduce the SPAC of soybean seeds from 18% to 11%. 4) Belide S et al. reported in "Modification of seed oil composition in Arabidopsis by artificial microRNA-Mediated Gene Silencing" that silencing the FATB gene in rapeseed can reduce the palmitic acid content in seeds from 8% to 4.4%. 5) Xiao Z et al. reported in "The Brassica napus fatty acid exporter FAX1-1 contributes to biological yield, seed oil content, and oil quality" that overexpression of the BnaFAX1 gene can significantly reduce the palmitic acid content in rapeseed seeds. Therefore, exploring candidate genes that regulate the palmitic acid content of rapeseed seeds and identifying excellent alleles with low SPAC that do not affect total oil content and seed yield can provide important gene resources for molecular breeding of rapeseed.

[0004] Genome-wide association analysis (GWAS) has been widely used to explore fatty acid-related genes in crops such as rice, corn, soybean and rapeseed. For example, Qi Z et al. conducted a GWAS analysis on the content of 6 fatty acids in 547 soybean varieties in "Natural variation in FattyAcid 9is a determinantoffatty acid andprotein content" and found a multi-fatty acid co-localization QTL on chromosome A09. The candidate gene GmFA9 was identified by combining fatty acid profile analysis, genome resequencing and population genetics analysis. Knocking out GmFA9 can significantly increase the palmitic acid content in soybean seeds. Qu C et al. conducted a GWAS analysis on the fatty acid content of 520 Brassica napus varieties in "Genome-wide association mapping and identification of candidate genes for fatty acid composition in Brassica napus L.using SNP markers", identified 6 genetic regions significantly associated with fatty acid content, and identified 24 candidate genes.

[0005] In the prior art, patent CN108300801B discloses a molecular marker and application closely related to rapeseed grain weight and silique length, which is a molecular marker for gene BnaA.ARF18a. Based on this molecular marker, the grain weight and silique length of a single plant of different varieties of rapeseed can be identified during the seedling stage. Patent CN113061616B discloses a gene related to rapeseed thousand-grain weight and its molecular marker and application. The patent compares and analyzes the 15bp difference of the 1000-grain weight-related gene BnaGRF7.C02 in different rapeseed germplasms, and then concludes that the difference of this 15bp is associated with the 1000-grain weight of rapeseed through association analysis. Then, molecular marker primers related to the 1000-grain weight of rapeseed are further designed to screen whether the rapeseed BnaGRF7.C02 gene contains 15bp, and are used for high-yield breeding of rapeseed.

[0006] Breeding high-quality rapeseed varieties is a long-term breeding goal, but there is currently a lack of means to effectively reduce the palmitic acid content in rapeseed seeds, as well as a lack of breeding methods for low-palmitic acid rapeseed. Summary of the invention

[0007] In view of this, one of the objects of the present invention is to provide a gene and / or gene combination for reducing the palmitic acid content in rapeseed seeds, wherein the gene and / or gene combination can improve the palmitic acid content in rapeseed seeds.

[0008] To achieve the above object, the technical solution of the present invention is:

[0009] Genes and / or gene combinations for reducing the palmitic acid content in rapeseed seeds, the gene combination comprising any one or more of the following genes: BnaA08.DAP, BnaA08.PAA1, BnaAO8.DUF106 and BnaC03.DAP.

[0010] As a combination method one, it can be: BnaA08.DAP and BnaA08.PAA1.

[0011] The second combination may be: BnaA08.DAP and BnaAO8.DUF106.

[0012] As a third combination: it can be: BnaAO8.DUF106 and BnaC03.DAP.

[0013] This is not an exhaustive list of all permutations and combinations.

[0014] Furthermore, the nucleotide sequences of BnaA08.DAP, BnaA08.PAA1, BnaAO8.DUF106 and BnaC03.DAP are shown in SEQ ID NO:1 to SEQ ID NO:4 respectively.

[0015] A second object of the present invention is to provide a method for reducing the palmitic acid content in rapeseed seeds.

[0016] To achieve the above object, the technical solution of the present invention is:

[0017] A method for reducing the palmitic acid content in rapeseed seeds, using the aforementioned gene and / or gene combination as a marker, and reducing the palmitic acid content in rapeseed seeds by knocking out and / or overexpressing the gene and / or gene combination; using the gene and / or gene combination as a marker for determination, the expression level of the gene and / or gene combination is correlated with the SPAC content.

[0018] This correlation can be either positive or negative.

[0019] Furthermore, the expression levels of BnaA08.DAP and BnaA08.PAA1 were negatively correlated with the SPAC content; the expression levels of BnaAO8.DUF106 and BnaC03.DAP were positively correlated with the SPAC content.

[0020] The third object of the present invention is to provide a molecular marker based on the aforementioned gene and / or gene combination, which can specifically detect the BnaA08.DUF106 gene. At the same time, a method for obtaining the molecular marker and its application are also provided.

[0021] To achieve the above object, the technical solution of the present invention is:

[0022] Based on the molecular marker of the aforementioned gene and / or gene combination, the gene is BnaA08.DUF106, and the detection primers of the molecular marker include BnaA08.DUF106-F with a nucleotide sequence as shown in SEQ ID NO:5 and BnaA08.DUF106-R with a nucleotide sequence as shown in SEQ ID NO:6.

[0023] Furthermore, the preparation method of the molecular marker of the gene and / or gene combination is:

[0024] The sequences of the aforementioned genes and / or gene combinations and their homologous genes are subjected to multiple sequence alignment to identify whether the SNP within the gene that is significantly associated with SPAC is located at the restriction site; then the AmplifX software is used to design SNP upstream and downstream specific primers for developing molecular markers.

[0025] Further, the method for reducing the palmitic acid content in rapeseed seeds based on the above molecular markers comprises the following steps:

[0026] (1) using the detection primers of the aforementioned molecular markers and the DNA of a single strain of Brassica oleracea as a template, to perform PCR amplification to obtain an amplified product;

[0027] (2) digesting the amplified product obtained in step (1) with NcoI, separating by electrophoresis, and identifying a rapeseed variety with a low palmitic acid content; if bands of 333 bp and 157 bp are observed in the digestion product, it indicates that the single strain of Brassica napus is a rapeseed variety with a high palmitic acid content; if bands of 333 bp and 157 bp are not observed in the digestion product, it indicates that the single strain of Brassica napus is a rapeseed variety with a low palmitic acid content;

[0028] (3) Using the rapeseed seeds identified as having low palmitic acid content in step (2) for breeding.

[0029] The fourth object of the present invention is to provide a method for identifying low-SPAC haplotypes using the aforementioned genes or gene markers, and low-SPAC haplotypes obtained by the method, and also to provide applications of the aforementioned genes or gene markers and molecular markers.

[0030] To achieve the above object, the technical solution of the present invention is:

[0031] The method for identifying low SPAC haplotypes using the aforementioned genes or gene markers is based on SNP sites within the aforementioned genes and / or gene combinations, and identifies low SPAC haplotypes through association analysis and haplotype analysis of the genes and / or gene combinations.

[0032] Further, when the low SPAC haplotype is identified, seeds that meet the conditions are used for breeding and / or large-scale planting.

[0033] Furthermore, the biological sequence obtained by the method is TAAC.

[0034] The biological sequence was voluntarily named LSPACHap.

[0035] The Brassica napus variety carrying the biological sequence has a lower SPAC content, and the seed oil content, protein content and single plant yield are not affected.

[0036] Furthermore, the aforementioned gene / gene combination, the aforementioned molecular marker and / or the aforementioned biological sequence are used in identifying rapeseed with low palmitic acid content and / or assisting in the breeding of rapeseed with low palmitic acid content.

[0037] The beneficial effects of the present invention are:

[0038] 1. The present invention investigated the seed palmitic acid content of 393 Brassica napus varieties in Wuhan, Xiema and Sansheng, and identified 9 QTLs significantly associated with SPAC through whole genome association analysis. By combining the whole transcriptome association analysis, 4 candidate genes affecting seed palmitic acid content were finally identified: BnaA08.DAP, BnaA08.PAA1, BnaA08.DUF106, BnaC03.DAP. The expression levels of these genes in seeds showed a significant correlation with SPAC.

[0039] 2. Based on the SNP sites of candidate genes, the present invention identified four low-SPAC haplotypes through candidate gene association analysis and haplotype analysis. The SPAC of Brassica napus varieties carrying low-SPAC haplotypes is significantly lower than that of rapeseed varieties carrying high-SPAC haplotypes, but the seed oil content, protein content and single plant yield are not affected.

[0040] 3. Based on SNP chrA08_9529850 (C / A) in the BnaA08.DUF106 promoter, the present invention developed a molecular marker Bn_A8_SPAC_Marker that can be used to assist low palmitic acid breeding, which is of great significance for the cultivation of rapeseed seeds with low palmitic acid content. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] Figure 1This is a graph showing the SPAC correlation analysis results for different locations in the association analysis group;

[0042] Figure 2 This is the result of genome-wide association analysis of palmitic acid content in Brassica napus seeds in Wuhan, where WH stands for Wuhan;

[0043] Figure 3 The results of genome-wide association analysis of palmitic acid content in Brassica napus seeds of Sansheng are shown in Figure 1, where SS stands for Sansheng;

[0044] Figure 4 The figure is the result of genome-wide association analysis of palmitic acid content in Brassica napus seeds of Xiema, where XM represents Xiema;

[0045] Figure 5 This is the mean result diagram of the genome-wide association analysis of palmitic acid content in Brassica napus seeds in Wuhan, Sansheng and Xiema, where MV represents the mean;

[0046] Figure 6 This is the result diagram of superior allele identification, where: Figure 6 -A is the SPAC identification result diagram of chrA08_229357; Figure 6 -B is the SPAC identification result diagram of ChrA08__10194057; Figure 6 -C is the SPAC identification result diagram of ChrA09__3050970; Figure 6 -D is the SPAC identification result diagram of ChrA09__31541180; Figure 6 -E is the SPAC identification result diagram of ChrC03__49325739; Figure 6 -F is the SPAC identification result diagram of ChrC03__55621804; Figure 6 -G is the SPAC identification result diagram of ChrC04__3880361; Figure 6 -H is the SPAC identification result diagram of ChrC06__33011759;

[0047] Figure 7 This is a graph showing the correlation analysis between the number of superior alleles carried by rapeseed varieties in the association analysis population and SPAC;

[0048] Figure 8 Manhattan plot of the whole transcriptome association analysis at 20 DAF;

[0049] Fig. 9 Manhattan plot of the whole transcriptome association analysis at 40 DAF;

[0050] Fig.10This is the correlation analysis diagram between the candidate gene expression and SPAC at 20DAF; Fig.10 -A is the correlation analysis diagram of BnaA08.DAP expression and SPAC at 20DAF; Fig.10 -B is the correlation analysis diagram of BnaA08.PAA1 expression and SPAC at 20DAF; Fig.10 -C is the correlation analysis diagram of BnaA08.DUF106 expression and SPAC at 20DAF; Fig.10 - Correlation analysis diagram of BnaC03.DAP expression and SPAC when D is 20DAF;

[0051] Fig.11 This is the correlation analysis diagram between the candidate gene expression and SPAC at 40DAF; Fig.11 -A is the correlation analysis diagram of BnaA08.DAP expression and SPAC at 40DAF; Fig.11 -B is the correlation analysis diagram of BnaA08.PAA1 expression and SPAC at 40DAF; Fig.11 -C is the correlation analysis diagram of BnaA08.DUF106 expression and SPAC at 40DAF; Fig.11 - Correlation analysis diagram of BnaC03.DAP expression and SPAC when D is 40DAF;

[0052] Fig.12 Gene enrichment analysis diagram of candidate genes significantly associated with SPAC;

[0053] Fig.13 It is a graph showing the association analysis of the SNP sites in the candidate gene BnaA08.DAP with the candidate gene of SPAC and two haplotypes of the BnaA08.DAP gene; wherein, Fig.13 -A is the association analysis diagram of the SNP sites in the BnaA08.DAP gene and the candidate genes of SPAC; Fig.13 -B is a diagram of two haplotypes of the BnaA08.DAP gene;

[0054] Fig.14 This is the association analysis diagram of the candidate gene BnaA08.PAA1 with the candidate gene of SPAC; Fig.14 -A is the association analysis diagram of the SNP sites in the BnaA08.PAA1 gene and the candidate genes of SPAC; Fig.14 -B is a diagram of two haplotypes of the BnaA08.PAA1 gene;

[0055] Fig.15 This is the association analysis diagram of the SNP sites in the candidate gene BnaA08.DUF106 and the candidate gene of SPAC; Fig.15 -A is the association analysis diagram of the SNP sites in the BnaA08.DUF106 gene and the candidate genes of SPAC; Fig.15 -B is a diagram of two haplotypes of the BnaA08.DUF106 gene;

[0056] Fig.16 This is the association analysis diagram of the SNP sites in the candidate gene BnaC03.DAP and the candidate gene of SPAC; Fig.16 -A is the association analysis diagram of the SNP sites in the BnaC03.DAP gene and the candidate genes of SPAC; Fig.16 -B is a diagram of two haplotypes of the BnaC03.DAP gene;

[0057] Fig.17 This is a comparison chart of the differences in seed palmitic acid content, total oil content, seed protein content and single plant yield between rapeseed varieties carrying LSPACHap and HSPACHap; Fig.17 -A is a comparison of the difference in seed palmitic acid content between rapeseed varieties carrying LSPACHap and HSPACHap; Fig.17 -B is a comparison of the total oil content between rapeseed varieties carrying LSPACHap and HSPACHap; Fig.17 -C is a comparison of the differences in seed protein content between rapeseed varieties carrying LSPACHap and HSPACHap; Fig.17 -D is a comparison of the difference in single plant yield between rapeseed varieties carrying LSPACHap and HSPACHap;

[0058] Fig.18 This is a differential analysis diagram of SPAC of two alleles of chrA08_9529850 (C / A) under different environments; Fig.18 -A is a differential analysis diagram of SPAC of rapeseed varieties carrying two alleles of chrA08_9529850 (C / A) in Xiema Town; Fig.18 -B is a differential analysis diagram of SPAC of rapeseed varieties carrying two alleles of chrA08_9529850 (C / A) in Wuhan; Fig.18 -C is a differential analysis diagram of SPAC of rapeseed varieties carrying two alleles of chrA08_9529850 (C / A) in Sansheng Town; Fig.18 -D is a differential analysis diagram of SPAC of the three locations of rapeseed varieties carrying two alleles of chrA08_9529850 (C / A);

[0059] Fig.19 A map showing the location of chrA08_9529850 (C / A) in BnaA08.DUF106;

[0060] Fig. 20 The electrophoresis diagram of 10 cabbage varieties with different genes after NcoI digestion. DETAILED DESCRIPTION

[0061] The technical solution of the present invention will be further described clearly and completely in conjunction with specific embodiments below. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all the embodiments. Therefore, based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative work belong to the protection scope of the present invention.

[0062] In order to enhance the understanding of the present invention, some key technical and scientific terms are clearly defined below. Unless otherwise specifically defined in this article, all other technical and scientific terms follow the meanings generally accepted and understood in the field to which the present invention belongs. It should be emphasized that the scope of the present invention is not limited to the specific methods, compositions or biological systems described, but allows reasonable flexibility and adjustment in these aspects. At the same time, please understand that the terms used in this article are intended to illustrate specific embodiments, rather than to be interpreted restrictively.

[0063] In addition, all literature cited herein, including but not limited to patents, patent applications, academic papers, textbooks and further citations therein, are deemed to be incorporated herein by reference as a whole to the extent not directly cited. If there is any inconsistency or conflict between the contents of these cited documents or similar materials and this application, especially in terms of term definitions, term usage, technical descriptions, etc., the contents of this application shall prevail.

[0064] In the embodiments of the present invention, some key technical and scientific terms are defined as follows:

[0065] Genome-wide association study (GWAS): A high-throughput, unbiased genetic research method that aims to identify genetic loci that are significantly associated with complex traits by comparing the correlation between genetic variations (such as SNPs) and specific phenotypes (such as disease states, physiological indicators, etc.) at the genome-wide level in different individuals. GWAS is based on the principle of linkage disequilibrium (LD), that is, adjacent genetic variants tend to be inherited together, so pathogenic variants can be captured indirectly through marker SNPs.

[0066] SNP site: Single Nucleotide Polymorphism (SNP) site refers to the DNA sequence polymorphism caused by the variation of a single nucleotide within the gene sequence.

[0067] Coding region (exon): SNPs located in the coding region of a gene may directly affect the amino acid sequence of the protein, thereby changing the structure and function of the protein.

[0068] Non-coding regions (introns, regulatory sequences, etc.): Although SNPs in non-coding regions do not directly change the amino acid sequence of proteins, they may indirectly affect the function of genes by affecting gene expression regulation (such as transcription factor binding sites, splicing sites, etc.).

[0069] Haplotype: A group of DNA variations (or polymorphisms) that tend to be inherited together along a chromosome. These variations tend to be inherited together because they are located close to each other on the chromosome and recombination between them is rare. A haplotype can include one or more genes that are located closely together on the chromosome and whose alleles (different forms of the gene that control the same trait) are arranged in sequence.

[0070] In the embodiment of the present invention, the sequence information involved is shown in Table 1.

[0071] Table 1. List of biological sequences

[0072] serial number name Involved rights SEQ ID NO:1 BnaA08.DAP Right 2 SEQ ID NO:2 BnaA08.PAA1 Right 2 SEQ ID NO:3 BnaAO8.DUF106 Right 2 SEQ ID NO:4 BnaC03.DAP Right 2 SEQ ID NO:5 BnaA08.DUF106-F Right 4 SEQ ID NO:6 BnaA08.DUF106-R Right 4

[0073] Example 1. Rapeseed planting and investigation of palmitic acid content in seeds

[0074] 393 rapeseed varieties were planted in Wuhan, Hubei, Sansheng, Chongqing, and Xiema, Chongqing. Each variety was planted in three rows, with 12 plants in each row, and the row and plant spacing was 20 cm. After harvest, the seeds were scanned three times using a near-infrared spectrometer, and the mean of the three scans was used as the final phenotypic value of seed palmitic acid content for subsequent GWAS analysis.

[0075] The results of the SPAC inspection are shown in Table 2. Figure 1 As shown, the SPAC of this group has a wide range of phenotypic variation. In Wuhan, the range of SPAC is between 2.98% and 5.6%, in Qingsansheng, the range of SPAC is between 3.06% and 5.86%, and in Xiema, the range of SPAC is between 3.23% and 5.97%. At the same time, the coefficient of variation of SPAC among the three planting sites ranges from 9.51% to 12.89%. In addition, the SPAC of this association analysis group at different planting sites also has a very significant correlation, for example, the correlation coefficient of SPAC between Wuhan and Sansheng is 0.70, and the correlation coefficient of SPAC between Wuhan and Xiema is 0.82.

[0076] Table 2. Statistical analysis of palmitic acid content in seeds of the association analysis population

[0077]

[0078] Example 2. Genome-wide association analysis

[0079] In the early stage, 505 samples of Brassica napus were whole-genome resequenced, and more than 10 million SNP sites were developed based on the Darmor reference genome. For details, see "Tang S, Zhao H, Lu S, et al. 2021. Genome-and transcriptome-wide association studies provide insights into the genetic basis of natural variation of seed oil content in Brassica napus. Molecular Plant, 14, 470-87". In this study, 393 samples of rapeseed were selected for subsequent whole-genome association analysis. First, the VCFtools software was used to filter the above SNP sites according to the screening criteria of near allele frequency>0.05 and missing rate<0.2, and 4.6 million SNP sites were obtained for this GWAS analysis. The Fast-LMM model was used to perform GWAS analysis on the SPACs of 393 rapeseed samples in Wuhan, Xiema, and Sansheng, with a 1×10 -10 As the threshold, SNP sites significantly associated with SPAC were screened.

[0080] Results: Figure 2 to Figure 5 As shown, the present invention identified 8 stable genetic regions significantly associated with SPAC. These QTLs are distributed on chromosomes A08, A09, C03, C04 and C06, which can explain 18.69% to 47.66% of the phenotypic variation. For details, see Figure 2 to Figure 5 and Table 3. Subsequently, eight low-SPAC alleles were identified based on the lead SNPs in the QTL, for example, the T allele in chrA08_229357 (C / T), the G allele in chrA08_10194057 (A / G), the A allele in chrA09_3050970 (G / A), and the C allele in chrA09_31541180 (A / C) are all low-SPAC alleles, see for details. Figure 6 At the same time, there is a very significant negative correlation between the number of low SPAC alleles carried by the variety and SPAC (p value: 2.2e-16, R: -0.641), see Figure 7 .

[0081] Table 3. Genetic regions significantly associated with SPAC identified by GWAS

[0082] ID SNP Name SNP physical location Phenotype explanation rate (%) environment qSPAC.A08.1 ChrA08__229357 229357 18.69％ XM / MV qSPAC.A08.2 ChrA08__10194057 10194057 47.66％ WH / XM / SS / MV qSPAC.A09.1 ChrA09__3050970 3050970 18.74％ SS / MV qSPAC.A09.2 ChrA09__31541180 31541180 23.65％ WH / XM / SS / MV qSPAC.C03.1 ChrC03__49325739 49325739 21.62％ SS / MV qSPAC.C03.2 ChrC03__55621804 55621804 33.27％ WH / XM / SS / MV qSPAC.C04 ChrC04__3880361 3880361 27.53％ WH / XM / SS / MV qSPAC.C06 ChrC06__33011759 33011759 29.28％ WH / XM / SS / MV

[0083] Example 3. Whole transcriptome association analysis

[0084] Tang et al. previously sequenced the transcriptome of seeds 20 days after flowering (20 DAF) and 40 days after flowering (40 DAF) in the association analysis population; the data have been uploaded to the BnIR database, see "Tang S, Zhao H, Lu S, et al. 2021. Genome- and transcriptome-wide association studies provide insights into the genetic basis of natural variation of seed oil content in Brassic anapus. Molecular Plant, 14, 470-87" and "Yang Z, Wang S, Wei L, et al. 2023. BnIR: A multi-omics database with various tools for Brassica napus research and breeding. Molecular Plant, 16, 775-89". In this study, BnIR was used to perform TWAS analysis on SPAC, with a 1×10 -5 The candidate genes significantly correlated with SPAC were screened as a threshold. The BnIR database was used to calculate the correlation between the gene expression of candidate genes at 20DAF and 40DAF and SPAC. Gene enrichment analysis was performed using the OmicShare online website (https: / / www.omicshare.com / ).

[0085] Results: The results of the whole transcriptome association analysis of 393 rapeseed varieties SPAC are as follows Figure 8 to Figure 12 As shown. The present invention uses the BnIR database to perform TWAS analysis on the SPAC of this group, and identifies 16 and 62 candidate genes significantly associated with SPAC at 20DAF and 40DAF, respectively. GO enrichment analysis was performed on the above candidate genes, and the results showed that these candidate genes were mainly enriched in hydrolase activity (GO: 0016836), carbonate dehydratase activity (GO / 0004089), same protein binding (GO: 0042802), methylpentanedione-CoA hydratase activity (GO: 0004490) and L, L-diaminopimelate aminotransferase activity (GO: 0010285), etc. For details, see Fig.12. The present invention compares the candidate genes significantly associated with SPAC identified by TWAS with the genetic regions significantly associated with SPAC identified by GWAS, and combines the correlation between gene expression levels and SPAC to identify a total of 4 candidate genes: BnaA08.DAP, BnaA08.PAA1, BnaA08.DUF106 and BnaC03.DAP, whose nucleotide sequences are shown in SEQ ID NO:1 to SEQ ID NO:4. For example, at 20 DAF, the gene expression level of BnaA08.DUF106 in the association analysis population was significantly positively correlated with SPAC (p: 2.8e-6; R: 0.24), see Fig. 9 The above genes may play an important role in SPAC in Brassica napus.

[0086] Example 4. Identification of superior haplotypes

[0087] 1. Candidate gene association analysis and haplotype analysis

[0088] In order to identify the excellent allelic variation in the above candidate genes and explore their breeding value, the present invention extracted SNPs in the promoter region and coding region of 4 candidate genes, and performed candidate gene association analysis based on the general linear model to identify SNP sites significantly associated with SPAC in the gene. Specifically, VCFtools software was used to extract SNP variations in candidate genes BnaA08.DAP, BnaA08.PAA1, BnaA08.DUF106 and BnaC03.DAP genes. The GLM model in Tassel 5.0 software was used to perform candidate gene association analysis on the SNP variations of the above candidate genes and the SPAC of the rapeseed association analysis population, see "Bradbury PJ, Zhang Z, Kroon DE, Casstevens TM, Ramdoss Y, Buckler ES. 2007. TASSEL: software for association mapping of complex traits in diverse samples. Bioinformatics, 23, 2633-5". Haploview.4.2 software was used to perform haplotype analysis on significant SNP loci.

[0089] The results of the association analysis between the SNP sites in the four candidate genes and the candidate genes of SPAC are as follows Figure 13 to Figure 16Ten SNP loci significantly associated with SPAC were identified in the BnaA08.DAP gene, and haplotype typing was performed based on the lead SNP chrA08_10438041 (C / T). The SPAC of Brassica napus varieties carrying BnaA08.DAPHap1 was much lower than that of varieties carrying BnaA08.DAPHap2. For details, see Fig.13 . Fourteen SNPs significantly associated with SPAC were identified in BnaA08.PAA1. Based on the lead SNP chrA08_10480638 (C / A), haplotype typing was performed. SPAC of B. napus varieties carrying BnaA08.PAA1Hap1 was much lower than that of varieties carrying BnaA08.PAA1Hap2. For details, see Fig.14 Six SNPs significantly associated with SPAC were identified in BnaA08.DUF106. Based on the lead SNP chrA08_10486876 (A / C), haplotype typing was performed. The SPAC of B. napus varieties carrying BnaA08.DUF106Hap1 was much lower than that of varieties carrying BnaA08.DUF106Hap2. For details, see Fig.15 . Seven SNPs significantly associated with SPAC were identified in BnaC03.DAP. Based on the lead SNP chrC03_56246200 (C / T), haplotype typing was performed. SPAC of B. napus varieties carrying BnaC03.DAPHap1 was much lower than that of varieties carrying BnaC03.DAPHap2. For details, see Fig.16 .

[0090] According to statistics, 49 materials carried all low SPAC haplotypes, and 164 materials carried all high SPAC haplotypes.

[0091] 2. Analysis of differences in seed quality and yield traits between HSPACHap and LSPACHap

[0092] 49 rapeseed varieties carrying four low-SPAC haplotypes were defined as LSPACHap, and 164 rapeseed varieties carrying four high-SPAC haplotypes were defined as HSPACHap. These varieties were planted in Meichuan Town, Wuhan City, Hubei Province. After harvest, the yield per plant was investigated, and the total oil content and protein content of each rapeseed variety were determined using a DS2500 near-infrared analyzer. The Student t-test was used to compare the differences in the above traits between LSPACHap and HSPACHap.

[0093] LSPAC is composed of 4 SNPs, namely the T allele in chrA08_10438041 (C / T), the A allele in chrA08_10438628 (C / A), the C allele in chrA06_10486876 (A / C), and the T allele in chrC03_56246230 (C / T). Therefore, the nucleotide sequence of LSPACHap is TAAC.

[0094] The results are as follows Fig.17 As shown in Table 4, the average SPAC of LSPACHap was 3.52%, which was significantly lower than 4.66% of HSPACHap. The average oil content of LSPACHap was 40.21%, which was not significantly different from 40.27% of HSPACHap. The average seed protein content of LSPACHap was 26.41%, which was not significantly different from 25.91% of HSPACHap. More importantly, LSPACHap did not affect the seed yield of Brassica napus. The above results show that LSPACHap can be used as a high-quality haplotype for improving Brassica napus varieties.

[0095] Table 4. Comparison of seed quality traits and seed yield between LSPACHap and HSPACHap rapeseed varieties

[0096]

[0097] Note: In Table 4, SPAC represents seed palmitic acid content; SOC represents total oil content; SY represents yield; Pro represents protein content.

[0098] Example 5. Molecular marker development

[0099] The sequences of the candidate gene (BnaA08.DUF106) and its homologous genes were downloaded from the BnIR database, and multiple sequence alignment was performed using DNAMAN software (https: / / www.lynnon.com / dnaman.html). SnapGene software (https: / / www.genoscope.cns.fr / brassicanapus / ) was used to identify whether the SNP significantly associated with SPAC in the gene was located at the restriction site. AmplifX software was used to design specific primers about 500 bp upstream and downstream of the SNP for developing molecular markers, including BnaA08.DUF106-F with a nucleotide sequence as shown in SEQ ID NO:5 and BnaA08.DUF106-R with a nucleotide sequence as shown in SEQ ID NO:6. Five varieties with LSPACHap and HSPACHap haplotypes were selected for verification. After DNA was extracted, PCR amplification was performed using the above primers, and the PCR product was digested with the restriction endonuclease corresponding to the target SNP to verify the accuracy of the newly developed molecular marker.

[0100] Among the SNP sites significantly associated with SPAC in the above candidate genes, chrA08_9529850 (C / A) is located in the specific recognition sequence of the restriction endonuclease NcoI. Among the 393 varieties in the association analysis population, 35 varieties carry the A allele in chrA08_9529850 (C / A) and 299 varieties carry the C allele in chroA08_9539850 (C / A). SPAC of the two types of Brassica napus varieties has significant differences in different locations, see the figure for details. Fig.18 Importantly, chrA08_9529850 (C / A) is located in the promoter of gene BnaA08.DUF106. In 385 materials, the gene expression of BnaA08.DUF106 was significantly positively correlated with SPAC, see Figure 10-11 , Fig.19 Therefore, the present invention selected chrA08_9529850 (C / A) to develop molecular markers.

[0101] As shown in Table 5, the Brassica napus varieties L60, L198, L226, L262 and L340 all carry the C allele in chrA08_9529850 (C / A), and the SPAC of these rape varieties ranges from 4.62% to 5.04%. The Brassica napus varieties L732, L984, L994, L976 and L1014 all carry the A allele in chrA08_9529850 (C / A), and the SPAC of these rape varieties ranges from 3.14% to 3.71%. First, primers BnaA08.DUF106-F and BnaA08.DUF106-R were used to amplify the above varieties, and then the amplified fragments of the above varieties were digested with NcoI. The amplified fragments of the five high-SPAC varieties were cut into two fragments of 333bp and 157bp by NcoI, while the amplified fragments of the five low-SPAC varieties could not be cut by NcoI. The electrophoresis diagram of 10 cabbage varieties with different genes after NcoI digestion is shown in Fig. 20 .

[0102] In summary, the present invention developed a molecular marker based on SNP chrA08_9529850 (C / A) that can be used to identify low-SPAC varieties and named it Bn_A8_SPAC_marker.

[0103] Table 5. Information on 10 varieties used for molecular marker development

[0104] Name of accessions AlleleinchrA08__9529850(C / A) SEACinMV L60 C 4.73％ L198 C 4.62％ L226 C 4.89％ L262 C 4.65％ L340 C 5.04％ L732 A 3.24％ L984 A 3.71％ L994 A 3.14％ L976 A 3.22％ L1014 A 3.28％

Claims

1. A gene and / or gene combination for reducing the palmitic acid content in rapeseed seeds, characterized in that The gene composition includes any one or more of the following genes: BnaA08.DAP, BnaA08.PAA1, BnaAO8.DUF106 and BnaC03.DAP.

2. The gene and / or gene combination according to claim 1, characterized in that: The nucleotide sequences of BnaA08.DAP, BnaA08.PAA1, BnaAO8.DUF106 and BnaC03.DAP are shown in SEQ ID NO:1 to SEQ ID NO:4 respectively.

3. A method for reducing the palmitic acid content in rapeseed seeds, characterized in that The gene and / or gene combination described in any one of claims 1 to 2 is used as a marker, and the palmitic acid content in rapeseed seeds is reduced by knocking out and / or overexpressing the gene and / or gene combination; the expression level of the gene and / or gene combination is correlated with the SPAC content.

4. The molecular marker based on the gene and / or gene combination according to claim 1, characterized in that: The gene is BnaA08.DUF106, the molecular marker detection primer includes a nucleotide sequence as shown in SEQ ID NO:5 BnaA08.DUF106-F and BnaA08.DUF106-R whose nucleotide sequence is shown in SEQ ID NO:

6.

5. The method for preparing a molecular marker of a gene and / or gene combination according to claim 1, characterized in that: The sequences of the gene and / or gene composition and their homologous genes described in claim 1 are subjected to multiple sequence alignment to identify whether the SNP significantly associated with SPAC in the gene is located at the restriction site; then, the AmplifX software is used to design SNP upstream and downstream specific primers for developing molecular markers.

6. The method for reducing the palmitic acid content in rapeseed seeds based on the molecular marker according to claim 4, characterized in that: The steps include: (1) using the detection primers of the molecular marker described in claim 4 and the DNA of a single strain of Brassica oleracea as a template to perform PCR amplification to obtain an amplified product; (2) digesting the amplified product obtained in step (1) with NcoI, separating by electrophoresis, and identifying a rapeseed variety with a low palmitic acid content; if bands of 333 bp and 157 bp are observed in the digestion product, it indicates that the single strain of Brassica napus is a rapeseed variety with a high palmitic acid content; if bands of 333 bp and 157 bp are not observed in the digestion product, it indicates that the single strain of Brassica napus is a rapeseed variety with a low palmitic acid content; (3) Using the rapeseed seeds identified as having low palmitic acid content in step (2) for breeding.

7. A method for identifying a low-SPAC haplotype using the gene or gene marker according to any one of claims 1 to 2, characterized in that: Based on the SNP sites in the gene and / or gene combination described in claim 1, low SPAC haplotypes are identified through association analysis and haplotype analysis of the gene and / or gene combination.

8. The method according to claim 7, characterized in that Once low-SPAC haplotypes are identified, seeds that meet the conditions are used for breeding and / or large-scale planting.

9. The biological sequence obtained by the method of claim 7, characterized in that The biological sequence is TAAC.

10. Use of the gene / gene combination according to claim 1 or 2, the molecular marker according to claim 4 and / or the biological sequence according to claim 9 in identifying rapeseed with low palmitic acid content and / or assisting in breeding of rapeseed with low palmitic acid content.

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