A method for detecting barley variety specificity using ssr molecular markers

Abstract

The present application relates to a kind of methods for detecting barley variety specificity using SSR molecular markers, comprising: extracting the DNA of the sample to be tested variety;Using 35 pairs of SSR fluorescent labeled primers to PCR amplification of the template DNA of the variety to be tested;PCR product is detected by capillary electrophoresis to collect allelic variation data;Then the data collected are clustered using PowerMarker software;The number of difference sites between the variety to be tested and its nearest known variety is calculated, when the number of difference sites is >2, the variety to be tested is determined to have specificity, when the number of difference sites is ≤2, the variety to be tested is determined to be "doubtful same variety" with the known variety;The method can realize high-throughput detection, and has the advantages of more efficient, accurate and low cost in barley variety specificity detection.

Description

Technical Field

[0001] This invention relates to the field of molecular technology for plant variety protection, and in particular to a method for detecting barley variety specificity using SSR molecular markers, belonging to the field of barley variety management and application technology in agriculture. Background Technology

[0002] Barley (Hordeum vulgare L.) is an important field crop in my country, but it is classified as a non-major crop in terms of variety management. my country's newly implemented Seed Law in 2022 stipulates a variety registration system for non-major crops. Applicants for variety registration must submit reports on distinctness, uniformity, and stability tests to the relevant agricultural authorities. Distinctness is a necessary condition for determining barley varieties. The Seed Law defines "distinctness" as a plant variety having one or more traits that clearly distinguish it from plant varieties that have already been accepted for application, approved, registered, or protected, or that have already been sold or promoted (i.e., known varieties). Distinctness testing is a key and challenging aspect of the Plant Variety Testing (DUS) process.

[0003] For a long time, variety-specific identification has primarily relied on morphological traits, supplemented by physiological characteristics. These characteristics are the primary basis for variety approval and the granting of new variety rights, and also the foundation for variety identification and resolving variety disputes. However, this traditional identification can generally only be completed after the plant has completed its entire growth cycle, or even after harvest. Furthermore, many traits are quantitative traits, exhibiting continuous variation and susceptibility to environmental influences, which is detrimental to the accurate description of variety characteristics. DNA variation reflects the essential variation of a variety, is unaffected by the environment, has a short testing cycle, and is easily standardized. Among various DNA markers, microsatellite markers (SSR markers) are considered superior and have been applied in practice for auxiliary new variety testing and review, variety identification, and forensic identification in crops such as maize and rice.

[0004] Barley is a self-pollinating diploid crop (2n=14) with a haploid genome of 5.1 Gb (Nature (2012), 491:711-716. https: / / doi.org / 10.1038 / nature11543). In 2007, RK Varshney et al. constructed a high-density barley microsatellite consensus map with 775 SSR loci. The applicant's prior patent 201210326416.3 discloses a method for identifying barley varieties using SSR primers and its application. This patent mainly utilizes 14 pairs of basic core primers and 14 pairs of extended core primers to perform PCR amplification of sample DNA, followed by denaturing polyacrylamide gel electrophoresis of the PCR amplification products, silver staining, and variety identification by analyzing SSR band patterns between the tested barley variety and known barley varieties. The applicant discovered the following problems with the method for identifying variety specificity in subsequent applications of this scheme: (1) denaturing polyacrylamide gel electrophoresis cannot achieve high throughput and has low efficiency; (2) there are deviations in the reading of electrophoretic patterns, and it is difficult to distinguish varieties with very small allelic variations; (3) the number of molecular markers used in this patent is too small, and it cannot effectively distinguish new varieties with very similar genetic backgrounds. Therefore, the development of new molecular markers and their application in the identification of barley variety specificity has become a technical problem that urgently needs to be solved in this field. Summary of the Invention

[0005] To address the aforementioned technical problems, this invention provides a method for detecting barley variety specificity using SSR molecular markers. This method selects 35 SSR molecular markers from the barley chromosome and uses capillary electrophoresis for detection. The specificity of barley varieties is determined based on genetic similarity, making this method highly efficient and accurate.

[0006] The technical solution provided in this application is as follows:

[0007] A method for detecting barley variety specificity using SSR molecular markers includes the following steps:

[0008] (1) Extract DNA from the barley variety to be tested and / or known barley varieties.

[0009] This step uses the conventional method in the art to extract leaf DNA from the barley variety to be tested and / or known barley varieties as the DNA template for subsequent PCR reactions. For example, in the examples, a commercially available DNA extraction kit was used to extract sample DNA.

[0010] (2) PCR amplification was performed on template DNA of the test variety and / or known barley varieties using 35 pairs of SSR fluorescently labeled primers to obtain amplification products;

[0011] The 35 pairs of SSR fluorescently labeled primers mentioned above are Bmag0211, Bmag0770, Bmag0382, Bmag0378, Bmag0711, HVM54, Scssr07759, HVM36, EBmag0793, Bmac0209, Bmag0877, HVM27, HVM60, EBmac0708, HVM62, EBmac0701, EBmac0635, Bmag0353, HVM40, Bmac0181, B... The primer pairs mag0808, Scssr10148, Scssr03907, Scssr07106, Bmag0387, Bmag0223, Bmag0009, Bmag0867, Bmac0018, Scssr09398, Bmag0613, Scssr05599, HVCMA, EBmac0603, and Scssr15864 each contain two sequences: an upstream primer (F) and a downstream primer (R). The primer sequences are shown in Table 4.

[0012] In the detection, the 5' end of the upstream primers of primers Bmag0211, HVM36, EBmag0793, EBmac0635, Scssr10148, Bmag0223, Bmag0867, Bmag0613, and Scssr15864 was all linked to the fluorescent group ROX; the 5' end of the upstream primers of primers Bmag0770, HVM54, Bmac020, HVM27, EBmac0708, HVM62, EBmac0701, Bmag0353, and Scssr05599 was all linked to the fluorescent group. The 5' end of the upstream primers of HEX group Bmag0382, Bmag0877, HVM60, HVM40, Scssr03907, Scssr07106, Bmag0009, and Scssr09398 is attached to the fluorescent group TAMRA; the 5' end of the upstream primers of Bmag0378, Bmag0711, Scssr07759, Bmac0181, Bmag0808, Bmag0387, Bmac0018, HVCMA, and EBmac0603 is attached to the fluorescent group FAM.

[0013] PCR amplification system: 0.2 μL of 5 U / μL DNA Polymerase, 2.5 μL of Mg... 2+ The following ingredients were prepared: 10×PCR Buffer, 2 μL of 2.5 mmol / L dNTP solution, 1 μL of 10 μmol / L upstream primer (F), 1 μL of 10 μmol / L downstream primer (R), 1 μL of 20 ng / μL DNA template, and double-distilled water to a final volume of 25 μL.

[0014] PCR reaction program: 94℃ pre-denaturation for 5 min; 94℃ for 30 sec, 47~62℃ for 30 sec, 72℃ for 1 min, for a total of 35 amplification cycles; 72℃ extension for 5 min, and storage at 4℃.

[0015] (3) Allelic variation data were collected by capillary electrophoresis of PCR products;

[0016] (4) Use PowerMarker software to cluster the collected data;

[0017] (5) Calculate the number of differential sites between the variety to be tested and the known variety that is closest to it in the cluster. When the number of differential sites is >2, the variety to be tested is determined to be specific. When the number of differential sites is ≤2, the variety to be tested and the known variety are determined to be “suspiciously the same variety”. For the cases determined to be “suspiciously the same variety”, the variety to be tested shall be identified in the field in accordance with the provisions of the national standard GB / T 19557.31-2018.

[0018] The aforementioned "known barley varieties" refer to the known barley varieties as defined in the Seed Law: plant varieties whose applications have been accepted or have passed variety approval, registration, new variety protection, or have already been sold or promoted. In practice, the detection results of 35 primer pairs for known barley varieties can be stored in a computer to form a barley variety database, and then compared with the characteristics of the barley variety to be tested to obtain the "known variety with the closest cluster"; alternatively, allelic variation data can be collected simultaneously with the barley variety to be tested, and then compared to obtain the "known variety with the closest cluster".

[0019] The above step (3) capillary electrophoresis detection and collection of allelic variation data are as follows: 1) Dilute the FAM and HEX fluorescently labeled PCR products 30 times with ultrapure water, and dilute the TAMRA and ROX fluorescently labeled PCR products 10 times. Take equal volumes of the diluted solutions of different fluorescently labeled amplification products and mix them. After mixing, take 1 μL from the mixture and add it to a 96-well plate for the DNA analyzer. Add 0.1 μL of molecular weight internal standard and 8.9 μL of deionized formamide to each well of the plate. Denature the sample at 95℃ for 5 min on the PCR instrument, take it out, and immediately place it on crushed ice to cool for more than 10 min. Centrifuge briefly for 10 s and then place it on the DNA analyzer. 2) Turn on the DNA analyzer, check the instrument working status and reagent status, place the 96-well plate containing the sample on the sample rack base, open the data collection software, edit the sample table according to the instrument user manual, execute the running program, and the DNA analyzer will run automatically and save the original electrophoresis data. Allelic variations at each SSR locus are named in terms of amplified fragment size. Fragment analysis software from a capillary electrophoresis detection device is used to read the allelic variation data of the tested variety and its corresponding reference variety.

[0020] In specific implementation, when step (3) compares the variety to be tested with the varieties in the barley variety database to obtain the "most clustered known variety", it is preferable to use the reference variety correction data; that is, when detecting the allelic variation data of the variety to be tested, the PCR amplification products of 2 to 3 reference varieties (the varieties corresponding to each allelic variation of each SSR marker) are detected at the same time for each SSR site to correct the deviation of the allelic variation values ​​obtained from different batches.

[0021] Step (4) above uses PowerMarker software to cluster the collected data, which means: converting allelic variation data into a text document. Open PowerMarker software, import the data, New—create a .prj file; Dataser—right-click—import—open the above text document file, under Column Delimeters select Tab, Comma and Space—next; click “Sample” under Column (at this time, the Type column corresponding to “Sample” is Marker), then click Categorical (blue) below, the Type column corresponding to “Sample” becomes Categorical, select “Sample” in the Level-1 Column drop-down on the right—next; change the “?” to “0” on the right of Missing allele—next; finish, generate a file. Click Analysis—Phylogeny—computeFrequency in the toolbar—select the file generated in the previous step, select Compute frequency at level-1 in the Options on the right—Submit, generate a .Frequency file. Click on the toolbar: Analysis -> Phylogeny -> Frequency Based Distance -> Select the Frequency file generated in the previous step, choose Nei1983 in Choose Methods on the right, and submit to generate a .Frequency.Nei1983 file. Click on the toolbar again: Analysis -> Phylogeny -> UPGMA / NJ tree -> Select the Frequency.Nei1983 file generated in the previous step, choose Neighbor-Joining tree in Options on the right, and submit to generate a .Frequency.Nei1983.NJ file. Click on the toolbar again: Data -> Batch Export -> Select the .Frequency.Nei1983.NJ file on the left, choose Nexus data in Options Save Dataset as on the right, select the file save path, and submit to generate the clustering tree file.

[0022] In this application, the term "distinctiveness" means that a plant variety has more than one trait that is clearly different from known varieties.

[0023] Secondly, this application also provides the application of the above-mentioned method for detecting barley variety specificity using SSR molecular markers, namely, using the above-mentioned 35 pairs of SSR fluorescent marker primers for PCR amplification, collecting allelic variation data by capillary electrophoresis detection, using PowerMarker software to cluster the collected data, and identifying the barley variety to be tested and known barley varieties.

[0024] Third, this application also provides the application of the above-mentioned method for detecting barley variety specificity using SSR molecular markers, namely, using the above-mentioned 35 pairs of SSR fluorescent marker primers for PCR amplification, collecting allelic variation data by capillary electrophoresis detection, and using PowerMarker software to cluster the collected data to construct a barley variety database.

[0025] Compared with existing technologies (such as Chinese Patent 201210326416.3), the technical solution provided in this application can achieve the following beneficial effects: This application uses 35 pairs of SSR fluorescently labeled primers to perform PCR amplification, capillary electrophoresis detection, and analysis on barley varieties to obtain a large amount of allelic variation data. PowerMarker software is used to cluster the collected data, and then the number of differentially expressed sites between the tested variety and its closest known cluster is calculated. When the number of differentially expressed sites > 2, the tested variety is determined to be specific; when the number of differentially expressed sites ≤ 2, the tested variety and the known variety are determined to be "suspected similar varieties". For "suspected similar varieties", field identification is carried out according to GB / T 19557.31-2018. Its advantages are reflected in:

[0026] (1) High throughput can be achieved in electrophoresis detection, data reading is more accurate, time is more efficient, and cost is reduced;

[0027] (2) First, the collected data were clustered using PowerMarker software, and then the number of differential sites between the tested variety and the known varieties that were closest to it in the cluster was calculated, which improved the efficiency of statistical analysis.

[0028] (3) Planting only “similar varieties” in the field reduces a lot of time spent observing growth in the field, saving labor and financial resources;

[0029] (4) Barley has 7 pairs of chromosomes. In order to better represent the genetic variation among barley varieties, 35 SSR molecular markers were selected and distributed as evenly as possible on different chromosome sets. The increased number of molecular markers provides more complete chromosome coverage and better reflects the differences in genetic variation among varieties. The genetic similarity between varieties and the genetic similarity at 10K SNP loci calculated by this invention based on 35 molecular markers are highly correlated with the phenotypic distance between varieties, which is more conducive to the accuracy and rigor of specific detection. The detection results are more reliable. The cost of specific testing is further reduced. The accuracy of the experiment is improved. Attached Figure Description

[0030] Figure 1 Cluster diagram of 6 varieties to be tested and 100 known varieties.

[0031] Figure 2 This is a clustering diagram of SSR molecular data for an example.

[0032] Figure 3 This is a clustering diagram of SNP genotyping data for an example. Detailed Implementation

[0033] Source of experimental materials:

[0034] Table 1 lists the varieties to be tested, which were tested by the Plant Variety Testing Center (Nanjing) of the Ministry of Agriculture and Rural Affairs. The applicant collected the samples on March 10, 2021, at the DUS testing experimental field of the Lishui Plant Science Base of the Jiangsu Academy of Agricultural Sciences.

[0035] The known varieties listed in Table 2 have been deposited with the Plant Variety Preservation Center of the Plant Variety Protection Office of the Ministry of Agriculture and Rural Affairs (starting with "XIN") or with the Plant Variety Testing (Nanjing) Branch Center of the Ministry of Agriculture and Rural Affairs (starting with "NJ") at the Jiangsu Provincial Crop Germplasm Resource Bank. These varieties are all those whose applications have been accepted or have passed variety approval, variety registration, new variety protection, or have already been sold or promoted. They are all existing conventional varieties, some of which have been published on the "China Seed Industry Big Data Platform" (http: / / 202.127.42.145 / ) or reported in other literature.

[0036] Table 3 lists 227 barley varieties (some of which overlap with those in Table 2), all of which are existing varieties. Some of these varieties have been publicly available on the "China Seed Industry Big Data Platform" (http: / / 202.127.42.145 / ) or have been reported in other literature. In the examples, these seeds were sourced from the Plant Variety Preservation Center of the Plant Variety Protection Office of the Ministry of Agriculture and Rural Affairs or the Jiangsu Provincial Crop Germplasm Resource Bank.

[0037] Example 1

[0038] 1. Extract DNA from the sample of the variety to be tested.

[0039] DNA was extracted from the leaves of the barley variety to be tested using the DNAsecure novel plant genomic DNA extraction kit (centrifuge column type) produced by Tiangen Biotech (Beijing) Co., Ltd. For specific operating procedures, please refer to the kit instructions.

[0040] The test varieties used in this embodiment are the 6 test varieties shown in Table 1 and the 100 known varieties shown in Table 2. The sampling location is DNA from seeds or seedling leaves. The extraction method is the same as that in patent CN 201210326416.3, which is a conventional method in this field.

[0041] Table 1 Six varieties to be tested

[0042] D1 NJ20200018A D4 NJ20190017A D2 NJ20200016A D5 2017-1514A D3 NJ20190015A D6 NJ20170013A

[0043] Table 2 100 barley varieties

[0044]

[0045]

[0046] 1. Primer selection

[0047] By reviewing a large number of documents, such as the website "http: / / www.graingenes.org", and the literature "A highdensity barley microsatellite consensus map with 775 SSR loci" (Varshney RK et al., 2007) and "A Simple Sequence Repeat-Based Linkage Map of Barley" (R. Waugh et al., 2000), 325 barley SSR markers that had been mapped were selected. Further review of domestic and international literature on the genetic diversity of barley germplasm resources provided a preliminary understanding of the polymorphism research and application of the above markers. Analysis revealed 153 SSR markers with published primer sequences that exhibit polymorphism in barley varieties.

[0048] In this embodiment, the polymorphism of these 153 primer pairs was initially screened using 8 barley varieties, identifying 65 markers with polymorphism and clear amplification bands. These 65 markers were then used for PCR amplification of 63 barley varieties with significant differences in botanical traits. Reaction conditions were optimized, and the amplification products were detected by 6% denaturing polyacrylamide gel electrophoresis. The amplification stability and polymorphism of the primers were analyzed, identifying 45 primer pairs. Based on the fragment lengths amplified by the 45 primer pairs, one fluorescent dye from 6-FAM, ROX, TAMRA, and HEX was selected to label the 5' end of the upstream primer. The synthesized fluorescent primers were used to amplify 227 varieties (Table 3). After dilution, the amplified products were analyzed on an ABI 3730XL gene analyzer to analyze the distribution of primers on chromosomes. Based on the principles of easy reading of peak diagrams, high polymorphism, high amplification stability, high variety differentiation, and easy identification by electrophoresis of amplified products, 35 core primer pairs were finally determined for barley variety identification. Each primer pair consists of an upstream primer (F) and a downstream primer (R). The 5' end of the upstream primer (F) is connected to a fluorescent group to make it suitable for capillary fluorescence detection platforms as a barley variety-specific detection primer.

[0049] For the 35 labeled primer sequences, the upstream and downstream primers corresponding to the SSRs were obtained from http: / / www.graingenes.org, and the fluorescent labels with different fluorescent dyes at the 5' end of each primer pair were obtained (see Table 4).

[0050] Table 3227 Barley Varieties

[0051]

[0052]

[0053]

[0054]

[0055] Table 4 35 pairs of fluorescently labeled primers

[0056]

[0057]

[0058]

[0059] 3. PCR amplification was performed on the test varieties using 35 pairs of SSR fluorescent primers.

[0060] PCR amplification was performed using a 25 μL reaction system containing 0.2 μL of... 5 U / μL DNA Polymerase, 2.5 μL containing Mg 2+ 10×PCR Buffer (Shanghai Pudi Biotechnology Co., Ltd.), 2μL 2.5mmol / L dNTP solution (Shanghai Pudi Biotechnology Co., Ltd.), 1μL 10μmol / L upstream primer, 1μL 10μmol / L downstream primer, 1μL 20ng / μL DNA template, and double-distilled water to make up to 25μL.

[0061] The PCR reaction program was as follows: pre-denaturation at 94℃ for 5 min, 35 amplification cycles (94℃ for 30 sec, 47–62℃ (depending on the SSR primer annealing temperature recommended in Table 4) for 30 sec, 72℃ for 1 min), extension at 72℃ for 5 min, and storage at 4℃.

[0062] 4. Capillary electrophoresis

[0063] FAM and HEX fluorescently labeled PCR products were diluted 30-fold with ultrapure water, and TAMRA and ROX fluorescently labeled PCR products were diluted 10-fold. Equal volumes of the diluted solutions of the different fluorescently labeled amplification products were mixed, and 1 μL of the mixture was added to a 96-well plate for a DNA analyzer. 0.1 μL of molecular weight internal standard (LIZ 500 molecular weight internal standard, manufactured by ABI, USA) and 8.9 μL of deionized formamide were added to each well of the plate. The samples were denatured at 95°C for 5 min on a PCR instrument, then immediately placed on crushed ice and cooled for at least 10 min. After a brief centrifugation for 10 s, the samples were placed on the DNA analyzer. In addition to the sample to be tested, each SSR locus should also include amplification products from 2–3 reference strains.

[0064] The capillary electrophoresis experiment involved in this step is a conventional technique in this field, as disclosed in the literature “Dai Jian, Zhang Yunhui. Comparison of SSR amplification product detection methods and their experimental operation precautions. Seeds, 2013, 32(9): 120-123”.

[0065] 5. Analyze the results of capillary electrophoresis.

[0066] Image analysis and data acquisition were performed using GENEMAPPER software. Based on the different fluorescent groups inserted into the primers (Table 4), ROX was red fluorescence, FAM was blue fluorescence, TAMRA was black fluorescence, and HEX was green fluorescence.

[0067] Using pBR322DNA / Msp I as the DNA molecular weight standard, the allelic variation at each locus in the test sample was determined based on the amplified fragment size of the reference variety. Allelic variation data for homozygous loci were denoted as X / X, where X represents the allelic variation at that locus; allelic variation data for heterozygous loci were recorded as X / Y, where X and Y represent the two allelic variations at that locus, with the smaller fragment data appearing first, followed by the larger fragment data. Allelic variation data for deletion loci were recorded as 0 / 0. Allelic variation data for PCR amplification products from 106 varieties using 35 pairs of primers were obtained.

[0068] 6. Use PowerMarker software to cluster the collected data.

[0069] (1) Convert the data obtained in the above steps into a text document;

[0070] (2) Import data

[0071] Open PowerMarker software, New—I recommend one .prj file; Dataser—right-click—import—open the above text document file, under Column Detailers select Tab, Comma, and Space—next; click “Sample” under Column (at this time, the Type column corresponding to “Sample” will be Marker), then click Categorical (blue) below, the Type column corresponding to “Sample” will change to Categorical, select “Sample” in the Level-1 Column drop-down on the right—next; change the “?” to the right of Missing allele to “0”—next; finish, a file will be generated, and the data import is successful.

[0072] (3) After the data import is successful, click the toolbar Analysis——Phylogeny——computeFrequency——select the file generated in the previous step, select Compute frequency at level-1 in the Options on the right——Submit, and generate a .Frequency file;

[0073] (4) Click on the toolbar Analysis——Phylogeny——Frequency Based Distance——select the Frequency file generated in the previous step, select Nei1983 in Choose Methods on the right——Submit, and generate a .Frequency.Nei1983 file;

[0074] (5) Click the toolbar Analysis——Phylogeny——UPGMA / NJ tree——select the Frequency.Nei1983 file generated in the previous step, select Neighbor-Joining tree in the Options on the right——Submit, and generate a .Fquency.Nei1983.NJ file;

[0075] (6) Click Data in the toolbar—Batch Export—select the .Frequency.Nei1983.NJ file on the left—select Nexus data in Options Save Dataset on the right—select the file save path—Submit to generate the clustering tree file. Open and edit the clustering tree file using MEGA software, such as... Figure 1 .

[0076] 7. Calculation Figure 1 The number of differential sites between the tested variety and its nearest known variety is shown in Table 5.

[0077] Table 5. Number of differentially expressed sites between the tested variety and its nearest neighboring variety.

[0078] D1 B63 8 D1 B80 8 D2 B11 0 D3 B16 1 D4 B17 0 D4 B46 0 D5 B52 1 D6 B76 2

[0079] The genetic diversity of the 227 varieties at 35 marker loci in Table 3 was analyzed. Cluster analysis of the 227 barley varieties was performed based on Nei's standard genetic distance. The results showed that the 35 primer pairs shown in Table 4 could distinguish 198 of the 227 variety combinations, leaving only 9 groups (29 varieties) that could not be distinguished. Analysis of the relationships between varieties with genetic similarity greater than 90% revealed that these tested materials were mostly varieties of the same name from different sources or batches, or varieties with derivative relationships. The number of differing loci between these varieties ranged from 0 to 2. Therefore, varieties with a difference of >2 loci were classified as "different" varieties; varieties with a difference of ≤2 loci (genetic similarity ≥ 92%) were classified as "suspected similarity" varieties.

[0080] Based on the data in Table 5, the number of differing loci between D1 and B63 and B80 is 8, which is greater than 2, thus indicating specificity. The number of differing loci between D2 and B11, D3 and B16, D4 and B17 and B46, D5 and B52, and D6 and B76 is ≤2, thus these varieties are classified as "suspected homologous varieties." Field adjacent planting trials were conducted on these "suspected homologous varieties" according to GB / T 19557.31-2018, and the specificity of D2, D3, D4, D5, and D6 was ultimately determined based on the field identification results.

[0081] Example 2: Specificity Detection and Verification

[0082] 1. Phenotypic similarity analysis of combinations of varieties with SSR molecular marker genetic similarity of over 90%.

[0083] To verify the accuracy and efficiency of primers in distinguishing varieties, this embodiment collected phenotypic data of 227 varieties (Table 3) according to GB / T 19557.31-2018 "Guidelines for Testing Variety Specificity, Uniformity and Stability of Barley". Using 35 primer pairs (Table 4), 198 of the 227 variety combinations could be distinguished, leaving only 9 groups indistinguishable. Analysis of the phenotypic similarity of barley DUS test traits among the 29 varieties in the 9 groups revealed varying degrees of difference in field phenotypic traits among varieties indistinguishable by SSR molecular markers, with phenotypic similarity ranging from 0.797 to 1. Of the 10 pairs of varieties with phenotypic similarity above 0.99, 7 pairs were the same variety Supi 3, and 3 pairs were Supi 3 and Edan 259, SP30-5 and two different sources of Hua 30, respectively. Edan 259 was bred from a hybrid system of Supi 3 and Edamai 68231, while SP30-5 was bred from the chemically induced "Hua 30" system. There is a strong derivational relationship between Edan 259 and Supi 3, and between SP30-5 and Hua 30. Variety pairs with a phenotypic similarity of less than 0.99 include different varieties, different batches, or different years of planting with the same name. Among these barley varieties, Supi 3 and Hua 30 are both publicly known and approved varieties. Edan 259 is also a conventional variety, publicly available on the China Seed Industry Big Data Platform (http: / / 202.127.42.145 / ). SP30-5 is a known variety bred by the Shanghai Academy of Agricultural Sciences.

[0084] The reasons for the differences in phenotypic similarity despite the same genetic similarity are summarized as follows: (1) there is a derivational relationship between varieties, (2) different seed sources or batches, and (3) differences in phenotypic data collected in different years. Therefore, for varieties with ≤2 different loci (corresponding genetic similarity ≥92%) that are suspected to be identical, field adjacent planting identification should be carried out in accordance with the provisions of GB / T19557.31-2018 "Guidelines for Testing the Distinctiveness, Uniformity and Stability of Plant Varieties (Barley)".

[0085] The above experiments demonstrate that combining SSR molecular markers and field identification methods can effectively improve the accuracy of identification.

[0086] 2. Comparative Analysis of SSR Molecular Clustering and SNP Genotyping Clustering

[0087] To verify the feasibility of primers in differentiating varieties, duplicate varieties with the same name were removed from the 227 varieties detected in Table 3, and 194 distinct varieties were selected. Targeted sequencing of these varieties was performed using a 10K SNP liquid-phase chip covering all seven chromosomes of barley, developed using GenoBaits, a probe hybridization-based targeted sequencing genotyping technology developed by Bored Biotechnology Co., Ltd. (Shijiazhuang, China). Cluster analysis was performed based on the genotyping data of the 194 varieties at 28,143 SNP loci. The SSR molecular data clustering was compared (…). Figure 2 Clustering of SNP genotyping data Figure 3 The results showed that SSR clustering and SNP clustering were similar, and varieties with SNPs clustered together or close together had the same SSR clustering results. This indicates that the discrimination ability of the 35 pairs of SSR primers for barley varieties is consistent with the discrimination ability of the 28,143 SNP loci.

[0088] The above embodiments are not specific limitations of the present invention. Any use of the 35 pairs of SSR primers involved in the present invention, combined with basic common sense in the field, for barley variety specificity evaluation, variety identification, or data preparation for establishing a barley database, falls within the protection scope of the present invention.

Claims

1. A method for detecting barley variety specificity using SSR molecular markers, characterized in that, The specific steps are as follows: (1) Extract DNA from the barley variety to be tested and known barley varieties as template DNA, and perform PCR amplification using 35 pairs of SSR fluorescently labeled primers to obtain amplification products; The 35 pairs of SSR fluorescently labeled primers are as follows: upstream primer Bmag0211F and downstream primer Bmag0211R, as shown in SEQ IN NO.1 and SEQ IN NO.2, respectively; upstream primer Bmag0770F and downstream primer Bmag0770R, as shown in SEQ IN NO.3 and SEQ IN NO.4, respectively; upstream primer Bmag0382F and downstream primer Bmag0382R, as shown in SEQ IN NO.5 and SEQ IN NO.6, respectively; upstream primer Bmag0378F and downstream primer Bmag0378R, as shown in SEQ IN NO.7 and SEQ IN NO.8, respectively; upstream primer Bmag0711F and downstream primer Bmag0711R, as shown in SEQ IN NO.9 and SEQ IN NO.10, respectively; upstream primer HVM54F and downstream primer HVM54R, as shown in SEQ IN NO.11 and SEQ IN NO.12, respectively; and so on. The upstream primer Scssr07759F and downstream primer Scssr07759R shown in SEQ IN NO.13 and SEQ IN NO.14; the upstream primer HVM36F and downstream primer HVM36R shown in SEQ IN NO.15 and SEQ IN NO.16; the upstream primer EBmag0793F and downstream primer EBmag0793R shown in SEQ IN NO.17 and SEQ IN NO.18; the upstream primer Bmac0209F and downstream primer Bmac0209R shown in SEQ IN NO.19 and SEQ IN NO.20; the upstream primer Bmag0877F and downstream primer Bmag0877R shown in SEQ IN NO.21 and SEQ IN NO.22; the upstream primer HVM27F and downstream primer HVM27R shown in SEQ IN NO.23 and SEQ IN NO.24; and the nucleotide sequences shown in SEQ IN NO.25 and SEQ IN NO.

26. The upstream primer HVM60F and downstream primer HVM60R shown in SEQ IN NO.26; the upstream primer EBmac0708F and downstream primer EBmac0708R shown in SEQ IN NO.27 and SEQ IN NO.28, respectively; the upstream primer HVM62F and downstream primer HVM62R shown in SEQ IN NO.29 and SEQ IN NO.30, respectively; and the nucleotide sequences shown in SEQ IN NO.31 and SEQ IN NO.The upstream primer EBmac0701F and downstream primer EBmac0701R shown in SEQ IN NO. 32; the upstream primer EBmac0635F and downstream primer EBmac0635R shown in SEQ IN NO. 33 and SEQ IN NO. 34; the upstream primer Bmag0353F and downstream primer Bmag0353R shown in SEQ IN NO. 35 and SEQ IN NO. 36; the upstream primer HVM40F and downstream primer HVM40R shown in SEQ IN NO. 37 and SEQ IN NO. 38; the upstream primer Bmac0181F and downstream primer Bmac0181R shown in SEQ IN NO. 39 and SEQ IN NO. 40; the upstream primer Bmag0808F and downstream primer Bmag0808R shown in SEQ IN NO. 41 and SEQ IN NO. 42; and the primers Bmag0808F and Bmag0808R shown in SEQ IN NO. 43 and SEQ IN NO.

44. The upstream primer Scssr10148F and downstream primer Scssr10148R shown in SEQ IN NO.44; the upstream primer Scssr03907F and downstream primer Scssr03907R shown in SEQ IN NO.45 and SEQ IN NO.46; the upstream primer Scssr07106F and downstream primer Scssr07106R shown in SEQ IN NO.47 and SEQ IN NO.48; the upstream primer Bmag0387F and downstream primer Bmag0387R shown in SEQ IN NO.49 and SEQ IN NO.50; the upstream primer Bmag0223F and downstream primer Bmag0223R shown in SEQ IN NO.51 and SEQ IN NO.52; and the primers Bmag0223F and Bmag0223R shown in SEQ IN NO.53 and SEQ IN NO.

54. The upstream primer Bmag0009F and downstream primer Bmag0009R shown in SEQ IN NO. 54; the upstream primer Bmag0867F and downstream primer Bmag0867R shown in SEQ IN NO. 55 and SEQ IN NO. 56, respectively; the upstream primer Bmac0018F and downstream primer Bmac0018R shown in SEQ IN NO. 57 and SEQ IN NO. 58, respectively; the upstream primer Scssr09398F and downstream primer Scssr09398R shown in SEQ IN NO. 59 and SEQ IN NO. 60, respectively; and the nucleotide sequences shown in SEQ IN NO. 61 and SEQ IN NO. 54, respectively.The upstream primer Bmag0613F and downstream primer Bmag0613R shown in SEQ IN NO. 62; the upstream primer Scssr05599F and downstream primer Scssr05599R shown in SEQ IN NO. 63 and SEQ IN NO. 64, respectively; the upstream primer HVCMAF and downstream primer HVCMAR shown in SEQ IN NO. 65 and SEQ IN NO. 66, respectively; the upstream primer EBmac0603F and downstream primer EBmac0603R shown in SEQ IN NO. 67 and SEQ IN NO. 68, respectively; and the upstream primer Scssr15864F and downstream primer Scssr15864R shown in SEQ IN NO. 69 and SEQ IN NO. 70, respectively. The 5' ends of the upstream primers Bmag0211F, HVM36F, EBmag0793F, EBmac0635F, Scssr10148F, Bmag0223F, Bmag0867F, Bmag0613F, and Scssr15864F are all linked to the fluorescent group ROX; the 5' ends of the upstream primers Bmag0770F, HVM54F, Bmac0209F, HVM27F, EBmac0708F, HVM62F, EBmac0701F, Bmag0353F, and Scssr05599F are all linked to the fluorescent group. HEX; the 5' ends of upstream primers Bmag0382F, Bmag0877F, HVM60F, HVM40F, Scssr03907F, Scssr07106F, Bmag0009F, and Scssr09398F are all linked to the fluorescent group TAMRA; the 5' ends of upstream primers Bmag0378F, Bmag0711F, Scssr07759F, Bmac0181F, Bmag0808F, Bmag0387F, Bmac0018F, HVCMAF, and EBmac0603F are all linked to the fluorescent group FAM. (2) Allelic variation data were collected by capillary electrophoresis of PCR products; (3) Cluster the collected data using PowerMarker software; (4) Calculate the number of differential sites between the barley variety to be tested and the known barley variety that is closest to it in the cluster. When the number of differential sites is >2, the barley variety to be tested is determined to be specific. When the number of differential sites is ≤2, the barley variety to be tested and the known barley variety are determined to be "suspiciously the same variety".

2. The method for detecting barley variety specificity using SSR molecular markers according to claim 1, characterized in that, In step (1), the PCR amplification refers to, PCR amplification system: 0.2 µL DNA Polymerase at a concentration of 5 U / µL, 2.5 µL containing Mg 2+ 10×PCR Buffer, 2 µL dNTP solution with a concentration of 2.5 mmol / L, 1 µL upstream primer with a concentration of 10 µmol / L, 1 µL downstream primer with a concentration of 10 µmol / L, 1 µL DNA template with a concentration of 20 ng / µL, and double-distilled water to make up to 25 µL; PCR reaction program: 94℃ pre-denaturation for 5 min; 94℃ for 30 sec, 47~62℃ for 30 sec, 72℃ for 1 min, for a total of 35 amplification cycles; 72℃ extension for 5 min, and storage at 4℃.

3. The method for detecting barley variety specificity using SSR molecular markers according to claim 1, characterized in that, Step (2) involves collecting allelic variation data by capillary electrophoresis of the PCR products. This means: 1) Diluting the PCR amplification products linked with FAM and HEX fluorescent primers 30 times with ultrapure water, and diluting the PCR amplification products linked with TAMRA and ROX fluorescent labels 10 times with ultrapure water; 2) Mixing equal volumes of the diluted solutions of the different fluorescently labeled amplification products, and then adding 1 µL of the mixture to a 96-well plate; 3) Adding 0.1 µL of molecular weight internal standard and 8.9 µL of deionized formamide to each well of the 96-well plate; 4) Denaturing the samples at 95°C for 5 min on a PCR instrument, cooling them on crushed ice for more than 10 min, centrifuging them briefly for 10 s, and then placing them in a DNA analyzer to obtain allelic variation data of the test variety and the corresponding reference variety.

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