SSR molecular marker combination, primer pair thereof and application of SSR molecular marker combination in genetic diversity analysis and fingerprint construction of pistacia chinensis bunge

Abstract

The invention belongs to the technical field of molecular biology, and particularly relates to an SSR molecular marker combination, a primer pair of the SSR molecular marker combination and application of the SSR molecular marker combination in pistacia chinensis bunge genetic diversity analysis and fingerprint spectrum construction. The SSR molecular marker combination comprises an SSR molecular marker CUPVD117, an SSR molecular marker PC64, an SSR molecular marker Ptg12, an SSR molecular marker PCB-b12, an SSR molecular marker PCB-b13, an SSR molecular marker PCB-b32, an SSR molecular marker PCB-c11, an SSR molecular marker PCB-d2, an SSR molecular marker PCB-d4 and an SSR molecular marker PCB-j12. The SSR molecular marker combination can be applied to pistacia chinensis bunge genetic diversity analysis and pistacia chinensis bunge fingerprint spectrum construction. A first genome of pistacia chinensis bunge is analyzed, 10 pairs of SSR molecular marker primers are screened, genetic diversity analysis is performed on Chinese pistacia chinensis bunge germplasm resources nationwide by utilizing the 10 pairs of SSR molecular marker primers, and a pistacia chinensis bunge fingerprint spectrum is constructed by utilizing the 10 pairs of SSR molecular marker primers, so that the pistacia chinensis bunge polymorphic sites are expected to be accurately positioned; the method has important production and scientific research values.

Description

Technical Field

[0001] The present invention belongs to the technical field of molecular biology, and particularly relates to a combination of SSR molecular markers and primer pairs thereof, and their application in genetic diversity analysis and fingerprint map construction of Pistacia chinensis Bunge. Background Art

[0002] Chinese Pistacia chinensis Bunge belongs to the genus Pistacia of the family Anacardiaceae, and is a deciduous tree. It is an important pioneer tree species for barren mountain greening and an oil-use economic forest tree species in China, and has high ornamental value, medicinal value and wood-use value. It has strong resistance and a wide distribution, mainly growing in warm temperate and subtropical zones, and is distributed in 27 provinces, autonomous regions and municipalities directly under the Central Government in China. Most of them are scattered and distributed in small patches, and occasionally there are large areas of pure forests and mixed forests, and the distribution area accounts for about 44% of the national land area of China. The rich genetic resources of Chinese Pistacia chinensis Bunge provide good natural conditions for studying its diversity, and the huge differences in its site conditions have promoted the formation of rich phenotypic diversity. However, at present, there is only one species of Pistacia chinensis Bunge in the whole country, and there is only 'Huaxia Red' red-leaf Pistacia chinensis Bunge in terms of varieties and improved varieties. There is a lack of systematic classification, identification and evaluation for a large number of other germplasms, and there are phenomena such as chaotic resource management and unclear population classification for many Pistacia chinensis Bunge germplasms.

[0003] Although some predecessors have carried out diversity analysis on the germplasm resources of Chinese Pistacia chinensis Bunge, the accuracy of the analysis results is not high. As early as 2003, some scholars used RAPD markers to conduct genetic diversity analysis on Pistacia vera L. in Syria, and conducted correlation analysis between its fruit traits and the clustering results at the molecular level. Abuduli et al. used SSR, RAPD, ISSR and ITS markers to conduct genetic diversity analysis on Pistacia lentiscus L., and based on this, conducted correlation analysis between male and female genders and phylogenetic genotypes, and screened out ISSR markers that could clearly separate male and female genotypes. Guan Ju et al. and Li Wanting et al. both used AFLP markers to conduct genetic diversity research on male and female Pistacia chinensis Bunge populations in Changge and Anyang, Henan, which has guiding significance for the variety identification and subsequent breeding of Pistacia chinensis Bunge. In the current relevant research, there has not been a systematic diversity analysis and fingerprint map construction based on the whole genome of Pistacia chinensis Bunge. Therefore, developing a set of identification systems for clarifying the status of Pistacia chinensis Bunge germplasm resources, their genetic background and genetic relationship is expected to accurately locate the polymorphic loci of Pistacia chinensis Bunge, and has important production and scientific research value. Summary of the Invention

[0004] The purpose of the present invention is to provide a combination of SSR molecular markers and primer pairs thereof, and their application in genetic diversity analysis and fingerprint map construction of Pistacia chinensis Bunge.

[0005] The implementation process of the present invention is as follows:

[0006] An SSR molecular marker combination, comprising SSR molecular markers CUPVD117, PC64, Ptg12, PCB-b12, PCB-b13, PCB-b32, PCB-c11, PCB-d2, PCB-d4 and PCB-j12.

[0007] Furthermore, the primer pairs of the SSR molecular marker CUPVD117 are respectively the forward primer sequence: TGAATTAGGACGGGTTTTGG and the reverse primer sequence: AACCAACTAAACTGCCTTGCAT; the primer pairs of the SSR molecular marker PC64 are respectively the forward primer sequence: AAATAGGGAGAGGACTGGAG and the reverse primer sequence: ACTCTCGTTACCTTGTGCTT; the primer pairs of the SSR molecular marker Ptg12 are respectively the forward primer sequence: ACACTGATACACGGAAGCGGAAAC and the reverse primer sequence: TTACCTTGCCAGATCGCTTGAGATG; the primer pairs of the SSR molecular marker PCB-b12 are respectively the forward primer sequence: CAAGAGATGAGCTCCCGTTG and the reverse primer sequence: TAGCACGTGTGGCATGATGT; the primer pairs of the SSR molecular marker PCB-b13 are respectively the forward primer sequence: TGTTGGGTGTGAGTATGTCTTCA and the reverse primer sequence: AGCCCGACCTGACGAGTTT; the primer pairs of the SSR molecular marker PCB-b32 are respectively the forward primer sequence: ATGCACCACTGATCGACATGA and the reverse primer sequence: GCACACACATATGACTTTGGGTTA; the primer pairs of the SSR molecular marker PCB-c11 are respectively the forward primer sequence: GATATGTTGGAGAGAATTCGGCTTA and the reverse primer sequence: GAGCAGAAACAAATCAGGACACA; the primer pairs of the SSR molecular marker PCB-d2 are respectively the forward primer sequence: AACGCTCAATCTTCCATCTCCATCC and the reverse primer sequence: TGGGGACGATGAAGTTATCAACTCC; the primer pairs of the SSR molecular marker PCB-d4 are respectively the forward primer sequence: GAAGGAACACAACACGAACCTC and the reverse primer sequence: TTATATGCATGACGGTGTAGTAACG; the primer pairs of the SSR molecular marker PCB-j12 are respectively the forward primer sequence: GCGCTCTACAACCACATTTCTTGAG and the reverse primer sequence: TCGTCCAAGAGATGGCACATATTGC.

[0008] The screening method for the above SSR molecular marker combination includes the following steps:

[0009] (1) Extract the genomic DNA of the Pistacia chinensis to be tested

[0010] The young and tender leaves of Pistacia chinensis Bunge were selected, ground, and the genomic DNA of Pistacia chinensis Bunge was extracted using the centrifugal adsorption column method of the DNA secure kit. The MISA software was used to detect SSR loci in the genome of Pistacia chinensis Bunge;

[0011] (2) Primer design and PCR amplification reaction of SSR loci

[0012] A total of 217 SSR loci were randomly selected at the whole-genome level for primer design to obtain 217 pairs of primers. Using the extracted Pistacia chinensis Bunge DNA as the amplification template, a PCR amplification reaction was carried out. Through the primary screening of non-denaturing polyacrylamide gel electrophoresis with a mass percentage of 8% and the re-screening of fluorescence capillary electrophoresis, 10 pairs of primers with good peak patterns, high polymorphism, and strong stability were obtained.

[0013] Furthermore, the PCR amplification reaction system of non-denaturing polyacrylamide gel electrophoresis with a mass percentage of 8% includes 1.0 μL of DNA at 30 ng / μL, 0.5 μL of forward primer at 10 μmol / L, 0.5 μL of reverse primer at 10 μmol / L, 10.0 μL of 2× TaqMaster Mix, and 8.0 μL of double-distilled water, with a total volume of 20.0 μL;

[0014] The reaction procedure is to first perform pre-denaturation at 94 °C for 3 minutes; then denaturation at 94 °C for 30 seconds, annealing at the annealing temperature (Tm) for 30 seconds, extension at 72 °C for 30 seconds, and cycle 35 times; finally, extension at 72 °C for 5 minutes. After the program ends, silver staining is performed after non-denaturing polyacrylamide gel electrophoresis with a mass percentage of 8% to read the bands and take pictures.

[0015] Furthermore, the PCR amplification reaction system of fluorescence capillary electrophoresis includes 1.0 μL of DNA at 30 ng / μL, 0.1 μL of M13 forward primer at 10 μmol / L, 0.3 μL of reverse primer at 10 μmol / L, 0.2 μL of M13 primer at 10 μmol / L, 10.0 μL of 2× TaqMaster Mix, and 8.4 μL of double-distilled water, with a total volume of 20.0 μL.

[0016] Application of the above SSR molecular marker combination in the genetic diversity analysis of Pistacia chinensis Bunge.

[0017] Application of the above SSR molecular marker combination in the construction of fingerprint maps of Pistacia chinensis Bunge.

[0018] A method for genetic diversity analysis of Pistacia chinensis Bunge using the above SSR molecular marker combination, including the following steps:

[0019] (1) After analyzing the SSR data detected by the SSR molecular marker combination of claim 1 or 2 using PowerMarker V3.25, the Nei's genetic distance matrix of the Pistacia chinensis sample was obtained, and UPGMA clustering was performed;

[0020] (2) The genetic background of Pistacia chinensis samples was analyzed by hybrid mode. The capillary electrophoresis results were analyzed by Structure V2.3.4. The LnP (D) value increased with the increase of K value and reached the maximum value when K = 7. However, the inflection point was not obvious and the optimal K value could not be determined. Then the ΔK method was used to determine the number of clusters.

[0021] (3) Compare the two clustering results of cluster analysis and population structure analysis, color the branches of the cluster diagram according to their clustering results and mark the clusters;

[0022] (4) Based on the genetic distance between Pistacia chinensis individuals, principal coordinate analysis was performed on Pistacia chinensis samples;

[0023] (5) Combining the cluster analysis with the results of population structure and principal coordinates, the Pistacia chinensis samples were divided into groups, and the genetic diversity analysis and Hardy-Weinberg equilibrium test of the Pistacia chinensis population were performed using GenAlEx 6.503.

[0024] The method for constructing a fingerprint of Pistacia chinensis using the above-mentioned SSR molecular marker combination comprises the following steps:

[0025] (1) After the SSR molecular marker combination described in claim 1 or 2 is sorted according to the size of the PIC value, it is numbered from A to J, and the product size of the Pistacia chinensis sample is numbered: the homozygote is marked as X, the heterozygote is marked as X / Y, and the absence of amplification product is marked as 0;

[0026] (2) According to the method of step (1), corresponding SSR-DNA fingerprint codes are constructed for multiple Pistacia chinensis samples respectively, and the information and fingerprint code of each sample are imported into the forage QR code generator to generate the fingerprint code QR code of the sample.

[0027] Positive effects of the present invention:

[0028] (1) The method for batch screening of polymorphic SSR primers based on the Pistacia chinensis genome of the present invention is more accurate, efficient and has a high success rate. The peak diagram of the capillary electrophoresis result is clear and standardized, with almost no miscellaneous peaks such as shadow peaks, and the screened primers have high PIC, good polymorphism, and good stability and versatility.

[0029] (2) The present invention has analyzed the first genome of Pistacia chinensis, screened 10 pairs of SSR molecular marker primers, used the 10 pairs of SSR molecular marker primers to conduct genetic diversity analysis on the germplasm resources of Pistacia chinensis nationwide, and also used the 10 pairs of SSR molecular marker primers to construct the fingerprint map of Pistacia chinensis, which is expected to accurately locate the polymorphic sites of Pistacia chinensis and has important production and scientific research value. Description of the Drawings

[0030] Figure 1 It is a diagram of the quality detection results of partial Pistacia chinensis DNA;

[0031] Figure 2 It is a diagram of partial fluorescence capillary electrophoresis results of primer PCB-d2;

[0032] Figure 3 It is a UPGMA clustering diagram of 220 Pistacia chinensis germplasms;

[0033] Figure 4 It is a diagram of population structure analysis of 220 Pistacia chinensis samples; among them, A. The change relationship between the LnK(D) value and the K value; B. The curve diagram of the Delta K value changing with the K value; C. The classification of Pistacia chinensis sample groups when K = 3;

[0034] Figure 5 It is a comparison diagram of the clustering results of 220 Pistacia chinensis germplasms and the population structure grouping results;

[0035] Figure 6 It is a principal coordinate analysis result diagram of 220 Pistacia chinensis samples;

[0036] Figure 7 It is a diagram of the fingerprint information two-dimensional code of partial Pistacia chinensis samples. Detailed Embodiment

[0039] The present invention will be further described below in conjunction with the embodiments.

[0040] Embodiment 1 SSR Molecular Marker Combination and Screening

[0041] An SSR molecular marker combination, including SSR molecular markers CUPVD117, PC64, Ptg12, PCB-b12, PCB-b13, PCB-b32, PCB-c11, PCB-d2, PCB-d4, and PCB-j12. The primer pairs of the SSR molecular marker CUPVD117 are respectively the forward primer sequence: TGAATTAGGACGGGTTTTGG and the reverse primer sequence: AACCAACTAAACTGCCTTGCAT; the primer pairs of the SSR molecular marker PC64 are respectively the forward primer sequence: AAATAGGGAGAGGACTGGAG and the reverse primer sequence: ACTCTCGTTACCTTGTGCTT; the primer pairs of the SSR molecular marker Ptg12 are respectively the forward primer sequence: ACACTGATACACGGAAGCGGAAAC and the reverse primer sequence: TTACCTTGCCAGATCGCTTGAGATG; the primer pairs of the SSR molecular marker PCB-b12 are respectively the forward primer sequence: CAAGAGATGAGCTCCCGTTG and the reverse primer sequence: TAGCACGTGTGGCATGATGT; the primer pairs of the SSR molecular marker PCB-b13 are respectively the forward primer sequence: TGTTGGGTGTGAGTATGTCTTCA and the reverse primer sequence: AGCCCGACCTGACGAGTTT; the primer pairs of the SSR molecular marker PCB-b32 are respectively the forward primer sequence: ATGCACCACTGATCGACATGA and the reverse primer sequence: GCACACACATATGACTTTGGGTTA; the primer pairs of the SSR molecular marker PCB-c11 are respectively the forward primer sequence: GATATGTTGGAGAGAATTCGGCTTA and the reverse primer sequence: GAGCAGAAACAAATCAGGACACA; the primer pairs of the SSR molecular marker PCB-d2 are respectively the forward primer sequence: AACGCTCAATCTTCCATCTCCATCC and the reverse primer sequence: TGGGGACGATGAAGTTATCAACTCC; the primer pairs of the SSR molecular marker PCB-d4 are respectively the forward primer sequence: GAAGGAACACAACACGAACCTC and the reverse primer sequence: TTATATGCATGACGGTGTAGTAACG; the primer pairs of the SSR molecular marker PCB-j12 are respectively the forward primer sequence: GCGCTCTACAACCACATTTCTTGAG and the reverse primer sequence: TCGTCCAAGAGATGGCACATATTGC.

[0042] (1.1) Plant materials

[0043] The materials for the genetic diversity analysis of Pistacia chinensis in this invention come from the Pistacia chinensis samples preserved by the research group and some additional Pistacia chinensis samples from across the country from 2022 to 2023, totaling 220 samples, distributed in 70 Pistacia chinensis populations across the country (specific to counties / districts) (Table 1). After the above-mentioned Pistacia chinensis leaves were quickly frozen with liquid nitrogen, they were stored in a -80°C refrigerator for later use.

[0044] Table 1 Information of Pistacia chinensis samples

[0045]

[0046]

[0047] (1.2) Main reagents and drugs

[0048] DNA secure new DNA extraction kit (DP320) (Tiangen); 2×Taq PCR Mix polymerase, DL15000 DNA Marker, DL500 DNA Marker (Takara Bio); acrylamide solution with a mass percentage of 30% (29:1), nucleic acid dye, TAE buffer, TBE buffer, agarose (Biyuntian); N,N,N',N'-Tetramethylethylenediamine, ammonium persulfate, sodium hydroxide, silver nitrate, anhydrous sodium carbonate, absolute ethanol were purchased from Beijing Lanyi Chemical Products Co., Ltd. through the school platform.

[0049] (1.3) Instruments and equipment

[0050] -80°C ultra-low temperature refrigerator, tissue grinder (Mini-Beadbeater), electronic balance (Mettler Toledo), NanoDrop 2000 micro-spectrophotometer (Thermo Scientifc), PCR instrument (T100TM ThermalCycle, Bio-Rad Laboratories Co., Ltd. 700W), agarose gel electrophoresis instrument, polyacrylamide gel electrophoresis instrument, gel imaging system, microwave oven, high-speed centrifuge (Eppendorf), vortex oscillator (MS3 B S25), microplate centrifuge (MINIP-2500), pipette (Eppendorf), etc.

[0051] (1.4) The screening method of the above SSR molecular marker combination is as follows:

[0052] (S1) DNA extraction

[0053] Put an appropriate amount of Pistacia chinensis leaves pre-frozen in an -80°C refrigerator into a 2 mL centrifuge tube. Use a tissue grinder to grind them into powder, and then extract Pistacia chinensis DNA step by step according to the instruction manual of the DNAsecure kit (DP320). Use 1% (mass percentage) agarose gel electrophoresis and a micro-spectrophotometer to detect the quality and measure the concentration of the extracted Pistacia chinensis DNA. After passing the quality inspection, dilute the concentration of the Pistacia chinensis DNA to 30 ng / μL with double-distilled water (ddH2O) or buffer, and store it in a -20°C refrigerator for later use.

[0054] The specific operation steps of electrophoresis are as follows:

[0055] First, select a 50 mL gel-making plate and a 24-well comb for making the gel, and prepare reagent drugs: agarose, 1×TAE buffer, GelRed nucleic acid dye, 6×Loading buffer, DL15000 DNA Marker.

[0056] Second, weigh 0.5 g of agarose powder with a ten-thousandth balance, then measure 50 mL of 1×TAE buffer and add it to a conical flask. After shaking well, put the conical flask into the microwave oven and select high-temperature heating for about 1 minute. Take it out after the agarose is completely dissolved. Add 5 μL of GelRed nucleic acid dye to the conical flask. After the dye is fully dissolved in the agarose solution, slowly pour it into the gel-making plate with the tray already placed and the comb inserted. Avoid generating bubbles during this process.

[0057] Third, after the agarose gel placed at room temperature is completely solidified, slowly pull out the comb on the gel, and then put the agarose gel together with the tray into the electrophoresis tank so that the 1×TAE buffer in the tank covers the sample wells.

[0058] Third, mix the DNA sample and 6×Loading buffer in a centrifuge tube according to a volume ratio of 5:1, and then load them into the sample wells in sequence. Add Marker to the first sample well.

[0059] Finally, set the electrophoresis instrument to 200 V and 200 mA, run for 20 minutes and then take it out. Place the gel in a gel imaging system to observe the DNA bands.

[0060] Quality detection of Pistacia chinensis DNA: Use 1% (mass percentage) agarose gel electrophoresis and a micro-spectrophotometer to detect the quality of 220 samples of extracted Pistacia chinensis DNA. The results show ( Figure 1) The DNA bands were clear and bright, without trailing or smearing. The A260 / A280 ratio was between 1.80 and 2.00, indicating that the extracted DNA sample had a high purity and was not contaminated with impurities such as RNA, polysaccharides, and proteins. The DNA was diluted to 30 ng / μL with ddH2O or buffer and stored in a -20°C refrigerator for subsequent PCR amplification.

[0061] The MISA software was used to detect SSR loci in the Pistacia chinensis genome:

[0062] Based on the whole-genome sequence of Pistacia chinensis obtained by sequencing, the perl script MicroSAtellite (MISA, http: / / pgrc.ipkgatersleben.de / misa / ) was used to retrieve SSR-specific loci in the Pistacia chinensis genome data. MISA can identify perfect and compound microsatellites in DNA sequences and determine their locations. The criteria for screening loci were as follows: the number of repeats of the mononucleotide motif in the locus was ≥10; the number of repeats of the dinucleotide was ≥6; the number of repeats of the tri-, tetra-, penta-, and hexanucleotide repeats was ≥5. At the same time, imperfect repeat SSR loci formed due to base mutations and other reasons were also screened out.

[0063] According to the uniqueness of the SSR flanks, the repeat sequences of the identified Pistacia chinensis SSR loci were extended 100 - 200 bp outward from both ends, and the software Primer Premier 6 was used to design primers. The relevant parameter settings were as follows: the lengths of the forward and reverse primers were set to 17 - 25 bp, the GC content was 40% - 60%, the annealing temperature (Tm) was 55 - 65°C, and the predicted molecular weight of the amplified product was 150 - 300 bp.

[0064] (S2) Primer design and PCR amplification reaction of SSR loci

[0065] A total of 217 SSR loci were randomly selected at the whole-genome level for primer design to obtain 217 pairs of primers. Using the extracted Pistacia chinensis DNA as the amplification template, a PCR amplification reaction was carried out using a 20 μL reaction system suitable for Pistacia chinensis (Table 2).

[0066] Table 2 PCR reaction system for 8% non-denaturing polyacrylamide gel electrophoresis

[0067]

[0068] Reaction procedure: First, perform pre-denaturation at 94°C for 3 minutes; then denature at 94°C for 30 seconds, anneal at the optimal annealing temperature (Tm, which varies for different primers, see Table 3) for 30 seconds, extend at 72°C for 30 seconds, and repeat the cycle 35 times; finally, extend at 72°C for 5 minutes. After the program ends, read the bands by silver staining after non-denaturing polyacrylamide gel electrophoresis with a mass percentage of 8%, and take pictures.

[0069] Table 3 Information of 10 pairs of polymorphic SSR primers

[0070]

[0071]

[0072] Amplification sequence of CUPVD117 (SEQ ID NO:21):

[0073] TGAATTAGGA CGGGTTTTGG TAGAGAATGG GAGATATTGTAGAGAGAAGA AGGAGAAGAAGGTGGGAAAA GAGAAGGGCGGCGAAGAGAG AGGGGAGAGA AGAGAGAAAATGGAGAAGAAGAAGAAGAAGAGAGGGCCAT GCAAGGCAGT TTAGTTTGATT

[0074] Amplification sequence of PC64 (SEQ ID NO:22):

[0075] AA ATAGGGAGAG GACTGGAGGG CTCAAAGGAT AATTATTATGGATTTGATTT GATGAAGCAAAGAGAAGAGA TATGACAAACAGAGAGAGAG AGAGAGAGAG AGAGAGAGAG AGAAGGAGGAGAACTGTGAGTAAGCACAAG GTAACGAGAG T

[0076] Amplification sequence of Ptg12 (SEQ ID NO:23):

[0077] ACACTGATAC ACGGAAGCGG AAACCCTAGA GAGGAGTAAGAGAGAGAGAG CGAGGCTAACTCAGTCAGTA CCCAACCCCATCTGCCCTTA ACCAGCTCTC CTGCTCTGCT TTGTTGCTTCAGCCATGGCCACTGCTAAAA CTGTCAAGGA CGTCTCTCCT CATGAGTTTG TTAAGGCTTACTCTGCCCATCTCAAGCGAT CTGGCAAGGTAA

[0078] PCB-b12 amplification sequence (SEQ ID NO:24):

[0079] CAAGAGATGA GCTCCCGTTG TATATATCAG TAATTTGCCTACACAATTAA TTCGAACATCACAGATATGA GACATCTTCC CATAGAGAGAGAGAGAGAGA GAGAGAGAGA GAGGGACTATTACATGATTGTTACATCAAG TTCTCAAAAC TACTTAATTA TTAATTTGTA TTTGTTCAATCACATCATGCCACACGTGCTA

[0080] PCB-b13 amplification sequence (SEQ ID NO:25):

[0081] TGTTGGGTGT GAGTATGTCT TCAGTCTTGG CCCAGCCTGGTCCAACCTGA CAATTTTACTAAATTAGCCT TATACTATAT ATTTAATTACAGAATTATCC TATATATATA TATATATATA TAAAATTGAAATTTATTAATATTTAAAAAT TCACATTATA AATATGGGTA GACTTGGGCTCGGACTAAGATTAGAAAAAACTCGTCAGGT CGGGCT

[0082] PCB-b32 amplification sequence (SEQ ID NO:26):

[0083] ATGCACCACT GATCGACATG ATACAGGGCC GTGGCAAACTTGGTAAGCTA CCATATTTCTCTTTAATCTT CTTACGTATC CTTGATATTTATATATATAT ATATATTTTG TTTTATGTAG AGTTTGATGACGTGAGTAATGGGTGCTGCG GGACTGGATA TTTGGAAGCA GCATTCTTAT GTAACCCAAAGTCATATGTGTGTGC

[0084] PCB-c11 amplification sequence (SEQ ID NO:27):

[0085] GATATGTTGG AGAGAATTCG GCTTACTGTC ATTAACAATCTCTTGAAGTA TCATCCTGTATGTATGCTGA GTTGATACCT TTAAATTCTTGTCCTTGCAT CTCTCTCTCT CTCTGTGTTGGAGTGGGTGAAGCAAGAAAAATTCCCTATT TAAATTTTCA AGCATTTATG TTCTTCATGTGTCCTGATTTGTTTCTGCTC

[0086] PCB-d2 amplification sequence (SEQ ID NO:28):

[0087] AACGCTCAAT CTTCCATCTC CATCCTTATC CATAACCCTAAACACATCCT CCATAACCCCACCACCACGA GATTTAACAC CGTTTCTTCTTTTCCCTCCT CCTCCTCCTC CTCCTCCTCC GTACCTCAAAACTCGTTCAAATTCGTCATA CTCAACGTAC CCGTCTTTGT TGAAATCCGCAACGGAGATCATGGAGTTGATAACTTCATC GTCCCCA

[0088] PCB-d4 amplification sequence (SEQ ID NO:29):

[0089] GAAGGAACAC AACACGAACC TCTAATCTCT CCCTCATAAAAACCATCATT TGCAAATTATCATGAAGCGT AAACAGACCC TAAAGCCAGGAGTATCCTTT ATATATATAT ATATATATAT ATATATATATTTCTGGAGGTTTAACTTGGT CATTCATTGC TTGACGGGAG GAGAAGGGGTGAAACGTTACTACACCGTCATGCATATAA

[0090] PCB-j12 amplified sequence (SEQ ID NO: 30):

[0091] GCGCTCTACA ACCACATTTC TTGAGAATTA TTAGTGAATTTACCAACACT TCACTACATTCACTCCTTAT TAAAGGAGAA AGAACTGAATTAAATAATAA TAATAATAAT AATAATAATG CACCTCATTTTTTACTTACATTCACTCGCA GTAAAGACAC GCAATTGCCT GTATCCCGAC CATTTGCAATATGTGCCATCTCTTGGACGA

[0092] Among them, the operating steps of 8% non-denaturing polyacrylamide gel electrophoresis (PAGE) are as follows:

[0093] First, make the gel; prepare the reagents: 30% (29:1) acrylamide solution, tetramethylethylenediamine (TEMED) solution, 10% ammonium persulfate (APS) solution, TBE buffer. Prepare 8% acrylamide solution: 88mL of 30% acrylamide solution, 185mL of 1×TBE buffer, 231mL of ddH2O, mix well and store in the dark. Prepare 10% APS solution: Mix 1g of APS powder with 10mL of double distilled water, store in a 4℃ refrigerator for 2 weeks, or -20℃ for 3 months for use. Prepare the gel (one plate): 35mL of 8% acrylamide solution, 22μL of TEMED, 260μL of 10% APS, prepare two plates. Preparation of glass plates: Clean the two glass plates in advance and dry them without water stains. Place the side with short glass pieces at both ends between the two glass plates, and seal the bottom and sides of the glass plate with tape to prevent gel from overflowing during gel pouring. Gel pouring: Make the bottom of the glass plate 15° with the tabletop for gel pouring. Use a disposable pipette to slowly inject the prepared gel solution into the glass plate. Avoid bubbles during this process. If bubbles occur, slightly lift the top of the glass plate and tap it gently. After the gel is filled, slowly insert the comb into the top of the glass plate to avoid bubbles. Let the glass plate stand for 1 to 2 hours until the gel is completely solidified before electrophoresis.

[0094] Secondly, electrophoresis; after pulling out the comb in the glass plate, removing the tape and cleaning the residual glue on the glass plate, put it into the electrophoresis tank with 1×TBE buffer added, clamp the two ends of the two glass plates with clips, and add 1×TBE buffer to the middle to cover the gel spotting hole. Spotting: The sample volume is 1.5μL, add the marker to the second hole, and then add the sample in turn. The voltage is 150V, 120mA, and the electrophoresis is 1 hour and 40 minutes.

[0095] Finally, silver staining; prepare the following chemicals: sodium hydroxide (NaOH), anhydrous sodium carbonate (Na2CO3), silver nitrate (AgNO3), formaldehyde (CH2O). Prepare the staining solution and developer solution as needed. Prepare the staining solution: 300 mL of 1% AgNO3 solution by mass. Prepare the developer solution: 500 mL of 1% NaOH solution, 0.2 g Na2CO3, and 1 mL CH2O by mass. Staining: After the electrophoresis is completed, carefully remove the gel from the glass plate. Pour the staining solution into the tray and stain on a shaker for 6 to 8 minutes in the dark. Development: Rinse the stained gel carefully and quickly with distilled water, pour in the developer solution, place it on a shaker and shake gently until clear bands appear, and pour out the developer solution in time to avoid over-development of the bands. After adding distilled water to wash away the floating color, place the gel on a light box to read the bands and take pictures.

[0096] Among them, fluorescence capillary electrophoresis uses a four-color fluorescence detection method (refer to Huang Jian'an, Li Juan, Tan Yueping, etc. Analysis of tea tree SSR markers by capillary electrophoresis four-color fluorescence detection method (English) [J]. Life Science Research, 2009, 13(03): 251-257). PCR amplification is carried out with three primers, namely M13 forward primer, reverse primer, and M13 primer (modified by ROX, HEX, TAMRA, or FAM). After PCR amplification with different fluorescence-modified primer combinations (Table 4), the amplified products of the same DNA samples are mixed one by one, and a fluorescence capillary electrophoresis experiment is carried out. Using this method, 4 pairs of primers can be detected simultaneously by one capillary electrophoresis, greatly saving the experimental cost.

[0097] Table 4 PCR reaction system for fluorescence capillary electrophoresis

[0098]

[0099] Among them, the M13 forward primer is a forward primer with an M13 sequence (5'-TGTAAAACGACGGCCAGT-3') at the 5' end; the M13 primer is synthesized with an M13 sequence with a fluorescence modification (FAM, HEX, ROX, or TAMRA) at the 5' end.

[0100] Under the same PCR amplification conditions, the finally selected polymorphic SSR primer pairs are used to repeat the amplification of 10 randomly selected Pistacia chinensis Bunge DNA samples 3 times to verify the accuracy and stability of the results. The selected polymorphic SSR primers are used for PCR amplification of all tested Pistacia chinensis Bunge samples.

[0101] Ten pairs of primers were used for PCR amplification of Pistacia chinensis samples nationwide. The results showed (Table 5) that the number of alleles (Na) detected by the ten pairs of primers in 220 Pistacia chinensis samples ranged from 6 to 13, with an average of 8.6 alleles per pair of primers. Among them, CUPVD117 had the least number of alleles, which was 6, and PC64 had the most, which was 13. The number of effective alleles (Ne) ranged from 2.542 to 6.303, with an average of 3.881. Among them, PCB-b13 had the least number of effective alleles, which was 2.542, and PC64 had the most, which was 6.303. The gene diversity (GD) at each locus ranged from 0.662 to 0.930, with an average value of 0.787. The observed heterozygosity (Ho) was between 0.352 and 0.762, with an average value of 0.544. The expected heterozygosity (He) ranged from 0.510 to 0.912, with an average value of 0.695. Shannon's diversity information index (I) ranged from 1.085 to 2.169, with an average value of 1.530. The polymorphic information content (PIC) ranged from 0.640 to 0.925, with an average value of 0.766. The polymorphic information content of the ten pairs of primers was greater than 0.5. Therefore, the ten pairs of primers were all highly polymorphic primers and could be used for the analysis of genetic diversity and the construction of fingerprint maps of Pistacia chinensis.

[0102] Table 5 Genetic diversity parameters of ten pairs of SSR primers for Pistacia chinensis

[0103]

[0104] The method for screening polymorphic SSR primers in batches based on the genome of Pistacia chinensis in the present invention is more accurate, efficient, and has a high success rate. The peak maps of capillary electrophoresis results are clear and standard, with almost no ghost peaks or other miscellaneous peaks. The primers screened have high PIC and good polymorphism, and have good stability and universality.

[0105] Example 2 Application of SSR molecular marker combination in the analysis of genetic diversity of Pistacia chinensis

[0106] The method for analyzing the genetic diversity of Pistacia chinensis using the SSR molecular marker combination described in the present invention includes the following steps:

[0107] (2.1) After analyzing the SSR data detected by the SSR molecular marker combination described in Example 1 using PowerMarker V3.25, a Nei's genetic distance matrix of 220 Pistacia chinensis samples was obtained, and UPGMA clustering was performed.

[0108] The statistical results showed that the genetic distances among 220 Pistacia chinensis samples ranged from 0.079 to 0.950, with an average genetic distance of 0.704. Among them, there were 143 pairs with the maximum genetic distance of 0.950 between individuals, all of which were samples from different regions; there were 4 samples with genetic distances less than 0.200, namely No. 1 and No. 9 from Chongzuo, Guangxi, No. 1 and No. 7 from Langyashan, Anhui, No. 1 from Xinmin Village, Jiangxi and No. 5 from Sanliya, Shaanxi, and No. 2 from Tai'an, Shandong and No. 10 from Qufu, Shandong.

[0109] Cluster analysis was performed by the UPGMA method ( Figure 3 ), and 10 pairs of primers could distinguish all 220 samples. According to the analysis results, all Pistacia chinensis samples could be divided into three major groups: Group Ⅰ consisted of 37 samples, mainly from the southeastern coastal areas and some southern regions, including provinces (municipalities directly under the Central Government / autonomous regions) such as Guangdong, Fujian, Hainan, Hunan, and Guangxi; Group Ⅱ consisted of 87 samples, mainly from the southwestern regions and most of the Qinling-Bashan Mountains, including provinces (municipalities directly under the Central Government / autonomous regions) such as Yunnan, Jiangxi, Guangxi, Sichuan, Chongqing, Shaanxi, Gansu, and Guizhou; Group Ⅲ consisted of 96 samples, mainly from the Huang-Huai-Hai region, including provinces (municipalities directly under the Central Government / autonomous regions) such as Henan, Shandong, Anhui, Hebei, Beijing, Zhejiang, Hubei, and Shanghai. The individual clustering results were somewhat related to their geographical distributions, and there was also interpenetration among different populations.

[0110] (2.2) The population structure of the genetic background of Pistacia chinensis samples was analyzed using a mixed model. The capillary electrophoresis results were analyzed using Structure V2.3.4, as Figure 4 -A, the value of LnP(D) showed an upward trend with the increase of K value, reaching the maximum value when K = 7, but the inflection point was not obvious, and the optimal K value could not be determined. Therefore, the ΔK method was used to determine the number of clusters. When K = 3, ΔK was the maximum value, that is, the optimal K value was 3 ( Figure 4 -B). Based on this, 220 Pistacia chinensis germplasms were divided into 3 groups, and the corresponding color regions were red (P1), green (P2), and blue (P3) ( Figure 4 -C), among which, P1 contained 95 samples, P2 contained 97 samples, and P3 contained 28 samples. The probability of each sample belonging to its respective group was represented by the Q value. The larger the Q value, the greater the possibility that the sample belonged to that group. When Q ≥ 0.6, it indicated that the sample had a single provenance; when Q < 0.6, it indicated that the sample was a hybrid of two or more provenances, thus dividing the Pistacia chinensis samples into their respective groups. The results showed that the Q values of all samples were greater than 0.6. Although some samples contained the genetic backgrounds of two or three groups, the content was relatively small compared to the proportion of their respective groups, indicating that the genetic backgrounds of the tested samples were relatively single.

[0111] (2.3) Compare the two clustering results of cluster analysis and population structure analysis. As Figure 5 shown, color the branches of the clustering tree according to their clustering results and label the groups. In the population structure clustering results, when K = 2, the Bayesian algorithm divides all samples into two groups; when K = 3, it divides them into three groups; when K = 4, it divides them into four groups. After verification, only when K = 3 does each group maximally conform to the Hardy-Weinberg equilibrium within the group. When K = 3, the population structure clustering results are basically consistent with the three-group division of the phylogenetic tree. P1 in the population structure is mainly the germplasm within Group III of the phylogenetic tree, containing a small number of germplasms from Group II; P2 is mainly the germplasm of Group II, containing a small number of germplasms from Group I and Group III; P3 is the germplasm of Group I. The specific corresponding relationship is shown in Table 6. In summary, the clustering results are consistent with the population structure analysis results, both dividing 220 Pistacia chinensis germplasms into three major groups, and there is an obvious gene introgression phenomenon between the groups. Among the three major groups divided according to Nei's genetic distance, each major group has germplasms from different regions, and the germplasms from the same region are mostly scattered among the three major groups in the phylogenetic tree.

[0112] Table 6 Clustering results of 220 Pistacia chinensis germplasms and population structure clustering results

[0113]

[0114]

[0115]

[0116] (2.4) Conduct principal coordinate analysis on Pistacia chinensis samples based on the genetic distance between individuals;

[0117] The principal coordinate results can more intuitively present the relationships between Pistacia chinensis individuals from different levels and directions. As Figure 7, based on the genetic distance among Pistacia chinensis individuals, principal coordinate analysis (PCoA) was performed on 220 Pistacia chinensis samples. The results showed that PC1, PC2, and PC3 explained 10.38%, 7.65%, and 5.29% of the variation respectively, indicating that the molecular markers used had high independence. In the three-dimensional coordinates, the principal coordinates were basically consistent with the clustering results, phylogenetic tree, and population structure. The 220 Pistacia chinensis samples were divided into three groups: a, b, and c, corresponding to groups I, II, and III in the cluster analysis and P3, P2, and P1 in the population structure respectively. Group a was located within the negative axes of PC1 and PC3 and the positive axis of PC2, with a relatively concentrated distribution; group b was located within the negative axes of PC1 and PC2 and the entire coordinate range of PC3, with a large span on the vertical axis; group c was distributed in the opposite direction to groups a and b, located within the positive axis of PC1, the negative axes of PC2 and PC3, and there were also a small number of individuals distributed on the positive axis of PC3. There were a few overlapping individuals between groups a and b, and group c was clustered separately, indicating that the genetic relationship between groups a and b was closer than that of group c, and the gene flow of group c to the outside was relatively small. The individuals in group c were relatively closely distributed, indicating a relatively close genetic relationship within the population.

[0118] (2.5) Combining the results of cluster analysis, population structure, and principal coordinate clustering, the 220 Pistacia chinensis samples can be divided into three major groups: the southeastern region (37), the western region (87), and the Huang-Huai-Hai region (96). Genetic diversity analysis and Hardy-Weinberg equilibrium detection of the Pistacia chinensis population were carried out using GenAlEx 6.503, and the specific parameters are shown in Table 7. The results of genetic diversity analysis showed that at the population level, there were significant differences in the parameters of the number of alleles (Na) and the corresponding effective number of alleles (Ne). The range of Na was 8.700 - 10.100, with an average of 9.500; the range of Ne was 3.732 - 5.514, with an average of 4.623; the range of observed heterozygosity was 0.509 - 0.603, with an average of 0.557, and the expected heterozygosity (He) ranged from 0.664 to 0.790, with an average of 0.721. Both were greater than 0.500, indicating high genetic diversity. The Shannon's diversity index (I) showed the group diversity: southeastern region > western region > Huang-Huai-Hai region. After the Hardy-Weinberg test, it was shown that except for the groups in the Huang-Huai-Hai region, the groups in the southeastern region and the western region did not conform to the Hardy-Weinberg equilibrium, indicating that Pistacia chinensis was affected by evolutionary factors such as mutation, genetic drift, migration, and natural selection to a certain extent.

[0119] Table 7 Genetic diversity parameters among different groups of Pistacia chinensis populations in China

[0120]

[0121] Example 3 Application of SSR molecular marker combination in the construction of Pistacia chinensis fingerprint

[0122] The method for constructing a Pistacia chinensis fingerprint using the SSR molecular marker combination comprises the following steps:

[0123] (1) The 10 pairs of polymorphic SSR primers screened were sorted from large to small according to their PIC values as PC64, PCB-d4, PCB-b12, CUPVD117, PCB-b32, PCB-d2, PCB-c11, Ptg12, PCB-j12, and PCB-b13, and numbered from A to J. The sizes of the products amplified with the 10 pairs of primers were numbered: homozygotes were marked as X, heterozygotes were marked as X / Y, and no amplified products were marked as 0. For example, the fingerprint code of the sample from Shangfangshan, Beijing, is: A170B211C218D170E240 / 242F236 / 239G221H228I220 / 238J225 / 227.

[0124] (2) According to the method in step (1), the corresponding SSR-DNA fingerprint codes were constructed for the 220 Pistacia chinensis samples (see Appendix A), and the information of each Pistacia chinensis sample (botanical classification, name, sampling location, etc.) and the corresponding fingerprint code were imported into the forage QR code software to generate the fingerprint information QR code of the sample ( Figure 7 ) to provide detailed information such as the source of samples, germplasm types, and fingerprint codes for subsequent research. The SSR-DNA fingerprints of the 220 Pistacia samples are all unique, and each fingerprint information represents only one independent sample. See Table 8 for the SSR-DNA fingerprint codes of some Pistacia samples in China.

[0125] Table 8 SSR-DNA fingerprint codes of some Chinese Pistacia samples

[0126]

[0127]

[0128]

[0129]

[0130]

[0131]

[0132]

[0133] Identifying the genotypes of Pistacia chinensis Bunge through SSR markers and constructing the fingerprint map of Pistacia chinensis germplasm in China can provide an important theoretical basis for the rapid and accurate identification and preservation of Pistacia chinensis germplasm resources in China. Among them, selecting the best primers to identify the most Pistacia chinensis individuals is the key to constructing the DNA fingerprint map of Pistacia chinensis in China. The present invention screens out 10 pairs of SSR primers with high polymorphism and strong stability, uses 220 Pistacia chinensis germplasm in China as DNA templates for PCR amplification, writes the DNA fingerprint map codes of each individual based on the amplified band sizes, and generates two-dimensional codes for the efficient and accurate identification of Pistacia chinensis germplasm resources in China. The present invention uses fluorescence capillary electrophoresis to detect the PCR amplification products, which can be accurate to 1 bp. The detection result of the product length is more accurate than that of traditional gel electrophoresis. Based on this, the accuracy of the constructed fingerprint map will be higher. The DNA fingerprint map constructed by the polymorphic SSR primers screened based on the whole genome of Pistacia chinensis in China will be more accurate in identifying Pistacia chinensis germplasm resources, and the number of preserved germplasm resources will be larger.

[0134] After considering the specification and the practice disclosed herein, those skilled in the art will readily conceive of other embodiments of the present application. The present application is intended to cover any variations, uses, or adaptations of the present application, which follow the general principles of the present application and include the common general knowledge or conventional technical means in the technical field not disclosed in the present application. The specification and the embodiments are only regarded as exemplary, and the present application is not limited to the exact structures described above and shown in the drawings, and various modifications and changes can be made without departing from its scope.

Claims

1. A SSR molecular marker combination, characterized in that: Including SSR molecular marker CUPVD117, SSR molecular marker PC64, SSR molecular marker Ptg12, SSR molecular marker PCB-b12, SSR molecular marker PCB-b13, SSR molecular marker PCB-b32, SSR molecular marker PCB-c11, SSR molecular marker PCB-d2, SSR molecular marker PCB-d4 and SSR molecular marker PCB-j12.

2. The SSR molecular marker combination according to claim 1, characterized in that: The primer pairs of the SSR molecular marker CUPVD117 are respectively the forward primer sequence: TGAATTAGGACGGGTTTTGG and the reverse primer sequence: AACCAACTAAACTGCCTTGCAT; the primer pairs of the SSR molecular marker PC64 are respectively the forward primer sequence: AAATAGGGAGAGGACTGGAG and the reverse primer sequence: ACTCTCGTTACCTTGTGCTT; the primer pairs of the SSR molecular marker Ptg12 are respectively the forward primer sequence: ACACTGATACACGGAAGCGGAAAC and the reverse primer sequence: TTACCTTGCCAGATCGCTTGAGATG; the primer pairs of the SSR molecular marker PCB-b12 are respectively the forward primer sequence: CAAGAGATGAGCTCCCGTTG and the reverse primer sequence: TAGCACGTGTGGCATGATGT; the primer pairs of the SSR molecular marker PCB-b13 are respectively the forward primer sequence: TGTTGGGTGTGAGTATGTCTTCA and the reverse primer sequence: AGCCCGACCTGACGAGTTT; the primer pairs of the SSR molecular marker PCB-b32 are respectively the forward primer sequence: ATGCACCACTGATCGACATGA and the reverse primer sequence: GCACACACATATGACTTTGGGTTA; the primer pairs of the SSR molecular marker PCB-c11 are respectively the forward primer sequence: GATATGTTGGAGAGAATTCGGCTTA and the reverse primer sequence: GAGCAGAAACAAATCAGGACACA; the primer pairs of the SSR molecular marker PCB-d2 are respectively the forward primer sequence: AACGCTCAATCTTCCATCTCCATCC and the reverse primer sequence: TGGGGACGATGAAGTTATCAACTCC; the primer pairs of the SSR molecular marker PCB-d4 are respectively the forward primer sequence: GAAGGAACACAACACGAACCTC and the reverse primer sequence: TTATATGCATGACGGTGTAGTAACG; the primer pairs of the SSR molecular marker PCB-j12 are respectively the forward primer sequence: GCGCTCTACAACCACATTTCTTGAG and the reverse primer sequence: TCGTCCAAGAGATGGCACATATTGC.

3. The screening method of the SSR molecular marker combination according to claim 1 or 2, characterized in that Including the following steps: (1) Extract the genomic DNA of the Pistacia chinensis to be tested The young and tender leaves of Pistacia chinensis were selected, ground, and then the genomic DNA of Pistacia chinensis was extracted using the centrifugal adsorption column method of the DNA secure kit. The MISA software was used to detect SSR loci in the genomic DNA of Pistacia chinensis. (2) Primer design and PCR amplification reaction of SSR loci A total of 217 SSR loci were randomly selected at the whole-genome level for primer design to obtain 217 pairs of primers. Using the extracted Pistacia chinensis DNA as the amplification template, PCR amplification reaction was carried out. Through the preliminary screening of non-denaturing polyacrylamide gel electrophoresis with a mass percentage of 8% and the re-screening of fluorescence capillary electrophoresis, 10 pairs of primers with good peak patterns, high polymorphism, and strong stability were obtained.

4. The screening method of the SSR molecular marker combination according to claim 3, characterized in that: The PCR amplification reaction system of the non-denaturing polyacrylamide gel electrophoresis with a mass percentage of 8% includes 1.0 μL of DNA at 30 ng / μL, 0.5 μL of forward primer at 10 μmol / L, 0.5 μL of reverse primer at 10 μmol / L, 10.0 μL of 2× Taq Master Mix, and 8.0 μL of double-distilled water, with a total volume of 20.0 μL. The reaction procedure is as follows: first, pre-denaturation at 94 °C for 3 minutes; then denaturation at 94 °C for 30 seconds, annealing at the annealing temperature Tm for 30 seconds, extension at 72 °C for 30 seconds, with 35 cycles; finally, extension at 72 °C for 5 minutes. After the program ends, the bands are read by silver staining after non-denaturing polyacrylamide gel electrophoresis with a mass percentage of 8%, and photos are taken.

5. The screening method of the SSR molecular marker combination according to claim 3, characterized in that: The PCR amplification reaction system of the fluorescence capillary electrophoresis includes 1.0 μL of DNA at 30 ng / μL, 0.1 μL of M13 forward primer at 10 μmol / L, 0.3 μL of reverse primer at 10 μmol / L, 0.2 μL of M13 primer at 10 μmol / L, 10.0 μL of 2× Taq Master Mix, and 8.4 μL of double-distilled water, with a total volume of 20.0 μL.

6. The application of the SSR molecular marker combination according to claim 1 or 2 in the genetic diversity analysis of Pistacia chinensis.

7. The application of the SSR molecular marker combination according to claim 1 or 2 in the construction of the fingerprint map of Pistacia chinensis.

8. A method for analyzing the genetic diversity of Pistacia chinensis Bunge using the SSR molecular marker combination according to claim 1 or 2, characterized in that It includes the following steps: (1) After analyzing the SSR data detected by the SSR molecular marker combination according to claim 1 or 2 using PowerMarker V3.25, the Nei's genetic distance matrix of Pistacia chinensis samples was obtained, and UPGMA clustering was performed. (2) The population structure analysis of the genetic background of Pistacia chinensis samples was carried out in a mixed mode. The capillary electrophoresis results were analyzed using StructureV2.3.

4. The value of LnP(D) showed an upward trend with the increase of the value of K. When K = 7, it reached the maximum value, but the inflection point was not obvious, and the optimal K value could not be judged. Then the ΔK method was used to determine the number of subpopulations. (3) The two subpopulation results of the cluster analysis and the population structure analysis were compared, and the branches of the cluster diagram were colored and labeled according to their subpopulation results. (4) Based on the genetic distance between Pistacia chinensis individuals, principal coordinate analysis was carried out on Pistacia chinensis samples. (5) Combining the cluster analysis with the results of population structure and principal coordinates, the Pistacia chinensis samples were divided into groups, and the genetic diversity analysis and Hardy-Weinberg equilibrium test of the Pistacia chinensis population were performed using GenAlEx 6.

503.

9. A method for constructing a fingerprint map of Pistacia chinensis Bunge using the SSR molecular marker combination according to claim 1 or 2, characterized in that, The following steps are involved: (1) After the SSR molecular marker combination described in claim 1 or 2 is sorted according to the size of the PIC value, it is numbered from A to J, and the product size of the Pistacia chinensis sample is numbered: the homozygote is marked as X, the heterozygote is marked as X / Y, and the absence of amplification product is marked as 0; (2) According to the method of step (1), corresponding SSR-DNA fingerprint codes are constructed for multiple Pistacia chinensis samples respectively, and the information and fingerprint code of each sample are imported into the forage QR code generator to generate the fingerprint code QR code of the sample.

Images