Method for identifying Ningxia wolfberry varieties based on selective clearance analysis

Abstract

The invention relates to the technical field of biological detection, in particular to a method for identifying Ningxia wolfberry varieties based on selective clearance analysis. The method comprises the following steps: collecting Ningxia wolfberry leaves, extracting DNA samples of the Ningxia wolfberry leaves, re-sequencing the DNA samples to obtain effective sequences, analyzing heritable variation and genetic relationship of the Ningxia wolfberry leaves based on nucleotide polymorphism, performing population differentiation index and selective clearance analysis, revealing biological differences among various varieties by adopting selective clearance analysis, and determining the genetic relationship between the Ningxia wolfberry leaves and the genetic relationship between the Ningxia wolfberry leaves and the Ningxia wolfberry leaves. The four Ningxia Chinese wolfberry varieties including the hemp leaf, the Ningxia Chinese wolfberry No.1, the Ningxia Chinese wolfberry No.7 and the Ningxia Chinese wolfberry No.10 are effectively distinguished in pairs by taking the KEGG pathway enrichment characteristics as identification indexes, and a basis is provided for germplasm resource identification and classification of the Ningxia Chinese wolfberry.

Description

Technical Field

[0001] The invention relates to the technical field of biological detection, and in particular to a method for identifying Ningxia wolfberry varieties based on selective elimination analysis. Background Art

[0002] Lycium barbarum (Lycium barabrum L.), a plant of the genus Lycium (Lycium L.) of the Solanaceae family, has a long history of medicinal use. It is a food and medicine product with the effects of nourishing the liver and kidneys, improving the essence and improving eyesight. In the Ming and Qing Dynasties, Ningxia began to grow wolfberries on a large scale and gradually became the authentic production area of ​​Ningxia wolfberries. At present, there are many varieties of Ningxia wolfberries, most of which are selected and bred based on economic characteristics such as high yield, large fruit, and strong resistance. Hemp leaves are the main strains of Ningxia wolfberry cultivation, and have a long history of cultivation in Ningxia. In 1978, the "Ningqi No. 1" was selected from the hemp leaves using the single plant selection method. Since then, Ningqi series such as Ningqi No. 2 to No. 10 have been selected and bred. Due to the characteristics of "Ningqi No. 7" with large fruit, high commercial grade rate, strong resistance, and wide suitable area, the cultivation area has gradually increased in recent years. The newly bred Ningqi No. 10 has the characteristics of fruit stalks not easily falling off, fresh fruits not easily cracking when exposed to rain, strong self-compatibility and strong stress resistance, and has also been gradually promoted.

[0003] Resequencing refers to obtaining the genome sequence of a species, comparing it with existing gene sequences, and performing difference analysis to explore its genetic, evolutionary, and biological characteristics.

[0004] At present, the dried mature fruits of all varieties of Ningqi series are no longer distinguished after entering the market, and only the evaluation indicators such as traits and color are used as the standard for the sale of wolfberries, which makes it difficult to distinguish. At the same time, the whole genome sequence of Ningxia wolfberry has been reported, but there is still a lack of reports on the biological identification of the main varieties of Ningxia wolfberry cultivated at different times. Summary of the invention

[0005] The technical problem to be solved by the present invention is to provide a method for identifying Ningxia wolfberry varieties based on selective elimination analysis in view of the deficiencies in the prior art.

[0006] In order to solve the above technical problems, the technical solution adopted by the present invention is as follows:

[0007] A method for identifying Ningxia wolfberry varieties based on selection elimination analysis, collecting Ningxia wolfberry leaves and extracting their DNA samples, resequencing the DNA samples to obtain valid sequences, and conducting population differentiation index and selection elimination analysis based on nucleotide polymorphism, and using KEGG pathway enrichment features as identification indicators to distinguish Ningxia wolfberry varieties pairwise.

[0008] Among them, the Ningxia wolfberry varieties are any two of hemp leaf, Ningqi No. 1, Ningqi No. 7 and Ningqi No. 10.

[0009] Specifically, before resequencing the DNA sample, the DNA sequence is first fragmented using ultrasound, and the fragmented DNA is sequentially end-repaired, 3'-end A is added, and sequencing adapters are connected. The magnetic bead enrichment method is then used to enrich fragments with a length of 340 to 360 bp, and PCR amplification is performed to form a sequencing library.

[0010] The resequencing was performed using Illumnia NovaSeq TM The platform was used for sequencing, with a total sequencing length of 300 bp.

[0011] The effective sequence is obtained by removing the adapter sequence in the reads, removing the bases containing non-AGCT at the 5' end, trimming the ends of the reads with sequencing quality values ​​less than Q20, removing the reads containing N at a ratio of 10%, discarding the adapter and the small fragments less than 25bp in length after quality trimming.

[0012] Among them, the selection and elimination analysis specifically divides the genes into 10Kb non-overlapping sliding windows, then groups the Ningxia wolfberry varieties in pairs, calculates the Fst values ​​between groups and the π values ​​within each group, selects the top 5% of the regions as the selected regions, and takes the selected regions as the significant regions. Based on the significant regions, KO annotation is performed, and according to the KO annotation information, the enrichment degree of each functional level of KEGG in different Ningxia wolfberry varieties is statistically analyzed.

[0013] Specifically, the significant region includes a significant selection clearance site, and the significant selection clearance site includes a selected gene; when KO annotation is performed based on the significant region, the enrichment degree of each functional level of KEGG in different Ningxia wolfberry varieties is statistically analyzed according to the KO annotation information, and the significant functional enrichment information of the selected gene is obtained.

[0014] Furthermore,

[0015] (1) When Ningxia wolfberry is hemp leaf and Ningxia wolfberry No. 1,

[0016] When the terpenoids and polyketide metabolism pathways are the dominant enrichment pathways, the Ningxia wolfberry is hemp leaf; when the carbohydrate metabolism pathway is the dominant enrichment pathway, the Ningxia wolfberry is Ningqi No. 1. In some embodiments of the present invention, the terpenoids and polyketide metabolism pathways are diterpene biosynthesis ko00904 and monoterpene biosynthesis ko00902; the carbohydrate metabolism pathways are propionate metabolism ko00640, phosphoinositide metabolism ko00562, and pyruvate metabolism ko00620.

[0017] or,

[0018] (2) When Ningxia wolfberry is hemp leaf and Ningqi No. 7,

[0019] When the amino acid metabolic pathway is the dominant enrichment pathway, the Ningxia wolfberry is hemp leaf; when the auxiliary factor and vitamin metabolic pathway is the dominant enrichment pathway, the Ningxia wolfberry is Ningqi No. 7. In some embodiments of the present invention, the amino acid metabolic pathway is cysteine ​​and methionine metabolism ko00270, selenium compound metabolism ko00450, cyanoamino acid metabolism ko00460, valine, leucine and isoleucine degradation ko00280, alanine, aspartic acid and glutamate metabolism ko00250; the auxiliary factor and vitamin metabolic pathway is porphyrin and chlorophyll metabolism ko00860, vitamin B6 metabolism ko00750.

[0020] or,

[0021] (3) When Ningxia wolfberry is hemp leaf and Ningqi No. 10,

[0022] Or, when the amino acid metabolism pathway is the dominant enrichment pathway, the Ningxia wolfberry is hemp leaf; when the terpenoid and polyketide metabolism is the dominant enrichment pathway, the Ningxia wolfberry is Ningqi No. 10. In some embodiments of the present invention, the amino acid metabolism pathway is cysteine ​​and methionine metabolism ko00270, selenium compound metabolism ko00450, cyanoamino acid metabolism ko00460, lysine degradation ko00310; the terpenoid and polyketide metabolism pathway is zeatin synthesis ko00908, monoterpene biosynthesis ko00902.

[0023] (4) When Ningxia wolfberry is Ningqi No. 1 and Ningqi No. 7,

[0024] When the amino acid metabolic pathway and the environmental information processing pathway are the dominant enrichment pathways, the Ningxia wolfberry is Ningqi No. 1; when the photosynthetic antenna protein pathway is the dominant enrichment pathway, the Ningxia wolfberry is Ningqi No. 7. In some embodiments of the present invention, the amino acid metabolic pathway is phenylalanine metabolism ko00360, cysteine ​​and methionine metabolism ko00270, and tryptophan metabolism ko00380, and the environmental information processing pathway is plant hormone signal transduction ko04075 and plant MAPK signaling pathway ko04016; the photosynthetic antenna protein pathway is photosynthetic antenna protein ko00196.

[0025] or,

[0026] (5) When Ningxia wolfberry is Ningqi No. 1 and Ningqi No. 10,

[0027] When the amino acid metabolic pathway is the dominant enrichment pathway, the Ningxia wolfberry is Ningqi No. 1; when the zeatin biosynthesis pathway and the monoterpene biosynthesis pathway are the dominant enrichment pathways, the Ningxia wolfberry is Ningqi No. 10. In some embodiments of the present invention, the amino acid metabolic pathway is phenylalanine metabolism ko00360, cysteine ​​and methionine metabolism ko00270; the zeatin biosynthesis pathway and the monoterpene biosynthesis pathway are zeatin synthesis ko00908, and monoterpene biosynthesis ko00902.

[0028] or,

[0029] (6) When Ningxia wolfberry is Ningqi No. 7 and Ningqi No. 10,

[0030] When the energy metabolism pathway, the amino acid metabolism pathway, and the carbohydrate metabolism pathway are the dominant enrichment pathways, the Ningxia wolfberry is Ningqi No. 7; when the terpenoid and polyketide metabolism pathway and the fatty acid metabolism pathway are the dominant enrichment pathways, the Ningxia wolfberry is Ningqi No. 10. In some embodiments of the present invention, the energy metabolism pathway is nitrogen metabolism ko00910, the amino acid metabolism pathway is the biosynthesis of valine, leucine and isoleucine ko00290, the carbohydrate metabolism pathway is C5-branched dibasic acid metabolism ko00660; the terpenoid and polyketide metabolism pathway is monoterpene biosynthesis ko00902 and brassinosteroid biosynthesis ko00905; the fatty acid metabolism pathway is α-linolenic acid metabolism ko00592 and linoleic acid metabolism ko00591.

[0031] A high-throughput detection system for identifying Ningxia wolfberry varieties based on selective elimination analysis is also within the scope of protection of the present invention.

[0032] Specifically, the high-throughput detection system includes a processor and a memory; wherein the memory is used to store instructions, and when the processor executes the stored instructions, the high-throughput detection system implements the steps of the method for identifying Ningxia wolfberry varieties based on selection and elimination analysis.

[0033] A kit for identifying Ningxia wolfberry varieties is also within the scope of protection of the present invention.

[0034] Specifically, the kit includes a DNA sample extraction reagent from Ningxia wolfberry leaves, a DNA sample resequencing reagent, and a DNA sample resequencing data analysis software.

[0035] Beneficial effects:

[0036] The present invention uses resequencing technology to deeply study the biological differences of four dominant varieties of Ningxia wolfberry, analyzes their genetic variation and kinship based on single nucleic acid polymorphism (SNP), and uses selection elimination analysis to reveal the biological differences between the varieties. The experimental results show that the selection elimination analysis determined by the present invention can distinguish four Ningxia wolfberry varieties, namely, Damaye, Ningqi No. 1, Ningqi No. 7 and Ningqi No. 10. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] The present invention will be further described in detail below with reference to the accompanying drawings, and the above and / or other advantages of the present invention will become more clear.

[0038] Figure 1 The agarose gel electrophoresis DNA band diagram of 60 samples from three species of Lycium genus.

[0039] Figure 2 This is a phylogenetic tree of three species of the genus Lycium constructed based on the maximum likelihood tree.

[0040] Figure 3 There are three species group structures of Lycium barbarum.

[0041] Figure 4 These are the cross-validation error values ​​for population structure analysis of three Lycium species.

[0042] Figure 5 Principal component analysis of three species of Lycium.

[0043] Figure 6 This paper analyzes the phylogenetic relationships of three species of Lycium.

[0044] Figure 7 This study was to analyze the nucleotide polymorphism within three populations of Lycium barbarum and the genetic differentiation index among populations.

[0045] Figure 8 This is a linkage disequilibrium decay analysis of three species of Lycium.

[0046] Fig. 9 This is the phylogenetic tree of four varieties of Ningxia wolfberry constructed based on the maximum likelihood tree.

[0047] Fig.10 It is the group structure of four varieties of Ningxia wolfberry.

[0048] Fig.11 This is the cross-validation error value for population structure analysis of four varieties of Ningxia wolfberry.

[0049] Fig.12 This is the principal component analysis of four varieties of Ningxia wolfberry.

[0050] Fig.13 This paper analyzes the genetic relationships of four varieties of Ningxia wolfberry.

[0051] Fig.14 This study was to analyze the nucleotide polymorphism within four Ningxia wolfberry cultivars and the genetic differentiation index between populations.

[0052] Fig.15 This is the Manhattan plot of the genetic differentiation coefficient Fst between cannabis leaves and Ningqi No. 1.

[0053] Fig.16 KEGG pathway enrichment of selected genes based on Fst cannabis leaves and Ningqi No. 1.

[0054] Fig.17 This is the Manhattan plot of the πratio of the nucleotide polymorphism between cannabis leaves and Ningqi No. 1.

[0055] Fig.18 KEGG pathway enrichment of selected genes in cannabis leaves (A) and Ningqi 1 (B) based on πratio.

[0056] Fig.19 This is the Manhattan plot of the genetic differentiation coefficient Fst between cannabis leaves and Ningqi No. 7.

[0057] Fig. 20 KEGG pathway enrichment of selected genes based on Fst cannabis leaves and Ningqi No. 7.

[0058] Fig.21 This is the Manhattan plot of the πratio of the nucleotide polymorphism between cannabis leaves and Ningqi No. 7.

[0059] Fig. 22 KEGG pathway enrichment of selected genes in cannabis leaves (A) and Ningqi No. 7 (B) based on πratio.

[0060] Fig.23 This is the Manhattan plot of the genetic differentiation coefficient Fst of cannabis leaves and Ningqi No. 10.

[0061] Fig.24 KEGG pathway enrichment of selected genes based on Fst cannabis leaves and Ningqi No. 10.

[0062] Fig.25 This is the Manhattan plot of the πratio of the nucleotide polymorphism of cannabis leaves and Ningqi No. 10.

[0063] Fig.26 KEGG pathway enrichment of selected genes in cannabis leaves (A) and Ningqi No. 10 (B) based on πratio.

[0064] Fig. 27 This is the Manhattan plot of the genetic differentiation coefficient Fst of Ningqi 1 and Ningqi 7.

[0065] Fig.28 KEGG pathway enrichment of selected genes based on Fst Ningqi No. 1 and Ningqi No. 7.

[0066] Fig.29 This is the Manhattan plot of the πratio of the nucleotide polymorphisms of Ningqi 1 and Ningqi 7.

[0067] Fig.30 KEGG pathway enrichment of selected genes in Ningqi No. 1 (A) and Ningqi No. 7 (B) based on πratio.

[0068] Fig.31 This is the Manhattan plot of the genetic differentiation coefficient Fst of Ningqi No. 1 and Ningqi No. 10.

[0069] Fig.32 KEGG pathway enrichment of selected genes based on Fst Ningqi No. 1 and Ningqi No. 10.

[0070] Fig.33 This is the Manhattan plot of the πratio of the nucleotide polymorphisms of Ningqi 1 and Ningqi 10.

[0071] Fig.34 KEGG pathway enrichment of selected genes in Ningqi No. 1 (A) and Ningqi No. 10 (B) based on πratio.

[0072] Fig.35 This is the Manhattan plot of the genetic differentiation coefficient Fst of Ningqi 7 and Ningqi 10.

[0073] Fig.36 KEGG pathway enrichment of selected genes based on Fst Ningqi No. 7 and Ningqi No. 10.

[0074] Fig.37 This is the Manhattan plot of the πratio of the nucleotide polymorphisms of Ningqi 7 and Ningqi 10.

[0075] Fig.38 KEGG pathway enrichment of selected genes in Ningqi No. 7 (A) and Ningqi No. 10 (B) based on πratio. DETAILED DESCRIPTION

[0076] The present invention will be further described in detail below in conjunction with specific implementations, and the above and / or other advantages of the present invention will become more clear.

[0077] The experimental methods described in the following examples are conventional methods unless otherwise specified; the reagents and materials described are commercially available unless otherwise specified.

[0078] In the following embodiments, the methods of variation detection, phylogenetic tree analysis, population structure analysis, principal component analysis, kinship analysis, Lycium / Ningxia Lycium barbarum variety polymorphism analysis, linkage disequilibrium decay analysis, and selection elimination analysis are all conventional methods of bioinformatics analysis in the art, and the specific analysis steps of the corresponding methods are not repeated here.

[0079] Example 1: Collection and resequencing of Lycium barbarum plant samples

[0080] 1. Sample collection

[0081] Samples of Lycium barbarum plants were collected: Ningxia wolfberry (Lycium barbarum L., GQ) series hemp leaves (DMY), Ningqi No. 1 (NQ1), Ningqi No. 7 (NQ7) and Ningqi No. 10 (NQ10), as well as black wolfberry (Lycium ruthenicum Murr., HG) and Chinese wolfberry (Lycium chinense Mill., ZH), 10 samples from each population, a total of 60 samples, and their dried leaves were collected, dried over silica gel and set aside.

[0082] 2. Sample genome extraction and detection

[0083] The genomic DNA of the above-mentioned Lycium plant samples was extracted using a DNA extraction kit. The DNA purity was tested using a NanoDrop2000 spectrophotometer, and the DNA concentration was tested using a Quantus Fluorometer (Picogreen). The DNA integrity was checked using agarose gel electrophoresis. The test results are as follows: Figure 1 As shown in the figure, the DNA band is single, the DNA solution is non-viscous, free of pigments and suspended matter, and free of contamination by impurities such as RNA, protein, and sugar, which meets the requirements of standard library construction and can be used for standard library construction.

[0084] 3. Library construction and sequencing

[0085] The DNA sequence was fragmented by ultrasound, and the fragmented DNA was repaired at the end, A was added to the 3' end, and the sequencing adapter was connected. Then, the magnetic bead enrichment method was used to enrich the fragments of about 350bp in length, and PCR amplification was used to form a sequencing library. After passing the quality inspection, the Illumnia NovaSeq TM The platform was used for sequencing, with a total sequencing length of 300 bp.

[0086] 4. Raw data filtering

[0087] Fastp was used to evaluate the quality of the raw data produced by resequencing, removing the adapter sequence in the reads, removing the bases containing non-AGCT at the 5' end, trimming the ends of reads with sequencing quality values ​​less than Q20, removing reads containing N at a ratio of 10%, discarding the adapter and small fragments less than 25bp in length after quality trimming, and obtaining valid sequences (Clean Reads) after quality control.

[0088] 5. Sequence alignment

[0089] The Lycium barabrum L. genome sequence was used as the reference genome, and the BWA-MEME software was used to align the effective sequences (Clean Reads) after quality control with the reference genome. Subsequently, based on the alignment results, the variations in the gene sequences were detected and analyzed, the detected variation sites were annotated, and the resequencing data were used for population genetics and other studies.

[0090] Example 2: Genetic evolution analysis among different species

[0091] 1. Mutation Detection

[0092] GATK software was used for population SNP and InDel detection, and SnpEff software was used for SNP and InDel annotation. The results showed that a total of 2,023,600 SNP sites and 140,770 InDels were obtained from three species of Ningxia wolfberry (n=40), Chinese wolfberry (n=10) and black wolfberry (n=10) for further analysis.

[0093] 2. Phylogenetic tree analysis

[0094] Based on the SNP loci information with high credibility obtained after comparison, a phylogenetic tree of 60 samples of three species, namely, Lycium barbarum, Lycium chinense and Lycium ruthenicum, was constructed. Figure 2 As shown, among the three common species of Lycium, Ningxia wolfberry (GQ), black wolfberry (HG) and Chinese wolfberry (ZH) are clustered into one branch respectively.

[0095] 3. Group structure analysis

[0096] The sample was subjected to Structure analysis, and the results were as follows: Figure 3 As shown in the results, when K = 3, the three species of Lycium can be divided into three subgroups: Ningxia Lycium, Lycium barbarum and black Lycium barbarum; when K = 2, the three species of Lycium barbarum are divided into two subgroups, namely, Ningxia Lycium barbarum subgroup, Lycium barbarum and black Lycium barbarum subgroup. Cross-validation is used to calculate the CV error value under the K value, and the results are as follows Figure 4As shown in the figure, the minimum CV error value is 0.41136 when K = 2, and the CV error value is 0.4245 when K = 3. Considering that the difference in CV error values ​​is small when K = 2 and K = 3, combined with the characteristics of each species, it is believed that the three species of Lycium can be divided into three subgroups, namely, Ningxia wolfberry group, wolfberry group and black fruit wolfberry group.

[0097] 4. Principal Component Analysis

[0098] The principal component analysis of the sample SNPs was performed, and the results were as follows Figure 5 As shown in the figure, the first and second principal components can be used to clearly distinguish the three species, and each species is clustered into a cluster. This distribution feature is highly consistent with the phylogenetic tree and population structure grouping.

[0099] 5. Kinship analysis

[0100] The results of the phylogenetic analysis of the three species are as follows: Figure 6 As shown, there is no genetic relationship among the samples of Ningxia wolfberry, black wolfberry and Chinese wolfberry, which is consistent with the results of phylogenetic tree, population structure grouping and principal component analysis.

[0101] 6. Analysis of Lycium polymorphism

[0102] The population differentiation index (Fst) was used to evaluate the genetic differentiation among the three species of Lycium. Figure 7 As shown in the figure, there are different degrees of genetic differentiation among the three species. The Fst of Ningxia wolfberry, black wolfberry and Chinese wolfberry are 0.104 and 0.101 respectively, indicating that the genetic differentiation between Ningxia wolfberry and black wolfberry, Ningxia wolfberry and Chinese wolfberry is similar. The Fst of black wolfberry and Chinese wolfberry is 0.15, which is higher than the genetic differentiation between Ningxia wolfberry and black wolfberry and between Ningxia wolfberry and Chinese wolfberry. The results of nucleotide polymorphism detection showed that Ningxia wolfberry (Pi = 0.201) and black wolfberry (Pi = 0.182) were greater than Chinese wolfberry (Pi = 0.168), indicating that among the three species of Lycium genus, Ningxia wolfberry has the highest genetic diversity, while Chinese wolfberry has the lowest.

[0103] 7. Linkage disequilibrium decay analysis

[0104] The linkage disequilibrium decay analysis of three species of Lycium was carried out. The linkage disequilibrium coefficient (r 2 ) is taken as the distance when the decay is halfway, and the result is as follows: Figure 8 As shown, the attenuation distance of Ningxia wolfberry is 211.1Kb, and the attenuation distances of Chinese wolfberry and black wolfberry are both 500Kb, indicating that the attenuation rate of Ningxia wolfberry is faster and the species is more primitive than wolfberry and black wolfberry.

[0105] Example 3: Analysis of genetic differentiation within Ningxia wolfberry species

[0106] 1. Mutation Detection

[0107] GATK software was used for population SNP and InDel detection, and SnpEff software was used for SNP and InDel annotation. The results showed that a total of 4,484,970 SNP sites and 313,726 InDels were obtained from four varieties of DMY (Dammaye, n = 10), NQ1 (NQ1, n = 10), NQ7 (NQ7, n = 10) and NQ10 (NQ10, n = 10) for further analysis.

[0108] 2. Phylogenetic tree analysis

[0109] Based on the SNP loci information with high credibility obtained after comparison, a phylogenetic tree of 40 samples of four varieties, DMY, NQ1, NQ7 and NQ10, was constructed. Fig. 9 As shown, among the four fine cultivars of Ningxia wolfberry, except for a few individual samples, each variety can be clustered into one branch, followed by NQ7 and NQ10, and DMY and NQ1, suggesting that NQ7 and NQ10 are more closely related genetically, and DMY and NQ1 are more closely related genetically.

[0110] 3. Group structure analysis

[0111] The sample was subjected to Structure analysis, and the results were as follows: Fig.10 As shown in the results, when K = 4, the four varieties of Ningxia wolfberry are divided into different subgroups. Cross-validation is used to calculate the CV error value under the K value, and the results are as follows Fig.11 The data showed that when K = 3, the minimum CVerror value was 0.32801, and K = 3 was considered to be the best grouping. The four varieties of Ningxia wolfberry could be divided into four subgroups. NQ10 showed the same genotype (K = 3 green), DMY showed the same genotype (K = 3 red), most samples of NQ7 showed another group of genotypes (K = 3 blue), and NQ1 showed 60% of the genotypes of NQ10 and 40% of the genotypes of DMY.

[0112] 4. Principal Component Analysis

[0113] The principal component analysis of the sample SNPs was performed, and the results were as follows Fig.12 As shown in the figure, the first two principal components can clearly distinguish the four varieties of Ningxia wolfberry, and each variety is clustered into a cluster. This distribution feature is highly consistent with the phylogenetic tree and population structure grouping.

[0114] 5. Kinship analysis

[0115] The relationship between the four varieties was analyzed and the results were as follows Fig.13As shown in the figure, the four varieties of Ningxia wolfberry are related, among which Damaye and Ningqi No. 1 are parents or siblings. According to the variety breeding process, Ningqi No. 1 is the single plant selected variety of Damaye, and Ningqi No. 7 is a variant of Ningqi No. 1, which is consistent with the results of genetic relationship analysis; Ningqi No. 10 and Damaye are the second generation relationship. Ningqi No. 10 is bred by crossing Ningqi No. 4 as the male parent and Ningqi No. 5 as the female parent. Ningqi No. 4 is the selected strain of Damaye, and Ningqi No. 5 is the male sterile strain of Ningqi No. 1. The results of genetic relationship analysis are consistent with the actual breeding. It can be seen that the four selected varieties of Ningxia wolfberry have a clear genetic relationship and are genetically similar.

[0116] 6. Analysis of polymorphism of Ningxia wolfberry varieties

[0117] The population differentiation index (Fst) was used to evaluate the genetic differentiation among the four varieties of Ningxia wolfberry. Fig.14 As shown in the figure, there are different degrees of genetic differentiation among the four varieties. The Fst of Damaye and Ningqi No. 1, Ningqi No. 7 and Ningqi No. 10 are 0.16, 0.183 and 0.215 respectively, the Fst of Ningqi No. 1, Ningqi No. 7 and Ningqi No. 10 are 0.141 and 0.131 respectively, and the Fst of Ningqi No. 7 and Ningqi No. 10 is 0.148. The above results show that the genetic differentiation between Damaye and Ningqi No. 10 is higher than that of other varieties, and the genetic differentiation between the other three varieties is relatively small. The results of nucleotide polymorphism detection show that the four varieties of Ningxia wolfberry have high genetic diversity, with Ningqi No. 1 having the highest genetic diversity (Pi = 0.361), Ningqi No. 7 second (Pi = 0.354), and Damaye the lowest (Pi = 0.318).

[0118] 7. Select Clear Analysis

[0119] The selection and elimination analysis was used to compare the populations of different varieties according to the specificity between different varieties, and the functional annotation of differential genes in the domestication process was performed. The population differentiation index (Fst) and nucleotide polymorphism (πRatio) methods were used for selection and elimination analysis. The genes were divided into 10Kb non-overlapping sliding windows and grouped into two groups according to cannabis leaves (DMY), Ningqi No. 1 (NQ1), Ningqi No. 7 (NQ7) and Ningqi No. 10 (NQ10). The Fst values ​​between groups and the π values ​​within each group were calculated, and the top 5% of the regions were selected as the selected regions. Based on the significant regions, KO annotation and KEGG pathway enrichment were performed to obtain the significant functional enrichment information of the selected genes.

[0120] (1) Manhattan plot of genetic differentiation coefficient Fst of cannabis leaf and Ningqi No. 1 ( Fig.15 ) showed that the top 5% of the significant selection sites in the 12 windows contained 3346 selected genes. A total of 707 genes were annotated to KO, and the enrichment results of the top 20 KEGG pathways were as follows Fig.16 As shown, there were 9 significantly enriched pathways (p<0.05), including 3 carbohydrate metabolism pathways (propionic acid metabolism ko00640; phosphoinositide metabolism ko00562; pyruvate metabolism ko00620), 2 terpenoid synthesis and polyketide metabolism pathways (diterpenoid biosynthesis ko00904; monoterpenoid biosynthesis ko00902), 1 other secondary metabolite biosynthesis pathway (aflatoxin biosynthesis ko00254), 1 lipid metabolism pathway (linoleic acid metabolism ko00591), 1 genetic information processing pathway (RNA transport ko03013) and 1 cellular process (peroxisome ko04146). The above results suggest that the selected genes mainly affect the content of carbohydrates, terpenes, aflatoxin, etc. in cannabis leaves and Ningqi No. 1. Nucleotide polymorphism πratio Manhattan plot ( Fig.17 ) showed that the top 5% of the significant selection sites in the 12 windows included 3365 selected genes in cannabis leaves and 1651 selected genes in Ningqi No. 1. KO annotation A total of 728 genes were annotated in cannabis leaves and 304 genes were annotated in Ningqi No. 1. The KEGG pathway enrichment results of the two species are shown as follows Fig.18 As shown, the results showed that the KEGG pathway enrichment of Fst and πRatio selection clearance analysis was significantly enriched in diterpene biosynthesis (ko00904), monoterpene biosynthesis (ko00902), propionate metabolism (ko00640), phosphoinositide metabolism (ko00562), and pyruvate metabolism (ko00620) pathways, but the terpenoid synthesis and polyketide metabolism pathways (diterpene biosynthesis ko00904; monoterpene biosynthesis ko00902) were mainly significantly enriched in cannabis leaves, and the carbohydrate metabolism pathway (propionate metabolism ko00640; phosphoinositide metabolism ko00562; pyruvate metabolism ko00620) was mainly significantly enriched in Ningqi No. 1. The above results suggest that there are differences in the effects of selected genes on different types of compounds in cannabis leaves and Ningqi No. 1.

[0121] (2) Manhattan plot of genetic differentiation coefficient Fst of cannabis leaf and Ningqi 7 ( Fig.19 ) showed that the top 5% of the significant selection sites in the 12 windows contained 2572 selected genes. A total of 562 genes were annotated to KO, and the enrichment results of the top 20 KEGG pathways were as follows Fig. 20 As shown, the significantly enriched pathways (p<0.05) are non-homologous end joining repair (ko03450), sphingolipid metabolism (ko00600), circadian rhythm (ko04712), amino sugar and nucleotide sugar metabolism (ko00520) and base excision repair (ko03410). Manhattan plot of nucleotide polymorphism πratio ( Fig.21) showed that the top 5% of the significant selection sites in the 12 windows included 3649 selected genes in cannabis leaves and 2501 selected genes in Ningqi No. 1. KO annotation A total of 791 genes were annotated in cannabis leaves and 546 genes were annotated in Ningqi No. 1. The KEGG pathway enrichment results of the two species are as follows Fig. 22 As shown, the results showed that the KEGG pathway enrichment of Fst and πRatio selection clearance analysis was significantly enriched in the diterpene biosynthesis (ko00904) pathway. In addition, cannabis leaves were significantly enriched in amino acid metabolism pathways, including cysteine ​​and methionine metabolism (ko00270), selenium compound metabolism (ko00450), cyanoamino acid metabolism (ko00460), valine, leucine and isoleucine degradation (ko00280) and alanine, aspartate and glutamate metabolism (ko00250); Ningqi No. 7 was significantly enriched in two auxiliary factor and vitamin metabolism pathways (porphyrin and chlorophyll metabolism ko00860; vitamin B6 metabolism ko00750). This result suggests that cannabis leaves are more conducive to amino acid enrichment, while Ningqi No. 7 is more conducive to vitamin enrichment.

[0122] (3) Manhattan plot of genetic differentiation coefficient Fst of cannabis leaf and Ningqi No. 10 ( Fig.23 ) showed that the top 5% of the significant selection clearance sites in the 12 windows contained 1692 selected genes. A total of 386 genes were annotated to KO, and the enrichment results of the top 20 KEGG pathways were as follows Fig.24 As shown, there are 7 significantly enriched pathways (p < 0.05), including 3 other secondary metabolite biosynthesis pathways (flavonoid biosynthesis ko00941; biosynthesis of diphenyl, diarylheptanoid and gingerol ko00945; phenylpropanoid biosynthesis ko00940), 3 carbohydrate metabolism pathways (glyoxylate and dicarboxylate metabolism ko00630; galactose metabolism ko00052; glycolysis / gluconeogenesis ko00010) and 1 auxiliary factor and vitamin metabolism (a folate carbon pool ko00670), suggesting that there are differences in the secondary metabolite and carbohydrate enrichment process between the two. Nucleotide polymorphism πratio Manhattan plot ( Fig.25 ) showed that the top 5% significant selection sites in the 12 windows included 3305 selected genes in cannabis leaves and 1942 selected genes in Ningqi No. 10. KO annotation: A total of 699 genes were annotated in cannabis leaves and 386 genes were annotated in Ningqi No. 10. The KEGG pathway enrichment results of the two species are shown in Fig.26As shown in the figure, the enriched pathways of both are mainly metabolic pathways, including amino acid metabolism, terpenoid and polyketide metabolism, carbohydrate metabolism, etc. Among them, the significantly enriched pathways of Ningqi No. 10 are terpenoid and polyketide metabolism (zeatin synthesis ko00908, monoterpene biosynthesis ko00902), and the significantly enriched pathways of cannabis leaves are amino acid metabolic pathways (cysteine ​​and methionine metabolism ko00270, selenium compound metabolism ko00450, cyanoamino acid metabolism ko00460, lysine degradation ko00310).

[0123] (4) Manhattan plot of genetic differentiation coefficient Fst of Ningqi 1 and Ningqi 7 ( Fig. 27 ) showed that the top 5% of the significant selection clearance sites in the 12 windows contained 2455 selected genes. A total of 539 genes were annotated to KO, and the enrichment results of the top 20 KEGG pathways were as follows Fig.28 As shown, the significantly enriched pathways (p<0.05) are pyrimidine metabolism (ko00240), mucopolysaccharide degradation (ko00531) and photosynthetic antenna protein (ko00196). Manhattan plot of nucleotide polymorphism πratio ( Fig.29 ) showed that the top 5% significant selection sites in the 12 windows included 1856 selected genes in Ningqi 1 and 2605 selected genes in Ningqi 7. KO annotation Ningqi 1 annotated 376 genes and Ningqi 7 annotated 586 genes. The KEGG pathway enrichment results of the two species are shown in Fig.30 As shown, Ningqi No. 1 significantly enriched 8 pathways (p<0.05), of which 3 were amino acid metabolism pathways (phenylalanine metabolism ko00360; cysteine ​​and methionine metabolism ko00270; tryptophan metabolism ko00380), and 2 were involved in environmental information processing pathways (plant hormone signal transduction ko04075; plant MAPK signaling pathway ko04016); Ningqi No. 7 significantly enriched pathway photosynthesis antenna protein (ko00196), which was consistent with the KEGG enrichment result of Fst analysis, indicating that Ningqi No. 1 may enrich amino acid substances, while Ningqi No. 7 affects photosynthesis antenna protein and causes energy metabolism differences.

[0124] (5) Manhattan plot of genetic differentiation coefficient Fst of Ningqi No. 1 and Ningqi No. 10 ( Fig.31 ) showed that the top 5% of the significant selection clearance sites in the 12 windows contained 2533 selected genes. A total of 552 genes were annotated to KO, and the enrichment results of the top 20 KEGG pathways were as follows Fig.32As shown, there are 7 significantly enriched pathways (p<0.05), of which 3 of the 5 metabolic pathways are terpenoid and polyketide metabolic pathways (zeatin biosynthesis ko00908; monoterpene biosynthesis ko00902; terpene skeleton biosynthesis ko00900), 1 is carbohydrate metabolism (propionic acid metabolism ko00640), and the other 1 is fatty acid metabolism (unsaturated fatty acid biosynthesis ko01040). Nucleotide polymorphism πratio Manhattan plot ( Fig.33 ) showed that the top 5% significant selection sites in the 12 windows included 1737 selected genes in Ningqi No. 1 and 2125 selected genes in Ningqi No. 10. KO annotation Ningqi No. 1 annotated 350 genes and Ningqi No. 10 annotated 451 genes. The KEGG pathway enrichment results of the two species are shown as follows Fig.34 As shown in the figure, the significantly enriched pathways of Ningqi No. 1 include two amino acid metabolisms (phenylalanine metabolism ko00360; cysteine ​​and methionine metabolism ko00270), while the significantly enriched pathways of Ningqi No. 7 include zeatin biosynthesis (ko00908) and monoterpene biosynthesis (ko00902), which are consistent with the KEGG enrichment results in Fst analysis, suggesting that Ningqi No. 1 may be enriched in amino acid substances, while Ningqi No. 10 is enriched in terpenoids such as zeatin.

[0125] (6) Manhattan plot of genetic differentiation coefficient Fst of Ningqi 7 and Ningqi 10 ( Fig.35 ) showed that the top 5% of the significant selection sites in the 12 windows contained 2438 selected genes. A total of 527 genes were annotated to KO, and the enrichment results of the top 20 KEGG pathways were as follows Fig.36 As shown, 7 of the 11 pathways that were significantly enriched (p<0.05) were metabolic pathways, including 3 secondary metabolite synthesis pathways (flavonoid biosynthesis ko00941; biosynthesis of diphenyl, diarylheptanoids and gingerol ko00945; biosynthesis of flavonoids and flavonols ko00944), pyrimidine metabolism (ko00240), glycolysis / gluconeogenesis (ko00010), metabolism of nicotinate and nicotinamide (ko00760), and butyrate metabolism (ko00650), suggesting that the main differential metabolites between the two may be secondary metabolites such as flavonoids. Nucleotide polymorphism πratio Manhattan plot ( Fig.37 ) showed that the top 5% significant selection sites in the 12 windows included 2085 selected genes in Ningqi 7 and 1872 selected genes in Ningqi 10. KO annotation Ningqi 7 annotated 453 genes and Ningqi 10 annotated 397 genes. The KEGG pathway enrichment results of the two species are shown in Fig.38As shown in the figure, the five significantly enriched metabolic pathways of Ningqi No. 7 included energy metabolism (nitrogen metabolism ko00910), amino acid metabolism (biosynthesis of valine, leucine and isoleucine ko00290), carbohydrate metabolism (C5-branched dicarboxylic acid metabolism ko00660), etc., while the six significantly enriched metabolic pathways of Ningqi No. 10 included two terpenoid and polyketide metabolism (monoterpene biosynthesis ko00902 and brassinosteroid biosynthesis ko00905) and two fatty acid metabolism (α-linolenic acid metabolism ko00592 and linoleic acid metabolism ko00591), suggesting that Ningqi No. 10 may be enriched in terpenes and fatty acids.

[0126] Among them, the selected genes significantly enriched in the amino acid metabolic pathways of cannabis leaves and Ningqi No. 1 are shown in Tables 1 and 2.

[0127] Table 1 Selected genes significantly enriched in amino acid pathways in cannabis leaves

[0128]

[0129] Table 2 Selected genes significantly enriched in amino acid pathways in Ningqi 1

[0130]

[0131]

[0132] A total of 23 amino acid contents were determined by LC-MS, and the results are shown in Table 3. The results showed that the amino acid content of Ningqi No. 7 among the four varieties of Ningxia wolfberry was significantly higher than that of Ningqi No. 1 and cannabis leaves. From the results of selected gene pathway enrichment, it can be seen that the selected genes in Ningqi No. 1 and cannabis leaves are significantly enriched in some amino acid metabolic pathways, which is consistent with the results of the above-mentioned identification of Ningqi No. 7 and Ningqi No. 1, Ningqi No. 7 and cannabis leaves based on selection clearance analysis. It can also be seen that the significant enrichment of selected genes in amino acid metabolic pathways leads to enhanced amino acid metabolism.

[0133] Table 3 Determination results of amino acid content of different varieties of Ningxia wolfberry (mg / 100g)

[0134] Cannabis leaves Ningqi No.1 Ningqi No.7 Ningqi No.10 Leucine <![CDATA[11.73±0.80 c ]]> <![CDATA[16.25±1.34 b ]]> <![CDATA[21.97±1.81 a ]]> <![CDATA[10.41±3.16 c ]]> Isoleucine <![CDATA[4.19±0.26 b ]]> <![CDATA[3.67±0.37 b ]]> <![CDATA[9.08±0.86 a ]]> <![CDATA[3.12±0.63 b ]]> Hydroxyproline <![CDATA[0.41±0.09 a ]]> <![CDATA[0.07±0.05 bc ]]> <![CDATA[0.30±0.10 ab ]]> <![CDATA[0.02±0.01 c ]]> Phenylalanine <![CDATA[5.96±0.50 b ]]> <![CDATA[4.96±0.48 b ]]> <![CDATA[8.30±0.61 a ]]> <![CDATA[6.38±2.01 ab ]]> Tryptophan <![CDATA[2.67±0.22 b ]]> <![CDATA[4.65±0.32 a ]]> <![CDATA[4.34±0.41 a ]]> <![CDATA[2.55±0.64 b ]]> GABA 6.38±0.16c <![CDATA[8.98±0.52 b ]]> <![CDATA[11.41±0.85 a ]]> <![CDATA[5.23±0.97 c ]]> Methionine <![CDATA[1.42±0.11 ab ]]> <![CDATA[1.16±0.11 b ]]> <![CDATA[1.62±0.10 a ]]> <![CDATA[1.11±0.33 b ]]> Proline <![CDATA[234.84±10.41 ab ]]> <![CDATA[241.07±11.52 a ]]> <![CDATA[215.58±3.84 c ]]> <![CDATA[222.61±7.89 bc ]]> Valine <![CDATA[8.18±0.46 c ]]> <![CDATA[12.75±0.72 b ]]> <![CDATA[28.14±2.47 a ]]> <![CDATA[9.28±1.87 c ]]> Tyrosine <![CDATA[5.18±0.36 b ]]> <![CDATA[5.46±0.61 b ]]> <![CDATA[7.97±0.85 a ]]> <![CDATA[5.47±1.50 b ]]> Alanine <![CDATA[106.07±3.82 c ]]> <![CDATA[157.00±8.96 b ]]> <![CDATA[307.10±23.12 a ]]> <![CDATA[134.33±22.63 bc ]]> Threonine <![CDATA[47.54±3.61 b ]]> <![CDATA[40.07±4.39 b ]]> <![CDATA[65.19±5.18 a ]]> <![CDATA[50.72±14.87 ab ]]> Glutamate <![CDATA[45.15±1.94 b ]]> <![CDATA[40.19±2.37 b ]]> <![CDATA[228.93±21.37 a ]]> <![CDATA[36.31±7.96 b ]]> Serine <![CDATA[30.19±3.32 bc ]]> <![CDATA[41.62±1.85 b ]]> <![CDATA[103.54±10.39 a ]]> <![CDATA[27.24±6.19 c ]]> Asparagine <![CDATA[134.84±5.51 b ]]> <![CDATA[117.64±6.85 b ]]> <![CDATA[382.16±35.56 a ]]> <![CDATA[96.94±16.81 b ]]> Citrulline <![CDATA[3.67±0.30 c ]]> <![CDATA[6.06±0.43 b ]]> <![CDATA[14.09±1.59 a ]]> <![CDATA[3.59±0.77 c ]]> Arginine <![CDATA[48.86±2.28 b ]]> <![CDATA[50.67±4.49 b ]]> <![CDATA[188.77±23.66 a ]]> <![CDATA[45.30±10.49 b ]]> Histidine <![CDATA[8.53±0.75 c ]]> <![CDATA[12.86±1.36 b ]]> <![CDATA[21.42±3.53 a ]]> <![CDATA[6.84±1.83 c ]]> Aspartic acid <![CDATA[51.67±1.37 b ]]> <![CDATA[45.42±1.93 b ]]> <![CDATA[82.46±5.03 a ]]> <![CDATA[43.93±6.13 b ]]> Glycine <![CDATA[4.13±0.42 ab ]]> <![CDATA[3.64±1.19 b ]]> <![CDATA[5.35±0.32 a ]]> <![CDATA[1.84±0.64 c ]]> Glutamine <![CDATA[33.79±1.24 b ]]> <![CDATA[30.26±2.57 b ]]> <![CDATA[193.44±19.87 a ]]> <![CDATA[28.93±5.75 b ]]> Lysine <![CDATA[2.61±0.24 ab ]]> <![CDATA[2.60±0.40 ab ]]> <![CDATA[3.37±0.47 a ]]> <![CDATA[2.03±0.69 b ]]> Ornithine <![CDATA[9.08±0.33 b ]]> <![CDATA[7.58±0.44 bc ]]> <![CDATA[26.01±1.90 a ]]> <![CDATA[6.54±1.08 c ]]> Total amino acids <![CDATA[807.10±18.85 b ]]> <![CDATA[854.60±36.02 b ]]> <![CDATA[1930.54±156.55 a ]]> <![CDATA[750.71±108.97 b ]]>

[0135] The present invention provides a method and method for identifying Ningxia wolfberry varieties based on selective elimination analysis. There are many methods and ways to implement the technical solution. The above is only a preferred embodiment of the present invention. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principle of the present invention. These improvements and modifications should also be regarded as the protection scope of the present invention. All components not specified in this embodiment can be implemented by existing technologies.

Claims

1. A method for identifying Ningxia wolfberry varieties based on selective elimination analysis, characterized in that: The leaves of Ningxia wolfberry were collected and their DNA samples were extracted. The DNA samples were resequenced to obtain valid sequences. Based on nucleotide polymorphism, population differentiation index and selection elimination analysis were carried out. The KEGG pathway enrichment characteristics were used as identification indicators to distinguish Ningxia wolfberry varieties pairwise.

2. The method according to claim 1, characterized in that The Ningxia wolfberry varieties are any two of hemp leaf, Ningqi No. 1, Ningqi No. 7 and Ningqi No.

10.

3. The method according to claim 1, characterized in that Before resequencing the DNA sample, the DNA sequence is first fragmented using ultrasound, and the fragmented DNA is then end-repaired, A is added to the 3' end, and the sequencing adapter is connected. The magnetic bead enrichment method is then used to enrich fragments with a length of 340 to 360 bp, and PCR amplification is performed to form a sequencing library.

4. The method according to claim 1, characterized in that The resequencing was performed using Illumnia NovaSeq TM The platform was used for sequencing, with a total sequencing length of 300 bp.

5. The method according to claim 1, characterized in that The effective sequence is obtained by removing the adapter sequence in the reads, removing the bases containing non-AGCT at the 5' end, trimming the ends of the reads with a sequencing quality value less than Q20, removing the reads containing N at a ratio of 10%, discarding the adapter and the small fragments with a length less than 25bp after quality trimming.

6. The method according to claim 1, characterized in that The selection and elimination analysis specifically involves dividing the genes into 10Kb non-overlapping sliding windows, then grouping the Ningxia wolfberry varieties in pairs, calculating the Fst values ​​between groups and the π values ​​within each group, selecting the top 5% of the regions as the selected regions, and taking the selected regions as the significant regions. Based on the significant regions, KO annotation is performed, and according to the KO annotation information, the enrichment levels of each functional level of KEGG in different Ningxia wolfberry varieties are statistically analyzed.

7. The method according to claim 6, characterized in that The significant region includes a significant selection clearance site, and the significant selection clearance site includes a selected gene; when KO annotation is performed based on the significant region, the enrichment degree of each functional level of KEGG in different Ningxia wolfberry varieties is statistically analyzed according to the KO annotation information, and the significant functional enrichment information of the selected gene is obtained.

8. The method according to claim 6, characterized in that (1) When Ningxia wolfberry is hemp leaf and Ningxia wolfberry No. 1, When the terpenoid synthesis and polyketide metabolism pathways are the dominant enrichment pathways, the Ningxia wolfberry is hemp leaf; when the carbohydrate metabolism pathway is the dominant enrichment pathway, the Ningxia wolfberry is Ningqi No. 1; or, (2) When Ningxia wolfberry is hemp leaf and Ningqi No. 7, When the amino acid metabolic pathway is the dominant enrichment pathway, the Ningxia wolfberry is hemp leaf; when the auxiliary factor and vitamin metabolic pathways are the dominant enrichment pathways, the Ningxia wolfberry is Ningqi No. 7; or, (3) When Ningxia wolfberry is hemp leaf and Ningqi No. 10, When the amino acid metabolism pathway is the dominant enrichment pathway, the Ningxia wolfberry is hemp leaf; when the terpenoid and polyketide metabolism is the dominant enrichment pathway, the Ningxia wolfberry is Ningqi No. 10; or, (4) When Ningxia wolfberry is Ningqi No. 1 and Ningqi No. 7, When the amino acid metabolism pathway and the environmental information processing pathway are the dominant enrichment pathways, the Ningxia wolfberry is Ningqi No. 1; when the photosynthesis antenna protein pathway is the dominant enrichment pathway, the Ningxia wolfberry is Ningqi No. 7; or, (5) When Ningxia wolfberry is Ningqi No. 1 and Ningqi No. 10, When the amino acid metabolic pathway is the dominant enrichment pathway, the Ningxia wolfberry is Ningqi No. 1; when the zeatin biosynthesis pathway and the monoterpene biosynthesis pathway are the dominant enrichment pathways, the Ningxia wolfberry is Ningqi No. 10; or, (6) When Ningxia wolfberry is Ningqi No. 7 and Ningqi No. 10, When the energy metabolism pathway, the amino acid metabolism pathway, and the carbohydrate metabolism pathway are the dominant enrichment pathways, the Ningxia wolfberry is Ningqi No. 7; when the terpenoid and polyketide metabolism pathway and the fatty acid metabolism pathway are the dominant enrichment pathways, the Ningxia wolfberry is Ningqi No.

10.

9. A high-throughput detection system for identifying Ningxia wolfberry varieties based on selective elimination analysis, characterized in that: The high-throughput detection system includes a processor and a memory; wherein the memory is used to store instructions, and when the processor executes the stored instructions, the high-throughput detection system implements the steps of the method described in any one of claims 1 to 8.

10. A kit for identifying Ningxia wolfberry varieties, characterized in that: The kit comprises a DNA sample extraction reagent from Ningxia wolfberry leaves, a DNA sample resequencing reagent, and a DNA sample resequencing data analysis software.

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