A SNP chip for identifying guangdong xiaorhua pig breed, preparation method and application thereof

Abstract

The application belongs to the field of modern agricultural technology, and particularly relates to a SNP chip for Guangdong small-ear flower pig breed identification, a preparation method and application thereof. The SNP chip for Guangdong small-ear flower pig breed identification has very high accuracy, and the internal cross-validation accuracy reaches 100%, and the external independent verification accuracy reaches 98.7%. The SNP chip integrates 1000 SNP sites most representing the Guangdong small-ear flower pig breed, and can largely generalize the population genetic characteristics of the Guangdong small-ear flower pig breed, so that the Guangdong small-ear flower pig can be effectively distinguished from other pig breeds.

Description

Technical Field

[0001] This invention belongs to the field of modern agricultural technology, specifically relating to an SNP chip for identifying the Guangdong Small-eared Pig breed, its preparation method, and its application. Background Technology

[0002] The Guangdong Small-eared Flower Pig is a representative of South China pig breeds, known for its early maturity, easy fattening, thin skin, tender meat, delicious flavor, docile temperament, and tolerance to roughage. Through years of breeding and industrial development by local Guangdong enterprises, the meat quality of the Guangdong Small-eared Flower Pig has been improved, its hybrid vigor is significant, and the breed's population size has been protected. After years of branding, local enterprises have continuously improved reproductive traits, developing a new high-fertility strain of the Guangdong Small-eared Flower Pig, which has been promoted to the national market. Enterprises use the Guangdong Small-eared Flower Pig as the maternal line to produce crossbred commercial pigs, and also use the Guangdong Small-eared Flower Pig, other local pigs, and lean-type Duroc breeds as breeding materials to develop a new "country black pig" breed with high lean meat percentage, high intramuscular fat content, tender muscle fibers, and strong reproductive capacity. The pork sales network covers the entire country, meeting the consumption needs of different regions and levels in my country's pork market.

[0003] With the improvement of living standards, people's demand for high-quality pork, represented by local pigs, is increasing, and their preference for native pigs is becoming more pronounced. However, there is currently a lack of clear industry standards, and the definition of native pork products is not yet clear, resulting in a mixed bag of quality in the market. Some products are of inferior quality, selling ordinary pork under the guise of "native pigs"; while some truly high-quality native pork products are overlooked, making it difficult for consumers to distinguish them when purchasing. The industrialized breeding and utilization of local pigs is also harmed by this counterfeiting, which exacerbates the genetic pollution of local pig breeds, leading to the mixing of purebred pigs, distorting breeding data, further increasing breeding costs, undermining confidence in the protection and utilization of local pigs, allowing foreign pig breeds to continue to dominate the market, and causing a continuous loss of local pig genetic resources.

[0004] In the context of an increasingly complex hybridization environment and an incomplete meat product value evaluation standard, traditional identification methods relying on epigenetic characteristics are no longer sustainable. Establishing a precise and scalable breed identification system at the genomic level has become a crucial pathway for protecting the genetic resources of local pig breeds in my country. SNP chips, with their high throughput, broad coverage, and ease of data integration, have achieved industrial application in pig genetic breeding. However, most commercially available SNP chips integrate specific loci from multiple pig breeds, both domestic and international. In the current reality of widespread genetic information exchange, these broad-spectrum commercial SNP chips lack breed specificity and are difficult to accurately identify local pig breeds. Furthermore, SNP chips can cover a much larger number of SNP loci in a single detection, far exceeding the dozens covered by SSR microsatellite markers. Therefore, breed identification methods based on SSR microsatellite markers, such as sequence alignment and sequence tag statistical methods, are no longer suitable for the application of SNP chips.

[0005] Ensuring the stability of local pig genetic information and breed purity impacts the development of germplasm resource protection and genetic improvement, providing a positive impetus for independent innovation in the breeding industry and ultimately achieving self-reliance and control over the pig breeding industry. Therefore, the development of an SNP chip and its application method for identifying local pig breeds is urgently needed to provide technical support for the accurate identification of Guangdong Small-eared Spotted Pigs and effectively safeguard their market brand. Simultaneously, establishing a local pig breed identification system is the cornerstone for protecting my country's livestock and poultry genetic diversity and maintaining seed industry security, promoting the high-quality development of the local pig industry, and achieving a combination of protection and utilization, with utilization promoting protection. Summary of the Invention

[0006] To address the aforementioned technical problems, this invention provides an SNP chip for identifying the Guangdong Small-eared Pig breed, its preparation method, and its application.

[0007] To achieve the above-mentioned objectives of this invention, the technical solution adopted by this invention is as follows: The first aspect of the present invention provides the application of reagents for detecting SNP molecular marker combinations in the preparation, identification, and screening of products from Guangdong small-eared pigs; In some embodiments of the present invention, the SNP molecular marker combination includes 1000 SNP molecular markers; In some embodiments of the present invention, the SNP molecular marker combinations are shown in Table 1 of the specification.

[0008] In some embodiments of the present invention, the physical location of the SNP site is based on the pig reference genome Sscrofa11.1; the SNP site is represented in the form of "chromosome_physical location: reference genotype / variant genotype".

[0009] A second aspect of the present invention provides a method for identifying SNP molecular marker combinations as described in the first aspect of the present invention, comprising the following steps: 1) SNP marker detection was performed on the whole genome sequencing data of Guangdong Small-eared Spotted Pigs and control breeds to identify and genotype polymorphic variation sites in the populations and obtain the whole genome SNP site set; 2) The whole genome SNP locus set was analyzed and compared to obtain the characteristic SNP locus set of Guangdong Small-eared Pig; 3) The characteristic SNP locus set of Guangdong Small-eared Pig was screened in the independent screening samples to obtain the SNP molecular marker combination for identifying Guangdong Small-eared Pig.

[0010] Specifically, the method for identifying the SNP molecular marker combination includes the following steps: Step 1: Whole genome resequencing was performed on pig samples from 25 breeds, with a sequencing depth of 10~30×. Step 2: Perform SNP marker detection on the resequencing data from Step 1 to identify and genotype polymorphic variant sites in the population and obtain a genome-wide SNP site set; Step 3: Divide the whole genome SNP locus set of 25 pig breeds in Step 2 into Guangdong Small-eared Spotted Pig population and other breed populations according to breed. Compare the allele frequencies of the two populations, screen out SNP loci with significant differences, and then remove redundant loci through linkage disequilibrium analysis to obtain the characteristic SNP locus set of Guangdong Small-eared Spotted Pig. Step 4: Using the characteristic SNP locus set of Guangdong small-eared pigs from Step 3, extract loci from the whole genome SNP locus sets of the two populations respectively, and use stratified sampling to randomly select 30 samples from each of the two populations to construct a random forest model. Step 5: Using the random forest model constructed in Step 4 as the evaluator, the recursive feature elimination algorithm is used to further screen the characteristic SNP loci set of Guangdong Small-eared Pig in Step 3, forming a final set of 1000 SNP loci as identification loci for the Guangdong Small-eared Pig breed.

[0011] Based on the above scheme: the quality control parameters for polymorphic sites mentioned in step 2 are: allele frequency -- maf 0.01, Hardy-Weinberg equilibrium -- hwe 1e-6, site deletion rate -- geno 0.02, and only autosomal SNP sites with bases A / C / G / T are retained (--snps-only just-acgt --autosome); Based on the above scheme: the screening parameters for characteristic SNP sites of Guangdong small-eared pigs in step 3 are: the difference in allele frequency between the two populations is |ΔAF|>0.7, and sites with an indep-pairwise correlation coefficient r2 greater than 0.8 are removed. Based on the above scheme: the random forest model parameters mentioned in step 5 include using stratified sampling, with 30 samples each from the Guangdong Small Ear Flower Pig population and other pig breeds at a 1:1 ratio, and setting up a random forest model with 500 decision trees.

[0012] A third aspect of the present invention provides a product for detecting and screening Guangdong small-eared pigs, the product comprising a primer set and a probe set for detecting the SNP molecular markers described in the first aspect of the present invention.

[0013] In some embodiments of the present invention, the product includes an SNP chip and a reagent kit.

[0014] A fourth aspect of the present invention provides a method for detecting and screening Guangdong small-eared spotted pigs, comprising the following steps: The test sample was tested using the reagent for detecting SNP molecular marker combinations as described in the first aspect of the present invention.

[0015] In some embodiments of the present invention, the reagent includes the product described in the third aspect of the present invention.

[0016] The fifth aspect of this invention provides the application of the product described in the third aspect of this invention in cluster analysis and kinship identification of Guangdong small-eared pigs.

[0017] The sixth aspect of this invention provides the application of the product described in the third aspect of this invention in the identification of genetic diversity in Guangdong small-eared pigs.

[0018] The seventh aspect of the present invention provides the application of the product described in the third aspect of the present invention in the breeding or assisted breeding of Guangdong small-eared spotted pigs.

[0019] In some embodiments of the present invention, the breeding or assisted breeding includes at least one of assisted major gene selection, molecular assisted breeding, whole genome selection breeding, genetic map construction, gene localization, species evolution analysis, and germplasm resource identification.

[0020] The beneficial effects of this invention are: The SNP chip of this invention has extremely high accuracy in identifying the Guangdong Small-eared Spotted Pig breed, with 100% accuracy in internal cross-validation and 98.7% accuracy in external independent validation. This SNP chip integrates 1000 SNP loci that are most representative of the Guangdong Small-eared Spotted Pig breed, which can largely summarize the population genetic characteristics of the Guangdong Small-eared Spotted Pig breed, thus effectively distinguishing the Guangdong Small-eared Spotted Pig from other pig breeds. Attached Figure Description

[0021] The present invention will be further described below with reference to the accompanying drawings and embodiments, wherein: Figure 1 Principal component analysis plots were generated using SNP chips for identifying the Guangdong Small-eared Flower Pig breed.

[0022] Figure 2 Principal component analysis plots based on a genome-wide SNP locus set.

[0023] Figure 3 An phylogenetic tree constructed using SNP chips for identifying the Guangdong Small-eared Pig breed.

[0024] Figure 4 This is a phylogenetic tree constructed based on a set of SNP sites across the entire genome.

[0025] Figure 5 A population stratification map constructed using SNP chips for identifying the Guangdong Small-eared Spotted Pig breed.

[0026] Figure 6 This is a population stratification map constructed based on a set of SNP sites across the entire genome. Detailed Implementation

[0027] The following will describe the concept and technical effects of the present invention clearly and completely with reference to embodiments, so as to fully understand the purpose, features and effects of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Other embodiments obtained by those skilled in the art based on the embodiments of the present invention without creative effort are all within the scope of protection of the present invention.

[0028] Example 1: Preparation of SNP chip for identifying Guangdong Small-eared Spotted Pig breed 1. Collection of genomic data from different pig breeds Ear tissues were collected from 218 samples of 25 Chinese and foreign pig breeds, including Guangdong Small-eared Spotted Pig, Bama Fragrant Pig, Erhualian Pig, Lantang Pig, and Guanzhuang Spotted Pig. DNA samples were extracted and whole-genome libraries were constructed. The sample genome libraries were resequencing at 10~30× to obtain high-depth genomic information. Polymorphic sites of the samples were first detected and genotyped using GATK software, and then PLINK (v1.90) software was used to strictly control the genotype data under the following conditions: (1) sites with minor allele frequencies ≥0.01 were retained (--maf 0.01); (2) sites deviating from Hardy-Weinberg equilibrium were removed (P<1×10). -6 (3) Remove sites with a missing rate > 2% (--geno 0.02); (4) Remove samples with an individual missing rate > 5% (--mind 0.05); (5) Only retain biallelic SNP sites with bases A / C / G / T (--snps-only just-acgt); (6) Only retain autosomal data (--autosome). The more than 7 million high-quality SNP datasets obtained are used as the data source for constructing SNP chips for variety identification, and are called "chip construction datasets".

[0029] Ear tissue samples from 154 individuals representing 20 Chinese and foreign pig breeds, including Guangdong Small-eared Spotted Pig and Duroc, were collected. The SNP dataset was extracted using the same standards and procedures described above and used for external validation of the subsequent model. This dataset is referred to as the "external validation dataset".

[0030] 2. Construction of SNP chips for variety identification 1) Initial screening of variety-specific SNP loci The breed identification SNP dataset was divided into the Guangdong Small-eared Spotted Pig population and other pig breeds. Based on the allele frequency difference between the two populations (|ΔAF|>0.7), breed-specific SNPs were initially screened, specifically loci with allele frequencies in the Guangdong Small-eared Spotted Pig population that were 0.7 or higher than those in other pig breeds, totaling 13,586 SNP loci. The selected SNP locus set for the Guangdong Small-eared Spotted Pig population was then genotyped using Beagle (version 5.4), and all loci with linkage disequilibrium squared correlation coefficients (r²) greater than 0.8 with neighboring loci were removed using PLINK (v1.90) software with the parameter "--indep-pairwise 50 5 0.8". After screening, 3,252 SNP loci were obtained in the Guangdong Small-eared Spotted Pig population.

[0031] 2) Construction of Random Forest Classification Model After genotyping of other pig breeds, the corresponding SNP loci sets were extracted using VCFtools software based on the initial screening SNP loci set of 3252 Guangdong Small-eared Spotted Pigs. The initial screening SNP loci sets of both groups were recoded in the form of 0, 1, and 2, representing homozygous, heterozygous, and homozygous alleles of the reference allele, respectively. The recoded SNP loci sets formed a dose matrix as the independent variable for model construction. The rows of the SNP locus dose matrix recorded individual information, and the columns recorded information about individual SNP loci. Based on the group information of the individuals in the rows, individuals belonging to the Guangdong Small-eared Spotted Pig group were labeled "HZ," and individuals belonging to other pig breed groups were labeled "other." These two types of labels were then combined into a vector, which served as the dependent variable. After merging the SNP locus dose matrices and label vectors of the two groups, the data were divided into training and test sets in an 8:2 ratio for random forest model training. During model training, stratified sampling was used to extract data from each tree, with 30 individuals labeled "HZ" and 30 individuals labeled "other" balanced.

[0032] 3) Secondary screening of variety-specific SNP sites To ensure the informative and concise nature of the SNP chip for identifying the Guangdong Small-eared Spotted Pig breed, a recursive feature elimination (RFE) algorithm was used for further screening based on the initially screened breed-specific SNP loci set. The `rfe` function from the `caret` package in R was used, with the previously constructed random forest as the evaluator, and a 5-fold cross-validation method was employed to evaluate feature subsets of different SNP loci sizes. The RFE algorithm iteratively eliminated redundant loci, scoring the calculation results of each iteration, and selecting the set with the highest cross-validation accuracy as the optimal breed-specific SNP locus set. Finally, 1000 biallelic SNP loci were selected to construct the Guangdong Small-eared Spotted Pig breed identification SNP chip, as detailed in Table 1.

[0033] Table 1. Location information and site variations of SNP chips for identifying the Guangdong Small-eared Spotted Pig breed.

[0034] Example 2: Application of SNP chip in breed identification of Guangdong Small-eared Spotted Pig To comprehensively evaluate the site validity of the Guangdong Small-eared Spotted Pig breed identification SNP chip and the performance and generalization ability of the random forest model, this study used the Guangdong Small-eared Spotted Pig breed identification SNP chip site set screened in Example 1 and the constructed random forest model. Two strategies, internal cross-validation and independent external validation, were employed to evaluate accuracy. Furthermore, to demonstrate the superiority of the Guangdong Small-eared Spotted Pig breed identification SNP chip, a commercially available 50K chip, KPS-PorcineBreeding, was used for comparison.

[0035] 1) Internal cross-validation of SNP chips for variety identification Following the 5-fold cross-validation method, a set of SNP loci for identifying the Guangdong Small-eared Pig breed was extracted from the chip-constructed dataset containing 218 samples in Example 1. The dataset was then divided into five subsets, ensuring that the ratio of the two breed category labels ("HZ" and "other") in each subset was consistent with the overall dataset. In each fold, one subset was used as the test set to evaluate performance, while the remaining four subsets were used as the training set, and a training model was constructed using the same random forest parameters as in Example 1. The prediction results of all test sets in the 5-fold cross-validation were summarized to construct an overall confusion matrix and generate a heatmap, thereby systematically evaluating the stability of this SNP locus set in the identification of the Guangdong Small-eared Pig breed.

[0036] The 218 pig samples from Example 1 were subjected to SNP detection using a 50K commercial chip to obtain 50K commercial chip SNP data. Following the method described above, the 50K chip SNP data was divided into five subsets, and models were constructed and breeds predicted in the same manner to calculate the accuracy of the 50K commercial chip.

[0037] The results of the SNP chip's predictions on the dataset are shown in Table 2. Under the model's prediction evaluation, the SNP chip's five-fold cross-validation results all showed that the predicted labels were consistent with the actual labels, and the average accuracy of the group classification reached 100%. Under the model's prediction evaluation, the 50K commercial chip showed that some individuals of other breeds were identified as Guangdong Small-eared Spotted Pigs in the five-fold cross-validation, and the average accuracy of the group classification was 98.63%. This indicates that the SNP chip for identifying the Guangdong Small-eared Spotted Pig breed has good stability and is superior to the 50K commercial chip.

[0038] 2) Independent external validation of the random forest model The SNP locus set for identifying the Guangdong Small-eared Spotted Pig breed was extracted from the chip-constructed dataset containing 218 samples in Example 1. A training model was constructed using the same random forest parameters as in Example 1. The trained random forest model was then used to predict the breed on the independent external validation SNP locus set containing 154 samples described in Example 1. The predicted breeds were compared with the actual breeds labeled, and the model's classification accuracy on the independent external samples was calculated.

[0039] The results of the SNP chip on the independent external validation dataset are shown in Table 2. Similarly, under the prediction and evaluation of the model, the SNP chip has an accuracy rate of 98.7% in identifying Guangdong Small-eared Pigs. There were no cases where individuals of other breeds were identified as Guangdong Small-eared Pigs. This shows that the SNP chip for identifying Guangdong Small-eared Pigs can accurately identify them with the assistance of the training model.

[0040] Table 2 Accuracy of Variety Identification

[0041] Example 3: Application of SNP chip in population structure analysis for identifying Guangdong Small-eared Spotted Pig breeds To evaluate the effectiveness of this chip in population genetic structure analysis, the similarity of the Guangdong Small-eared Pig breed identification SNP chip constructed in Example 1 with the whole genome resequencing SNP site set in the chip construction dataset containing 218 samples in Example 1 for population genetic structure analysis was compared.

[0042] 1) Principal component analysis To investigate the genetic structure of the sample population and the genetic differentiation among breeds, principal component analysis (PCA) was performed based on the whole-genome SNP locus set and the SNP chip for identifying the Guangdong Small-eared Pig breed. The snpgdsBED2GDS function of the SNPRelate package was used to convert the PLINK format genotype data to GDS format, and the snpgdsPCA function was called to perform PCA calculations, extracting the first two principal components (PC1 and PC2). Finally, a two-dimensional PCA scatter plot was plotted using the ggplot2 package, with different colors and shapes distinguishing breeds, visually displaying the genetic variation within the population and the clustering patterns among breeds.

[0043] Principal component analysis plot based on SNP chip for identifying the Guangdong Small-eared Pig breed is shown below. Figure 1 As shown, the principal component analysis plot based on the whole genome SNP locus set is as follows: Figure 2 As shown, Figure 1 and Figure 2 The Guangdong Small-eared Flower Pig group is identified by an oval circle.

[0044] Principal component analysis results showed that Guangdong Small-eared Spotted Pig individuals clustered independently under SNP chip dimensionality reduction clustering, while individuals of other pig breeds clustered together. This indicates that the Guangdong Small-eared Spotted Pig breed identification SNP chip obtained in Example 1 has breed specificity and can effectively distinguish Guangdong Small-eared Spotted Pig individuals from individuals of other breeds.

[0045] 2) Phylogenetic tree analysis Genetic distances were calculated based on both the whole-genome SNP locus set and the SNP microarray used for breed identification of the Guangdong Small-eared Flower Pig. A Neighbor-Joining (NJ) phylogenetic tree was constructed to analyze the evolutionary relationships between breeds. First, the snpgdsIBS function of the SNPRelate package was used to calculate the allele sharing distance (1-IBS) between all sample pairs, and this distance was converted into a genetic distance matrix. Then, the nj function of the ape package was used to construct a rootless phylogenetic tree based on this distance matrix.

[0046] The phylogenetic tree constructed based on the SNP chip for identifying the Guangdong Small-eared Pig breed is shown below. Figure 3 As shown, the phylogenetic tree constructed based on the whole genome SNP locus set is as follows: Figure 4 As shown in the diagram, each node represents an evolutionary unit, and the two branches under the same node have genetic similarity. Each color represents a population branch of a variety under an evolutionary node.

[0047] Phylogenetic tree analysis results show that the evolutionary tree constructed based on the SNP chip for identifying the Guangdong Small-eared Spotted Pig breed... Figure 3 The classification units are as shown in the actual sample data, and the phylogenetic tree is constructed based on the SNP chip for identifying the Guangdong Small-eared Flower Pig breed. Figure 3 Compared with phylogenetic trees constructed based on whole-genome SNP loci sets Figure 4 It exhibits excellent similarity, and the targeted design of the Guangdong Small-eared Spotted Pig breed identification SNP chip enables the construction of an evolutionary tree based on the Guangdong Small-eared Spotted Pig breed identification SNP chip. Figure 3 This study more significantly classifies the Guangdong Small-eared Spotted Pig breed into the same evolutionary node, clearly distinguishing it from the evolutionary nodes of other breeds. This demonstrates that the population genetic structure analysis capability of the Guangdong Small-eared Spotted Pig breed identification SNP chip obtained in Example 1 is similar to that of the whole genome SNP locus set, and can largely restore the analysis results of the whole genome SNP locus set. This proves the effectiveness of the SNP chip of the present invention not only for breed identification, but also for practical production applications such as pedigree division, breeding pig preservation and utilization.

[0048] 3) Bloodline composition analysis To infer the ancestral composition of the samples and reveal the gene flow history between breeds, model-based Bayesian clustering analysis was performed using Admixture (v1.3.0) software, based on the whole-genome SNP locus set and the SNP chip for identifying the Guangdong Small-eared Pig breed. The number of ancestral populations (K value) was set, and the model fit of each K value was evaluated using 5-fold cross-validation. The optimal K value was determined based on the principle of minimizing the cross-validation error rate.

[0049] Population stratification diagram constructed based on SNP chip for breed identification of Guangdong Small-eared Pig, as shown in the figure. Figure 5 As shown, the population stratification map constructed based on the whole genome SNP locus set is as follows: Figure 6 As shown in the image. The labels below the image are group identifiers for pig breeds, with the Guangdong Small-eared Spotted Pig labeled "HZ". All breeds in the image contain K colors, indicating that, based on the maximum likelihood estimation algorithm, all breeds as a whole can be divided into K ancestral origins. The length of the same color between different breeds represents the probability of a common ancestor.

[0050] The pedigree analysis results showed that the optimal K values ​​for the Guangdong Small-eared Spotted Pig breed identification SNP chip and the whole-genome resequencing SNP locus set were 4 and 8, respectively. The analysis results of the Guangdong Small-eared Spotted Pig breed identification SNP chip were just as accurate as those of the whole-genome resequencing SNP locus set, effectively distinguishing the ancestral composition of the Guangdong Small-eared Spotted Pig from other breeds. This indicates that the analysis results of the Guangdong Small-eared Spotted Pig breed identification SNP chip can largely reproduce the analysis results of the whole-genome resequencing SNP locus set. This proves that the Guangdong Small-eared Spotted Pig breed identification SNP chip obtained in Example 1 can be effectively used to infer the pedigree composition of a population.

[0051] The embodiments of the present invention have been described in detail above with reference to the accompanying drawings. However, the present invention is not limited to the above embodiments, and various changes can be made within the scope of knowledge possessed by those skilled in the art without departing from the spirit of the present invention. Furthermore, the embodiments of the present invention and the features thereof can be combined with each other unless otherwise specified.

Claims

1. Application of reagents for detecting SNP molecular marker combinations in the preparation, identification, and screening of products from Guangdong Small-eared Pigs; The SNP molecular marker combination includes 1000 SNP molecular markers; The SNP molecular marker combinations are shown in Table 1 of the specification.

2. The application according to claim 1, characterized in that: The reagents include a primer set and a probe set.

3. The method for identifying the SNP molecular marker combination in the application of claim 1 or 2, comprising the following steps: 1) SNP marker detection was performed on the whole genome sequencing data of Guangdong Small-eared Spotted Pigs and control breeds to identify and genotype polymorphic variation sites in the populations and obtain the whole genome SNP site set; 2) The whole genome SNP locus set was analyzed and compared to obtain the characteristic SNP locus set of Guangdong Small-eared Pig; 3) The characteristic SNP locus set of Guangdong Small-eared Pig was screened in the independent screening samples to obtain the SNP molecular marker combination for identifying Guangdong Small-eared Pig.

4. A product for detecting and screening Guangdong small-eared spotted pigs, characterized in that: The product includes a primer set and a probe set for detecting the SNP molecular markers described in claim 1 or 2.

5. The product according to claim 4, characterized in that: The products include SNP chips and reagent kits.

6. A method for detecting and screening Guangdong small-eared spotted pigs, comprising the following steps: The test sample was tested using the reagent for detecting SNP molecular marker combinations as described in claim 1.

7. The method according to claim 6, characterized in that: The reagent includes the product described in claim 4 or 5.

8. The application of the product according to claim 4 or 5 in cluster analysis and kinship identification of Guangdong small-eared pigs.

9. The application of the product according to claim 4 or 5 in the identification of genetic diversity in Guangdong small-eared pigs.

10. The application of the product according to claim 4 or 5 in the breeding or assisted breeding of Guangdong small-eared pigs.

Images