A combination of SNP loci associated with intestinal traits of pigs and its application

Abstract

The present invention discloses a SNP site combination related to the intestinal traits of pigs and its application, and relates to the field of molecular marker-assisted breeding. The SNP site combination includes the following SNP sites: rs330459736, rs330675368, rs320284886, rs81258727, rs81421300, rs81458281, rs319160989, rs343474009 and rs329338310. The SNP site combination provided by the present invention is significantly correlated with the intestinal traits of pigs, and can be used to screen pig varieties with excellent intestinal traits, thereby providing a reference basis for the selection and breeding of excellent pig quality.

Description

Technical Field

[0001] The present invention relates to the field of molecular marker-assisted breeding, and in particular to a SNP site combination related to intestinal traits of pigs and an application thereof. Background Art

[0002] Improving pig intestinal health and increasing production efficiency has long been a work of breeding scientists. With the continuous advancement of genome work and the extensive development of genetic markers, molecular selection is gradually becoming a reliable and effective selection method.

[0003] Single nucleotide polymorphism (SNP) markers are third-generation molecular markers, which refer to a polymorphism caused by a single base mutation in the genomic DNA sequence. This mutation includes single-base transversion, conversion, insertion and deletion. SNP has the advantages of large quantity, high frequency and low mutation rate. It is widely used in genome analysis, bioinformatics automated detection, genetic research on simple and complex diseases, livestock breeding markers and global ethnic genetics research. Molecular marker-assisted selection breeding is the selection of target traits at the molecular level. It can be unaffected by the environment and can reduce linkage drag through genetic background selection, thereby accelerating the breeding process and accuracy.

[0004] Genome-wide association studies (GWAS) are an important method for genetic improvement and mechanistic analysis of economic traits in livestock and poultry. The third-generation porcine genome analyzer (GGP), developed in collaboration with leading corporate and academic scientists, is the most widely used global genotyping chip today and is built on the basis of the most widely used porcine chip ever. The GGP Porcine array features more than 51,000 SNPs, selected for optimized chromosome spacing and high minor allele frequency values, and can be used in most commercial breeding lines. This medium-density array provides powerful capabilities and resolution for a wide range of applications in pig breeding and genomics, including studying marker-trait associations, evaluating pure lines, identifying multi-line reference populations, and research applications of genome-wide association studies (GWAS).

[0005] The present invention intends to develop a SNP site combination related to the intestinal traits of pigs, which is applied to pig molecular marker-assisted breeding, in order to accelerate the breeding speed of pig varieties with excellent intestinal traits and provide a reference basis for pig breeding. Summary of the invention

[0006] The purpose of the present invention is to provide a combination of SNP loci associated with intestinal traits of pigs and its application to solve the problems existing in the above-mentioned prior art. The combination of SNP loci provided by the present invention is significantly associated with intestinal traits of pigs and can be used to screen pig breeds with excellent intestinal traits, thereby providing a reference basis for the selection and breeding of excellent pig quality.

[0007] To achieve the above object, the present invention provides the following solutions:

[0008] The present invention provides a combination of SNP sites associated with intestinal traits of pigs, including the following SNP sites: rs330459736, rs330675368, rs320284886, rs81258727, rs81421300, rs81458281, rs319160989, rs343474009 and rs329338310.

[0009] The present invention also provides a primer combination for identifying pig intestinal traits, including primers with nucleotide sequences as shown in SEQ ID NO.1-18.

[0010] The present invention also provides a method for identifying the intestinal tract characteristics of pigs, characterized by comprising the following steps:

[0011] Extracting the genomic DNA of the individual pig to be tested;

[0012] The genotype of each SNP locus in the above SNP locus combination was obtained by PCR amplification and sequencing, and then judged according to the following standards:

[0013] The genotypes of rs330459736 in the pigs to be tested are AA and CC, and their duodenal villus height is greater than that of the AC genotype;

[0014] The pig individuals to be tested whose genotype of rs330675368 is CC have a larger small intestine weight than those of TT and CT genotypes;

[0015] The pig individual to be tested whose genotype of rs320284886 is GG has a longer small intestine than those of AA and AG genotypes;

[0016] The genotype of the rs81258727 in the pig to be tested is CC, and the length of the small intestine is greater than that of the genotypes TT and CT;

[0017] The pig individuals to be tested whose genotype of rs81421300 is AA have a longer small intestine than those with genotypes AG and GG;

[0018] The pig individual to be tested whose genotype of rs81458281 is AA has a longer small intestine than those of AG and GG genotypes;

[0019] The genotype of the rs319160989 pig to be tested is AA, and its duodenum maltase activity is greater than that of the genotypes AG and GG;

[0020] The genotype of rs343474009 in the pig to be tested is GG, and its duodenal aminopeptidase activity is greater than that of the genotype TG;

[0021] The pig individual to be tested whose genotype of rs329338310 is TT has a longer small intestine than those of CC and CT genotypes.

[0022] Furthermore, the above primer combination is used for PCR amplification.

[0023] The present invention also provides a primer pair for identifying pig intestinal traits, comprising a primer pair described in any one of the following (1)-(9):

[0024] (1) a primer pair for identifying the rs330459736 site, comprising a primer having a nucleotide sequence as shown in SEQ ID NO. 1-2;

[0025] (2) a primer pair for identifying the rs320284886 site, comprising a primer having a nucleotide sequence as shown in SEQ ID NO. 3-4;

[0026] (3) a primer pair for identifying the rs81332606 site, comprising primers having nucleotide sequences as shown in SEQ ID NOs. 5-6;

[0027] (4) a primer pair for identifying the rs81258727 site, comprising primers having nucleotide sequences as shown in SEQ ID NOs. 7-8;

[0028] (5) a primer pair for identifying the rs81421300 site, comprising primers having nucleotide sequences as shown in SEQ ID NOs. 9-10;

[0029] (6) a primer pair for identifying the rs81458281 site, comprising primers having nucleotide sequences as shown in SEQ ID NOs. 11-12;

[0030] (7) a primer pair for identifying the rs319160989 site, comprising primers having nucleotide sequences as shown in SEQ ID NOs. 13-14;

[0031] (8) a primer pair for identifying the rs343474009 site, comprising primers having nucleotide sequences as shown in SEQ ID NOs. 15-16;

[0032] (9) A primer pair for identifying the rs329338310 site, comprising primers whose nucleotide sequences are shown in SEQ ID NOs. 17-18.

[0033] Application of the SNP site in identifying pig intestinal traits, when the pig intestinal trait is pig duodenal villus height, the SNP site is rs330459736;

[0034] When the pig intestinal trait is pig small intestine weight, the SNP site is rs330675368;

[0035] When the porcine intestinal trait is the length of the porcine small intestine, the SNP site is rs320284886, rs81258727, rs81421300 or rs81458281;

[0036] When the porcine intestinal trait is porcine duodenum maltase activity, the SNP site is rs319160989.

[0037] When the porcine intestinal trait is porcine duodenal aminopeptidase activity, the SNP site is rs343474009;

[0038] When the pig intestinal trait is the amino acid digestibility of the pig terminal ileum, the SNP site is rs329338310.

[0039] The present invention also provides the use of the above primer combination or primer pair in the preparation of a product for identifying pig intestinal traits.

[0040] Furthermore, the product is a kit.

[0041] The present invention also provides a kit for identifying pig intestinal traits, comprising the above primer combination or primer pair.

[0042] The present invention also provides the use of the above-mentioned SNP site combination, primer combination, primer pair or kit in identifying pig intestinal traits.

[0043] The present invention discloses the following technical effects:

[0044] The present invention performs genome-wide association analysis on some intestinal-related traits of pig populations, preliminarily obtains 13 SNP sites significantly associated with various traits in the whole genome, and further performs association analysis on the SNP sites and traits. The results show that the genotype of the rs330459736 site is significantly associated with VH_Duo (P<0.05); the genotype of the rs330675368 site is significantly associated with Weight_SI (P<0.05); the genotype of the rs320284886 and rs81258727 sites is significantly associated with L ength_SI was extremely significantly associated (P<0.01); the genotypes of rs81421300 and rs81458281 were significantly associated with Length_SI (P<0.05); the genotype of rs319160989 was significantly associated with Maltase_Duo (P<0.05); the genotype of rs343474009 was significantly associated with APS_Duo (P<0.05); the genotype of rs329338310 was significantly associated with Arg_AID (P<0.05). Therefore, the combination of rs330459736, rs330675368, rs320284886, rs81258727, rs81421300, rs81458281, rs319160989, rs343474009 and rs329338310 can be applied to the screening of pig breeds with excellent intestinal traits, thus providing a reference for the breeding of excellent pig quality. BRIEF DESCRIPTION OF THE DRAWINGS

[0045] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0046] Figure 1 is the frequency distribution diagram of the phenotypic value of the height of duodenal villi; A is the frequency distribution diagram of the original phenotype; B is the frequency distribution diagram of the phenotype after normalization;

[0047] Figure 2 is the frequency distribution diagram of the phenotypic value of ileal villus height trait; A is the frequency distribution diagram of the original phenotype; B is the frequency distribution diagram of the phenotype after normalization;

[0048] Figure 3 is the frequency distribution diagram of the phenotypic value of small intestine weight trait; A is the frequency distribution diagram of the original phenotype; B is the frequency distribution diagram of the phenotype after normalization;

[0049] Figure 4is the frequency distribution diagram of the phenotypic value of small intestine length trait; A is the frequency distribution diagram of the original phenotype; B is the frequency distribution diagram of the phenotype after normalization;

[0050] Figure 5 is the frequency distribution diagram of the phenotypic value of duodenum maltase activity; wherein A is the frequency distribution diagram of the original phenotype; B is the frequency distribution diagram of the phenotype after normalization;

[0051] Figure 6 is the frequency distribution diagram of the phenotypic value of duodenal aminopeptidase activity; wherein A is the frequency distribution diagram of the original phenotype; B is the frequency distribution diagram of the phenotype after normalization;

[0052] Figure 7 is the frequency distribution diagram of the phenotypic value of aspartate digestibility at the end of the ileum; A is the frequency distribution diagram of the original phenotype; B is the frequency distribution diagram of the phenotype after normalization;

[0053] Figure 8 is the frequency distribution diagram of the phenotypic value of leucine digestibility at the end of the ileum; A is the frequency distribution diagram of the original phenotype; B is the frequency distribution diagram of the phenotype after normalization;

[0054] Fig. 9 is the frequency distribution diagram of the phenotypic value of histidine digestibility at the end of the ileum; A is the frequency distribution diagram of the original phenotype; B is the frequency distribution diagram of the phenotype after normalization;

[0055] Fig.10 is the frequency distribution diagram of the phenotypic value of arginine digestibility at the end of the ileum; wherein A is the frequency distribution diagram of the original phenotype; B is the frequency distribution diagram of the phenotype after normalization;

[0056] Fig.11 is the frequency distribution diagram of the phenotypic value of proline digestibility at the end of the ileum; A is the frequency distribution diagram of the original phenotype; B is the frequency distribution diagram of the phenotype after normalization;

[0057] Fig.12 is the GWAS analysis result of kinControl+covariate model of duodenal villus height (VH_Duo), where A is Manhattan plot; B is QQ plot;

[0058] Fig.13 The GWAS analysis results of the kinControl+covariate model for ileal villus height (VH_Ile), where A is the Manhattan plot; B is the QQ plot;

[0059] Fig.14These are the GWAS analysis results of the three models of small intestine weight (Weight_SI), GLM, MLM and FarmCPU. AC are the Manhattan plots of the GLM, MLM and FarmCPU models, respectively; DF are the QQ plots of the GLM, MLM and FarmCPU models, respectively;

[0060] Fig.15 These are the GWAS analysis results of the three models of small intestine length (Length_SI), namely, GLM, MLM and FarmCPU. AC are the Manhattan plots of the GLM, MLM and FarmCPU models, respectively; DF are the QQ plots of the GLM, MLM and FarmCPU models, respectively;

[0061] Fig.16 The following are the GWAS analysis results of the three models of duodenal maltase activity (Maltase_Duo): GLM, MLM and FarmCPU. AC are the Manhattan plots of the GLM, MLM and FarmCPU models, respectively; DF are the QQ plots of the GLM, MLM and FarmCPU models, respectively;

[0062] Fig.17 These are the GWAS analysis results of the three models of duodenal aminopeptidase activity (APS_Duo), namely, GLM, MLM and FarmCPU. AC are the Manhattan plots of the GLM, MLM and FarmCPU models, respectively; DF are the QQ plots of the GLM, MLM and FarmCPU models, respectively;

[0063] Fig.18 The GWAS analysis results of the three models of terminal ileum aspartate digestibility (Asp_AID) GLM, MLM and FarmCPU, where AC are the Manhattan plots of GLM, MLM and FarmCPU models, respectively; DF are the QQ plots of GLM, MLM and FarmCPU models, respectively;

[0064] Fig.19 The following are the GWAS analysis results of the three models of terminal ileum leucine digestibility (Leu_AID), namely, GLM, MLM and FarmCPU. AC are the Manhattan plots of GLM, MLM and FarmCPU models, respectively; DF are the QQ plots of GLM, MLM and FarmCPU models, respectively;

[0065] Fig. 20 The following are the GWAS analysis results of the three models of terminal ileum histidine digestibility (His_AID), namely GLM, MLM and FarmCPU. AC are the Manhattan plots of GLM, MLM and FarmCPU models respectively; DF are the QQ plots of GLM, MLM and FarmCPU models respectively;

[0066] Fig.21 These are the GWAS analysis results of the three models of terminal ileum arginine digestibility (Arg_AID), namely GLM, MLM and FarmCPU. AC are the Manhattan plots of the GLM, MLM and FarmCPU models, respectively; DF are the QQ plots of the GLM, MLM and FarmCPU models, respectively. DETAILED DESCRIPTION

[0067] Various exemplary embodiments of the present invention will now be described in detail. This detailed description should not be considered as limiting the present invention, but should be understood as a more detailed description of certain aspects, features, and embodiments of the present invention.

[0068] It should be understood that the terms described in the present invention are only for describing a particular embodiment and are not intended to limit the present invention. In addition, for the numerical range in the present invention, it should be understood that each intermediate value between the upper and lower limits of the scope is also specifically disclosed. The intermediate value in any stated value or stated range, and each smaller range between any other stated value or intermediate value in the described range is also included in the present invention. The upper and lower limits of these smaller ranges can be independently included or excluded in the scope.

[0069] Unless otherwise indicated, all technical and scientific terms used herein have the same meanings as those generally understood by those skilled in the art. Although the present invention describes only preferred methods and materials, any methods and materials similar or equivalent to those described herein may also be used in the implementation or testing of the present invention. All documents mentioned in this specification are incorporated by reference to disclose and describe the methods and / or materials associated with the documents. In the event of a conflict with any incorporated document, the content of this specification shall prevail.

[0070] It will be apparent to those skilled in the art that various modifications and variations may be made to the specific embodiments of the present invention description without departing from the scope or spirit of the present invention. Other embodiments derived from the present invention description will be apparent to those skilled in the art. The present invention description and examples are exemplary only.

[0071] The words “include,” “including,” “have,” “contain,” etc. used in this document are open-ended terms, meaning including but not limited to.

[0072] Example 1

[0073] The present invention uses a GGP Porcine 50K chip to perform genome-wide association analysis on the small intestine weight (Weight_SI), small intestine length (Length_SI), duodenum maltase activity (Maltase_Duo), duodenum aminopeptidase activity (APS_Duo), duodenum villus height (VH_Duo), ileum villus height (VH_Ile), and terminal ileum amino acid digestibility (AID) traits of pigs, systematically mines key sites or regulatory genes related to the intestinal organ index, amino acid digestibility, intestinal morphology and structure, and digestive enzyme activity of pigs, and uses these key sites or genes to perform molecular design breeding, improve feed digestion and utilization efficiency, and cultivate new strains or hybrid combinations with high nutrient digestion and utilization rate.

[0074] 1 Test materials

[0075] 1.1 Experimental animals and experimental design

[0076] Animal experiments were conducted according to the protocol approved by the Animal Care Committee of Hunan Normal University. The experimental animals were kept at

[0077] The pigs used in the present invention are pigs (Duroc×Landrace×Yorkshire), all of which are from Longhua Agriculture and Animal Husbandry. All pigs are raised by professionals, and the entire feeding conditions and feeding methods are consistent. All pigs are in good health. Before the start of the experiment, 3 portions of feed (100 g each) are taken from each group.

[0078] 1.2 Collection and preservation of tissue samples

[0079] 1.2.1 Intestinal fixed samples

[0080] Samples were collected from Guanglian Slaughterhouse and Tangrenshen Slaughterhouse. Intestinal tissue was removed through the assembly line, and the entire small intestine was separated, and its length was measured and weighed. 2 cm of duodenum and ileum were taken and fixed in 4% paraformaldehyde solution. The intestinal segment should be completely immersed in the paraformaldehyde solution. The solution was changed after 24 hours and stored in a wind-proof place at room temperature for intestinal morphological structure detection.

[0081] 1.2.2 Intestinal molecular samples

[0082] Two molecular samples from the duodenum and ileum were taken, wrapped in tin foil and quickly frozen with liquid nitrogen, and stored at -80°C. One sample was used for genotype detection and the other for enzyme activity detection.

[0083] 1.2.3 Ileal chyme

[0084] The ileal chyme was collected and placed in a 50 mL centrifuge tube, placed on dry ice, and stored at -20°C for the detection of hydrolyzed amino acids and energy.

[0085] 1.3 Main reagents, consumables and instruments

[0086] SYBR Premix Ex TaqTM and DNA marker, Takara; 2×TaqPCR MasterMix, Shanghai Shenggong Biotechnology Co., Ltd.; formaldehyde, xylene, paraffin, anhydrous ethanol (analytical grade), hematoxylin, eosin, glacial acetic acid, Nanjing Jiancheng Biotechnology Co., Ltd.

[0087] 2 Test methods and results

[0088] 2.1 Technical route

[0089] This experiment is a GWAS association analysis of some intestinal traits in the pig (Duroc×Landrace×Yorkshire) population. The content mainly includes: determination of phenotypic values ​​of various intestinal traits (Weight_SI, Length_SI, Maltase_Duo, APS_Duo, VH_Duo, VH_Ile, AID), individual genotype determination (intestinal segment collection, genomic DNA extraction, pig SNP50 chip data analysis) and whole genome association analysis.

[0090] 2.2 Phenotypic trait detection

[0091] (1) Pig intestinal phenotypic data

[0092] Table 1 mainly records the descriptive statistics of 11 intestinal traits of pigs. The analysis indicators include sample size, mean, standard deviation, standard error, maximum value, minimum value and coefficient of variation. From the data in Table 1, it can be seen that the difference between the maximum and minimum values ​​is large, and the coefficient of variation is large. Except for the low coefficient of variation of small intestine length (10.00%), the fluctuation range of the coefficient of variation of other traits is between 15.22% and 56.63%. The wide range of phenotypic differences provides a lot of material for the analysis of genetic variation, which shows that these traits can be greatly improved and stabilized through reasonable selection and breeding programs, and such a population is more suitable for studying the nature of genetics.

[0093] Table 1 Descriptive statistical analysis of phenotypic data

[0094]

[0095]

[0096] (2) Normal distribution test and transformation

[0097] The frequency distribution results of the phenotypic values ​​of each trait are shown in Figure 1-Figure 11 .

[0098] 2.3 SNP chip detection and genotyping

[0099] In this study, the phenol-chloroform extraction method was used to extract DNA from pig intestinal tissue samples, and the DNA concentration and OD were detected using Nanodrop ultra-micro spectrophotometer. 260 / 280 Ratio, record the qualified DNA samples in concentration and OD value, and put them in -20℃ refrigerator for standby use. This experiment commissioned Newgene Biotech (Shanghai) Co., Ltd. to use GGP Porcine 50K chip to perform genotyping on DNA samples. The chip has a total of 51,000 SNP sites, integrating the genetic differences of multiple breeds of pigs, including Duroc, Landrace, Large White and Pietrain pigs. Each evaluated breed has an average of 50,000 polymorphic sites, covering the entire genome information of pigs. The biochip system is mainly composed of chips, scanners and analysis software. The whole process goes through DNA sample preparation, denaturation, whole genome amplification, DNA fragmentation, precipitation resuspension, hybridization with chip, extension, chip scanning, and finally software typing output results. The main analysis software is GenomeStudio, which visualizes the chip data and obtains genotype data.

[0100] 600 copies of Neogen GGP_Porcine_HD-China pig gene chip data are provided. First, the present invention converts the genotype data in plink format into vcf format, and then merges the data to finally obtain the genotype files in vcf format of 41430 sites of 600 samples.

[0101] 2.4 Quality Control

[0102] After analyzing the chip data and individual data according to the quality control standards, 41,430 SNPs and 600 individuals were obtained for genome-wide association analysis. These SNPs are distributed on 18 autosomes and X / Y sex chromosomes. The specific distribution and average SNP distance are shown in Table 2.

[0103] Table 2 Distribution and average distance of SNP markers on each chromosome after quality control

[0104]

[0105]

[0106] Note: SNP density represents the average physical distance between two adjacent SNP sites.

[0107] 2.5 Genome-wide association analysis

[0108] The whole genome association analysis was performed on the SNP chip genotype data and phenotypic data of pigs. The present invention uses the R package rMVP to perform whole genome association analysis, which includes three models: general linear model (GLM), mixed linear model (MLM) and FarmCPU. The kinship matrix and principal components are added to the model as covariates for correction to reduce the influence of kinship and population structure. The significant threshold at the whole genome level is 0.05 / number of markers. GWAS analysis was performed on pig phenotypes respectively. Finally, 11 traits were located at significant sites.

[0109] The present invention uses the R package rMVP to perform genome-wide association analysis, which includes three models: general linear model (GLM), mixed linear model (MLM) and FarmCPU. The kinship matrix and principal components are added to the model as covariates for correction to reduce the influence of kinship and population structure. The significant threshold at the genome-wide level is 0.05 / number of markers. Through GWAS analysis, it was detected that chr2: 16695031 is highly correlated with duodenal villi; chr17: 61752127 is highly correlated with ileal villi. There was one SNP site significantly associated with small intestine weight, located on chromosome 10; there were six SNP sites significantly associated with small intestine length, of which the most significant SNP site ALGA0109178 was located on chromosome 6, with a P value of 8.51E-08; there was one site significantly associated with duodenal maltase activity, located on chromosome 13; both GLM and FarmCPU models located one site significantly associated with aminopeptidase activity, which was WU_10.2_1_255084089 and was located on chromosome 1; there was one SNP site that was significantly associated with the digestibility of aspartic acid, leucine, histidine, arginine and proline in the terminal ileum at the whole genome level, which was WU_10.2_3_33019982 and was located on chromosome 3.

[0110] All GWAS analysis results are shown in Table 3, which describes in detail the name of the significant SNP for each trait, the chromosome number and position of the SNP in the genome, and the P value of the association result. Figure 12-21 As shown in the figure, Manhattan plots of 11 traits were drawn using R language. Manhattan plots can more intuitively view the distribution of GWAS analysis-associated SNP sites on chromosomes and the distribution of significant SNP sites associated with each trait, where the horizontal axis is the chromosome number; the vertical axis is the -log10 (P) value of the SNP site; each point represents a SNP site, and the red line is the genome-wide significant level threshold. SNP sites above the red line indicate that they have reached a genome-wide significant level with the target trait.

[0111] Table 3 Statistics of growth-related SNP loci

[0112]

[0113]

[0114] 2.6 Analysis of group stratification results / group stratification test results

[0115] Population stratification refers to the existence of subgroups with different allele frequencies within a population. The main reason for its existence is that there are large differences in genetic backgrounds between different populations. Population stratification is believed to affect the accuracy of GWAS analysis and increase the detection of false positives. QQ Plot can reflect whether more significant loci are generated than expected, and provides a diagnostic standard for judging population stratification. Therefore, the present invention uses the QQ Plot method to evaluate the situation of this population. The specific analysis map is shown in Figure 12-21 . As can be seen from the figure, after correction by the λ expansion factor, compared with the zero expected distribution, the SNPs distribution deviation is reduced, thereby reducing the probability of false positives. Among them, the horizontal axis is the expected -log10(P) value, the vertical axis is the actual detected -log10(P) value, and each point represents a SNP site. The statistical distribution calculated by the association analysis does not deviate from the null hypothesis test, and the significant SNP sites in the association results are all above the expected value. This shows that there is no population stratification phenomenon in the experimental population of the present invention after correction by the association analysis, which proves the reliability of the association analysis results.

[0116] 2.7 GWAS results of significant SNP gene annotation

[0117] The present invention mines candidate gene data for 13 significant sites of association analysis based on the pig reference genome database (version number: Sscrofa10.2) of the Ensembl website (https: / / may2015.archive.ensembl.org / index.html), combines the NCBI website, and selects genes related to traits closest to the significant SNP site from these genes within 1 Mb upstream and downstream of the significant SNP site for functional annotation, see Table 4.

[0118] Table 4 SNP locus information related to each trait

[0119]

[0120]

[0121] 3. Association analysis between SNPs and traits

[0122] Another 200 pigs were selected as research subjects to conduct association analysis between SNPs and traits. Based on the initial screening results, primers were designed and then association analysis was performed between SNPs and trait data. The SNPs that were associated with the traits are shown in Table 6. The primer design results are shown in Table 5.

[0123] Table 5 PCR amplification primer sequence information

[0124]

[0125]

[0126] As shown in Table 6, the genotype of rs330459736 was significantly associated with VH_Duo (P<0.05); the genotype of rs330675368 was significantly associated with Weight_SI (P<0.05); the genotype of rs320284886 and rs81258727 was extremely significantly associated with Length_SI (P<0.01); the genotype of rs81421300 and rs81458281 was significantly associated with Length_SI (P<0.05); the genotype of rs319160989 was significantly associated with Maltase_Duo (P<0.05); the genotype of rs343474009 was significantly associated with APS_Duo (P<0.05); and the genotype of rs329338310 was significantly associated with Arg_AID (P<0.05). Therefore, the combination of rs330459736, rs330675368, rs320284886, rs81258727, rs81421300, rs81458281, rs319160989, rs343474009 and rs329338310 can be applied to the screening of pig breeds with excellent intestinal traits, thus providing a reference for the breeding of excellent pig quality.

[0127] Table 6 Results of association analysis between SNPs and traits

[0128]

[0129] Note: Numbers with different letters on their shoulders indicate significant differences (P<0.05).

[0130] The embodiments described above are only descriptions of the preferred modes of the present invention, and are not intended to limit the scope of the present invention. Without departing from the design spirit of the present invention, various modifications and improvements made to the technical solutions of the present invention by ordinary technicians in this field should all fall within the protection scope determined by the claims of the present invention.

Claims

1. Application of SNP site combination in identifying intestinal traits of pigs, characterized in that: The SNP site combination includes the following SNP sites: rs330459736, rs330675368, rs320284886, rs81258727, rs81421300, rs81458281, rs319160989, rs343474009 and rs329338310; When the porcine intestinal trait is the height of porcine duodenal villi, the SNP locus used is rs330459736; When the porcine intestinal trait is porcine small intestine weight, the SNP site used is rs330675368; When the porcine intestinal trait is the length of the porcine small intestine, the SNP sites used are rs320284886, rs81258727, rs81421300 or rs81458281; When the porcine intestinal trait is porcine duodenum maltase activity, the SNP site used is rs319160989; When the porcine intestinal trait is porcine duodenal aminopeptidase activity, the SNP site used is rs343474009; When the pig intestinal trait is the amino acid digestibility of the pig terminal ileum, the SNP site used is rs329338310.

2. A primer combination for identifying pig intestinal traits, characterized in that: The primers include nucleotide sequences as shown in SEQ ID NO.1-18.

3. A method for identifying the intestinal characteristics of pigs, characterized in that: The steps include: Extracting the genomic DNA of the individual pig to be tested; The genotype of each SNP locus in the SNP locus combination of claim 1 is obtained by PCR amplification and sequencing, and then judged according to the following standards: The genotypes of rs330459736 in the pigs to be tested are AA and CC, and their duodenal villus height is greater than that of the AC genotype; The pig individuals to be tested whose genotype of rs330675368 is CC have a larger small intestine weight than those of TT and CT genotypes; The pig individual to be tested whose genotype of rs320284886 is GG has a longer small intestine than those of AA and AG genotypes; The genotype of the rs81258727 in the pig to be tested is CC, and the length of the small intestine is greater than that of the genotypes TT and CT; The pig individuals to be tested whose genotype of rs81421300 is AA have a longer small intestine than those with genotypes AG and GG; The pig individual to be tested whose genotype of rs81458281 is AA has a longer small intestine than those of AG and GG genotypes; The genotype of the rs319160989 pig to be tested is AA, and its duodenum maltase activity is greater than that of the genotypes AG and GG; The genotype of rs343474009 in the pig to be tested is GG, and its duodenal aminopeptidase activity is greater than that of the genotype TG; The pig individual to be tested whose genotype of rs329338310 is TT has a longer small intestine than those of CC and CT genotypes.

4. The method according to claim 3, characterized in that The primer combination according to claim 2 is used for PCR amplification.

5. Use of the primer combination as claimed in claim 2 in the preparation of a product for identifying pig intestinal traits.

6. The use according to claim 5, characterized in that: The product is a test kit.

7. A kit for identifying the intestinal traits of pigs, characterized in that: Comprising the primer combination described in claim 2.

8. Use of the primer combination according to claim 2 or the kit according to claim 7 in identifying intestinal traits of pigs.

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