SNP (Single Nucleotide Polymorphism) primer combination for identifying variety of Jingyuan chicken and application of SNP primer combination

Abstract

The invention provides an SNP (Single Nucleotide Polymorphism) primer combination for identifying a Jingyuan chicken variety and application of the SNP primer combination, and belongs to the technical field of biology. Whether an individual to be detected belongs to the Jingyuan chicken or not is jointly judged by detecting the provided genotypes of the seven SNP loci of the Jingyuan chicken. The method is easy and convenient to operate and high in accuracy, the Jingyuan chicken variety can be accurately identified, and counterfeit and shoddy products of local Jingyuan chicken varieties on the market are effectively attacked.

Description

Technical Field

[0001] The invention belongs to the field of biotechnology, and in particular relates to a SNP primer combination for identifying a Jingyuan chicken variety and an application thereof. Background Art

[0002] Jingyuan chicken is a local chicken breed that can be used for both meat and eggs. It is mainly distributed in Jingning County, Gansu Province and Guyuan City, Ningxia Hui Autonomous Region. It is an excellent breed that can withstand the high cold and arid climate of the Loess Plateau. The phenotypic characteristics of Jingyuan chicken, such as feather color, skin color, and meat quality, have obvious local characteristics. The beak is mostly gray, the iris is mainly orange-red, the shank is gray and sturdy, and the physique is medium. The feather color of adult roosters is mainly red and red-black, while the feather color of adult hens is more complex, including yellow, black, white and colorful, among which yellow and hemp are the most common. There are many fake breeds of Jingyuan chicken and other breeds on the market. These breeds are similar in shape and appearance to Jingyuan chicken, which is difficult for consumers to distinguish, which harms the interests of the majority of breeders and affects the conservation and breeding of the original Jingyuan chicken. At present, the method of identifying the authenticity of Jingyuan chicken in the market mainly relies on appearance observation, which is highly subjective. Especially when identifying the hybrid offspring of Jingyuan chicken and other breeds of chicken, due to their similar appearance, the identification error rate is high. There is a need for an identification method that can accurately identify the breed of Jingyuan chicken. Summary of the invention

[0003] In view of this, the object of the present invention is to provide a SNP primer combination and application thereof for identifying the Jingyuan chicken variety.

[0004] In order to achieve the above-mentioned object of the invention, the present invention provides the following technical solutions:

[0005] The present invention provides a SNP primer combination for identifying a Jingyuan chicken variety, wherein the primer combination comprises primers for identifying any 5 to 7 sites among the following JY1 to JY7:

[0006] The JY1 locus is located on chromosome NC_006089.5 at chr2:88999342, and the bases at this locus are T / G;

[0007] The JY2 locus is located on chromosome NC_006089.5 at chr2:137016590, and the bases at this locus are C / T;

[0008] The JY3 locus is located on chromosome NC_006091.5 at chr4:22037922, and the bases at this locus are T / C;

[0009] The JY4 locus is located on chromosome NC_006095.5 at chr8:13527512, and the bases at this locus are C / A;

[0010] The JY5 locus is located on chromosome NC_006107.5 at chr20:9365087, and the bases at this locus are C / G;

[0011] The JY6 locus is located on chromosome NC_006111.5 at chr24:150425, and the bases at this locus are A / C;

[0012] The JY7 locus is located on chromosome NC_006114.5 at chr27:6092287, and the base of the locus is A / C.

[0013] Preferably, the sites identified by the primer combination include: JY1+JY2+JY3+JY4+JY5, JY1+JY2+JY3+JY4+JY6, JY1+JY2+JY3+JY5+JY6, JY1+JY2+JY3+JY5+JY7, JY1+JY2+JY3+JY6+JY7, JY1+JY2+JY4+JY5+JY6, JY1+JY2+JY4+JY5+JY7, JY1+JY2+JY4+JY6+JY7, JY1+JY2+JY5+JY6+JY7, JY1+JY3+J Y4+JY5+JY6, JY1+JY3+JY4+JY5+JY7, JY1+JY3+JY4+JY6+JY7, JY1+JY3+JY5+JY6+JY7 , JY1+JY4+JY5+JY6+JY7, JY2+JY3+JY4+JY6+JY7, JY2+JY4+JY5+JY6+JY7, JY3+JY4+ JY5+JY6+JY7, JY1+JY2+JY3+JY4+JY5+JY6, JY1+JY2+JY3+JY4+JY5+JY7, JY1+JY2+J Y3+JY4+JY6+JY7, JY1+JY2+JY3+JY5+JY6+JY7, JY1+JY2+JY4+JY5+JY6+JY7, JY1+JY 3+JY4+JY5+JY6+JY7, JY2+JY3+JY4+JY5+JY6+JY7 or JY1+JY2+JY3+JY4+JY5+JY6+JY7.

[0014] Preferably, the sequence of each SNP primer is:

[0015] The primer sequences for identifying the JY1 site are shown in SEQ ID NO.1-SEQ ID NO.3;

[0016] The primer sequences for identifying the JY2 site are shown in SEQ ID NO.4-SEQ ID NO.6;

[0017] The primer sequences for identifying the JY3 site are shown in SEQ ID NO.7-SEQ ID NO.9;

[0018] The primer sequences for identifying the JY4 site are shown in SEQ ID NO.10-SEQ ID NO.12;

[0019] The primer sequences for identifying the JY5 site are shown in SEQ ID NO.13-SEQ ID NO.15;

[0020] The primer sequences for identifying the JY6 site are shown in SEQ ID NO.16-SEQ ID NO.18;

[0021] The primer sequences for identifying the JY7 site are shown in SEQ ID NO.19-SEQ ID NO.21.

[0022] The present invention provides application of the SNP primer combination in identification of Jingyuan chicken varieties.

[0023] Preferably, the identification method comprises the following steps:

[0024] (1) Extracting the chicken genomic DNA to be tested;

[0025] (2) using the chicken genomic DNA to be tested as a template, and using the primers in the primer combination to perform amplification respectively to obtain an amplified product;

[0026] (3) Sequencing the amplified products and determining the genotypes at different loci;

[0027] (4) Determine whether the chicken to be tested belongs to the Jingyuan chicken breed based on the genotype results;

[0028] The genotypes of the JY1 to JY7 loci of the Jingyuan chicken are TG / GG, CC / CT / TT, TT / TC / CC, CC / CA / AA, CC / CG / GG, AA / AC / CC, AC / CC, respectively;

[0029] If the genotype corresponding to the selected SNP combination in the amplified product is consistent with that of the Jingyuan Chicken, it is determined that the chicken individual to be tested belongs to the Jingyuan Chicken; if not consistent, it is determined that the chicken individual to be tested does not belong to the Jingyuan Chicken.

[0030] Preferably, the genomic DNA of the chicken to be tested in step (1) is derived from wing vein blood.

[0031] Compared with the prior art, the present invention has the following beneficial effects:

[0032] The invention provides a SNP primer combination for Jingyuan chicken variety identification. When the SNP site primer combination of the invention is used for Jingyuan chicken variety identification, the probability of determining that the chicken to be tested is Jingyuan chicken by any one SNP site genotype reaches more than 86.57%; the probability of determining that the chicken to be tested is Jingyuan chicken by any two SNP site combined genotypes reaches more than 83.58%; the probability of determining that the chicken to be tested is Jingyuan chicken by any three SNP site combined genotypes reaches more than 83.58%; the probability of determining that the chicken to be tested is Jingyuan chicken by any four SNP site combined genotypes reaches more than 91.79%; the probability of determining that the chicken to be tested is Jingyuan chicken by any five SNP site combined genotypes reaches more than 94.03%; the probability of determining that the chicken to be tested is Jingyuan chicken by any six SNP site combined genotypes reaches more than 96.27%; the probability of determining that the chicken to be tested is Jingyuan chicken by the combined genotypes of all seven SNP sites is 98.51%. The prediction results of the combination of seven sites are analyzed by ROC curve, and it is found that the accuracy rate of Jingyuan chicken variety identification is 0.9938. By selecting any combination of 5 SNP sites and determining the genotype of the Jingyuan chicken, the detection success rate can reach more than 94%. This method is easy to operate and has high accuracy, and can effectively combat counterfeit Jingyuan chicken products on the market. BRIEF DESCRIPTION OF THE DRAWINGS

[0033] Figure 1 A graph was built for the SVM algorithm, where A is the use of GBDT to screen out the top 20 species-specific loci in the Jingyuan Chicken genome, and B is the use of 8 machine learning algorithms to analyze the ability of 20 loci to identify Jingyuan Chicken and obtain the best algorithm - SVM;

[0034] Figure 2 To obtain the TOP7 Jingyuan chicken breed identification loci through SVM algorithm screening;

[0035] Figure 3 This is a diagram for evaluating the accuracy of the SVN model in identifying the Jingyuan chicken breed using the ROC curve. DETAILED DESCRIPTION

[0036] The present invention provides a SNP primer combination for identifying a Jingyuan chicken variety, wherein the primer combination comprises primers for identifying any 5 to 7 sites among the following JY1 to JY7:

[0037] The JY1 locus is located on chromosome NC_006089.5 at chr2:88999342, and the bases at this locus are T / G;

[0038] The JY2 locus is located on chromosome NC_006089.5 at chr2:137016590, and the bases at this locus are C / T;

[0039] The JY3 locus is located on chromosome NC_006091.5 at chr4:22037922, and the bases at this locus are T / C;

[0040] The JY4 locus is located on chromosome NC_006095.5 at chr8:13527512, and the bases at this locus are C / A;

[0041] The JY5 locus is located on chromosome NC_006107.5 at chr20:9365087, and the bases at this locus are C / G;

[0042] The JY6 locus is located on chromosome NC_006111.5 at chr24:150425, and the bases at this locus are A / C;

[0043] The JY7 locus is located on chromosome NC_006114.5 at chr27:6092287, and the base of the locus is A / C.

[0044] In the present invention, the primer combination includes primers for identifying any 5 to 7 sites among the following JY1 to JY7, preferably JY1+JY2+JY3+JY4+JY5, JY1+JY2+JY3+JY4+JY6, JY1+JY2+JY3+JY5+JY6, JY1+JY2+JY3+JY5+JY7, JY1+JY2+JY3+JY6+JY7, JY1+JY2+JY4+JY 5+JY6, JY1+JY2+JY4+JY5+JY7, JY1+JY2+JY4+JY6+JY7, JY1+JY2+JY5+JY6+JY7, JY1+JY3+JY4+ JY5+JY6, JY1+JY3+JY4+JY5+JY7, JY1+JY3+JY4+JY6+JY7, JY1+JY3+JY5+JY6+JY7, JY1+JY4+JY 5+JY6+JY7, JY2+JY3+JY4+JY6+JY7, JY2+JY4+JY5+JY6+JY7, JY3+JY4+JY5+JY6+JY7, JY1+JY2+ JY3+JY4+JY5+JY6, JY1+JY2+JY3+JY4+JY5+JY7, JY1+JY2+JY3+JY4+JY6+JY7, JY1+JY2+JY3+JY 5+JY6+JY7, JY1+JY2+JY4+JY5+JY6+JY7, JY1+JY3+JY4+JY5+JY6+JY7, JY2+JY3+JY4+JY5+JY6+JY7 or JY1+JY2+JY3+JY4+JY5+JY6+JY7, further preferably JY1+JY2+JY4+JY6+JY7 or JY1+JY2+JY5+JY6+JY7.

[0045] In the present invention, the primer sequences of each SNP site are:

[0046] The primer sequences for identifying the JY1 site are shown in SEQ ID NO.1-SEQ ID NO.3:

[0047] SEQ ID NO.1: GAAGGTGACCAAGTTCATGCTTTGAATGTTCCAGCTAATCTCACTGA;

[0048] SEQ ID NO.2: GAAGGTCGGAGTCAACGGATTGAATGTTCCAGCTAATCTCACTG;

[0049] SEQ ID NO. 3: AAGGTTATTTATCTTTTTACAGAGAGTGAGG.

[0050] The primer sequences for identifying the JY2 site are shown in SEQ ID NO.4-SEQ ID NO.6:

[0051] SEQ ID NO.4: GAAGGTGACCAAGTTCATGCTAAGTAATTTCTTAACTGAGCCTAGCC;

[0052] SEQ ID NO.5: GAAGGTCGGAGTCAACGGATTTAAGTAATTTCTTAACTGAGCCTAGCT;

[0053] SEQ ID NO. 6: GTGACCTTGCATTGGATTTCTGCTTC.

[0054] The primer sequences for identifying the JY3 site are shown in SEQ ID NO.7-SEQ ID NO.9:

[0055] SEQ ID NO.7: GAAGGTGACCAAGTTCATGCTATAGTTGTTCCACTTCGAAGGTCTTT;

[0056] SEQ ID NO.8: GAAGGTCGGAGTCAACGGATTGTTGTTCCACTTCGAAGGTCTTC;

[0057] SEQ ID NO.9: GAGACACTCTAACAAAAGGAACAACAAG.

[0058] The primer sequences for identifying the JY4 site are shown in SEQ ID NO.10-SEQ ID NO.12:

[0059] SEQ ID NO.10: GAAGGTGACCAAGTTCATGCTCAGTCTCTTCTAGCAGCTAAGAC;

[0060] SEQ ID NO.11: GAAGGTCGGAGTCAACGGATTCCAGTCTCTTCTAGCAGCTAAGAA;

[0061] SEQ ID NO. 12: GCAATGAATCTTTCTTGCTGCTGGAAG.

[0062] The primer sequences for identifying the JY5 site are shown in SEQ ID NO.13-SEQ ID NO.15:

[0063] SEQ ID NO.13: GAAGGTGACCAAGTTCATGCTCAGAGACAGACTTCAGCTCTGC;

[0064] SEQ ID NO.14: GAAGGTCGGAGTCAACGGATTCAGAGACAGACTTCAGCTCTGG;

[0065] SEQ ID NO. 15: TACTGCAGGTGAGTTGTCAGTTAG.

[0066] The primer sequences for identifying the JY6 site are shown in SEQ ID NO.16-SEQ ID NO.18:

[0067] SEQ ID NO.16: GAAGGTGACCAAGTTCATGCTCATCAGAAACAGGATCAGCCATCAA;

[0068] SEQ ID NO.17: GAAGGTCGGAGTCAACGGATTTCAGAAACAGGATCAGCCATCAC;

[0069] SEQ ID NO. 18: CTCCCTGCTGTCGGAACAGTTAC.

[0070] The primer sequences for identifying the JY7 site are shown in SEQ ID NO.19-SEQ ID NO.21:

[0071] SEQ ID NO.19: GAAGGTGACCAAGTTCATGCTTGTTGTAACCACCAAATTCACTGTGT;

[0072] SEQ ID NO.20: GAAGGTCGGAGTCAACGGATTGTTGTAACCACCAAATTCACTGTGG;

[0073] SEQ ID NO. 21: GACAACGTCCTTACCTTCAGGAATG.

[0074] The three primer sequences of each SNP site are: forward primer, forward primer and reverse primer in order, and the italic part of the forward primer is the probe.

[0075] The present invention provides an application of the SNP primer combination in the identification of the Jingyuan chicken variety, which can accurately identify the Jingyuan chicken.

[0076] In the present invention, the identification method comprises the following steps:

[0077] (1) Extracting the chicken genomic DNA to be tested;

[0078] (2) using the chicken genomic DNA to be tested as a template, and using the primers in the primer combination to perform amplification respectively to obtain an amplified product;

[0079] (3) Sequencing the amplified products and determining the genotypes at different loci;

[0080] (4) Determine whether the chicken to be tested belongs to the Jingyuan chicken breed based on the genotype results;

[0081] The genotypes of the JY1 to JY7 loci of the Jingyuan chicken are TG / GG, CC / CT / TT, TT / TC / CC, CC / CA / AA, CC / CG / GG, AA / AC / CC, AC / CC, respectively;

[0082] If the genotype corresponding to the selected SNP combination in the amplified product is consistent with that of the Jingyuan Chicken, it is determined that the chicken individual to be tested belongs to the Jingyuan Chicken; if not consistent, it is determined that the chicken individual to be tested does not belong to the Jingyuan Chicken.

[0083] In the present invention, the genomic DNA of the chicken to be tested in step (1) is preferably derived from wing vein blood; the amplification method in step (2) preferably uses KASP amplification, and the amplification conditions are: pre-denaturation at 94°C, 15min, cycle number 1, denaturation at 94°C for 20sec, cycle number 10, annealing / extension at 61-55°C, 60sec, cycle number 10, denaturation at 94°C, 20sec, cycle number 26, annealing / extension at 55°C, 60sec, cycle number 26.

[0084] In the present invention, the chicken KASP amplification product to be tested is fluorescently labeled with a probe, and the genotype is determined and compared with the genotype corresponding to the selected SNP combination. If the genotypes corresponding to the selected SNP combination all conform to the genotypes corresponding to the Jingyuan Gallus gallus, the probability that the individual belongs to the Jingyuan Gallus gallus is determined according to the SVM machine learning algorithm (analyzed in the language environment of python3.0). The specific steps of the SVM machine learning algorithm are:

[0085] library(e1071)

[0086] library(caret)

[0087] library(dplyr)

[0088] rm(list=ls())

[0089] #The target variable isJY, indicating whether it is a Jingyuan chicken: 0 means no, 1 means yes

[0090] snp_data<-read.csv('SNP.txt',row.names=1,sep='\t',check.names=F)

[0091] #Convert SNP sites and target variables to factor types

[0092] snp_cols<-grep("SNP",names(snp_data),value=TRUE)#Select the column whose name contains "JY"

[0093] snp_data[,snp_cols]<-lapply(snp_data[,snp_cols],as.factor)

[0094] snp_data$isJY<-as.factor(snp_data$isJY)

[0095] # Split the data into training and test sets

[0096] set.seed(123) #Set the random seed to ensure repeatability

[0097] trainIndex<-createDataPartition(snp_data$isJY,p=.8,list=FALSE)

[0098] trainData<-snp_data[trainIndex,]

[0099] testData<-snp_data[-trainIndex,]

[0100] #Function: Train SVM model and calculate accuracy

[0101] train_and_evaluate<-function(trainData,testData,features){

[0102] #Train SVM model

[0103] formula<-as.formula(paste("isJY~",paste(features,collapse="+")))

[0104] svm_model<-svm(formula,data=trainData,kernel='radial')

[0105] # Make predictions

[0106] predictions<-predict(svm_model,newdata=testData)

[0107] #Calculate accuracy

[0108] accuracy<-mean(predictions==testData$isJY)

[0109] return(accuracy)

[0110] }

[0111] # Initialize a data frame to store the results

[0112] results<-data.frame(

[0113] num_features=integer(),

[0114] features=character(),

[0115] accuracy = numeric(),

[0116] stringsAsFactors=FALSE )

[0118] #Loop through different numbers of feature combinations, if there are 7 in total then the ratio is 1:7

[0119] for(num_features in 1:7){

[0120] feature_combinations<-combn(snp_cols,num_features,simplify=FALSE)

[0121] for(combo in feature_combinations){

[0122] features<-paste(combo,collapse="+")

[0123] accuracy<-train_and_evaluate(trainData,testData,combo)

[0124] results<-rbind(results,data.frame(

[0125] num_features=num_features,

[0126] features=features,

[0127] accuracy=accuracy,

[0128] stringsAsFactors=FALSE ))

[0130] }}

[0131] # View the results

[0132] print(results)

[0133] write.csv(results,'results.csv',row.names=F)

[0134] Experimental Materials:

[0135] The poultry germplasm resources genetic material bank of the laboratory of the local chicken germplasm resources protection and utilization team of Henan Agricultural University preserves Jingyuan chicken (JY), Arbor Acres broiler (AA), Gushi chicken x Anka broiler F2 (F2), Gushi chicken (GS), Hy-Line brown laying hen (HL), Xichuan black-bone chicken (XC), and Hubbard broiler (HBD).

[0136] The technical solutions provided by the present invention are described in detail below in conjunction with the embodiments, but they should not be construed as limiting the protection scope of the present invention.

[0137] Experimental Example 1 Identification of Gene Loci Screening and Primer Design for Jingyuan Chicken

[0138] The genetic differentiation index was analyzed by genome resequencing data of 60 Jingyuan chickens, resequencing data of 3536 chickens published in the database, and 600K chip sequencing data. For specific breed and sequencing information, see "Analysis of Genetic Structure of Local Chicken Populations in Henan Province and Development and Utilization of Molecular Identification System of Chicken Genetic Resources" (Zhi Yihao, Henan Agricultural University, June 1, 2023). The TOP20 loci of the genetic differentiation index of the Jingyuan chicken population were used to establish the GradientBoosting Decision Tree Machine (GBDT) model to extract important features, and then eight machine learning classification methods such as multiple linear regression (MLR), support vector machine (SVM), K-nearest neighbors (KNN), Naive Bayes (NB), Decision Trees (DT), random forest (RF), Back Propagation Neural Network (BPNN), and GBDT were used to build the training model, and GridSearchCV was used to find the best hyperparameter combination. The classification model was built in python 3.6. The breed-specific SNP loci obtained in the best training model were extracted for verification. As the number of SNPs increases, the accuracy of identifying the Jingyuan chicken breed also increases. The accuracy of SVM model identification reaches a peak when 7 SNPs are present ( Figure 1 ). The SVM model specifically identified seven molecular markers unique to the Jingyuan chicken: chr2:88999342, chr2:137016590, chr4:22037922, chr8:13527512, chr20:9365087, chr24:150425 and chr27:6092287 ( Figure 2 ), the information of 7 SNP sites is shown in Table 1 below.

[0139] Table 1 Information of 7 SNP loci

[0140] Serial number chromosome Location Reference genome loci Mutation site JY1 NC_006089.5 chr2:88999342 T G JY2 NC_006089.5 chr2:137016590 C T JY3 NC_006091.5 chr4:22037922 T C JY4 NC_006095.5 chr8:13527512 C A JY5 NC_006107.5 chr20:9365087 C G JY6 NC_006111.5 chr24:150425 A C JY7 NC_006114.5 chr27:6092287 A C

[0141] The genotypes of the SNP loci in Jingyuan chicken and other breeds are as shown in Table 2 (in the SNP column, 0 is wild homozygous, 1 is mutant heterozygous, and 2 is mutant homozygous; in the JY column, 0 is no and 1 is yes):

[0142] Table 2 Genotypes of SNP loci in Jingyuan chicken and other breeds

[0143]

[0144]

[0145]

[0146]

[0147]

[0148]

[0149]

[0150]

[0151]

[0152]

[0153]

[0154]

[0155]

[0156] Note: The letters are the abbreviations of the breeds, and the numbers are the sample numbers of the breeds. The specific breed abbreviations and names are (AA-broiler, CS-Changshun green-shell laying hen, DX-Dongxiang black-feathered green-shell laying hen, F2-F2 generation of hybrid of Ziyuanchang Anka broiler and Gushi chicken, GS-Gushi chicken, HBD-Hubbard broiler, HL-Hai-Line brown laying hen, JY-Jingyuan chicken, KB-Kobao broiler, RM-Roman laying hen, XC-Xichuan black-bone chicken.

[0157] According to the physical location of the 7 SNP sites, based on the red junglefowl reference genome sequence (Galgal6), the 7 SNP site DNA sequences were obtained using the NCBI website https: / / www.ncbi.nlm.nih.gov / , and then primers were designed according to the KASP detection rules. The sequences of the SNP primers are shown in Table 3 below:

[0158] Table 3 Sequences of primers for each SNP

[0159]

[0160]

[0161] The three primers for each SNP site are a forward primer, a forward primer and a reverse primer, respectively, and the italic part of the forward primer is a probe.

[0162] The SVM model was used to calculate the typing results to obtain the probability of identifying the individual as Jingyuan Chicken after different numbers and combinations of 7 SNP sites. The specific steps of the SVM machine learning algorithm to determine the probability of the individual belonging to Jingyuan Chicken are as follows:

[0163] library(e1071)

[0164] library(caret)

[0165] library(dplyr)

[0166] rm(list=ls())

[0167] #The target variable isJY, indicating whether it is a Jingyuan chicken: 0 means no, 1 means yes

[0168] snp_data<-read.csv('SNP.txt',row.names=1,sep='\t',check.names=F)

[0169] #Convert SNP sites and target variables to factor types

[0170] snp_cols<-grep("SNP",names(snp_data),value=TRUE)#Select the column whose name contains "JY"

[0171] snp_data[,snp_cols]<-lapply(snp_data[,snp_cols],as.factor)

[0172] snp_data$isJY<-as.factor(snp_data$isJY)

[0173] # Split the data into training and test sets

[0174] set.seed(123) #Set the random seed to ensure repeatability

[0175] trainIndex<-createDataPartition(snp_data$isJY,p=.8,list=FALSE)

[0176] trainData<-snp_data[trainIndex,]

[0177] testData<-snp_data[-trainIndex,]

[0178] #Function: Train SVM model and calculate accuracy

[0179] train_and_evaluate<-function(trainData,testData,features){

[0180] #Train SVM model

[0181] formula<-as.formula(paste("isJY~",paste(features,collapse="+")))

[0182] svm_model<-svm(formula,data=trainData,kernel='radial')

[0183] # Make predictions

[0184] predictions<-predict(svm_model,newdata=testData)

[0185] #Calculate accuracy

[0186] accuracy<-mean(predictions==testData$isJY)

[0187] return(accuracy)

[0188] }

[0189] # Initialize a data frame to store the results

[0190] results<-data.frame(

[0191] num_features=integer(),

[0192] features=character(),

[0193] accuracy = numeric(),

[0194] stringsAsFactors=FALSE )

[0196] #Loop through different numbers of feature combinations, if there are 7 in total then the ratio is 1:7

[0197] for(num_features in 1:7){

[0198] feature_combinations<-combn(snp_cols,num_features,simplify=FALSE)

[0199] for(combo in feature_combinations){

[0200] features<-paste(combo,collapse="+")

[0201] accuracy<-train_and_evaluate(trainData,testData,combo)

[0202] results<-rbind(results,data.frame(

[0203] num_features=num_features,

[0204] features=features,

[0205] accuracy=accuracy,

[0206] stringsAsFactors=FALSE ))

[0208] }}

[0209] # View the results

[0210] print(results)

[0211] write.csv(results,'results.csv',row.names=F)

[0212] The calculation results are shown in Table 4 below:

[0213] Table 4 The probability of identifying as Jingyuan chicken after different numbers and combinations of 7 SNP loci

[0214]

[0215]

[0216]

[0217]

[0218]

[0219] It can be seen that the probability of determining the combined genotype of any five SNP loci as Jingyuan chicken is more than 94.03%.

[0220] All samples in Table 2, including multiple breeds, are divided into a training set (80%) and a test set (20%) through sample.split. The training set is used for model training and parameter optimization, and the test set is used to verify the performance of the model. The SVM model is built on the training set, and the parameters are tuned to obtain the best model configuration. The trained model is used to make predictions on the test set, and the confusion matrix and ROC curve are generated, and the AUC value is calculated. The prediction results of this combination of 7 loci are analyzed through ROC curve analysis and AUC values. It is found that the accuracy of Jingyuan chicken breed identification is 0.9938. For details, see Figure 3 .

[0221] Example 1

[0222] A total of 25 Jingyuan chickens, 25 Arbor Acres broilers, 25 F2 generations of Gushi chickens x Anka broilers, 25 Gushi chickens, 25 Hy-Line brown laying hens, 25 Xichuan black-bone chickens, and 25 Hubbard broilers preserved in the poultry germplasm resources genetic material bank of the local chicken germplasm resources protection and utilization team laboratory of Henan Agricultural University were randomly selected, blood was collected from the wing vein, genomic DNA was extracted by the phenol-chloroform method, and primers for a total of 5 SNP sites, namely JY1, JY2, JY4, JY6, and JY7, were selected for KASP typing.

[0223] According to the typing results, all 25 Jingyuan Chicken individuals were identified as Jingyuan Chicken, and the remaining chicken breeds were not Jingyuan Chicken.

[0224] Example 2

[0225] Other conditions are the same as those in Example 1, except that primers corresponding to the six SNP sites of JY1, JY2, JY3, JY5, JY6, and JY7 are used for KASP amplification. According to the typing results, the probability of the combined genotype of the six sites being Jingyuan Gallus gallus is not less than 98.5%, indicating that the probability of the six sites being 98.5% can identify all 25 individuals as Jingyuan Gallus gallus. If the probability obtained by the algorithm is less than 98.5%, the individual is judged as non-Jingyuan Gallus gallus.

[0226] Example 3

[0227] Other conditions are the same as those in Example 1, except that primers of 7 SNP sites corresponding to JY1 to JY7 are used for KASP amplification. According to the typing results, the probability of the combined genotype of the 7 sites being Jingyuan Gallus gallus is not less than 98.5%, indicating that the probability of the 7 sites being 98.5% can identify all 25 individuals as Jingyuan Gallus gallus. If the probability obtained by the algorithm is less than 98.5%, the individual is judged as non-Jingyuan Gallus gallus.

[0228] 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 scope of protection of the present invention.

Claims

1. A SNP primer combination for identifying the variety of Jingyuan chicken, characterized in that: The primer combination includes primers for identifying any 5 to 7 sites among the following JY1 to JY7: The JY1 locus is located on chromosome NC_006089.5 at chr2:88999342, and the bases at this locus are T / G; The JY2 locus is located on chromosome NC_006089.5 at chr2:137016590, and the bases at this locus are C / T; The JY3 locus is located on chromosome NC_006091.5 at chr4:22037922, and the bases at this locus are T / C; The JY4 locus is located on chromosome NC_006095.5 at chr8:13527512, and the bases at this locus are C / A; The JY5 locus is located on chromosome NC_006107.5 at chr20:9365087, and the bases at this locus are C / G; The JY6 locus is located on chromosome NC_006111.5 at chr24:150425, and the bases at this locus are A / C; The JY7 locus is located on chromosome NC_006114.5 at chr27:6092287, and the base of the locus is A / C.

2. The SNP primer combination according to claim 1, characterized in that: The sites identified by the primer combination include: JY1+JY2+JY3+JY4+JY5, JY1+JY2+JY3+JY4+JY6, JY1+JY2+JY3+JY5+JY6, JY1+JY2+JY3+JY5+JY7, JY1+JY2+JY3+JY6+JY7, JY1+JY2+JY4+JY5+JY6, JY1 +JY2+JY4+JY5+JY7、JY1+JY2+JY4+JY6+JY7、JY1+JY2+JY5+JY6+JY7、JY1+JY3+JY4+ JY5+JY6, JY1+JY3+JY4+JY5+JY7, JY1+JY3+JY4+JY6+JY7, JY1+JY3+JY5+JY6+JY7, J Y1+JY4+JY5+JY6+JY7, JY2+JY3+JY4+JY6+JY7, JY2+JY4+JY5+JY6+JY7, JY3+JY4+J Y5+JY6+JY7, JY1+JY2+JY3+JY4+JY5+JY6, JY1+JY2+JY3+JY4+JY5+JY7, JY1+JY2+JY 3+JY4+JY6+JY7, JY1+JY2+JY3+JY5+JY6+JY7, JY1+JY2+JY4+JY5+JY6+JY7, JY1+JY3 +JY4+JY5+JY6+JY7, JY2+JY3+JY4+JY5+JY6+JY7 or JY1+JY2+JY3+JY4+JY5+JY6+JY7.

3. A SNP primer combination for identifying the Jingyuan chicken variety according to claim 1 or 2, characterized in that: The sequences of the SNP primers are: The primer sequences for identifying the JY1 site are shown in SEQ ID NO.1-SEQ ID NO.3; The primer sequences for identifying the JY2 site are shown in SEQ ID NO.4-SEQ ID NO.6; The primer sequences for identifying the JY3 site are shown in SEQ ID NO.7-SEQ ID NO.9; The primer sequences for identifying the JY4 site are shown in SEQ ID NO.10-SEQ ID NO.12; The primer sequences for identifying the JY5 site are shown in SEQ ID NO.13-SEQ ID NO.15; The primer sequences for identifying the JY6 site are shown in SEQ ID NO.16-SEQ ID NO.18; The primer sequences for identifying the JY7 site are shown in SEQ ID NO.19-SEQ ID NO.

21.

4. Use of the SNP primer combination according to any one of claims 1 to 3 in the identification of Shizuoka chicken varieties.

5. The use according to claim 4, characterized in that: The identification method comprises the following steps: (1) Extracting the chicken genomic DNA to be tested; (2) using the chicken genomic DNA to be tested as a template, and using the primers in the primer combination of claim 3 to perform amplification respectively to obtain an amplified product; (3) Sequencing the amplified products and determining the genotypes at different loci; (4) Determine whether the chicken to be tested belongs to the Jingyuan chicken breed based on the genotype results; The genotypes of the JY1 to JY7 loci of the Jingyuan chicken are TG / GG, CC / CT / TT, TT / TC / CC, CC / CA / AA, CC / CG / GG, AA / AC / CC, AC / CC, respectively; If the genotype corresponding to the selected SNP combination in the amplified product is consistent with that of the Jingyuan Chicken, then the chicken individual to be tested is determined to belong to the Jingyuan Chicken; If there is any inconsistency, it is determined that the chicken individual to be tested does not belong to the Jingyuan chicken.

6. The use according to claim 5, characterized in that: The genomic DNA of the chicken to be tested in step (1) is derived from wing vein blood.

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