A method for distinguishing Taihang chicken and Bashang long-tail chicken

Abstract

The present invention discloses a method for distinguishing Taihang chicken and Bashang long-tail chicken, which distinguishes whether an individual is Taihang chicken or Bashang long-tail chicken by 28 SNP sites. The method can quickly and accurately distinguish the two chicken breeds by only 28 SNP sites, and the method is simple and easy to promote and apply.

Description

Technical Field

[0001] The invention relates to the technical field of biological identification, and in particular to a method for identifying Taihang chicken and Bashang long-tail chicken according to SNP sites. Background Art

[0002] Taihang Chicken and Bashang Longwei Chicken are national-level local excellent chicken breeds that have passed the review. Taihang Chicken is distributed in the Taihang Mountain area of ​​Hebei Province. It is a dual-purpose chicken breed for eggs and meat. It has a delicate appearance, small body, thin neck, long tail feathers, and the feathers are mainly twisted color; Bashang Longwei Chicken is mainly distributed in Chengde in the north of Hebei Province and Bashang area of ​​Zhangjiakou. It is a dual-purpose chicken breed for eggs and meat. Its appearance is more like an egg-laying chicken, with a wide neck, long body, V-shaped or U-shaped back line. The tail feathers of roosters can be more than 60 cm long and the feathers are mostly red. The tail feathers of hens are upturned and the main tail feathers are about 20 to 25 cm long, and the feathers are mostly twisted color. As local chicken breeds, Taihang Chicken and Bashang Longwei Chicken both have strong survival and disease resistance, tolerance to roughage, and excellent egg and meat quality. Although there are certain differences in appearance between Taihang Chicken and Bashang Longwei Chicken, relying solely on phenotype to distinguish between the two is still highly subjective and has low accuracy, which is not conducive to the conservation and breeding of Taihang Chicken and Bashang Longwei Chicken.

[0003] Whole genome resequencing technology can reveal a large amount of genetic variation information. Single nucleotide polymorphism (SNP) has become an important molecular marker in genomic research due to its large number, wide distribution and strong genetic stability, and has great application potential in the field of germplasm resource identification. A large number of SNP marker combinations obtained based on whole genome resequencing can effectively identify different varieties, but the large number is not conducive to widespread promotion and implementation. Therefore, it is urgent to develop a method in scientific research and practice to effectively identify the Taihang chicken and Bashang long-tailed chicken varieties through a small number of SNP marker combinations, which can be applied to the distinction and identification of the two varieties, and provide a basis for the protection of genetic resources and innovative utilization. Summary of the invention

[0004] The purpose of the present invention is to provide a method for distinguishing Taihang chicken and Bashang long-tail chicken. The method can quickly and accurately distinguish the two chicken breeds only through the genotype data of 28 SNP sites. The method is simple and easy to promote and apply.

[0005] To achieve the above object, the present invention adopts the following technical solutions:

[0006] A method for distinguishing Taihang chicken and Bashang long-tail chicken, distinguishing whether an individual belongs to Taihang chicken or Bashang long-tail chicken according to the following 28 SNP loci:

[0007] SNP1: A or G at position chr1:83424842;

[0008] SNP2: T or G at position chr1:84642349;

[0009] SNP3: G or A at position chr1:124613919;

[0010] SNP4: G or A at position chr1:188821891;

[0011] SNP5: C or T at position chr2:21199573;

[0012] SNP6: T or C at position chr2:64783482;

[0013] SNP7: T or C at position chr3:52482379;

[0014] SNP8: A or C at position chr3:107385968;

[0015] SNP9: A or G at position chr4:83205244;

[0016] SNP10: A or G at position chr4:89928184;

[0017] SNP11: A or G at position chr4:90119859;

[0018] SNP12: A or C at position chr5:48014977;

[0019] SNP13: A or G at position chr6:3512624;

[0020] SNP14: A or G at position chr6:23346870;

[0021] SNP15: A or G at position chr8:4957820;

[0022] SNP16: C or G at position chr8:22102533;

[0023] SNP17: C or T at position chr9:3411829;

[0024] SNP18: C or T at position chr11:8491921;

[0025] SNP19: A or G at position chr11:8532637;

[0026] SNP20: C or T at position chr11:8851889;

[0027] SNP21: T or C at position chr24:671698;

[0028] SNP22: C or T at position chr24:5374821;

[0029] SNP23: A or G at position chr25:3692518;

[0030] SNP24: G or T at position chr26:3849905;

[0031] SNP25: C or T at position chr26:4170859;

[0032] SNP26: C or A at position chr27:5676121;

[0033] SNP27: G or A at position chr28:2536492;

[0034] SNP28: G or A at position chr33:5235050;

[0035] The position of the SNP site was determined based on the chicken Gallus_gallus.GRCg6a.reference genome sequence.

[0036] Preferably, the method for identifying Taihang chicken and Bashang long-tail chicken comprises the following steps:

[0037] Step 1: Extract genomic DNA from the individual to be tested;

[0038] Step 2: Obtaining the genotypes of the 28 SNP sites in the genomic DNA;

[0039] Step 3: Use the genotype to perform principal component analysis, evolutionary tree analysis or genome relationship matrix analysis, and determine whether the individual to be tested belongs to Taihang chicken or Bashang long-tail chicken according to the analysis results.

[0040] The present invention has the following beneficial effects: (1) Taihang chicken and Bashang long-tail chicken can be accurately identified by only using the genotype data of 28 SNP sites, and the method is simple and easy to operate, and is convenient for popularization; (2) A molecular marker combination for identifying Taihang chicken and Bashang long-tail chicken is established using 28 SNP sites, thereby enabling a deeper understanding and analysis of the breed specificity of Taihang chicken and Bashang long-tail chicken, which is conducive to the in-depth development of Taihang chicken and Bashang long-tail chicken seed conservation and breeding work. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] Figure 1 is a flow chart of a method in an embodiment of the present invention;

[0042] Figure 2Matthews correlation coefficient scatter plots of six models in the embodiments of the present invention;

[0043] Figure 3 It is a graph showing the variation of recall rate, precision rate and AUC with input SNP data in the embodiment of the present invention;

[0044] Figure 4 The result diagram of principal component analysis of new chicken samples (47 chickens) based on 28 SNP sites in the embodiment of the present invention is shown as follows: PC1: principal component 1; PC2: principal component 2;

[0045] Figure 5 This is a result diagram of a phylogenetic tree analysis of new chicken samples (47 chickens) based on 28 SNP sites in an embodiment of the present invention;

[0046] Figure 6 This is the result of phylogenetic tree analysis of 79 chickens based on 28 SNP sites in the example of the present invention. DETAILED DESCRIPTION

[0047] The present invention is further described below through specific implementation modes:

[0048] Example 1 Screening of 28 SNP sites (screening process reference Figure 1 )

[0049] The experimental materials include 70 samples, of which 35 Taihang chickens and 35 Bashang long-tailed chickens are from conservation populations. First, 70 chicken whole blood samples were obtained by venous blood sampling, and then genomic DNA was extracted and sent to Shijiazhuang Boridi Biotechnology Co., Ltd. for sequencing using the BGI-2000 / MGI-T7 sequencing platform after passing the quality control. After the sequencing data was filtered by fastp software, it was aligned to the chicken reference genome (GRCg6a) using BWA software, and variant detection and quality control were performed using GATK and Plink software. The quality control standards were: excluding SNP detection rate <99%, minimum allele frequency <0.05, and excluding SNP sites on sex chromosomes, and finally generating a vcf file containing 70 samples.

[0050] Plink was used to filter the vcf file by LD (parameter: --indep-pairwise 5001000.2), and 533820 loci were retained after filtering. VCFtools was used to calculate the genetic differentiation index between Taihang chicken and Bashang long-tailed chicken at 533820 loci, and the loci with the top 0.1% genetic differentiation index were extracted; the missing loci in the individuals were deleted, and 363 SNPs remained. The data set containing 70 individuals and 363 SNPs was converted into digital code, and the genotypes of wild homozygous were recorded as 0, heterozygous as 1, and mutant homozygous as 2 for machine learning. Six machine learning classification algorithms, including Random Forest, Logistic Regression, K-nearest neighbor algorithm (KNN), ensemble learning XGBoost, decision tree, and support vector machine (SVM), were used to construct training models, and grid search (Grid Search CV) and cross validation (CV=5) were used to determine the best hyperparameter combination under each model.

[0051] The optimal hyperparameters for each model of the present invention are as follows:

[0052] Logistic regression: C: 0.001;

[0053] RandomForest: max_depth: None, n_estimators: 100;

[0054] Decision Tree: max_depth: None;

[0055] K nearest neighbor algorithm: n_neighbors: 3;

[0056] Ensemble learning XGBoost: learning_rate: 0.1, max_depth: 3, n_estimators: 100;

[0057] Support vector machine: C: 1, gamma: 0.001.

[0058] The classification model was built based on Python 3.12.2, and the performance of six models was evaluated using confusion matrix, ROC curve and Matthews Correlation Coefficient (MCC). Figure 2It can be seen that the classification effect of logistic regression, random forest, K nearest neighbor algorithm, ensemble learning XGBoost and support vector machine model is good. The random forest model is used to evaluate the importance of features and show the changes of the three indicators of test set recall, accuracy and area under the ROC curve (AUC) with the number of input features. Figure 3 It can be seen that when the number of input SNPs is 28, the three indicators no longer change, and the following 28 SNPs are finally selected as the characteristic loci combination for identifying the Taihang chicken and Bashang long-tailed chicken varieties:

[0059] SNP1: A or G at position chr1:83424842;

[0060] SNP2: T or G at position chr1:84642349;

[0061] SNP3: G or A at position chr1:124613919;

[0062] SNP4: G or A at position chr1:188821891;

[0063] SNP5: C or T at position chr2:21199573;

[0064] SNP6: T or C at position chr2:64783482;

[0065] SNP7: T or C at position chr3:52482379;

[0066] SNP8: A or C at position chr3:107385968;

[0067] SNP9: A or G at position chr4:83205244;

[0068] SNP10: A or G at position chr4:89928184;

[0069] SNP11: A or G at position chr4:90119859;

[0070] SNP12: A or C at position chr5:48014977;

[0071] SNP13: A or G at position chr6:3512624;

[0072] SNP14: A or G at position chr6:23346870;

[0073] SNP15: A or G at position chr8:4957820;

[0074] SNP16: C or G at position chr8:22102533;

[0075] SNP17: C or T at position chr9:3411829;

[0076] SNP18: C or T at position chr11:8491921;

[0077] SNP19: A or G at position chr11:8532637;

[0078] SNP20: C or T at position chr11:8851889;

[0079] SNP21: T or C at position chr24:671698;

[0080] SNP22: C or T at position chr24:5374821;

[0081] SNP23: A or G at position chr25:3692518;

[0082] SNP24: G or T at position chr26:3849905;

[0083] SNP25: C or T at position chr26:4170859;

[0084] SNP26: C or A at position chr27:5676121;

[0085] SNP27: G or A at position chr28:2536492;

[0086] SNP28: G or A at position chr33:5235050;

[0087] The position of the SNP site was determined based on the chicken Gallus_gallus.GRCg6a.reference genome sequence.

[0088] The gene frequencies of the 28 SNPs in Taihang chicken and Bashang long-tail chicken are shown in Table 1. Taking SNP site 1:83424842 as an example, the G allele frequency in Bashang long-tail chicken is 0.9429, and the G allele frequency in Taihang chicken is 0.6429. Each SNP characteristic site is different in Taihang chicken and Bashang long-tail chicken, so Taihang chicken and Bashang long-tail chicken can be distinguished by the combination of the 28 characteristic sites.

[0089] Table 1 Distribution of 28 SNP characteristic loci in Taihang chicken and Bashang long-tail chicken

[0090]

[0091] Example 2 Verification of the validity of 28 SNP sites

[0092] 26 Taihang chickens and 21 Bashang long-tailed chickens were obtained again, and the genomic DNA of each chicken was extracted and then sequenced. The genotype information of the 28 SNP sites of each chicken was determined according to the sequencing results, and then principal component analysis, evolutionary tree analysis or genome relationship matrix analysis was performed. The genotype information of the 28 SNP sites is the genotype composed of the bases of the 28 SNP sites and their corresponding alleles.

[0093] Principal component analysis uses the pca function in Plink software to calculate the principal components of the SNP data set and uses the ggplot2 package in R language to visualize and analyze the clustering relationship between individuals in different varieties.

[0094] The phylogenetic tree analysis was performed by converting the vcf files of the genotypes into .nwk files based on the neighbor-joining method using PHYLIP software, and then visualizing them through the iTOL online website to analyze the phylogenetic relationships among different varieties.

[0095] The genomic relationship matrix (GRM) analysis was used. Specifically, the mean kinship (Mean_GRM) and standard deviation (SD_GRM) of each breed in the reference set were first calculated, and then the average kinship between the individual to be tested and each breed in the reference set was calculated. Finally, the individual to be tested was assigned to the breed with the highest average kinship. This process was mainly implemented using R's dplyr package, caret package, matrixStats package, and genefilter package.

[0096] The PCA and phylogenetic tree results based on 28 SNP loci are as follows Figure 4 and Figure 5 As shown in the figure, Taihang chicken and Bashang long-tail chicken were accurately distinguished. Mean_GRM and SD_GRM were used to assign Taihang chicken individuals and Bashang long-tail chicken individuals to their respective breeds with an accuracy rate of 100%.

[0097] Example 3 Application of Identification of Individuals to be Tested

[0098] For the individual to be tested, its genomic DNA is first obtained, and then the genotype of the above 28 SNP sites is determined, and then an evolutionary tree analysis is performed together with the genotype of the above 28 SNP sites of the known Taihang chicken and Bashang long-tail chicken. The breed affiliation of the individual to be tested is judged based on the clustering results of the individual to be tested with the known Taihang chicken or Bashang long-tail chicken.

[0099] A total of 32 chickens of unknown breeds were randomly selected and numbered TEST1-32. After extracting genomic DNA, the genotype information of the 32 individuals at the above 28 loci was determined, and the genotype information of the 47 individuals in Example 2 was combined to perform phylogenetic tree analysis. The results showed that the 32 individuals were accurately assigned to the corresponding breeds ( Figure 6 ), this result is consistent with the sequence of numbers (the sampling personnel know that individual numbers 1-16 are Taihang chickens, and individual numbers 17-32 are Bashang long-tail chickens).

[0100] The above embodiments are merely illustrative of the concept and implementation of the present invention, and are not intended to limit the concept and implementation of the present invention. Under the concept of the present invention, technical solutions that have not been substantially changed are still within the scope of protection.

Claims

1. A method for distinguishing Taihang chicken and Bashang long-tail chicken, distinguishing whether an individual belongs to Taihang chicken or Bashang long-tail chicken according to a SNP locus group, wherein the SNP locus group consists of the following 28 SNP loci: SNP1: A or G at position chr1:83424842; SNP2: T or G at position chr1:84642349; SNP3: G or A at position chr1:124613919; SNP4: G or A at position chr1:188821891; SNP5: C or T at position chr2:21199573; SNP6: T or C at position chr2:64783482; SNP7: T or C at position chr3:52482379; SNP8: A or C at position chr3:107385968; SNP9: A or G at position chr4:83205244; SNP10: A or G at position chr4:89928184; SNP11: A or G at position chr4:90119859; SNP12: A or C at position chr5:48014977; SNP13: A or G at position chr6:3512624; SNP14: A or G at position chr6:23346870; SNP15: A or G at position chr8:4957820; SNP16: C or G at position chr8:22102533; SNP17: C or T at position chr9:3411829; SNP18: C or T at position chr11:8491921; SNP19: A or G at position chr11:8532637; SNP20: C or T at position chr11:8851889; SNP21: T or C at position chr24:671698; SNP22: C or T at position chr24:5374821; SNP23: A or G at position chr25:3692518; SNP24: G or T at position chr26:3849905; SNP25: C or T at position chr26:4170859; SNP26: C or A at position chr27:5676121; SNP27: G or A at position chr28:2536492; SNP28: G or A at position chr33:5235050; The positions of the SNP sites are determined based on the reference genome sequence of chicken Gallus_gallus.GRCg6a.; the allele frequencies of the 28 SNP sites in Taihang chicken and Bashang long-tail chicken are shown in the following table: 。 2. The method for distinguishing Taihang chicken and Bashang long-tail chicken as claimed in claim 1, characterized in that The steps include: Step 1: Extract genomic DNA from the individual to be tested; Step 2: Obtaining the genotypes of the 28 SNP sites in the genomic DNA; Step 3: Use the genotype to perform principal component analysis, evolutionary tree analysis or genome relationship matrix analysis, and determine whether the individual to be tested belongs to Taihang chicken or Bashang long-tail chicken according to the analysis results.

3. The method for distinguishing Taihang chicken and Bashang long-tail chicken as claimed in claim 2, characterized in that When performing the principal component analysis, the principal components of the genotypes of the 28 SNP sites were calculated using the --pca in the Plink software, and visualized using the ggplot2 package in the R language to analyze the clustering relationship of individuals among varieties.

4. The method for distinguishing Taihang chicken and Bashang long-tail chicken as claimed in claim 2, characterized in that When performing the phylogenetic tree analysis, the vcf files of the genotypes of the 28 SNP sites were converted into .nwk files using PHYLIP software based on the neighbor-joining method, and then visualized through the iTOL online website to analyze the phylogenetic relationships among different varieties.

5. The method for distinguishing Taihang chicken and Bashang long-tail chicken as claimed in claim 2, characterized in that When performing the genome relationship matrix analysis, the average kinship and standard deviation of each variety in the reference set are first calculated, then the average kinship between the individual to be tested and each variety in the reference set is calculated, and finally the individual to be tested is assigned to the variety with the highest average kinship.

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