SNP (Single Nucleotide Polymorphism) site combination for quickly identifying Chinese merino sheep

Abstract

The invention belongs to the technical field of biological detection, and discloses an SNP (Single Nucleotide Polymorphism) site combination for rapidly identifying Chinese merino sheep. The invention provides the SNP locus combination for rapid identification of the Chinese merino sheep, and the combination consists of 10 SNP loci and has high specificity and relatively high prediction accuracy, so that variety identification of the Chinese merino sheep is realized. By integrating a molecular marker technology and bioinformatics analysis, the identification process is simplified, the identification efficiency and reliability are improved, and a solid foundation is laid for effective protection, scientific management and reasonable utilization of genetic resources of the Chinese merino sheep.

Description

Technical Field

[0001] The invention belongs to the technical field of biological detection and discloses a SNP site combination for rapid identification of Chinese Merino sheep. Background Art

[0002] As one of the important livestock breeds, Chinese Merino sheep are widely praised for their excellent meat quality, high-yield wool and good adaptability. However, with the rapid development of animal husbandry and the diversification of market demand, the requirements for breed purity are increasing. Although traditional breed identification methods, such as morphological observation and production performance evaluation, are effective to a certain extent, they are easily affected by external factors such as environment and feeding management, and are time-consuming and difficult to meet the needs of the rapid development of modern animal husbandry. In recent years, molecular marker technology, especially SNP (single nucleotide polymorphism) markers, have shown great potential in animal breed identification. As the most common type of genetic variation in the genome, SNP has the advantages of wide distribution, high stability and simple detection, and has become an important tool for breed identification and genetic resource assessment. For Chinese Merino sheep, developing a rapid identification system based on SNP loci is of great significance for improving breed purity, protecting genetic diversity and promoting breeding improvement. However, there is currently a lack of SNP identification combinations specifically for Chinese Merino sheep on the market, and existing studies mostly focus on the exploration of a small number of SNP loci, which is difficult to fully reflect the breed characteristics and affect the accuracy and reliability of the identification results. Therefore, the development of an efficient and accurate SNP identification combination for Chinese Merino sheep is of urgent need and great significance for promoting the protection and rational utilization of the genetic resources of this breed. Summary of the invention

[0003] The object of the present invention is to provide a SNP locus combination for rapid identification of Chinese Merino sheep, which consists of 10 carefully selected SNP loci, which are highly specific in the Chinese Merino sheep genome and can accurately distinguish this breed from other similar breeds or hybrid offspring.

[0004] On the one hand, the present invention relates to a SNP locus combination for rapid identification of Chinese Merino sheep, characterized in that it consists of 10 SNP loci located in the sheep reference genome ARS-UI_Ramb_v2.0, numbered NO.1 to NO.10 respectively, and the specific information is as follows:

[0005] Number (NO.) Nth chromosome Location Reference base Mutated base 1 3 43521750 A G 2 6 28030087 T A 3 6 29100317 T C 4 6 29772568 T C 5 8 63572173 C T 6 8 63576026 G A 7 8 63615387 A G 8 12 57099456 C T 9 15 10951762 A G 10 15 37756467 A G .

[0006] On the other hand, the present invention relates to a method for identifying the Chinese Merino sheep breed, which comprises: collecting the gene sequence of the sample to be detected, detecting the mutation of the SNP site of the SNP site combination for rapid identification of the Chinese Merino sheep, and determining the breed of the sample to be detected.

[0007] Furthermore, in the method for identifying the Chinese Merino sheep breed provided by the present invention, according to the position of the SNP site, the sheep reference genome ARS-UI_Ramb_v2.0 is extended by 60 bp before and after to obtain a base sequence with a length of 121 bp, and the reverse complementary sequence of the base sequence with a length of 121 bp is used as the probe sequence of the SNP site.

[0008] Furthermore, in the method for identifying the Chinese Merino sheep breed provided by the present invention, genotyping is performed according to the mutation situation.

[0009] Furthermore, in the method for identifying the Chinese Merino sheep breed provided by the present invention, the genotyping includes: extracting the genomic DNA of the sample to be tested to obtain a DNA sample, detecting the quality of the DNA sample, liquid chip testing, and performing quality control, comparison, and SNP testing on the raw data obtained by the test to obtain the genotyping result.

[0010] Furthermore, in the method for identifying the Chinese Merino sheep breed provided by the present invention, the quality control uses fastp software, the comparison uses bwa software, and the SNP detection uses GATK software.

[0011] Furthermore, in the method for identifying the Chinese Merino sheep breed provided by the present invention, breed identification is performed based on a classifier algorithm according to the result of the genotyping.

[0012] On the other hand, the present invention relates to the application of the SNP site combination for rapid identification of Chinese Merino sheep in distinguishing sheep breeds, and distinguishing Chinese Merino sheep breeds from multiple sheep genomic DNAs.

[0013] On the other hand, the present invention relates to a gene chip for Chinese Merino sheep breed identification, which is composed of sites for detecting the SNP site combination for rapid identification of Chinese Merino sheep.

[0014] Compared with the prior art, the technical solution provided by the present invention has at least the following beneficial effects or advantages.

[0015] The present invention is based on the 1st to 26th chromosomes and the X chromosome (or sex chromosome) disclosed in the sheep reference genome ARS-UI_Ramb_v2.0, and locates 10 SNP sites closely connected to the Chinese Merino sheep breed. When the SNP site combination of the present invention is applied to the variety identification of the Chinese Merino sheep breed, its prediction accuracy is 99.34%. Compared with the traditional solid phase chip, the present invention makes the SNP sites of the Chinese Merino sheep into a liquid phase chip, which has high flexibility and can add marker sites at any time according to application needs. The Chinese Merino sheep liquid phase chip of the present invention is based on targeted capture sequencing technology, which can not only type the target site, but also accurately type the SNP within a certain range around the target site, and can obtain more SNP typing information than the marker site. Compared with whole genome resequencing, the Chinese Merino sheep liquid phase chip provided by the present invention relies on the second generation sequencing platform, has a low typing cost, has obvious price advantages, can perform large-scale typing of Chinese Merino sheep, and thus promote the breeding of Chinese Merino sheep. The Chinese Merino sheep liquid phase chip of the present invention can be used for the variety identification, kinship identification and germplasm resource improvement of Chinese Merino sheep. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] 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 or the description of the prior art 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.

[0017] Figure 1 The invention provides a positioning map of the SNP site combination for rapid identification of Chinese Merino sheep on the sheep reference genome ARS-UI_Ramb_v2.0. DETAILED DESCRIPTION

[0018] The technical scheme of the present invention is described below in conjunction with the examples, but the present invention is not limited to the following examples. The experimental methods and detection methods described in each example are conventional methods unless otherwise specified; the reagents and materials are available on the market unless otherwise specified, and the % in the following examples are all mass percentages unless otherwise specified.

[0019] Example 1

[0020] This example provides a SNP site screening process for identifying Chinese Merino sheep.

[0021] (1) Sample data acquisition: Blood samples of 15 sheep breeds in Xinjiang (Lobu sheep, Duolang sheep, Kazakh sheep, Turpan black sheep, Altay sheep, Chinese Merino sheep, Bashbai sheep, Balchuk sheep, Kirgiz sheep, Yecheng sheep, Bayinbuluke sheep, Cele black sheep, Hotan sheep, Karakul sheep, and Chinese Merino sheep) were collected and sent to Xinjiang Compson Biotechnology Co., Ltd. for genome resequencing to obtain the fastq.gz data of each sample.

[0022] (2) Data format conversion: The fastq.gz data of each breed of sheep were quality controlled by fastqc software (default parameters, adapter r1-adapter: AGATCGGAAGAGCACACGTCTGAACTCCAGTCA, r2-adapter: AGATCGGAAGAGCGTCGTGTAGGGAAAGAGTGT), and then the sequencing data were aligned to the sheep reference genome ARS-Ul Ramb v2.0 using BWA software, sorted and deduplicated using SAMtools software, and then the vcf.gz format file was obtained through variant calling using GATK software;

[0023] (3) Filtering: GATK, BCFtools, and PLINK software were used to filter allele frequencies greater than 0.1 (--maf 0.1), locus missing rate less than 0.1 (--geno 0.1), and Hardy-Weinberg equilibrium test P value greater than 0.001 (--hwe0.001). Linked loci were removed using PLINK software, and the conditions were set as follows: window size of 50 SNPs, step size of 10 SNPs, and LD threshold of 0.2;

[0024] (4) Preliminary screening: PLINK software was used to calculate the inter-population genetic differentiation index (Fst) between Chinese Merino sheep and other breed groups. The top 10,000 SNP loci with the highest Fst in Chinese Merino sheep were selected as the breed selection loci according to the descending order of Fst values;

[0025] (5) Rescreening: The best loci were screened using the random forest model and support vector machine learning method in Python. The 10,000 SNP loci dataset of Chinese Merino sheep was divided into a training set and a test set at a ratio of 8:2, and stratified sampling was performed to ensure that the distribution ratio of each locus in the training set and the test set was consistent; the feature importance of the random forest model was used to select the most important SNP features, and the parameters controlled the number of selected features. 40 to 60 features were selected cyclically, and the number of decision trees was set to 1000; the random number seed was equal to 0; the parameters of SVC (support vector classifier) ​​were set as: C = [0.01, 0.1, 1, 5, 10, 100]; the number of cross-validation folds was set to 5;

[0026] (6) Site retention: The random forest (RF) model and support vector machine learning (SVG) were used to obtain the candidate SNP sites under the best model. The candidate SNP sites were removed from the duplicate sites, the SNP sites that could not be uniquely matched on the genome, and the SNP sites containing duplicate sequences in the flanking sequences. The spacing between the SNP sites was then evaluated to ensure that the spacing between any two adjacent SNP sites was greater than 60 bp to achieve probe synthesis. Finally, 10 SNP sites for Chinese Merino sheep breed identification were obtained (Table 1). The distribution of the above SNP sites on the sheep reference genome ARS-Ul Ramb v2.0 is shown in the figure. Figure 1 shown.

[0027] Table 1: SNP sites and corresponding mutations

[0028] Number (NO.) Nth chromosome Location Reference base Mutated base 1 3 43521750 A G 2 6 28030087 T A 3 6 29100317 T C 4 6 29772568 T C 5 8 63572173 C T 6 8 63576026 G A 7 8 63615387 A G 8 12 57099456 C T 9 15 10951762 A G 10 15 37756467 A G .

[0029] Example 2

[0030] This example provides a process for genotyping sheep using the above 10 SNP loci.

[0031] (1) Extraction of sheep genomic DNA: Blood was collected from the jugular vein of sheep and DNA was extracted using the phenol-chloroform method or a blood genomic extraction kit (Tiangen Biotechnology Co., Ltd., Beijing);

[0032] (2) DNA sample quality detection: Detection was performed by agarose gel electrophoresis with a mass fraction of 1-1.5%, and the electrophoresis results were judged by a gel imaging system (GelDocXRSystem, Bio-Rad, USA) to ensure the integrity of the genome; the concentration of genomic DNA was measured by a micro-volume UV spectrophotometer (Q5000, Quawell, USA) or a similar nucleic acid protein analyzer, and the DNA concentration was adjusted to a working concentration of 10-50 ng / μL;

[0033] (3) Liquid chip testing: follow the standard procedure for liquid chip testing;

[0034] (4) Data analysis: The obtained raw data were quality controlled using fastqc software, and then the sequencing data were aligned to the sheep reference genome ARS-Ul Ramb v2.0 using BWA software. The standard process of GATK software was used to detect SNPs and perform genotyping. The corresponding relationship between the genotypes and genotyping of the 10 SNP sites was marked as follows: genotyping is 0, the corresponding genotype is reference base + reference base; genotyping is 1, the corresponding genotype is reference base + mutant base; genotyping is 2, the corresponding genotype is mutant base + mutant base; genotyping is NA, indicating that the sequencing data is missing. For example, NO.1 is located at position 43521750 of chromosome 3, the reference base is A, and the mutant base is G. The marking method of NO.1 is: genotyping is 0, the corresponding genotype is AA; genotyping is 1, the corresponding genotype is AG; genotyping is 2, the corresponding genotype is GG. The genotyping results of Chinese Merino sheep are shown in Table 2.

[0035] Table 2: Correspondence between genotypes of SNP loci and genotyping

[0036]

[0037]

[0038]

[0039]

[0040]

[0041]

[0042] According to the genotyping results in Table 2, the varieties were classified using Python software. The test included the following steps:

[0043] 1. Import necessary libraries:

[0044] 1) Use numpy and pandas for data processing.

[0045] 2) Use joblib to save and load models and other objects.

[0046] 3) Use various modules in sklearn for data segmentation, model evaluation, missing value filling, feature selection, cross validation, model training and evaluation.

[0047] 2. Read and preprocess data:

[0048] 1) Read the raw data file (such as CSV or TSV format).

[0049] 2) Replace missing values ​​(such as 'NA') in the data with NaN for subsequent processing.

[0050] 3) Extract feature values ​​and labels (i.e. target variables).

[0051] 3. Missing value filling:

[0052] 1) Use KNN and other algorithms to fill in missing values.

[0053] 2) Save the filler (such as KNNImputer) for later use.

[0054] 4. Dataset Division:

[0055] 1) Use train_test_split to split the data into training and test sets.

[0056] 2) Ensure that the category distribution in the training set and test set is the same as the original data.

[0057] 5. Feature Selection

[0058] 1) Use a model (such as RandomForestClassifier) ​​for feature selection.

[0059] 2) Keep the important features after selection.

[0060] 3) Save the feature selector for later use.

[0061] 6. Model training and hyperparameter optimization:

[0062] 1) Use methods such as GridSearchCV for hyperparameter search and model optimization.

[0063] 2) Train the model and select the best model and parameters.

[0064] 3) Save the best model for later use.

[0065] 7. Model Evaluation

[0066] 1) Calculate the scores of the test set, such as accuracy, confusion matrix, classification report, etc.

[0067] 2) Save the results of model evaluation for subsequent analysis.

[0068] 8. New data processing and prediction:

[0069] 1) Read the new data and make sure it is aligned with the original data.

[0070] 2) Use the saved filler to fill missing values ​​in new data.

[0071] 3) Use the saved feature selector to select important features in the new data.

[0072] 4) Use the saved model to make predictions on new data.

[0073] 5) Save and output the prediction results.

[0074] 9. Result preservation and output:

[0075] Save the prediction results as a CSV file for subsequent analysis and application.

[0076] The prediction results are shown in Table 3, where 0 indicates that the sheep is identified as Chinese Merino sheep, and 1 indicates that the sheep is not identified as Chinese Merino sheep.

[0077] Table 3: Prediction results of Chinese Merino sheep

[0078]

[0079]

[0080]

[0081] As shown in Table 2 and Table 3, the 10 SNP sites provided by the present invention were tested in a total of 1486 sheep, including 15 breeds, of which 232 were Chinese Merino sheep, 231 were identified as Chinese Merino sheep, 1 was not identified as Chinese Merino sheep, and no sheep of other breeds were identified as Chinese Merino sheep. In summary, the accuracy of the SNP site combination for rapid identification of Chinese Merino sheep of the present invention is 99.34%, which has better specificity.

[0082] As described above, the basic principle, main features and advantages of the present invention are well described. The above embodiments and descriptions are only descriptions of the preferred implementation modes of the present invention, and the present invention is not limited by the above embodiments. Without departing from the spirit and scope of the present invention, various changes and improvements made by ordinary technicians in this field to the technical solution of the present invention should fall within the protection scope determined by the present invention.

Claims

1. A SNP locus combination for rapid identification of Chinese Merino sheep, characterized in that: It consists of 10 SNP sites located in the sheep reference genome ARS-UI_Ramb_v2.0, numbered NO.1 to NO.10; The NO.1 is located at position 43521750 on chromosome 3, the NO.2 is located at position 28030087 on chromosome 6, the NO.3 is located at position 29100317 on chromosome 6, the NO.4 is located at position 29772568 on chromosome 6, the NO.5 is located at position 63572173 on chromosome 8, the NO.6 is located at position 63576026 on chromosome 8, the NO.7 is located at position 63615387 on chromosome 8, the NO.8 is located at position 57099456 on chromosome 12, the NO.9 is located at position 10951762 on chromosome 15, and the NO.10 is located at position 37756467 on chromosome 15.

2. The SNP locus combination for rapid identification of Chinese Merino sheep according to claim 1, characterized in that: The reference base of NO.1 is A, and the mutant base is G; the reference base of NO.2 is T, and the mutant base is A; the reference base of NO.3 is T, and the mutant base is C; the reference base of NO.4 is T, and the mutant base is C; the reference base of NO.5 is C, and the mutant base is T; the reference base of NO.6 is G, and the mutant base is A; the reference base of NO.7 is A, and the mutant base is G; the reference base of NO.8 is C, and the mutant base is T; the reference base of NO.9 is A, and the mutant base is G; the reference base of NO.10 is A, and the mutant base is G.

3. A method for identifying the Chinese Merino sheep breed, characterized in that: include: Collect the gene sequence of the sample to be tested, detect the mutation of the SNP site of the SNP site combination for rapid identification of Chinese Merino sheep according to any one of claims 1 to 2, and determine the breed of the sample to be tested.

4. The method of claim 3, wherein: According to the position of the SNP site, the sheep reference genome ARS-UI_Ramb_v2.0 was extended by 60 bp forward and backward to obtain a base sequence with a length of 121 bp, and the reverse complementary sequence of the base sequence with a length of 121 bp was used as the probe sequence of the SNP site.

5. The method of claim 3, wherein: Genotyping was performed according to the mutation status.

6. The method of claim 5, wherein: The genotyping includes: extracting the genomic DNA of the sample to be tested to obtain a DNA sample, testing the quality of the DNA sample, liquid phase chip testing, quality control and comparison of the raw data obtained by the test, and SNP testing to obtain the genotyping result.

7. The method of claim 6, wherein: The quality control used fastp software, the alignment used bwa software, and the SNP detection used GATK software.

8. The method of claim 6, wherein: According to the results of the genotyping, variety identification is performed based on a classifier algorithm.

9. Use of the SNP locus combination for rapid identification of Chinese Merino sheep according to any one of claims 1 to 2 in distinguishing sheep breeds, characterized in that: Differentiation of Chinese Merino sheep breeds from multiple sheep genomic DNA.

10. A gene chip for identifying Chinese Merino sheep breeds, characterized in that: The method is composed of sites for detecting the SNP site combination for rapid identification of Chinese Merino sheep as described in any one of claims 1 to 2.

Images