SNP molecular site and its detection primer and application in predicting high and low egg laying traits of chicken
By using genome-wide association analysis and designing specific detection primers, the problem of low egg production rate in local or specialty egg-laying chicken breeds was solved, achieving rapid and accurate improvement in breeding efficiency and egg production rate.
Patent Information
- Application Number
- CN202510752096.5
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- Filing Date
- 2025-06-06
- Publication Date
- 2026-02-27
- Estimated Expiration
- 2045-06-06
AI Technical Summary
Existing local or specialty egg-laying chicken breeds generally suffer from low egg production rates, necessitating the use of molecular marker-assisted selection breeding to improve breeding efficiency and shorten the breeding cycle.
Through genome-wide association analysis, SNP marker loci significantly associated with egg production at 300 days of age in chickens were identified. Specific detection primers were designed, and PCR was used to detect the genotypes of SNP molecular loci in chickens to predict egg production levels, providing technical support for marker-assisted selection breeding.
It enables rapid and accurate screening of superior genotypes, improves breeding efficiency, shortens breeding time, and increases egg production rate in chickens.
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Figure CN120574956B_ABST
Abstract
Description
TECHNICAL FIELD
[0001] The present application relates to a SNP molecular site related to a chicken egg laying trait, in particular to a SNP molecular site related to a chicken 300-day egg laying number trait, a detection primer and application thereof in predicting an egg laying number, and belongs to the field of SNP molecular sites related to a chicken 300-day egg laying number trait and application thereof. BACKGROUND
[0002] The egg laying number is a main selection trait of a laying hen and a broiler breeder, and is also a main content of quantitative genetic research of a laying hen, but a current local or characteristic laying hen breed generally has a low egg laying rate and the like, and a breed with a high egg laying rate is urgently needed.
[0003] SNP molecular marker assisted selection breeding is to use a SNP molecular marker which is found to be closely linked to a target trait gene through whole genome association analysis, to quickly and accurately screen a superior genotype at a DNA molecular level, and to apply the same to molecular marker assisted breeding, therefore, using chicken SNP typing data and phenotype data related to an egg laying trait, performing whole genome association analysis, finding a SNP marker site significantly related to a chicken egg laying number, and providing technical support for molecular marker assisted selection breeding of a chicken egg laying trait, shortening a breeding period and improving breeding efficiency. SUMMARY
[0004] One of the purposes of the present application is to provide a SNP molecular site related to a chicken 300-day egg laying number trait.
[0005] The second purpose of the present application is to provide a PCR detection primer for detecting a SNP molecular site related to a chicken 300-day egg laying number trait.
[0006] The third purpose of the present application is to apply the SNP molecular site related to a chicken 300-day egg laying number trait or the detection primer to predicting a high or low egg laying number of a chicken.
[0007] In order to achieve the above purposes, the main technical solutions adopted by the present application include:
[0008] The present application discloses a SNP molecular site related to a chicken 300-day egg laying number trait, and the SNP molecular site related to a 300-day chicken egg laying number trait corresponds to sequence information 1 of a chicken reference genome GRC7b version published in an Ensembl website (https: / / www.ensembl.org), 61,577,523 bp of a first chromosome, A or G at this base, and rs740376220 as a SNP number.
[0009] Another aspect of the present application discloses a PCR detection primer for detecting the SNP molecular site related to the 300-day egg number trait of chicken, preferably, the PCR primer consists of an upstream primer shown in SEQ ID No. 1 and a downstream primer shown in SEQ ID No. 2.
[0010] Another aspect of the present application provides an application of the SNP molecular site related to the egg number trait in predicting the egg number of chicken, comprising:
[0011] (1) extracting the genomic DNA of the test egg-laying chicken;
[0012] (2) detecting the genotype of the SNP site related to the egg number trait of chicken;
[0013] (3) if the genotype of the SNP site related to the egg number trait is AA genotype or GA genotype, the test chicken has high egg number; if the genotype of the SNP site related to the egg number trait is GG genotype, the test chicken has low egg number.
[0014] In a preferred embodiment of the present application, the method for extracting the genomic DNA of the test egg-laying chicken in step (1) comprises: blood sampling of the test egg-laying chicken, anticoagulation with an anticoagulant, and extraction of the genomic DNA.
[0015] In a preferred embodiment of the present application, the method for detecting the genotype of the SNP site related to the egg number trait of chicken in step (2) comprises whole genome resequencing, targeted sequencing or Sanger sequencing.
[0016] In a preferred embodiment of the present application, the egg number trait is 300-day egg number; the test chicken is a young chicken or an early egg-laying chicken; preferably, the test chicken is a chicken related to the 300-day egg number trait.
[0017] Another aspect of the present application is to apply the PCR primer in predicting the egg number of chicken, comprising:
[0018] (1) extracting the genomic DNA of the test egg-laying chicken;
[0019] (2) using the extracted genomic DNA of the test chicken as the amplification template, establishing a PCR amplification system using the PCR primer to perform PCR amplification; and sequencing the PCR amplification product to determine the genotype of the SNP site related to the egg number trait of chicken;
[0020] (3) if the genotype of the SNP site related to the egg number trait is AA genotype or GA genotype, the test chicken has high egg number; if the genotype of the SNP site related to the egg number trait is GG genotype, the test chicken has low egg number.
[0021] In a preferred embodiment of the present application, the method for extracting the genomic DNA of the laying hen to be tested in step (1) comprises: taking blood from the laying hen to be tested, anticoagulating with an anticoagulant, and extracting the genomic DNA.
[0022] In a preferred embodiment of the present application, the egg laying number trait is the egg laying number at 300 days of age; the laying hen to be tested is a young hen or an early egg laying hen; preferably, the laying hen to be tested is a chicken associated with the egg laying number trait at 300 days of age.
[0023] In another aspect of the present application, a PCR kit for predicting the egg laying number of a chicken is provided, comprising PCR detection primers, wherein the PCR detection primers consist of an upstream primer shown in SEQ ID No. 1 and a downstream primer shown in SEQ ID No. 2.
[0024] The present application utilizes chicken SNP typing data and phenotype data related to the egg laying trait to perform association analysis to identify a SNP marker site significantly related to the egg laying number of a chicken at 300 days of age, which corresponds to the sequence information of chromosome 1, 61,577,523 bp in the chicken reference genome GRC7b version published on the Ensembl website, wherein the base is A or G, and the SNP number is rs740376220; the present application further designs specific detection primers for the SNP marker site, and the SNP marker site and the detection primers thereof can be applied to predict the egg laying trait of a chicken, and can provide technical support for molecular marker assisted selection breeding of the egg laying trait of a chicken, shorten the breeding period, and improve the breeding efficiency.
[0025] Definitions of terms involved in the present application
[0026] Single nucleotide polymorphism (SNP) refers to the polymorphism of DNA sequence caused by single nucleotide insertion, deletion, transversion and conversion at the genomic level. BRIEF DESCRIPTION OF DRAWINGS
[0027] Figure 1 Common genes associated with egg laying based on Fst, XPEHH and XPCLR selection signals of high, medium and low egg laying performance breed combinations; A figure represents the comparison results of high and low groups; B figure represents the comparison results of high and medium groups; C figure represents the comparison results of medium and low groups.
[0028] Figure 2 Enrichment analysis results of common genes identified by selection signals of different egg laying performance groups; HL, HM and ML represent high and low groups, high and medium groups and medium and low groups, respectively.
[0029] Figure 3Results of θπ, Tajima's D and Fst in the candidate gene region; the shaded part indicates the genomic region under strong selection.
[0030] Figure 4 Boxplot of 300-day egg production of different genotypes of candidate SNPs in Beijing oil chicken population.
[0031] Figure 5 Figure of Sanger sequencing results of associated SNP rs74037622. DETAILED DESCRIPTION
[0032] The present application will be further described below in connection with specific embodiments. The advantages and characteristics of the present application will become more apparent from the description. However, it should be understood that the described embodiments are only exemplary and do not constitute any limitation on the scope of the present application. Those skilled in the art should understand that modifications or substitutions can be made to the details and forms of the technical solutions of the present application without departing from the spirit and scope of the present application, and such modifications or substitutions all fall within the protection scope of the present application.
[0033] Experimental Example 1 Identification of molecular network and key genes related to 300-day egg production performance
[0034] In this experiment, 6 breeds of chickens, including Bailaihang chicken, Lu Dao red chicken, Guifei chicken, Wenshang Lu chicken, Beijing oil chicken and Pudong chicken, were selected as the research population. According to the egg production performance of each breed (data from Poultry Breeds and actual observation data), the 6 breeds were divided into 3 groups of high (H group: Bailaihang chicken, Lu Dao red chicken), medium (M group: Guifei chicken, Wenshang Lu chicken) and low (L group: Beijing oil chicken, Pudong chicken) egg production performance for genome comparison analysis. The genome data included 25 randomly selected female chicken individuals from each breed, totaling 150 samples.
[0035] 1. Obtaining high-quality whole genome SNP data
[0036] 1.1 DNA extraction and sequencing
[0037] Genomic DNA was extracted from 150 chicken whole blood samples obtained by intravenous blood sampling using a Tiangen kit. After quality control, the genomic DNA was sequenced using a Huada Zhi Zao DNBSEQ-T7 platform, with a sequencing depth of 10x, to obtain resequencing data.
[0038] 1.2 SNP genotyping
[0039] After quality control by fastp software, the sequencing data was aligned to chicken 7.0 reference genome (GRCg7b) using BWA software, SNP typing was performed according to the GATK optimal operation process, and the whole genome dataset of 150 DNA samples was generated. Further conversion of the whole genome dataset into ped and map files was performed by plink1.9 software.
[0040] 1.3 Quality control and genotype filling
[0041] Genotype files were quality controlled by plink1.9 software, including 1) applying --geno 0.05 to delete SNP sites with high SNP missing rates; 2) applying --maf 0.05 to delete SNP sites with low minimum allele frequency; 3) applying --hwe 0.00001 to delete SNPs not conforming to Hardy Weinberg equilibrium; 4) deleting Z and W chromosome sites; 5) using plink1.9 software to convert genotype files (.bim,.bed and.fam) into chromosome-specific vcf format files; 6) using beagle5.4 software to fill in missing genotypes. Based on the above operations, 3172126 SNPs and 150 samples were obtained, named dataset 1.
[0042] 1.4 Linkage disequilibrium (LD) pruning
[0043] The SNP sites in dataset 1 were subjected to linkage disequilibrium (LD) pruning using the --indep pairwise 25 5 0.2 function in plink1.9 software. This function calculates the LD value between a pair of SNPs in a 25-SNP window moving at a speed of 5 SNPs, and when the LD degree is greater than 0.2, one of the pair of SNPs is excluded. Removing SNPs in high-level LD has been shown to offset the effects of determination bias, so by pruning LD in the quality control program, determination bias can be greatly reduced. Finally, a dataset of 426566 SNPs and 150 samples was obtained, named dataset 2.
[0044] 2. Population genomic selection signal analysis
[0045] 2.1 Population fixation coefficient (Fst) analysis
[0046] The genotype files (.bim,.bed and.fam) of dataset 2 were converted into vcf format files using plink1.9 software. Fst analysis between each pair of high, medium and low egg performance groups was performed using --fst-window-size 100000 --fst-window-step 10000 in vcftools software. This command calculated the average Fst value and weighted Fst (wFst) value in 100 kb genomic interval with 10 kb step, in which wFst value was the Fst value corrected according to population structure and sample size, which was used as the selection criteria for candidate intervals. According to the wFst value, the top 1% (top 1%) intervals were selected as candidate intervals. Finally, 929 candidate intervals were identified in high-low (HL), high-medium (HM) and medium-low (ML) groups for subsequent annotation analysis.
[0047] 2.2 Extended haplotype homozygosity across populations (XP-EHH) analysis
[0048] The genomic vcf files of different egg performance groups of dataset 2 were extracted using plink1.9 software. The genomic data of different groups were phased using beagle5.4 software. After phasing, the genomic information was used for XP-EHH analysis of whole genome sites using the --xpehh command in selscan2.0.3 software. The absolute value of the XP-EHH value in the analysis results was taken, and the top 1% (top 1%) sites were selected as candidate sites. Finally, 4244, 4239 and 4246 candidate sites were identified in high-low (HL), high-medium (HM) and medium-low (ML) for subsequent annotation analysis.
[0049] 2.3 Cross-population composite likelihood ratio (XP-CLR) analysis
[0050] The genotype files (.bim,.bed and.fam) of dataset 2 were converted into chromosome-specific vcf format files using plink1.9 software. At the same time, the chromosome-specific genetic distance files were output. XP-CLR analysis between each two of the high, medium and low egg performance groups was performed using the --phased --size 100000 --step 10000 in the xpclr software. The command calculates the XP-CLR average value and the standardized XP-CLR (nXP-CLR) value in a 100 kb genomic interval with a 10 kb step, wherein the nXP-CLR value is the XP-CLR value standardized according to the population structure and sample size, which is used as the selection standard for candidate intervals. For the genomic intervals without nXP-CLR values, 0 is used instead. According to the nXP-CLR value, the top 1% intervals are selected as candidate intervals. Finally, 944 candidate intervals were identified in the high-low (HL), high-medium (HM) and medium-low (ML) groups for subsequent annotation analysis.
[0051] 3. Gene annotation of selected signal intervals and functional enrichment analysis
[0052] The top 1% results of the three (Fst, XP-EHH and XP-CLR) selection signals of the HL, HM and ML groups were obtained in the above analysis. Further gene annotation analysis was performed on the selection signal results, and the annotation reference file was selected as the annotation file of the GRCg7b reference genome (https: / / ftp.ensembl.org / pub / release-109 / gtf / gallus_gallus / Gallus_gallus.GalGal1.mat.broiler.GRCg7b.109.gtf.gz): 1) For Fst, bedtools software was used to annotate the top 1% candidate intervals (100 kb intervals). Finally, 2837, 2690 and 2370 ensembl genes were annotated in the HL, HM and ML groups, respectively; 2) For XP-EHH, the upstream and downstream 50 kb intervals of the top 1% candidate sites were taken as candidate intervals for annotation. Finally, 14578, 13876 and 15479 ensembl genes were annotated in the HL, HM and ML groups, respectively; 3) For XP-CLR, bedtools software was used to annotate the top 1% candidate intervals (100 kb intervals). Finally, 3472, 3715 and 3662 ensembl genes were annotated in the HL, HM and ML groups, respectively. Finally, based on the annotated ensembl gene information, the intersection of the three selection signal annotated genes in HL, HM and ML was taken, respectively, to obtain 128, 76 and 92 common genes. Figure 1 ).
[0053] The intersection genes were annotated by the 'clusterProfiler' package in R software, and it was found that the genes in the HL, HM and ML groups were enriched in 12, 5 and 1 KEGG signaling pathways, respectively. Among them, the GnRH signaling pathway, vascular smooth muscle contraction and adrenergic signaling in cardiomyocytes were significantly enriched in the HL and HM groups. Figure 2 The GnRH signaling pathway has an important regulatory effect on the development and function of the reproductive system, and it promotes the development and maturation of follicles by promoting the synthesis and release of gonadotropin in the anterior pituitary. By focusing on the GnRH signaling pathway, the common gene CACNA1C in the HL and HM groups was finally identified as a candidate gene, with accession number NC_052532.1, and molecular marker mining was carried out.
[0054] 4. Analysis of the gene interval of the candidate gene CACNA1C
[0055] The CACNA1C gene interval was extracted from the annotation file of the GRCg7b reference genome, and the gene was located at 61231143-61658619 bp on chromosome 1. The HL group was selected, and the plink1.9 software was used to extract the gene interval in the data set 1 to carry out Fst, nucleotide diversity (θπ) and Tajima' D analysis: 1) In the Fst analysis, the --fst-window-size 20000 --fst-window-step 20000 command in the vcftools software was used to calculate the 20 kb sliding window wFst; 2) In the θπ analysis, the --window-pi 20000 --window-pi-step 20000 command in the vcftools software was used to calculate the 20 kb sliding window θπ; 3) In the Tajima' D analysis, the --TajimaD 20000 command in the vcftools software was used to calculate the average Tajima' D value in the 20 kb window.
[0056] The results are shown in Figure 3 In the gene interval 61540001-61600000, strong selection signals were identified by the three analysis methods. Based on the data set 1, 133 SNPs in the selected gene interval were finally detected.
[0057] Experimental Example 2: Association analysis of CACNA1C selected gene interval SNPs and egg production performance
[0058] In this experiment, two breeds of chickens, Bailaihang and Beijing You, were selected as the research population. The individual 300-day-old egg production of 399 hens (196 Bailaihang and 203 Beijing You) was measured, and whole-genome resequencing was performed on all egg production measurement individuals.
[0059] 1. High-quality whole-genome SNP data acquisition
[0060] 1.1 DNA extraction and sequencing
[0061] Genomic DNA was extracted from 399 chicken whole blood samples obtained by intravenous blood sampling using a Tiangen kit. After quality control, the genomic DNA was sequenced using a Huada Zhi Zao DNBSEQ-T7 platform, with an average sequencing depth of >12x, to obtain resequencing data.
[0062] 1.2 SNP genotyping
[0063] After quality control of the sequencing data using fastp software, the data was aligned to the chicken 7.0 reference genome (GRCg7b) using BWA software, and SNP genotyping was performed according to the GATK optimal operation process to generate a whole-genome dataset for 399 DNA samples. Further conversion of the whole-genome dataset into ped and map files was performed using plink1.9 software.
[0064] 1.3 Quality control and genotype filling
[0065] Genotype files were quality controlled using plink1.9 software, including 1) removing SNP sites with high missing rates using --geno 0.05; 2) removing SNP sites with low minimum allele frequency using --maf 0.05; 3) removing SNPs not in Hardy Weinberg equilibrium using --hwe 0.00001; 4) removing Z and W chromosome sites; 5) converting genotype files (.bim,.bed, and.fam) to chromosome-specific vcf format files using plink1.9 software; 6) filling missing genotypes using beagle5.4 software; based on the above operations, 6270216 SNPs and 399 samples were obtained, named dataset 3, for subsequent analysis.
[0066] 2. Association analysis of CACNA1C selected gene region SNPs and egg production performance
[0067] Based on dataset 3, the SNPs in the selected gene region (61540001-61600000) of CACNA1C were extracted using plink1.9 software, and a total of 190 SNPs were detected. The intersection of these SNPs and the 133 SNPs detected in dataset 1 was obtained, resulting in 63 common SNPs, which were considered as reliable SNPs. The 63 SNPs were extracted using plink1.9 software, respectively, and converted to compound genotypes using the --recodecompound-genotypes command. In the Bailaihang chicken population, more than 96% of the individuals showed dominant homozygous SNP genotypes; in the Beijing oil chicken population, the 63 SNP genotypes showed polymorphism, but the number of individuals with minor alleles was small. The analysis results of selection signals showed that the CACNA1C gene was strongly selected in high-yield laying hens.
[0068] Further, the present experiment carried out association analysis of 63 SNP sites and 300-day egg production traits in the Beijing oil chicken population.
[0069] The pairwise.t.test function in R software was used to perform association analysis of SNP genotypes and 300-day egg production traits, and P<0.05 indicated significant difference.
[0070] Through significance test, SNP rs740376220 was significantly associated with egg production. SNP rs740376220 is located at 61577523 bp on chromosome 1, including AA, GA and GG genotypes. As shown in Table 1, the egg production of AA genotype chickens was significantly higher than that of GA and GG genotype chickens, and the egg production of GA genotype chickens was significantly higher than that of GG genotype chickens. Figure 4
[0071] The upstream and downstream sequences of this SNP rs740376220 (5' to 3', +) are as follows:
[0072] 1 dna:primary_assembly
[0073] primary_assembly:bGalGal1.mat.broiler.GRCg7b:1:61577123:61577923:1
[0074] AGGGCCCCTTCTTGTGGTTTGCTATGCATGCCACTGCTATGCCCACCACTTGATCTAAACTGATGGGAATGATGAGTGTTTTAGCTCACCTGTTTTACAGAATATCAATGGAAAGATGGAAGATGTAAGTTGGGCGCATTTGTTGCATGGCTAAATTACAGTCACAGTGATTCTGTTCAATTGGCAAAGCATTTCAAATTCTCTCTAACCCAGGGAAAGTCAGGGTAGAAGAAAAAGAAAAAAGAGAGCTTGTGCATCAATTTTCAGTCTGGGGTTTTTTTCCACCTTTTTGAGAGACACAGAGCAAGCCTGAATGGCAGTTAGGAAGAAGGAAGCTCAACTTTTCCACTGAGAGACGAGAAATCCTCATCTTCTCAGTTTGGAAATCTATTTAATAAAAACCCTTACATTGTCTGCTCTTTATCACATTCAATAAAGAAATGACTAAATATCCAATAAAGAAAGAAAATCCTACAACAGTAACAACCAAAAGCTTGTTTTCCCTCCAGAGCCCTCATGGGATTGTAACTTAGAAAATATTTCATGTAACGCTCTGCTTGTCCTATGTATCAGGACCTTCACTGTACTCTACAGGACATCGTTACAAAACCATTTTCCATTTAGTCCTCCTTTTTCCCTTGTTAAGAGACTTGTGTATTTGCTTTTGAACTGTGATTTCCCATTCCAGTGGCCAGTCACTGATCTACCCTCCCCACTCCTATTCCCTTTTGTTTTTTCAGGTTCTCTTTTATTTTGATATAGTTTTTACTGTCATTTTCACCATTGAAATTGCTCTGAAGG.
[0075] The primer sequence for detecting SNP rs740376220 is as follows:
[0076] F: ACCTTTTTGAGAGACACAGAGCA (SEQ ID No. 1)
[0077] R: CTAAGTTACAATCCCATGAGGGCT (SEQ ID No. 2).
[0078] Verification experiment of association between SNP rs740376220 molecular marker and 300-day egg number
[0079] In order to further verify the reliability of the association between the molecular marker of SNP rs740376220 locus and the high and low of 300-day egg number, the PCR-RFLP of SNP rs740376220 was carried out on 187 Beijing fowl hens (Note: The 187 hens used in this experiment were different from the hens in experimental example 1 and experimental example 2) whose 300-day egg number had been determined, to compare and analyze the egg number of hens with different genotypes.
[0080] The PCR amplification system is shown in Table 1, and the PCR amplification parameters are shown in Table 2.
[0081] Table 1 PCR amplification system
[0082]
[0083] Table 2 PCR amplification parameters
[0084] Step Temperature and time 1. Pre-denaturation 94°C, 3 min 2. Cycling phase 30 cycles Denaturation 94°C, 30 sec Annealing 55°C, 30 sec Extension 72°C, 1 min 3. Final extension 72°C, 5 min
[0085] F: ACCTTTTTGAGAGACACAGAGCA (SEQ ID No. 1)
[0086] R: CTAAGTTACAATCCCATGAGGGCT (SEQ ID No. 2)
[0087] The amplification product was sequenced, and the sequencing results of the SNP site are shown in Table 3. Figure 5 The statistical test results show that the polymorphism of SNP rs740376220 locus is significantly associated with the high and low of 300-day egg number (P<0.01) (Table 3).
[0088] Table 3 Comparison of phenotypes of individuals with different genotypes of SNP rs740376220
[0089]
Claims
1. The application of a reagent for detecting SNP loci associated with egg production at 300 days of age in predicting egg production levels at 300 days of age, characterized in that... The SNP locus corresponds to chromosome 1, 61,577,523 bp of the chicken reference genome GRC7b version sequence information, where the base is A or G, and the SNP number is rs740376220. The chicken is a Beijing You chicken. If the genotype of the SNP locus is AA or GA, the egg production of the chicken at 300 days of age will be high; if the genotype of the SNP locus is GG, the egg production of the chicken at 300 days of age will be low.
2. The application according to claim 1, characterized in that, include: (1) Extract genomic DNA from the laying hens to be tested; (2) Detect the genotype of the SNP locus; (3) If the genotype of the SNP locus is AA or GA, the number of eggs laid by the chickens at 300 days of age is high; if the genotype of the SNP locus is GG, the number of eggs laid by the chickens at 300 days of age is low.
3. The application according to claim 2, characterized in that, The method for extracting genomic DNA from the laying hen to be tested in step (1) includes: collecting blood from the laying hen to be tested, anticoagulating it with an anticoagulant, and extracting genomic DNA.
4. The application according to claim 2, characterized in that, The method for detecting the genotype of the SNP site in step (2) is whole genome resequencing.
5. The application according to claim 2, characterized in that, The method for detecting the genotype of the SNP site in step (2) is targeted sequencing.
6. The application according to claim 2, characterized in that, The method for detecting the genotype of the SNP site in step (2) is Sanger sequencing.
7. Applications of PCR primers in predicting egg production in chickens, including: (1) Extract genomic DNA from the laying hens to be tested; (2) Using the extracted genomic DNA of the chicken to be tested as an amplification template, a PCR amplification system was established using PCR primers for PCR amplification; the amplification products were sequenced to obtain the genotype of the SNP site described in claim 1; (3) If the genotype of the SNP locus is AA or GA, the egg production of the chicken to be tested is high; if the genotype of the SNP locus is GG, the egg production of the chicken to be tested is low. The chicken is a Beijing You chicken, and the egg production number is the egg production number at 300 days of age; the PCR primer consists of the upstream primer shown in SEQ ID No. 1 and the downstream primer shown in SEQ ID No. 2.