SNP (Single Nucleotide Polymorphism) molecular site related to laying number character of chicken, detection primer and application of SNP molecular site in breeding

Abstract

The invention discloses an SNP molecular site related to the laying number character of chickens, a detection primer and application of the SNP molecular site in breeding. SNP (Single Nucleotide Polymorphism) typing data comparative analysis of chicken varieties with different egg laying performances is utilized, correlation analysis is performed in combination with phenotypic data related to egg laying characters, finally, SNP marker sites remarkably related to the egg laying number are obtained through identification, and the SNP marker sites correspond to 139, 927 and 758bp positions of chromosomes 2 of chicken reference genome GRC7b version sequence information published in an Ensepbl website. The basic group is A or T, and the SNP (Single Nucleotide Polymorphism) number is rs794322365; by adopting the SNP marker site and the detection primer thereof provided by the invention, the egg laying traits of the chickens can be accurately predicted, a technical support can be provided for molecular marker-assisted selective breeding of the egg laying traits of the chickens, the breeding period is shortened, and the breeding efficiency is improved.

Description

Technical Field

[0001] The present invention relates to SNP molecular sites related to chicken egg-laying traits and detection primers thereof, and in particular to SNP molecular sites related to chicken egg-laying number traits, detection primers and applications thereof in predicting egg-laying number, belonging to the field of SNP molecular sites related to chicken egg-laying number traits and applications thereof. Background Art

[0002] Egg production is the main trait for breeding laying hens and broiler breeders, and is also the main content of genetic research on laying hen numbers. However, existing local or specialty laying hen breeds generally have problems such as low egg production rates, and there is an urgent need to select breeds with high egg production rates.

[0003] SNP molecular marker-assisted selection breeding uses molecular markers and SNP molecular markers that are found to be closely linked to the target trait gene through whole-genome association analysis to quickly and accurately screen dominant genotypes at the DNA molecular level and apply them to molecular marker-assisted breeding. Therefore, using chicken SNP typing data and phenotypic data related to egg-laying traits, genome-wide association analysis is performed to discover SNP marker sites that are significantly correlated with the number of eggs laid by chickens. This can provide technical support for molecular marker-assisted selection breeding of chicken egg-laying traits, shorten the breeding period, and improve breeding efficiency. Summary of the Invention

[0004] One of the purposes of the present invention is to provide a SNP molecular locus associated with the trait of egg production in chickens;

[0005] The second object of the present invention is to provide PCR detection primers for detecting SNP molecular sites related to the trait of chicken egg production;

[0006] The third purpose of the present invention is to apply the SNP molecular sites or detection primers related to the trait of chicken egg production to predict the number of eggs produced by chickens.

[0007] To achieve the above objectives, the main technical solutions adopted by the present invention include:

[0008] On the one hand, the present invention discloses a SNP molecular site associated with the egg production trait of chickens. The SNP molecular site associated with the egg production trait of chickens corresponds to chromosome 2 139,927,758bp of the chicken reference genome GRC7b version sequence information published on the Ensembl website (https: / / www.ensembl.org), where the base is A or T, and the SNP number is rs794322365.

[0009] Another aspect of the present invention is to disclose PCR detection primers for detecting the SNP molecular site associated with the chicken egg production trait. Preferably, the PCR primers consist of the upstream primer shown in SEQ ID No. 1 and the downstream primer shown in SEQ ID No. 2.

[0010] Another aspect of the present invention is to provide an application of a SNP molecular locus associated with the trait of egg production in chickens to predict the number of eggs produced by chickens, including:

[0011] (1) Extracting genomic DNA from the laying hens to be tested;

[0012] (2) detecting the genotype of the SNP site associated with the trait of egg production in chickens;

[0013] (3) If the genotype of the SNP site related to the trait of egg production is TT genotype, the egg production of the tested chicken is high; if the genotype of the SNP site related to the trait of egg production is AT genotype or AA genotype, the egg production of the tested chicken is low.

[0014] In a preferred embodiment of the present invention, the method for extracting genomic DNA from the laying hens to be tested in step (1) comprises: collecting blood from the laying hens to be tested, anticoagulating the blood with an anticoagulant, and extracting genomic DNA.

[0015] In a preferred embodiment of the present invention, the method for detecting the genotype of the SNP site associated with the egg production trait of laying hens in step (2) comprises whole genome resequencing, targeted sequencing or Sanger sequencing.

[0016] In a preferred embodiment of the present invention, the egg production trait is the number of eggs produced at 500 days of age; the chicken to be tested is a young chicken or an early laying hen; preferably, the chicken to be tested is a chicken associated with the egg production trait at 500 days of age.

[0017] Another aspect of the present invention is to use the PCR primers to predict the number of eggs produced by chickens, comprising:

[0018] (1) Extracting genomic DNA from the laying hens to be tested;

[0019] (2) using the genomic DNA of the chicken to be tested as an amplification template, establishing a PCR amplification system using the PCR primers, and performing PCR amplification; sequencing the PCR amplification product to determine the genotype of the SNP site associated with the chicken egg production trait;

[0020] (3) If the genotype of the SNP site related to the trait of egg production is TT genotype, the egg production of the tested chicken is high; if the genotype of the SNP site related to the trait of egg production is AT genotype or AA genotype, the egg production of the tested chicken is low.

[0021] In a preferred embodiment of the present invention, the method for extracting genomic DNA from the laying hens to be tested in step (1) comprises: collecting blood from the laying hens to be tested, anticoagulating the blood with an anticoagulant, and extracting genomic DNA.

[0022] In a preferred embodiment of the present invention, the chicken to be tested is a young chicken or an early laying hen; preferably, the chicken to be tested is a chicken associated with the trait of egg production at 500 days of age.

[0023] Another aspect of the present invention is to provide a PCR kit for predicting the number of eggs produced by chickens, comprising PCR detection primers, wherein the PCR detection primers are composed of an upstream primer shown in SEQ ID No. 1 and a downstream primer shown in SEQ ID No. 2.

[0024] The present invention uses chicken SNP typing data and phenotypic data related to egg-laying traits to perform association analysis, and identifies a SNP marker site significantly associated with the number of eggs laid in chickens. The SNP marker site corresponds to 139,927,758 bp of chromosome 2 in the GRC7b version sequence information of the chicken reference genome published on the Ensembl website, where the base is A or T, and the SNP number is rs794322365. The present invention designs specific detection primers for the SNP marker site. The SNP marker site and the detection primers can be used to screen and predict egg-laying traits in chickens, and can provide technical support for molecular marker-assisted selection breeding of egg-laying traits in chickens, thereby shortening the breeding period and improving breeding efficiency.

[0025] Definitions of terms used in this invention

[0026] Single nucleotide polymorphism (SNP) refers to the polymorphism of DNA sequence caused by mutations such as insertion, deletion, transversion and conversion of single nucleotides at the genomic level. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] Figure 1 Based on the combination of high, medium and low egg-laying performance breeds, Fst, XPEHH, and XPCLR selection signals were used to identify common genes associated with egg production; Figure A shows the comparison results between the high and low groups; Figure B shows the comparison results between the high and medium groups; Figure C shows the comparison results between the medium and low groups.

[0028] Figure 2 Results of the common gene enrichment analysis of the selection signals identified in different egg production performance groups; HL, HM and ML represent the high-low group, the high-medium group and the medium-low group, respectively.

[0029] Figure 3Results for θπ, TajimaD, and Fst within the candidate gene interval; the shaded area indicates the genomic interval under strong selection.

[0030] Figure 4 Box plot of the number of eggs produced at 500 days of age for different genotypes of candidate SNPs in the Beijing Oily Chicken population.

[0031] Figure 5 Figure 3. Sanger sequencing results of the associated SNP rs794322365. DETAILED DESCRIPTION

[0032] The present invention will be further described below in conjunction with specific embodiments, and the advantages and features of the present invention will become clearer as the description proceeds. However, it should be understood that the embodiments are merely exemplary and do not limit the scope of the present invention in any way. It should be understood by those skilled in the art that the details and forms of the technical solutions of the present invention may be modified or replaced without departing from the spirit and scope of the present invention, but such modifications or replacements fall within the scope of protection of the present invention.

[0033] Experimental Example 1 Identification of molecular networks and key genes related to egg production performance

[0034] This study selected six chicken breeds: White Leghorn, Luodao Red, Guifei, Wenshang Reed, Beijing Oily, and Pudong. Based on each breed's egg-laying performance (data from poultry breed catalogs and actual observational data), the six breeds were divided into three groups: high (H group: White Leghorn, Luodao Red), medium (M group: Guifei, Wenshang Reed), and low (L group: Beijing Oily, Pudong) egg-laying performance. Genomic data were collected from 25 randomly selected hens per breed, for a total of 150 hen samples.

[0035] 1. Acquisition of high-quality genome-wide SNP data

[0036] 1.1 DNA extraction and sequencing

[0037] Genomic DNA was extracted from 150 chicken whole blood samples obtained through venous blood collection using the Tiangen kit. After passing quality control, the genomic DNA was sequenced at a depth of 10× using the MGI DNBSEQ-T7 platform to generate resequencing data.

[0038] 1.2 SNP genotyping

[0039] After quality control using fastp software, the sequencing data were aligned to the chicken 7.0 reference genome (GRCg7b) using BWA software. SNP typing was performed according to the GATK optimal operation process to generate a whole-genome data set of 150 DNA samples. The whole-genome data set was further converted into ped and map files using plink1.9 software.

[0040] 1.3 Quality Control and Genotype Filling

[0041] Genotype files were quality-controlled using Plink 1.9 software, including: 1) using --geno 0.05 to delete SNP sites with excessively high missing SNP rates; 2) using --maf 0.05 to delete SNP sites with low minor allele frequencies; 3) using --hwe 0.00001 to delete SNPs that did not conform to Hardy-Weinberg equilibrium; 4) deleting sites on chromosomes Z and W; 5) using Plink 1.9 to convert genotype files (.bim, .bed, and .fam) into chromosomal VCF format files; and 6) using Beagle 5.4 software to fill in missing genotypes. Based on the above operations, 3,172,126 SNPs and 150 samples were obtained, named Dataset 1.

[0042] 1.4 Linkage disequilibrium (LD) deletion

[0043] Linkage disequilibrium (LD) pruning was performed on the SNPs in Dataset 1 using the --indep pairwise 25 5 0.2 function in plink 1.9. This function calculated the LD between a pair of SNPs within a window of 25 SNPs, moving at a rate of 5 SNPs. When the LD was greater than 0.2, one of the SNPs in the pair was excluded. This resulted in a dataset of 426,566 SNPs and 150 samples, named Dataset 2.

[0044] 2. Analysis of Population Genomic Selection Signals

[0045] 2.1 Analysis of population fixed coefficient (Fst)

[0046] The genotype files (.bim, .bed, and .fam) of Dataset 2 were converted into vcf format files using plink1.9 software. Fst analysis was performed between high, medium, and low egg production performance groups using the --fst-window-size 100000 --fst-window-step 10000 command in the vcftools software. This command calculated the average Fst value and weighted Fst (wFst) value in a 100kb genomic interval with a step size of 10kb. The wFst value is the Fst value corrected for population structure and sample size and used as the selection criterion for candidate intervals. Based on the wFst value, the top 1% (top 1%) intervals were selected as candidate intervals. Ultimately, 929 candidate intervals were identified in the high-low (HL), high-middle (HM), and low-medium (ML) groups for subsequent annotation analysis.

[0047] 2.2 Analysis of extended haplotype homozygosity across populations (XP-EHH)

[0048] Plink1.9 software was used to extract the genomic vcf files of different egg production performance groups in Dataset 2. Beagle5.4 software was used to phase the genomic data of different groups. After phasing, the genomic information was analyzed for XP-EHH of the whole genome 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%) of the sites were selected as candidate sites. Finally, 4244, 4239, and 4246 candidate sites were identified in the high-low (HL), high-medium (HM), and low-medium (ML) categories, respectively, for subsequent annotation analysis.

[0049] 2.3 Cross-population coincidence likelihood ratio (XP-CLR) analysis

[0050] Genotype files (.bim, .bed, and .fam) from Dataset 2 were converted to chromosome-specific VCF files using Plink 1.9 software. Genetic distance files for each chromosome were also output. Pairwise XP-CLR analysis was performed for high, medium, and low egg production performance groups using the --phased --size100000 --step 10000 command in the xpclr software. This command calculated the mean XP-CLR and the normalized XP-CLR (nXP-CLR) value within a 100 kb genomic interval with a 10 kb step size. The nXP-CLR value is the XP-CLR value normalized for population structure and sample size and used as the candidate interval selection criterion. Genomic intervals without nXP-CLR values were replaced with 0. Intervals ranked in the top 1% (based on the nXP-CLR value) were selected as candidate intervals. Finally, 944 candidate intervals were identified in the high-low (HL), high-middle (HM), and medium-low (ML) groups for subsequent annotation analysis.

[0051] 3. Gene annotation and functional enrichment analysis of selected signal intervals

[0052] The above analysis yielded the top 1% of selection signals for three genes (Fst, XP-EHH, and XP-CLR) in the HL, HM, and ML groups, respectively. This study further analyzed these selection signal results using the GRCg7b reference genome annotation file (https: / / ftp.ensembl.org / pub / release-109 / gtf / gallus_gallus / Gallus_gallus.bGalGal1.mat.broiler.GRCg7b.109.gtf.gz). 1) For Fst, we used bedtools software to annotate the top 1% candidate intervals (100 kb intervals). Ultimately, 2837, 2690, and 2370 ensembl genes were annotated in the HL, HM, and ML groups, respectively. 2) For XP-EHH, we selected candidate intervals 50 kb upstream and downstream of the top 1% candidate loci 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 (100kb 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 genes annotated by the three selection signals was taken in HL, HM, and ML, and 128, 76, and 92 common genes were obtained, respectively. Figure 1 ).

[0053] The 'clusterProfiler' package in R software was used to perform functional annotation on the intersection genes. 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 both the HL and HM groups ( Figure 2 The GnRH signaling pathway plays an important regulatory role in the development and function of the reproductive system. It promotes the synthesis and release of gonadotropins by the anterior pituitary, further promoting the development and maturation of follicles. Ultimately, by focusing on the GnRH signaling pathway, ADCY8, a common gene in the HL and HM groups, was identified as a candidate gene for molecular marker mining.

[0054] 4. Gene Interval Analysis of the Candidate Gene ADCY8

[0055] The ADCY8 gene interval was extracted from the annotation file of the GRCg7b reference genome. The gene is located at 139868327 to 139987072 bp on chromosome 2. The HL group was selected and the plink1.9 software was used to extract the ADCY8 gene interval in Dataset 1. Fst, nucleotide diversity (θπ), and Tajima's D analysis were performed: 1) In the Fst analysis, the --fst-window-size 5000 --fst-window-step 5000 command in the vcftools software was used to calculate the 5kb sliding frame wFst; 2) In the θπ analysis, the --window-pi 5000 --window-pi-step 5000 command in the vcftools software was used to calculate the 5kb sliding frame θπ; 3) In the Tajima's D analysis, the --TajimaD 5000 command in the vcftools software was used to calculate the average Tajima's D value of the 5kb window; the results are shown in Figure 2. Figure 3 As shown, all three analysis methods identified strong selection signals in the gene intervals 139900001-139905000 and 139925001-139930000. Based on Dataset 1, 25 SNP sites were finally detected in these two selected gene intervals.

[0056] Experimental Example 2 Association Analysis between SNPs in the Selected ADCY8 Gene Region and Egg Production Performance

[0057] The experiment selected two breeds, White Leghorn and Beijing Fatty chickens, as the study populations. Egg production was measured at 500 days of age for 364 hens from both populations (196 White Leghorn and 168 Beijing Fatty chickens; note: the 364 hens in Experiment 2 were completely different from the 150 laying hens from six breeds in Experiment 1). Whole-genome resequencing was performed on all individuals with measured egg production.

[0058] 1. Acquisition of high-quality genome-wide SNP data

[0059] 1.1 DNA extraction and sequencing

[0060] Genomic DNA was extracted from 364 chicken whole blood samples obtained through venous blood collection using the Tiangen kit. After passing quality control, the genomic DNA was sequenced using the MGI DNBSEQ-T7 platform, with an average sequencing depth of >12×, generating resequencing data.

[0061] 1.2 SNP genotyping

[0062] After quality control using fastp software, the sequencing data were aligned to the chicken reference genome version 7.0 (GRCg7b) using BWA software. SNP typing was performed according to the GATK optimal operation process, generating a whole-genome dataset for 364 DNA samples. The whole-genome dataset was further converted into ped and map files using plink 1.9 software.

[0063] 1.3 Quality Control and Genotype Filling

[0064] Genotype files were quality-controlled using plink1.9 software, including: 1) using --geno 0.05 to delete SNP sites with excessively high missing SNP rates; 2) using --maf 0.05 to delete SNP sites with low minimum allele frequencies; 3) using --hwe 0.00001 to delete SNPs that did not conform to Hardy-Weinberg equilibrium; 4) deleting sites on chromosomes Z and W; 5) using plink1.9 to convert genotype files (.bim, .bed, and .fam) into chromosomal VCF format files; and 6) using beagle5.4 software to fill in missing genotypes. Based on the above operations, 6,270,216 SNPs and 364 samples were obtained, named Dataset 3, for subsequent analysis.

[0065] 2. Association analysis between SNPs in the ADCY8 selected gene region and egg production performance

[0066] Based on Dataset 3, plink1.9 software was used to extract SNPs within the ADCY8 gene's selection-affected regions (139900001-139905000 and 139925001-139930000). A total of 25 SNPs were detected. These SNPs were intersected with the 25 SNPs detected in Dataset 1, yielding six shared SNPs, which were considered reliable SNPs. Six SNPs were extracted separately using plink1.9 software and converted into compound genotypes using the --recode compound-genotypes command. In the White Leghorn chicken population, 99% of individuals exhibited dominant homozygous SNP genotypes. In the Beijing Oily chicken population, all six SNP genotypes were polymorphic, but individuals with minor genotypes were relatively rare. This confirms the results of the selection signal analysis, indicating that the ADCY8 gene is under strong selection in high-yielding laying hens.

[0067] Furthermore, this experiment conducted an association analysis between four SNPs and the 500-day-old egg production trait in the Beijing Oily Chicken population. The pairwise.t.test function in R software was used to perform an association analysis between the SNP genotype and the 500-day-old egg production trait. P < 0.05 indicated a significant difference. Through the significance test, SNP rs794322365 was screened to be significantly associated with egg production. The SNP rs794322365 is located at 139927758bp on chromosome 2 and includes three genotypes: AA, AT, and TT.

[0068] The upstream and downstream sequences (5' to 3', +) of the SNP rs794322365 are as follows:

[0069] 2dna:primary_assemblyprimary_assembly:bGalGal1.mat.broiler.GRCg7b:2:139927358:139928158:1CAAGAATCATCAAGTCCAACTCCTGGCTCTACACAGGACTGCCAAATACTAAAAACGTATTTGTGAGACAGTTGTCCAAACACTCCTAAAACTCCTGCAGTTCAGGGCCATGCCCACTGCCCTGGGGAACGTGCTCCATGCCCATCACCCTCTGGTGAAGAACTTCTGCCTAACCCCAAGCCTCCCCTCCCCTGATGCAGCTCCATGCCGTTCCCTCGGGCCCTGTCGCTGTCACAGACAGCAGAGCTCAGTGCTGCCCTTCCTCCTGTGAGGAGCTGTGGCTGCCATGAGGCCTCCCCTCAGCTCCTCCACTCTGTACTGAGTACACTCAGGAACCTCAGCAGCTCCCCTCCAAACCCTTCACCATCTTTGTAGTCCTCCTTTGAACACTCTGATAGTTTTATGTCCTTCATATGTTGTAGCCCCAAAACTTCATGCAGTGCTTGAGCTGAGACTGCACCAATGTGTTTTTGCTGAAGTCCTTTGAAGTTTTACACGTGCCAAGGAGGGTAAAATCTGCTCTGAGCACTGAGACAAAGTTAGCTGATTGACCCCGAGATCTCCTTAAAGCACCAATAGGAGCTCACGGAAGCCTTGACCATACTGTATACTACAATATAGATATATATATTATATATATATCATTTATCTATAATGTAGCTGTATACACTGTATAGTATATATATTTACTATATGTATACTATATAGCATATATGCTACTATACAGTATGTATACTCTATACTCTATCTGGCTTTAAGGGTGCAATGCCTAGATTTCAATATTTCACAATTAAAATCAAA。

[0070] The sequences of the PCR primers for amplifying this SNP are as follows:

[0071] F:GTAGTCCCTTTTGAACACTCTGA (SEQ ID No. 1);

[0072] R: GGGGTCAATCAGCTAACTTTGT (SEQ ID No. 2).

[0073] according to Figure 4 The results of the association analysis between the genotype of the SNP rs794322365 site and the number of eggs produced show that the number of eggs produced by chickens with the TT genotype of the SNP rs794322365 site is significantly higher than that of chickens with the AT genotype and the AA genotype.

[0074] Experimental Example 3: Verification of the validity of the association between SNP rs794322365 molecular marker and egg production

[0075] In order to verify the reliability of the association between the molecular marker of SNP rs794322365 and the number of eggs produced, this experiment used 157 hens from the Beijing Oily Chicken group whose egg production at 500 days of age had been measured (Note: the 157 hens used in this experiment were from a different source than the 150 hen samples in Experimental Example 1 and the 364 hen samples in Experimental Example 2). Restriction fragment length polymorphism analysis (PCR-RFLP) was performed on the significantly associated SNP rs794322365 screened in Experimental Examples 1 and 2 above, and the egg production of hens with different genotypes was compared.

[0076] The PCR amplification system is shown in Table 1, and the PCR amplification parameters are shown in Table 2.

[0077] Table 1 PCR amplification system

[0078]

[0079] Table 2 PCR amplification parameters

[0080] step Temperature and time 1. Pre-denaturation 94℃, 3min 2. Cycle phase 30 cycles transsexual 94℃,30sec annealing 55℃, 30sec extend 72℃, 1min 3. Final extension 72℃, 5min

[0081] The amplified products were sequenced, and the SNP site sequencing results were as follows: Figure 5 As shown; the statistical test results showed that the polymorphism of SNPrs794322365 site was significantly associated with the high and low performance of egg production at 500 days of age (P<0.01) (Table 3).

[0082] Table 3 Comparison of individual phenotypes of laying hens with different genotypes of SNP rs794322365

[0083]

Claims

1. Application of SNP molecular sites related to the trait of egg production in predicting the number of eggs produced by chickens, including: The SNP molecular site associated with the chicken egg production trait corresponds to chromosome 2 139,927,758bp of the chicken reference genome GRC7b version sequence information published on the Ensembl website, where the base is A or T, and the SNP number is rs794322365.

2. The use according to claim 1, characterized in that include: (1) Extracting genomic DNA from the laying hens to be tested; (2) detecting the genotype of the SNP site associated with the trait of egg production in chickens; (3) If the genotype of the SNP site related to the trait of egg production is TT genotype, the egg production of the tested chicken is high; if the genotype of the SNP site related to the trait of egg production is AT genotype or AA genotype, the egg production of the tested chicken is low.

3. The use according to claim 2, characterized in that The method for extracting genomic DNA from the laying hen to be tested in step (1) comprises: collecting blood from the laying hen to be tested, anticoagulating the blood with an anticoagulant, and extracting genomic DNA.

4. The use according to claim 2, characterized in that The method for detecting the genotype of the SNP site related to the egg production trait of laying hens in step (2) includes whole genome resequencing, targeted sequencing or Sanger sequencing.

5. The use according to claim 1, characterized in that The egg production trait is the number of eggs produced at 500 days of age; the chicken to be tested is a young chicken or an early laying hen; preferably, the chicken to be tested is a chicken associated with the egg production trait at 500 days of age.

6. A PCR primer for amplifying a SNP molecular marker associated with the egg production trait of chickens, characterized in that: The PCR primers consist of an upstream primer shown in SEQ ID No. 1 and a downstream primer shown in SEQ ID No.

2.

7. The PCR primer according to claim 6, characterized in that The SNP molecular site associated with the chicken egg production trait corresponds to chromosome 2 139,927,758bp of the chicken reference genome GRC7b version sequence information published on the Ensembl website, where the base is A or T, and the SNP number is rs794322365.

8. Use of the PCR primers according to claim 6 in predicting the number of eggs produced by chickens, comprising: (1) Extracting genomic DNA from the laying hens to be tested; (2) using the genomic DNA extracted from the chicken to be tested as an amplification template, establishing a PCR amplification system using the PCR primers described in claim 6 to perform PCR amplification; sequencing the amplified product to obtain the genotype of the SNP site associated with the chicken egg production trait; (3) If the genotype of the SNP site related to the trait of egg production is TT genotype, the egg production of the tested chicken is high; if the genotype of the SNP site related to the trait of egg production is AT genotype or AA genotype, the egg production of the tested chicken is low.

9. The use according to claim 8, characterized in that The chicken to be tested is a young chicken or an early laying hen; preferably, the chicken to be tested is a chicken associated with the trait of egg production at 500 days of age.

10. A PCR kit for predicting the number of eggs produced by chickens, comprising PCR primers, characterized in that: The PCR primer is the PCR primer according to claim 6.

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