SNP marker related to seminal fluid volume of white-feathered broiler and application thereof

Abstract

The present application relates to the technical field of white-feathered broiler reproductive trait improvement molecular breeding, and particularly relates to SNP markers related to white-feathered broiler semen volume and application thereof. It is found for the first time that SNP markers rs313665848, rs312925749, rs315630382, rs313283202, rs318221479 or rs316183450 are closely related to white-feathered broiler semen volume. The present application increases the estimation accuracy of breeding value by increasing the weight of significant SNPs in the estimation of SSGBLUP method, provides data support for realizing accurate selection of semen volume traits and rapid homozygosis of trait-related alleles, accelerating genetic selection progress, cultivating superior allele sites of the strain in a high frequency or pure state, and avoiding the problem of offspring trait separation to a large extent in the process of applying new strains to the creation of matching lines.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of white-feathered broiler reproductive trait improvement molecular breeding, and particularly relates to a SNP marker related to white-feathered broiler semen volume and application thereof. BACKGROUND

[0002] In the past, the attention of breeding workers was often focused on growth traits in the selection process of white-feathered broilers, and in actual production, growth traits and reproductive traits often showed a negative correlation. The fecundity of white-feathered broilers is poor, and the annual egg production is only 160, which is only equivalent to 60 weeks of egg production of high-yield laying hens. There is less selection for reproductive traits in white-feathered broiler breeding, and one of the most important performances of breeding hens is reproductive performance. Semen volume is an important indicator for measuring the fecundity of breeding roosters, and its advantages and disadvantages directly affect the production performance of offspring and even the economic benefits of broiler breeding.

[0003] In poultry breeding, it is difficult to improve individual reproductive performance by traditional methods. In 2001, Meuwissen et al. proposed (GS), that is, the breeding value is predicted by estimating the effect value of all SNPs in the whole genome. The breeding value obtained by this method is called genomic estimated breeding value (GEBV). Now GS technology has been widely used in cattle, pigs, sheep, and aquaculture.

[0004] Because there are a large number of available SNPs in the chicken genome, GS technology can be used for broiler breeding. Now there are poultry breeding companies in the international community that apply GS technology to poultry breeding. Many reports show that in the selection of complex economic traits, GS technology is applied, combined with pedigree information, phenotype information, and whole-genome association analysis technology, a large number of individual genotypes are detected by SNP chips, which reduces the breeding cost, improves the selection efficiency, shortens the breeding cycle, and improves the selection accuracy by 20%-40% compared with not using GS technology.

[0005] Direct and indirect methods are two methods for estimating GEBV, which are divided into two categories, including GBLUP method and single-step (GBLUP, SSGBLUP) method for directly estimating genomic breeding value, and BayesA, BayesB, RRBLUP method for calculating genomic breeding value through marker effect, and other indirect methods. Compared with other livestock and poultry, the population size of poultry is larger, and the use of Bayes method to weight the effect of SNP is less efficient, so SSGBLUP is most suitable for poultry GS breeding.

[0006] The difference in semen volume in individuals mainly manifests in the group matching of breeding roosters, and the difference in semen volume of roosters, so it can be used as an indicator for measuring the reproductive performance of broiler breeder roosters to guide breeding.

[0007] In summary, under the background of the sharp rise in current poultry breeding costs (feed, labor, environmental control, etc.), the use of SNP integrated genomic selection method for selecting the amount of cock semen can not only save the cost of new strain breeding, but also improve the success rate of matching breeding, and help to improve breeding efficiency. SUMMARY

[0008] The purpose of the present application is to provide a set of significant SNP markers related to the amount of semen of fast-growing white-feathered broilers on chicken chromosome 7 affecting hatching traits.

[0009] The present application is aimed at the breeding and production practice requirements of white-feathered broilers, and by using the amount of semen as a phenotype and whole-genome SNP determination, significant SNP markers for controlling the amount of semen of white-feathered broilers are screened and verified. By increasing the weight of significant SNPs in the estimation of SSGBLUP method, the estimation accuracy of breeding value is improved, which provides data support for accurate selection of complex traits such as the amount of semen and rapid homozygosis of trait-related alleles, speeds up the progress of genetic selection, and cultivates the advantage of allele sites in high frequency or pure state. In the process of applying new strains to the creation of matching systems, the problem of offspring trait separation can be largely avoided.

[0010] In the first aspect, the SNP marker provided by the present application related to the amount of semen of white-feathered broilers has an rs number of rs313665848, rs312925749, rs315630382, rs313283202, rs318221479 or rs316183450.

[0011] In the SNP marker provided by the present application, the polymorphism of rs313665848 is C / T; the polymorphism of rs312925749 is C / T; the polymorphism of rs315630382 is C / T; the polymorphism of rs313283202 is A / T; the polymorphism of rs318221479 is C / A; and the polymorphism of rs316183450 is G / T.

[0012] The SNP marker provided by the present application is obtained by amplification with primers shown in SEQ ID NO. 1-12.

[0013] In the second aspect, the present application provides primers for detecting the SNP marker related to the amount of semen of white-feathered broilers, and the rs number of the SNP marker is rs313665848, rs312925749, rs315630382, rs313283202, rs318221479 or rs316183450.

[0014] The primers for detecting the SNP markers related to the seminal fluid volume of white-feathered broilers are as follows: the primers for detecting the SNP marker rs313665848 are as shown in SEQ ID NO. 1-2; the primers for detecting the SNP marker rs312925749 are as shown in SEQ ID NO. 3-4; the primers for detecting the SNP marker rs315630382 are as shown in SEQ ID NO. 5-6; the primers for detecting the SNP marker rs313283202 are as shown in SEQ ID NO. 7-8; the primers for detecting the SNP marker rs318221479 are as shown in SEQ ID NO. 9-10; and the primers for detecting the SNP marker rs316183450 are as shown in SEQ ID NO. 11-12.

[0015] In a third aspect, the present application provides a reagent or a kit for identifying the seminal fluid volume of white-feathered broilers, wherein the reagent or the kit contains the primers described above.

[0016] According to the understanding of those skilled in the art, the present application also claims the use of the SNP markers described above or the primers described above or the reagent or the kit described above in the identification of high seminal fluid volume poultry, and the use of the SNP markers described above or the primers described above or the reagent or the kit described above in the breeding of poultry.

[0017] In a fourth aspect, the present application provides a breeding method of white-feathered broilers with high reproductive capacity, comprising: using the reagent or the kit described above to determine the genotypes of the SNP markers of a candidate population, and selecting white-feathered broilers in the candidate population according to the genotyping results; and the SNP markers include rs313665848, rs312925749, rs315630382, rs313283202, rs318221479 and rs316183450.

[0018] From the perspective of whole genome analysis, the present application provides a breeding method of white-feathered broilers with high reproductive capacity, comprising:

[0019] (1) establishing a reference population, determining the phenotypic traits and genotypes of the reference population, and determining the SNP marker genotyping of the reference population;

[0020] (2) taking the white-feathered broilers for breeding the next generation as a candidate breeding population, and determining the whole genome SNP sites and genotypes of the candidate breeding population;

[0021] (3) using the phenotypic values of each individual of the reference population, the genotypes of the whole genome 50,000 sites of each individual of the reference population, the whole genome genotypes of each individual of the candidate breeding population, and the pedigree records of the individuals of the reference population and the candidate breeding population.

[0022] (4) according to the size of the GEBV of the candidate breeding population and its live siblings calculated by whole genome selection, the semen volume GEBV of the candidate breeding population is evaluated and sorted in the case of phenotype absence, and the candidate population individuals with high GEBV are selected as parents. Generally, 100-500 cocks are selected, 1000-2000 hens are selected, and a breeding group is formed; or the semen volume GEBV is selected after weighting and index selection with other traits.

[0023] The beneficial effects of the present application are:

[0024] The present application first discovers that the SNP markers rs313665848, rs312925749, rs315630382, rs313283202, rs318221479 or rs316183450 are closely related to the semen volume of poultry. By increasing the weight of significant SNPs in the estimation of the SSGBLUP method, the estimation accuracy of breeding value is improved, which provides data support for realizing accurate selection of complex semen volume traits and rapid homozygosis of trait-related alleles, and accelerating genetic selection progress.

[0025] More specifically, when the SNP markers closely related to the semen volume of poultry provided by the present application are used for genomic selection of semen volume of white-feathered broilers, the accuracy is improved by 8.21%. BRIEF DESCRIPTION OF DRAWINGS

[0026] Figure 1 The sequencing map of the SNP marker rs313665848 of the present application.

[0027] Figure 2 The sequencing map of the SNP marker rs312925749 of the present application.

[0028] Figure 3 The sequencing map of the SNP marker rs315630382 of the present application.

[0029] Figure 4 The sequencing map of the SNP marker rs313283202 of the present application.

[0030] Figure 5 The sequencing map of the SNP marker rs318221479 of the present application.

[0031] Figure 6 The sequencing map of the SNP marker rs316183450 of the present application. DETAILED DESCRIPTION

[0032] The following examples are used to illustrate the present application, but not to limit the scope of the present application.

[0033] Example 1: Obtaining significant SNP markers related to hatching traits

[0034] 1. SNPs significantly associated with hatchability traits obtained by genome-wide association study (GWAS)

[0035] (1) Test animals and determination of target traits

[0036] 337 male chickens of a generation of fast large white-feathered broiler chickens provided by Milu Xinguang Nongmu Technology Co., Ltd. were raised, and the test period was 250d-350d. The semen volume of 300-day-old individuals was determined. A total of 337 male chickens were genotyped, and the semen volume statistics are shown in Table 2. 236 were used for genome-wide association analysis, and the semen volume statistics are shown in Table 1.

[0037] Table 1 Descriptive statistics of semen volume of 236 male chickens

[0038]

[0039] Table 2 Descriptive statistics of semen volume of 337 male chickens

[0040]

[0041] (2) Analysis of correlation between whole genome SNPs and target traits

[0042] All samples were genotyped for whole genome SNPs using "Jingxin No. 1" chicken 55K custom chips. PLINK (V1.90b) software was used to control the quality of chip genotype data, and finally 220 individuals and 41471 SNPs were obtained. The single trait mixed linear model (LMM) in GEMMA (V0.98.1) software (https: / / github.com / genetics-statistics / GEMMA / releases) was used to perform GWAS on the hatchability traits.

[0043] The model includes SNPs as fixed factors and additive polygenic effects as random effects. We use the parameter --indep-pairwise 25 5 0.2 in PLINK (V1.90) software to infer the effective independent test. A total of 6950 independent tests for SNPs throughout the chromosome were obtained. The whole genome significant line and reference line were 1.44E-04 (1.00 / 6,950) and 7.19E-06 (0.05 / 6,950), respectively.

[0044] The single variable linear mixed model implemented in GEMMA version 0.98.1 software was used to perform GWAS analysis on the semen volume trait, and the SNP site information significantly associated with the semen volume trait was finally obtained, as shown in Table 3.

[0045] Table 3 SNP sites information associated with semen volume traits obtained by GWAS

[0046]

[0047] Example 2 Detection of the effect of 6 markers on semen volume

[0048] This example provides the effect of 6 SNP markers and their different genotypes on semen volume of white-feathered broilers, as shown in Table 4; the sequencing results of different genotypes of 6 SNP markers are shown in Table 5. Figure 1 、 Figure 2 、 Figure 3 、 Figure 4 、 Figure 5 and Figure 6 .

[0049] Table 4 Effect of SNP markers on semen volume of white-feathered broilers

[0050]

[0051]

[0052] Example 3 Effect evaluation of genomic selection of semen volume of white-feathered broilers using integrated significant SNP markers

[0053] (1) Using a white-feathered broiler chicken test population, 337 individuals in one generation. Phenotype records the semen volume phenotype of 337 individuals at 300 days of age.

[0054] In this example, the target trait of genomic selection is semen volume of rooster. Whole genome SNP typing is performed using a 55K SNP chip and typing of 6 most significant SNPs, and a kinship matrix is constructed, respectively. Two matrices are given different weights, and combined with a pedigree-based kinship matrix to form a H matrix. Then, 5-fold cross-validation method is used to randomly divide the two-generation population, that is, 335 chickens are randomly divided into 5 uniform groups, 67 chickens in each group. In the 5 uniform groups, 1 group is selected to cover the semen volume phenotype value as the candidate population, and the remaining chickens are used as the reference population.

[0055] (2) Genetic marker quality control

[0056] Common standards are used for quality control of whole genome SNPs: individual genotype detection rate less than 90%, single SNP site detection rate less than 90% and minimum allele frequency less than 5%. Beagle 5.0 software is used to fill in the genotypes of missing SNPs to ensure statistical accuracy and effectiveness.

[0057] (3) Weighted G matrix construction

[0058] Based on the VanRaden algorithm, for the microarray genomic data and 5 SNPs, phylogenetic matrices, namely G1 and Gsnp, were constructed using the A.mat function in the sommer package. The Gsnp matrix was then corrected to the G1 matrix level.

[0059]

[0060] In the formula, This represents adjusting the Gsnp matrix, where Gsnp represents constructing a kinship matrix based on significant SNPs. The formulas for calculating a and b are:

[0061] Avg(diag(Gsnp))*b+a=avg(diag(G1))

[0062] avg(offdiag(Gsnp)*b+a=Avg(offdiag(G1)

[0063] Set G1 and The relative weight formula is:

[0064]

[0065] In the formula, G2 represents the weight matrix G, and G1 and See the formula above. Let c and d be the weighting coefficients respectively.

[0066] (4) Construction of the H matrix

[0067] H-matrix construction is a common method. Correcting the G2 matrix to the level of the sequencing individual phylogenetic kinship matrix (A22):

[0068] G * =e+f*G2

[0069] In the formula, G* represents the adjustment G2 matrix. The formulas for calculating e and f are as follows:

[0070] Avg(diag(G2))*f+e=Avg(diag(A 22 ))

[0071] Avg(offdiag(G2)*f+e=Avg(offdiag(A 22 )

[0072] Let G* and A22 have relative weights in matrix H as G. w = 0.95 * G * + 0.05 * A22. The formula for the H matrix is:

[0073]

[0074] In the formula, H -1 represents the combined pedigree and genomic kinship inverse matrix, A -1 represents the pedigree-based kinship inverse matrix, represents the relative weight G* inverse matrix and represents the is the genotyped individual pedigree kinship inverse matrix.

[0075] (5) Estimate breeding value

[0076] Using the ASReml v4.1 software, the genetic parameters and breeding value of RFI were estimated by using the single trait animal model of the restricted maximum likelihood method (REML). The animal model for estimating genetic force is as follows:

[0077] y = Xb + Za + e,

[0078] In the formula, y represents the observation vector, b represents the fixed effect vector, including batch and gender, a represents the random additive genetic effect vector, and e represents the random residual error effect vector. X and Z represent the correlation matrix of fixed effect and random additive genetic effect, respectively.

[0079] The (co) variance matrix of the random vector is as follows:

[0080]

[0081] In the formula, and respectively represent the additive genetic variance and the residual environmental variance; H represents the combined pedigree and genomic kinship matrix; I represents the unit matrix

[0082] (6) Additive genetic variance proportion calculation

[0083] The G matrix (control group) and Gsnp additive genetic variance were calculated. The results are shown in Table 5.

[0084] Table 5 G matrix (control group) and Gsnp additive genetic variance results

[0085] SNP matrix Additive genetic variance Proportion G matrix (control) 0.02766 - Gsnp 0.00214 - Gsnp / G matrix - 0.077

[0086] After genetic variance calculation, the proportion of significant SNP site additive genetic variance to G matrix (control) additive genetic variance was 0.077, so the weighted weight ratio of significant SNP site was 0.923:0.077.

[0087] (7) Genetic force and cross-validation results, using the caret package in R (V3.6.0) software to generate random numbers. The results are shown in Table 6.

[0088] Table 6 Genetic force and cross-validation results

[0089] SNP matrix weight Heritability Accuracy Percentage of improvement G matrix (control) 0.4414±0.135 0.233924 - H matrix (control) 0.4730±0.139 0.245621 - 0.0.923*G1+0.077*G* snp ]] 0.4152±0.129 0.254849 8.21％

[0090] According to the above cross-validation test results, compared with the one-step method without setting weights for the five significant SNPs, the new method can improve the accuracy by 8.21%, and the optimal weight ratio of the G matrix constructed by significant SNPs to the conventional G matrix is 0.923:0.077. Compared with the breeding value estimation based on the genomic matrix, the accuracy of the one-step method and the accuracy of the present method can both be improved by more than 8%.

[0091] Example 4: Breeding method for genomic selection of white-feathered broiler chicken semen volume by integrating significant SNP markers

[0092] (1) Establishment of reference population, phenotypic trait determination and genotypic determination

[0093] An independent reference population is established for each line, and the source of the reference population is required to cover all existing families of the line. When the reference population of chickens is raised for approximately 52 weeks of age, a population of 1000-1500 chickens is formed as the reference population. The reference population has clear phenotypic records (method see Example 3), pedigree records, blood samples are collected, DNA is extracted, and chicken whole genome SNP chips are sent for testing. The genotypes of 30,000-50,000 whole genome SNP sites evenly distributed are determined. For specific procedures, please refer to the content of the patent "Chicken Whole Genome SNP Chip and Its Application" (Application No.: 201780023241.X). The results of determining the whole genome of about 50,000 sites of each chicken in the reference population are used for the estimation of GEBV in the next step.

[0094] (2) Establishment of the population to be tested and collection of whole genome genotypes

[0095] The population to be tested refers to a candidate breeder population that has no phenotypic trait records and is intended to be used for breeding the next generation. The population to be tested is required to have a kinship within 5 generations with the reference population. The blood samples of the population to be tested are collected as early as possible under the premise of not affecting the survival rate and growth and development of the chickens, and chicken whole genome SNP chips are sent for testing. Then, the whole genome SNP site genotypes are detected and quality controlled by the method in step 3 above.

[0096] (3) Analysis of individual genomic estimated breeding value (GEBV) of the reference population and the candidate population

[0097] Using ① the phenotypic value of each individual in the reference population, ② the genotype of 50,000 whole genome sites of each individual in the reference population, ③ the whole genome genotype of each individual in the population to be tested, and ④ the pedigree records of the reference population and all remaining individual breeders (including the reference population), a total of four types of files are prepared to estimate the genomic estimated breeding value (GEBV) by using this method.

[0098] (4) Selection method of chicken high semen volume line

[0099] According to the size of GEBV of the test population and its on-hand siblings calculated by whole genome selection, the semen volume GEBV of the candidate breeding population is evaluated and ranked in the case of phenotype absence, and the candidate population individuals with high GEBV are selected as parents, generally 100-500 roosters and 1000-2000 hens, and a breeding family is established; or the weighted GEBV is used for index selection with other traits.

[0100] Example 5: Molecular breeding method for white-feathered broiler breeding selection assisted by SNP marker allele state

[0101] The above 6 SNP markers significantly related to semen volume can also be selected and reserved by using common methods, and the specific process is as follows:

[0102] 1. Population to be selected

[0103] Randomly select chickens to be tested. Collect blood from the wing vein after 280 days of age, and store it at -20℃ for standby after ACD anticoagulation.

[0104] 2. DNA extraction

[0105] Genomic DNA is extracted by the conventional phenol simulation method, dissolved in TE, and the purity and concentration of the DNA are detected by agarose gel electrophoresis and ultraviolet spectrophotometry, and then diluted to a concentration of 50 ng / μl.

[0106] 3. PCR reaction and sequence determination

[0107] The primer sequences for amplifying SNPs are shown in Table 7, and the PCR amplification is performed in an ABI Life ProFlex PCR instrument thermal cycler. The PCR reaction program is: 95℃ for 3 min, 95℃ for 30 s, 58℃ for 30 s, 72℃ for 1 min, for a total of 35 cycles; 72℃ for 5 min. The PCR reaction system is 20 μl: template DNA 1 μl, 10 pmol / μl upstream primer 1 μl, 10 pmol / μl downstream primer 1 μl, 2×Master mix 10 μl, and ddH2O 7 μl.

[0108] Table 7 Primer sequences for amplifying SNPs

[0109]

[0110] The amplified products are detected for alleles by direct sequencing or other effective methods. According to the genotyping results, the selection is made: since the screened sites are located on chromosome 7, the amplified products can be detected for alleles by direct sequencing or other effective methods.

[0111] According to the genotyping results, the cock is selected as follows: the genotype of the polymorphic site contained in the marker rs313665848 is CC or TC or TT, and / or the genotype of the polymorphic site contained in the marker rs312925749 is CC or TC or TT, and / or the genotype of the polymorphic site contained in the marker rs315630382 is CC or TC or TT, and / or the genotype of the polymorphic site contained in the marker rs313283202 is TT or AT or AA, and / or the genotype of the polymorphic site contained in the marker rs318221479 is AC or AA or CC, and / or the genotype of the polymorphic site contained in the marker rs316183450 is GG or GT or TT. The healthy cock is selected according to the number of not less than 80 cocks, the ratio of male to female is not less than 1:10, and a new family is established for breeding in the egg laying peak period.

[0112] Although the present application has been described in detail with general description and specific embodiments above, some modifications or improvements can be made on the basis of the present application, which is obvious to those skilled in the art. Therefore, these modifications or improvements made on the basis of not deviating from the spirit of the present application, all belong to the scope of the present application.

Claims

1. The use of a SNP marker related to the seminal fluid volume of white-feathered broilers in marker-assisted selection of white-feathered broilers with high seminal fluid volume, characterized in that, The SNP marker is rs313665848, rs312925749, rs315630382, rs313283202, rs318221479 or rs316183450; The polymorphism of rs313665848 is C / T; the polymorphism of rs312925749 is C / T; the polymorphism of rs315630382 is C / T; the polymorphism of rs313283202 is A / T; the polymorphism of rs318221479 is C / A; and the polymorphism of rs316183450 is G / T; The genotype of the high semen volume white-feather broiler chicken is: The genotype of the SNP marker rs313283202 is TT; The genotype of the SNP marker rs318221479 is CC; The genotype of the SNP marker rs312925749 is CC; The genotype of the SNP marker rs315630382 is CC; The genotype of the SNP marker rs313665848 is CC; The genotype of the SNP marker rs316183450 is GT.

2. Use according to claim 1, characterized in that, The SNP marker is amplified by primers shown in SEQ ID NO. 1-12; The SNP marker is rs313665848, rs312925749, rs315630382, rs313283202, rs318221479 or rs316183450; The primers for detecting the SNP marker rs313665848 are shown in SEQ ID NO. 1-2; the primers for detecting the SNP marker rs312925749 are shown in SEQ ID NO. 3-4; the primers for detecting the SNP marker rs315630382 are shown in SEQ ID NO. 5-6; the primers for detecting the SNP marker rs313283202 are shown in SEQ ID NO. 7-8; the primers for detecting the SNP marker rs318221479 are shown in SEQ ID NO. 9-10; and the primers for detecting the SNP marker rs316183450 are shown in SEQ ID NO. 11-12.

3. Application of the SNP marker in screening high semen volume white-feather broiler chickens; characterized in that The SNP marker is rs313665848, rs312925749, rs315630382, rs313283202, rs318221479 or rs316183450; The application comprises detecting the genotype of the SNP marker, and selecting a white-feather broiler chicken carrying at least one of the following high semen volume dominant genotypes: The genotype of the SNP marker rs313283202 is TT; The genotype of the SNP marker rs318221479 is CC; The genotype of the SNP marker rs312925749 is CC; The genotype of the SNP marker rs315630382 is CC; The genotype of the SNP marker rs313665848 is CC; The genotype of the SNP marker rs316183450 is GT.

4. Application of the SNP marker in white-feathered broiler breeding; characterized in that The rs number of the SNP marker is rs313665848, rs312925749, rs315630382, rs313283202, rs318221479 or rs316183450; The application comprises detecting the genotype of the SNP marker, and selecting a white-feathered broiler carrying at least one high semen volume dominant genotype as a breeding cockerel: The genotype of the SNP marker rs313283202 is TT; The genotype of the SNP marker rs318221479 is CC; The genotype of the SNP marker rs312925749 is CC; The genotype of the SNP marker rs315630382 is CC; The genotype of the SNP marker rs313665848 is CC; The genotype of the SNP marker rs316183450 is GT.

5. A method of breeding high-egg-yield white- feathered broiler chickens, characterized by, The application comprises: The genotype of the SNP marker is determined by using a primer combination, and a white-feathered broiler in the candidate population is selected according to the genotyping result; the SNP marker comprises rs313665848, rs312925749, rs315630382, rs313283202, rs318221479 and rs316183450; The primer for detecting the SNP marker rs313665848 is shown as SEQ ID NO. 1-2; the primer for detecting the SNP marker rs312925749 is shown as SEQ ID NO. 3-4; the primer for detecting the SNP marker rs315630382 is shown as SEQ ID NO. 5-6; the primer for detecting the SNP marker rs313283202 is shown as SEQ ID NO. 7-8; The primer for detecting the SNP marker rs318221479 is shown as SEQ ID NO. 9-10; the primer for detecting the SNP marker rs316183450 is shown as SEQ ID NO. 11-12 According to the genotyping result, a white-feathered broiler carrying a high semen volume dominant genotype is selected as a parent for subsequent breeding; wherein The high semen volume dominant genotype is: The genotype of the SNP marker rs313283202 is TT; The genotype of the SNP marker rs318221479 is CC; The genotype of the SNP marker rs312925749 is CC; The genotype of the SNP marker rs315630382 is CC; The genotype of the SNP marker rs313665848 is CC; The genotype of the SNP marker rs316183450 is GT.

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