Method for evaluating reproductive performance of sows

Abstract

The invention discloses a method for evaluating the reproductive performance of sows. The reproductive performance is at least one of the number of healthy piglets, the number of weak piglets and the weaning litter weight. According to the specific method, genotypes based on an SNP site 1, an SNP site 3, an SNP site 4, an SNP site 7, an SNP site 10, an SNP site 11 and / or an SNP site 12 in a sow genome are detected, so that the reproductive performance of the sow is evaluated or assisted to be evaluated. The method has the advantages of being reliable in result, high in repeatability and high in accuracy, is suitable for stage-by-stage management of reproductive performance of sows in a pig farm and breeding of boars, and has important application prospects and popularization value in modern breeding.

Description

Technical Field

[0001] The invention belongs to the field of biotechnology, and in particular relates to a method for evaluating sow reproductive performance. Background Art

[0002] Sow reproductive efficiency directly impacts pig farm profitability and population improvement. However, because reproductive traits are complex quantitative traits with low heritability and regulated by multiple factors, rapid genetic improvement is difficult to achieve using conventional breeding methods. By identifying functional genes and genetic variants associated with target breeding traits and combining them with molecular breeding techniques, reproductive performance and breeding efficiency can be significantly improved.

[0003] In the pig farming industry, piglet number and weaning litter weight are important indicators of sow reproductive performance. Litter number is one of the core indicators of sow reproductive performance and is often used as a key indicator of pig farm production efficiency. Litter weight at weaning is a key indicator for assessing piglet early growth and survival. A sow's milk production and milk quality directly impact piglet weaning litter weight. Sows with strong lactation ability provide adequate nutrition for their piglets, promoting their growth. Larger litter weights indicate more vigorous piglets, faster growth, and greater disease resistance. Therefore, piglet number and weaning litter weight are not only directly related to a farm's reproductive efficiency and economic benefits, but also reflect the health of the herd. Continuously improving these two indicators through scientific breeding and improvement is a key path to achieving high-quality and efficient development in the pig farming industry.

[0004] With the widespread use of commercial single nucleotide polymorphism (SNP) microarrays and the rapid development of genome sequencing technology, the use of genome-wide association studies (GWAS) to identify SNPs or major genes that influence sow reproductive performance has become a research hotspot. Numerous studies have identified candidate genes on different chromosomes that are significantly associated with key reproductive indicators such as total litter size, number of live piglets, and number of healthy piglets. However, since most of the significant SNPs identified by SNP microarray-based GWAS are not located within genes, identifying specific candidate genes is difficult, and analysis of their genetic effects is lacking, resulting in their underutilization in practical breeding applications. Summary of the Invention

[0005] The purpose of the present invention is to evaluate the reproductive performance of sows, especially the number of healthy piglets, the number of weak piglets and the weaning litter weight.

[0006] The present invention firstly protects a method for evaluating the number of healthy piglets in the reproductive performance of sows, which may include the following steps: detecting whether the genotype of the sow to be tested is AA homozygous, AG heterozygous, or GG homozygous based on SNP site 1, and then making the following judgment: the number of healthy piglets of sows whose genotype is AA homozygous based on SNP site 1> the number of healthy piglets of sows whose genotype is AG heterozygous based on SNP site 1> the number of healthy piglets of sows whose genotype is GG homozygous based on SNP site 1;

[0007] The SNP site 1 is the 67th nucleotide from the 5' end of SEQ ID NO: 1 in the pig genome.

[0008] The present invention also protects a method for evaluating the number of weak piglets in the reproductive performance of sows, which may include the following steps: detecting whether the genotype of the sow to be tested is CC homozygous, CT heterozygous, or TT homozygous based on SNP site 3, whether the genotype based on SNP site 4 is GG homozygous, AG heterozygous, or AA homozygous, and / or whether the genotype based on SNP site 7 is AA homozygous, AG heterozygous, or GG homozygous, and then performing the following judgment:

[0009] The number of weak piglets of sows whose genotype at SNP site 3 is CC homozygous is greater than the number of weak piglets of sows whose genotype at SNP site 3 is CT heterozygous or TT homozygous; the SNP site 3 is the 78th nucleotide from the 5' end of SEQ ID NO: 2 in the pig genome;

[0010] The number of weak piglets of sows whose genotype at SNP site 4 is GG homozygous is greater than the number of weak piglets of sows whose genotype at SNP site 4 is AG heterozygous or AA homozygous; the SNP site 4 is the 79th nucleotide from the 5' end of SEQ ID NO: 3 in the pig genome;

[0011] The number of weak piglets of sows whose genotype at SNP site 7 is GG homozygous is greater than the number of weak piglets of sows whose genotype at SNP site 7 is AA homozygous or AG heterozygous; the SNP site 7 is the 76th nucleotide from the 5' end of SEQ ID NO: 4 in the pig genome.

[0012] The present invention also protects a method for evaluating the weaning litter weight in the reproductive performance of sows, which may include the following steps: detecting whether the genotype of the sow to be tested is AA homozygous, AG heterozygous, or GG homozygous based on SNP site 10, whether the genotype based on SNP site 11 is CC homozygous, CT heterozygous, or TT homozygous, and / or whether the genotype based on SNP site 12 is AA homozygous, AC heterozygous, or CC homozygous, and then performing the following judgment:

[0013] The weaning litter weight of sows whose genotype at SNP site 10 is AG heterozygous or GG homozygous is greater than the weaning litter weight of sows whose genotype at SNP site 10 is AA homozygous; the SNP site 10 is the 204th nucleotide from the 5' end of SEQ ID NO: 5 in the pig genome;

[0014] The weaning litter weight of sows whose genotype at SNP site 11 is CT heterozygous or TT homozygous is greater than the weaning litter weight of sows whose genotype at SNP site 11 is CC homozygous; the SNP site 11 is the 236th nucleotide from the 5' end of SEQ ID NO: 5 in the pig genome;

[0015] The weaning litter weight of sows whose genotype at SNP site 12 is AC heterozygous or CC homozygous is greater than the weaning litter weight of sows whose genotype at SNP site 12 is AA homozygous; the SNP site 12 is the 76th nucleotide from the 5' end of SEQ ID NO: 6 in the pig genome.

[0016] The present invention also protects a kit for evaluating the reproductive performance of sows, which may include substance A for detecting the genotype of the sow to be tested based on SNP site 1, substance B for detecting the genotype of the sow to be tested based on SNP site 3, substance C for detecting the genotype of the sow to be tested based on SNP site 4, substance D for detecting the genotype of the sow to be tested based on SNP site 7, substance E for detecting the genotype of the sow to be tested based on SNP site 10, substance F for detecting the genotype of the sow to be tested based on SNP site 11, and / or substance G for detecting the genotype of the sow to be tested based on SNP site 12.

[0017] SNP site 1 is the 67th nucleotide from the 5′ end of SEQ ID NO: 1 in the pig genome;

[0018] SNP site 3 is the 78th nucleotide from the 5' end of SEQ ID NO: 2 in the pig genome;

[0019] SNP site 4 is the 79th nucleotide from the 5' end of SEQ ID NO: 3 in the pig genome;

[0020] SNP site 7 is the 76th nucleotide from the 5' end of SEQ ID NO: 4 in the pig genome;

[0021] SNP site 10 is the nucleotide 204 from the 5′ end of SEQ ID NO: 5 in the pig genome;

[0022] SNP site 11 is the nucleotide 236 from the 5′ end of SEQ ID NO: 5 in the pig genome;

[0023] SNP site 12 is the 76th nucleotide from the 5' end of SEQ ID NO: 6 in the pig genome.

[0024] In the above-mentioned kit, the substance A can be used to evaluate the number of healthy piglets in the reproductive performance of sows.

[0025] In the above kit, the substance B, substance C and / or substance D can be used to evaluate the number of weak piglets in the reproductive performance of sows.

[0026] In the above kit, the substance E, substance F and / or substance G can be used to evaluate the weaning litter weight in the reproductive performance of sows.

[0027] Any of the above-mentioned kits may specifically be composed of at least one of substance A, substance B, substance C, substance D, substance E, substance F and substance G.

[0028] The present invention also protects molecular markers, which may include molecular marker A shown in SEQ ID NO: 1, molecular marker B shown in SEQ ID NO: 2, molecular marker C shown in SEQ ID NO: 3, molecular marker D shown in SEQ ID NO: 4, molecular marker E shown in SEQ ID NO: 5, and / or molecular marker F shown in SEQ ID NO: 6.

[0029] Use of any of the above-mentioned kits or any of the above-mentioned molecular markers in evaluating sow reproductive performance.

[0030] Use of any of the above-mentioned kits or any of the above-mentioned molecular markers in screening sows with high reproductive performance.

[0031] Use of any of the above-mentioned kits or any of the above-mentioned molecular markers in sow breeding; the purpose of sow breeding is to cultivate sow breeds with high reproductive performance.

[0032] In any of the above applications, the reproductive performance is at least one of the number of healthy piglets, the number of weak piglets and the weaning litter weight.

[0033] In any of the above applications, high reproductive performance may be a high number of healthy piglets, a low number of weak piglets and / or a high litter weight at weaning.

[0034] Any of the above-mentioned sows with a high number of healthy piglets can specifically be a sow whose genotype based on the SNP site 1 is AA homozygous.

[0035] Any of the above-mentioned sows with low piglet number can specifically be a sow whose genotype based on the SNP site 3 is CT heterozygous or TT homozygous, a sow whose genotype based on the SNP site 4 is AG heterozygous or AA homozygous, or a sow whose genotype based on the SNP site 7 is AA homozygous or AG heterozygous.

[0036] Any of the above-mentioned sows with high litter weight can specifically be a sow whose genotype based on the SNP site 10 is AG heterozygous or GG homozygous, a sow whose genotype based on the SNP site 11 is CT heterozygous or TT homozygous, or a sow whose genotype based on the SNP site 12 is AC heterozygous or CC homozygous.

[0037] In the above, the > may specifically be a statistical >.

[0038] The breed of any of the above-mentioned sows can be Large White, Landrace or Duroc.

[0039] Any of the above-mentioned pigs can be a Large White pig, a Landrace pig or a Duroc pig.

[0040] The present invention conducts GWAS research on sow reproductive traits based on whole genome resequencing data. Significant SNP sites can be directly located inside the gene. Combined with molecular breeding technology, high-fertility sows can be accurately selected to accelerate the breeding process of sow reproductive traits. At the same time, the inventors of this application have experimentally proved that by detecting the genotype based on the SNP site 1, the genotype based on the SNP site 3, the genotype based on the SNP site 4, the genotype based on the SNP site 7, the genotype based on the SNP site 10, the genotype based on the SNP site 11 and / or the genotype based on the SNP site 12 in the sow genome, the reproductive performance of the sow can be evaluated or assisted in the evaluation, and the results are reliable, stable and accurate. The present invention is suitable for large-scale group detection and has important application value. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] Figure 1 This is the distribution structure of the Large White pig population.

[0042] Figure 2 The Manhattan plot and QQ-Plot plot of the total litter size in the association analysis in step 4 of Example 2 are shown.

[0043] Figure 3 The Manhattan plot and QQ-Plot plot of the number of healthy individuals in the association analysis in step 4 of Example 2 are shown.

[0044] Figure 4 The Manhattan plot and QQ-Plot plot of the number of piglets born alive in the association analysis in step 4 of Example 2 are shown.

[0045] Figure 5 This is the Manhattan plot and QQ-Plot diagram of the number of teats weaned after the correlation analysis in step 4 of Example 2.

[0046] Figure 6 The Manhattan plot and QQ-Plot diagram of the number of weak offspring in the association analysis in step 4 of Example 2 are shown.

[0047] Figure 7 This is the Manhattan plot and QQ-Plot plot of weaning litter weight after the association analysis in step 4 of Example 2.

[0048] Figure 8 These are the Manhattan plot and QQ-Plot graph of the corrected 21-day-old litter weight in the association analysis in step 4 of Example 2.

[0049] Figure 9 The Manhattan plot and QQ-Plot plot of the newborn litter weight in the association analysis in step 4 of Example 2 are shown.

[0050] Figure 10 These are the Manhattan plot and QQ-Plot graph of the mummy in the association analysis in step 4 of Example 2.

[0051] Figure 11 The Manhattan plot and QQ-Plot plot of stillbirth in the association analysis in step 4 of Example 2 are shown. DETAILED DESCRIPTION

[0052] The present invention will be further described in detail below in conjunction with specific embodiments. The examples provided are only for illustrating the present invention and are not intended to limit the scope of the present invention. The examples provided below can serve as a guide for further improvements by those skilled in the art and are not intended to limit the present invention in any way.

[0053] Unless otherwise specified, the experimental methods in the following examples are conventional methods and were performed according to the techniques or conditions described in the literature in the field or according to the product instructions. The materials and reagents used in the following examples, unless otherwise specified, were all commercially available.

[0054] The quantitative tests in the following examples were all repeated three times, and the results were averaged.

[0055] Example 1: Whole-genome resequencing analysis of Large White pigs and detection of SNP sites

[0056] 1. Obtaining genomic DNA from pig ear tissue

[0057] Ear tissues of 656 Large White pigs were collected, and genomic DNA was extracted using a blood / cell / tissue genomic DNA extraction kit (Beijing Tiangen Biochemical Technology Co., Ltd.), thus obtaining genomic DNA from the ear tissues of 656 Large White pigs.

[0058] The specific steps are as follows:

[0059] 1. Crush the pig ear tissue to prepare a cell suspension, then centrifuge at 12,000 rpm for 1 minute. Pour off the supernatant, add 200 μl of Buffer GA, and shake until the cell suspension is completely suspended.

[0060] 2. Add 20 μl of Proteinase K to the solution obtained in step 1, mix well, and digest overnight at 56°C in a molecular hybridization oven until the tissue is dissolved. Briefly centrifuge to remove water droplets on the inner wall of the tube cap.

[0061] 3. Add 200 μl of Buffer GB to the solution obtained in step 2, mix thoroughly by inversion, and incubate at 70°C for 10 minutes. The solution should become clear. Centrifuge briefly to remove water droplets on the inner wall.

[0062] 4. Add 200 μl of anhydrous ethanol to the solution obtained in step 3 and mix thoroughly by shaking for 15 seconds. Then, perform a short centrifugation to remove water droplets on the inner wall of the tube cap.

[0063] 5. Add the solution and flocculent precipitate obtained in step 4 to the adsorption column CB3 (the adsorption column CB3 is placed in the collection tube), centrifuge at 12,000 rpm for 30 seconds, pour out the waste liquid, and then place the adsorption column CB3 back in the collection tube.

[0064] 6. After completing step 5, add 500 μl of Buffer GD (diluted with anhydrous ethanol before use) to the adsorption column CB3, centrifuge at 12,000 rpm for 30 seconds, pour out the waste liquid, and then place the adsorption column CB3 back in the collection tube.

[0065] 7. After completing step 6, add 600 μl of Buffer PW (diluted with anhydrous ethanol before use) to the adsorption column CB3, centrifuge at 12,000 rpm for 30 seconds, pour out the waste liquid, and then place the adsorption column CB3 back in the collection tube.

[0066] 8. After completing step 7, add 600 μl of Buffer PW (diluted with anhydrous ethanol before use) to the adsorption column CB3, centrifuge at 12,000 rpm for 30 seconds, pour out the waste liquid, and then place the adsorption column CB3 back in the collection tube.

[0067] 9. After completing step 8, centrifuge at 12,000 rpm for 2 minutes and discard the waste liquid; then, leave it at room temperature for 3 minutes to allow the residual liquid in the adsorption material to completely evaporate.

[0068] 10. After completing step 9, transfer the adsorption column CB3 to a new centrifuge tube. Slowly add 80 μl of Buffer TE to the center of the tube and let it sit for 2-5 minutes to allow for a complete reaction. Then, centrifuge at 12,000 rpm for 2 minutes and collect the liquid in a centrifuge tube. The liquid in the centrifuge tube is the genomic DNA from the pig ear tissue.

[0069] Adsorption column CB3, Buffer GA, Buffer GB, Buffer GD, Buffer PW, and Buffer TE are all components of the blood / cell / tissue genomic DNA extraction kit.

[0070] Considering the strict requirements of DNA chip hybridization experiments on DNA quality, genomic DNA that does not meet the standards needs to be re-extracted. The requirements for genomic DNA that meets the standards are as follows: the concentration of DNA is higher than 50ng / μl, the OD 260nm / OD 280nm The ratio of DNA to PCR products was between 1.8 and 2.0, and the DNA bands were clear and had no tailing when detected by agarose gel electrophoresis.

[0071] 11. Take 1 μl of the genomic DNA from the pig ear tissue obtained in step 10 and use the NanoDrop 2000 nucleic acid analyzer to determine its concentration and OD 260nm and OD 280nm .

[0072] The results showed that the concentration of genomic DNA in ear tissues of 656 large white pigs was higher than 50 ng / μl, and the OD 260nm / OD 280nm The ratios are all between 1.8 and 2.0.

[0073] 12. Take 1 μl of the genomic DNA from the pig ear tissue obtained in step 10 and check its integrity by 1% agarose gel electrophoresis.

[0074] The results showed that the DNA bands of genomic DNA from ear tissues of 656 Large White pigs were clear and had no tailing phenomenon, indicating that the DNA quality was good.

[0075] 2. Genome Resequencing Data Analysis and SNP Detection

[0076] 1. Whole-genome resequencing of the genomic DNA of ear tissues of 656 large white pigs obtained in step 1 was performed at a sequencing depth of 50×. The raw image data files obtained by sequencing were then converted into raw sequencing sequences (Raw Reads) using Fastp software through base calling analysis.

[0077] 2. Sequencing data quality control

[0078] The original sequencing sequence obtained in step 1 was quality controlled, including removing readpairs with adapters, paired reads in which the N content in the single-end sequencing reads exceeded 10% of the read length ratio, and reads containing low-quality (Q≤5) bases exceeding 50% of the read length ratio to obtain clean reads.

[0079] 3. After completing step 2, use BWA software to align the quality-controlled clean reads to the porcine reference genome (Sscrofa11.1) to generate a sam file. Use the view command of Samtools software to convert the sam file to bam format and sort the bam file using the sort command.

[0080] 4. Comparison quality assessment

[0081] The flagstat module of Samtools (1.9) software was used to calculate the alignment rate of paired-end reads to the reference genome to evaluate the quality of sequencing data and alignment efficiency.

[0082] 5. Use the GATKHaplotypeCaller command to generate a gVCF file for each sample, then use the CombineGVCFs command to merge all individual gVCF files into a total gVCF file, and then use the GenotypeGVCFs command to convert the total gVCF file into a VCF file, and use the SelectVariants command to screen SNP sites.

[0083] 6. GATK VariantFiltration was used to perform hard filtering on the resequencing data with the filtering conditions of QD<2.0||QUAL<30.0||SOR>3.0||FS>60.0||MQ<40.0||MQRankSum<-12.5||ReadPosRankSu m<-8.0. After filtering, 41,919,442 valid SNPs were obtained.

[0084] Example 2: Genome-wide association analysis of sow reproductive traits based on the sequencing data of Example 1

[0085] 1. Filling and quality control of experimental population SNP chip data based on sequencing data of Example 1

[0086] 1. The 41,919,442 valid SNPs obtained in Example 1 were used as the haplotype reference panel for populating a SNP chip (i.e., a commercially available 50K SNP chip, "Semiconductor One") from a 4,996-person Large White sow experimental population. All SNP chip data were populated to the sequencing data level using Beagle (v5.1) software. The populated SNP data were quality-controlled again using Plink software. Specific quality control standards were as follows:

[0087] (1) Eliminate sites with a single SNP detection rate of less than 95%;

[0088] (2) samples with a site deletion rate greater than 5% were eliminated;

[0089] (3) Eliminate sites with Hardy-Weinberg equilibrium test P < 1E-6;

[0090] (4) Eliminate sites with a minor allele frequency (MAF) less than 0.05.

[0091] After quality control, 4992 individuals and 32866 SNPs sites were retained for subsequent genotype filling.

[0092] 2. Use Beagle (v5.1) to fill the 50K SNP chip after quality control to the sequencing level and perform quality control on the genotype data after filling. The specific quality control standards are as follows:

[0093] (1) Eliminate sites with a single SNP detection rate of less than 95%.

[0094] (2) samples with a site deletion rate greater than 5% were eliminated;

[0095] (3) Eliminate sites with Hardy-Weinberg equilibrium test p < 1E-6;

[0096] (4) Eliminate sites with a minor allele frequency (MAF) less than 0.05.

[0097] After quality control, 4992 individuals and 6531642 SNPs sites were retained for subsequent whole-genome association analysis.

[0098] 2. Analysis of experimental group structure

[0099] Population genetic stratification can influence the results of association analyses, potentially leading to biased results and false-positive or false-negative results. In this study, principal component analysis (PCA) was performed on the genotype data obtained in step 1 using Plink (V1.90). Scatter plots were generated using R (R version 4.4.0). Based on the PCA results, the first two principal components were added to the genome-wide association analysis model to eliminate the influence of population stratification.

[0100] The distribution of the Large White pig population is shown in Figure 1 .

[0101] 3. Estimation of breeding values ​​for sow reproductive traits

[0102] A total of 10,058 French and American sows were used as the study population. A total of 37,166 raw phenotypic data for all reproductive traits and 244,584 raw pedigree data were collected between 2012 and 2022. Breeding values ​​for 10 sow reproductive traits, including total number born (TNB), number born alive (NBA), number of healthy born (NHB), number of weak born (NWB), stillbirth (SB), mummy (MUM), litter birth weight (LBW), number of piglets weaned (NPW), weaning litter weight (WWT), and adjusted 21-day litter weight (ALW21), were estimated using DMU software. Data were organized using R (version 4.4.0).

[0103] The DMU program requires three input files: a data file, a pedigree file, and a parameter file. The pedigree and data files are presented in purely numerical format, while the parameter file can contain additional information. The pedigree file primarily consists of the individual number, sire number, and dam number; the data file includes information such as the individual number, fixed effects, random effects, and phenotypic values. Integer variables (such as field, year, season, and sex) should be placed first, while real variables (such as total litter size and number of piglets born alive) should be placed after. Missing values ​​should be replaced with -999.

[0104] The breeding values ​​of 10 reproductive traits of 10,058 sows were estimated using a replicated model. The model is as follows:

[0105] Y=Xb+Za+Wpe+e(Formula I);

[0106] Y is the reproductive trait phenotype vector, b is the fixed effect vector of farm year, season, parity and strain, X is the correlation matrix of fixed effect b; a is the additive random effect vector, Z is the correlation matrix of the additive random effect a, is the individual additive genetic variance, A is the kinship matrix based on pedigree; pe is the individual permanent environmental effect vector,; W is the association matrix of the permanent environmental effect vector, e is the random residual effect vector, is the residual variance, and I is the identity matrix.

[0107] Fixed effects included farm-year-season, parity, and strain. The farm effect was divided into four levels (farms 1-4) based on the sow's farrowing farm; the year effect was divided into ten levels (2013 to 2022) based on the sow's farrowing year; the season effect was divided into four levels based on the time of farrowing (spring: March-May, summer: June-August, autumn: September-November, winter: December-February); the parity effect was divided into seven levels (parities 1-7) based on the sow's farrowing number; and the strain effect was divided into six levels (French Large White, American Large White, French Landrace, American Landrace, French Duroc, and American Duroc). In addition, individual number was treated as a random effect.

[0108] 4. Genome-wide association analysis of sow reproductive traits

[0109] The genome-wide association analysis was performed using GEMMA software, and the model was as follows:

[0110] Y=Xβ+Zα+Wa+e (Formula II);

[0111] Where Y is the breeding value vector of a certain reproductive trait of an individual; β is the fixed effect vector, including the first two principal components, α is the SNP effect value vector, and a is the remaining polygenic effect vector, which follows a normal distribution. in is the additive genetic variance, G is the SNP-based genomic kinship matrix; X, Z, and W are the association matrices of β, α, and a, respectively, and e is the normal distribution. The random residuals of , I is the identity matrix, is the residual variance.

[0112] The Bonferrini method was used to correct for multiple testing and determine the significance threshold for SNP statistical testing. 0.05 / N = 0.05 / 6531642 = 7.66E-9; the genomic potential significance threshold was set at 1 / N = 1 / 6531642 = 1.53E-7, where N is the number of SNPs analyzed. Manhattan plots and QQ-Plot plots were drawn using the CMplot package in R software. Specific trait results are shown in [ 1 ]. Figure 2-Figure 11 .

[0113] A genome-wide association study was performed for all reproductive traits, and after multiple testing and correction, 90 significant SNPs were identified. Functional gene annotation of these 90 significant SNPs was performed using the porcine reference genome Sscrofa11.1 in the Ensemble database. Ultimately, 12 significant SNPs within six genes (HS3ST4, PDE4DIP, MGAT4C, CDYL, CAMK1D, and SP2) were identified, reaching chromosomal significance. These SNPs are located on chromosomes 3, 4, 5, 7, 10, and 12, respectively. Detailed information is shown in Table 1.

[0114] Table 1. Information on significant SNP sites within genes in genome-wide association analysis

[0115]

[0116]

[0117] V. Variance analysis of reproductive phenotypes of sows with different genotypes at significant SNP sites

[0118] Using R software, we performed population-level variance analysis between different genotypes and reproductive trait phenotypes at the 12 significant SNPs identified through genome-wide association analysis. Specifically, we used analysis of variance (ANOVA) and post hoc tests (Tukey HSD) to assess whether there were significant differences in reproductive trait phenotypes between individuals with different genotypes. The results identified seven SNPs with significant differences in the phenotypic values ​​of three reproductive traits between different genotype groups. For one SNP, there was a significant difference in the number of healthy piglets born between different genotype groups; for three SNPs, there was a significant difference in the number of weak piglets born between different genotype groups; and for three SNPs, there was a significant difference in litter weight at weaning between different genotype groups. Details are shown in Table 2.

[0119] Table 2. Results of phenotypic variance analysis of reproductive traits among different genotype populations at 7 significant SNP sites

[0120]

[0121]

[0122] Note: a, b, and c in the table represent the significance level. The same letters indicate no significant difference between the groups (P≥0.05), and different letters indicate significant difference (P<0.05).

[0123] The results showed that SNP1, SNP4, SNP3, SNP7, SNP10, SNP11 and SNP12 were all significantly associated with sow reproductive performance phenotypes; specifically as follows:

[0124] Different genotypes at the SNP1 locus have a significant effect on healthy piglet number: as the frequency of the A allele decreases, the average estimated breeding value of healthy piglet number decreases significantly. This shows that the frequency of the A allele at the SNP1 locus is significantly associated with the healthy piglet number phenotype. The AA homozygous type has a clear advantage in the phenotype of healthy piglet number in sow reproduction, and individuals with the A allele should be considered in breeding practices.

[0125] Different genotypes at SNP3 have a significant effect on weak piglet size: as the frequency of the C allele decreases, the average estimated breeding value for weak piglet size decreases significantly. This suggests that the frequency of the C allele at SNP3 is significantly associated with the weak piglet size phenotype, and that the TT homozygous genotype has a clear advantage in promoting weak piglet size in sows. Therefore, individuals with the C allele should be considered for elimination in breeding practices.

[0126] Different genotypes at SNP4 have a significant effect on weak piglet size: as the frequency of the G allele decreases, the average estimated breeding value for weak piglet size decreases significantly. This suggests that the frequency of the G allele at SNP4 is significantly associated with the weak piglet size phenotype, and that the AA homozygous genotype has a clear advantage in promoting weak piglet size in sow reproduction. Therefore, individuals with the G allele should be considered for elimination in breeding practices.

[0127] Different genotypes at SNP7 have a significant effect on weak piglet size: as the frequency of the G allele decreases, the average estimated breeding value for weak piglet size decreases significantly. This suggests that the frequency of the G allele at SNP7 is significantly associated with the weak piglet size phenotype, and that the AA homozygous genotype has a clear advantage in promoting weak piglet size in sow reproduction. Therefore, individuals with the G allele should be considered for elimination in breeding practices.

[0128] Different genotypes at SNP10 have a significant effect on weaning litter weight: as the frequency of the G allele decreases, the average estimated breeding value of weaning litter weight decreases significantly. This suggests that the frequency of the G allele at SNP10 is significantly associated with the weaning litter weight phenotype, and that the GG homozygous phenotype has a clear advantage in achieving the weaning litter weight phenotype during sow reproduction. Therefore, individuals with the G allele should be considered in breeding practices.

[0129] Different genotypes at SNP11 have a significant effect on weaning litter weight: as the frequency of the T allele decreases, the average estimated breeding value of weaning litter weight decreases significantly. This suggests that the frequency of the T allele at SNP11 is significantly associated with the weaning litter weight phenotype, and that the TT homozygous phenotype has a clear advantage in achieving weaning litter weight in sow reproduction. In breeding practices, individuals with the T allele should be considered for retention.

[0130] Different genotypes at SNP12 have a significant effect on weaning litter weight: as the frequency of the C allele decreases, the average estimated breeding value of weaning litter weight decreases significantly. This suggests that the frequency of the C allele at SNP12 is significantly associated with the weaning litter weight phenotype, and that CC homozygotes have a clear advantage in achieving the weaning litter weight phenotype during sow reproduction. Therefore, individuals with the C allele should be considered in breeding practices.

[0131] According to the genome sequencing results, the locations of the above 7 SNP sites in the Large White pig genome are as follows:

[0132] SNP site 1 is the 67th nucleotide from the 5' end of SEQ ID NO: 1 in the Large White pig genome;

[0133] SNP site 3 is the 78th nucleotide from the 5' end of SEQ ID NO: 2 in the Large White pig genome;

[0134] SNP site 4 is the 79th nucleotide from the 5' end of SEQ ID NO: 3 in the Large White pig genome;

[0135] SNP site 7 is the 76th nucleotide from the 5' end of SEQ ID NO: 4 in the Large White pig genome;

[0136] SNP site 10 is the 204th nucleotide from the 5' end of SEQ ID NO: 5 in the Large White pig genome;

[0137] SNP site 11 is the nucleotide at position 236 from the 5′ end of SEQ ID NO: 5 in the Large White pig genome;

[0138] SNP site 12 is the 76th nucleotide from the 5' end of SEQ ID NO: 6 in the Large White pig genome.

[0139] TTTTGCTTTTTAGGGCCACACCTGTGGCAGGTTCACAGGCTAGGGGTCAAA TCAGAGATCTGGTTGRCAGCCTATGCCACAGTCACAGCAACGCAGGAACTGAG CTGCATCTGCGACCTACACCACAGCTCATGGCAATCCAACTAGTATC(R is G / A)

[0140] (SEQ ID NO:1)

[0141] AATGGTACAATGAATTCAGTATTGTGATGACTGTGTGATTTTCGTAGATCTTT CTTCTAATCCATATTGATTGTGGAYATATTACATTGCTACTAAAGTAGCTGAAGCA AAACTCAGCCTTTGGTTACCTTGGAAATCCTCAATTTGTTTA(Y is T / C)(SEQ ID NO:2)

[0142] TACTGTATAGCACAGAGAACTACATCCAGTCTCTTGGAATAGACCATGATGGA AGATAATATGAGAAAAAGAATGTGTRTGTGTATATATATATATGTATGACTGAGTCAT ATAATCTGTTGAGAATAATATAGACATTACTGCTTGTTCA(R is A / G)(SEQ ID NO:3)

[0143] CCGTGTCAGAGCCCTAAGCCCCTGCCCTCCACCTGTAGTACAGAACTCAAGT ACCCACAGAGGTTGAATGAAACCRCCAATGAATAATAGAATCCTGTCTTTCAAAG AAGAAATGAGCTCCCAAACTGAAGCGAGCTACTCTTTCCTCGTG(R is G / A)(SEQ ID NO:4)

[0144] ACCATCCCCCAGTGGCCCCCACTCACTTCTCCAGGGTCCCTTCCATAAGATAGGATGCCGATGAGCAAGGGACACAGTCAGGTGTTCAGGAGAGAGATTCAGGGTGGAGACAGCTAAAGAGGTATTCAGATGGCAGGTCCCTCATCGTCTTAACTCCTCAGGACGAGTGAACTGAAAGAAGCATTGAGATGGGGGTGCCTGGTRTGTGC TGTTGAGGTGTGCTTTGAGATTTCYGTCTAGGATGGGGATGGGTCTGTGCCGGCCCGTGCCCAGGCTCTAGTCCCCAGGTGAGGGGACTGGCAGGGTGAGAGCTCCCTCTGGGACTGGAATTGGCTGAGCTGACCTAGTGAGGGGATCCCAGCCTGGCGCCAGGATAGGCAGGCTTTGTCCTTTGGTTC (R is A / G, Y is C / T) (SEQ ID NO:5)

[0145] AGTTTCCATTGTGGTTCAGCAGTAACAAACCCAACTAGTATCCATGAGGATGC AGCTTTGATCCCTGGCCTCGCTMAGTGGGTTCAGGATCCAGCTTTGCTGTGAGCT GCAGTGTAGGTTGCAGACCATGATTTGGATCTGGTTTGGCTGT (M is A / C) (SEQ ID NO: 6)

[0146] The present invention has been described in detail above. For those skilled in the art, without departing from the purpose and scope of the present invention, and without the need to carry out unnecessary experimental conditions, the present invention can be implemented in a wide range under equivalent parameters, concentrations and conditions. Although the present invention provides specific embodiments, it should be understood that further improvements can be made to the present invention. In short, according to the principles of the present invention, this application is intended to include any changes, uses or improvements to the present invention, including changes that depart from the disclosed scope in this application and are made using conventional techniques known in the art.

Claims

1. A method for evaluating the number of healthy piglets in sow reproductive performance, comprising the following steps: detecting whether the genotype of the sow to be tested is AA homozygous, AG heterozygous, or GG homozygous based on SNP site 1, and then making the following judgment: The number of healthy piglets of sows whose genotype at SNP site 1 is AA homozygous>the number of healthy piglets of sows whose genotype at SNP site 1 is AG heterozygous>the number of healthy piglets of sows whose genotype at SNP site 1 is GG homozygous; the SNP site 1 is the 67th nucleotide from the 5' end of SEQ ID NO: 1 in the pig genome.

2. A method for evaluating the number of weak piglets in sow reproductive performance, comprising the steps of: detecting whether the genotype of the sow to be tested is CC homozygous, CT heterozygous, or TT homozygous based on SNP site 3, whether the genotype of the sow to be tested is GG homozygous, AG heterozygous, or AA homozygous based on SNP site 4, and / or whether the genotype of the sow to be tested is AA homozygous, AG heterozygous, or GG homozygous based on SNP site 7, and then performing the following judgment: The number of weak piglets of sows whose genotype at SNP site 3 is CC homozygous is greater than the number of weak piglets of sows whose genotype at SNP site 3 is CT heterozygous or TT homozygous; the SNP site 3 is the 78th nucleotide from the 5' end of SEQ ID NO: 2 in the pig genome; The number of weak piglets of sows whose genotype at SNP site 4 is GG homozygous is greater than the number of weak piglets of sows whose genotype at SNP site 4 is AG heterozygous or AA homozygous; the SNP site 4 is the 79th nucleotide from the 5' end of SEQ ID NO: 3 in the pig genome; The number of weak piglets of sows whose genotype at SNP site 7 is GG homozygous is greater than the number of weak piglets of sows whose genotype at SNP site 7 is AA homozygous or AG heterozygous; the SNP site 7 is the 76th nucleotide from the 5' end of SEQ ID NO: 4 in the pig genome.

3. A method for evaluating weaning litter weight in sow reproductive performance, comprising the steps of: detecting whether the genotype of the sow to be tested is AA homozygous, AG heterozygous, or GG homozygous based on SNP site 10, whether the genotype of the sow to be tested is CC homozygous, CT heterozygous, or TT homozygous based on SNP site 11, and / or whether the genotype of the sow to be tested is AA homozygous, AC heterozygous, or CC homozygous based on SNP site 12, and then performing the following judgment: The weaning litter weight of sows whose genotype at SNP site 10 is AG heterozygous or GG homozygous is greater than the weaning litter weight of sows whose genotype at SNP site 10 is AA homozygous; the SNP site 10 is the 204th nucleotide from the 5' end of SEQ ID NO: 5 in the pig genome; The weaning litter weight of sows whose genotype at SNP site 11 is CT heterozygous or TT homozygous is greater than the weaning litter weight of sows whose genotype at SNP site 11 is CC homozygous; the SNP site 11 is the 236th nucleotide from the 5' end of SEQ ID NO: 5 in the pig genome; The weaning litter weight of sows whose genotype at SNP site 12 is AC heterozygous or CC homozygous is greater than the weaning litter weight of sows whose genotype at SNP site 12 is AA homozygous; the SNP site 12 is the 76th nucleotide from the 5' end of SEQ ID NO: 6 in the pig genome.

4. A kit for evaluating the reproductive performance of a sow, comprising a substance A for detecting the genotype of the sow to be tested based on SNP site 1, a substance B for detecting the genotype of the sow to be tested based on SNP site 3, a substance C for detecting the genotype of the sow to be tested based on SNP site 4, a substance D for detecting the genotype of the sow to be tested based on SNP site 7, a substance E for detecting the genotype of the sow to be tested based on SNP site 10, a substance F for detecting the genotype of the sow to be tested based on SNP site 11, and / or a substance G for detecting the genotype of the sow to be tested based on SNP site 12; SNP site 1 is the 67th nucleotide from the 5′ end of SEQ ID NO: 1 in the pig genome; SNP site 3 is the 78th nucleotide from the 5' end of SEQ ID NO: 2 in the pig genome; SNP site 4 is the 79th nucleotide from the 5' end of SEQ ID NO: 3 in the pig genome; SNP site 7 is the 76th nucleotide from the 5' end of SEQ ID NO: 4 in the pig genome; SNP site 10 is the nucleotide 204 from the 5′ end of SEQ ID NO: 5 in the pig genome; SNP site 11 is the nucleotide 236 from the 5′ end of SEQ ID NO: 5 in the pig genome; SNP site 12 is the 76th nucleotide from the 5' end of SEQ ID NO: 6 in the pig genome.

5. The kit according to claim 4, wherein: The substance A is used to evaluate the number of healthy piglets in the reproductive performance of sows; The substance B, substance C and / or substance D are used to evaluate the number of weak piglets in the reproductive performance of sows; The substance E, substance F and / or substance G are used for evaluating the weaning litter weight in the reproductive performance of sows.

6. Molecular markers, including molecular marker A shown in SEQ ID NO: 1, molecular marker B shown in SEQ ID NO: 2, molecular marker C shown in SEQ ID NO: 3, molecular marker D shown in SEQ ID NO: 4, molecular marker E shown in SEQ ID NO: 5 and / or molecular marker F shown in SEQ ID NO:

6.

7. Use of the kit according to claim 4 or 5 or the molecular marker according to claim 6 in evaluating the reproductive performance of sows.

8. Use of the kit according to claim 4 or 5 or the molecular marker according to claim 6 in screening sows with high reproductive performance.

9. Use of the kit according to claim 4 or 5 or the molecular marker according to claim 6 in sow breeding; the purpose of sow breeding is to cultivate sow breeds with high reproductive performance.

10. The use according to any one of claims 7 to 9, characterized in that: The reproductive performance is at least one of the number of healthy piglets, the number of weak piglets and the weaning litter weight.

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