A SNP molecular marker associated with the traits of number of pig mummies and number of stillbirths and its application

Abstract

This invention provides a SNP molecular marker associated with the traits of pig mummified fetus number and stillbirth number, and its application, relating to the field of biotechnology. The application includes using substances detecting SNP sites in the preparation of products predicting pig fetal mortality. The SNP sites include one or more of the following: SNP sites rs318687930, rs337505213, rs321068825, and rs340473552. These SNP sites are associated with the pig fetal mortality trait and can be used to predict pig fetal mortality and for the screening and breeding of sows with low fetal mortality rates.

Description

Technical Field

[0001] This invention relates to the field of biotechnology, and in particular to a SNP molecular marker and its application related to traits such as the number of pig mummies and stillbirths. Background Technology

[0002] Reproductive traits in pigs are important indicators for measuring the reproductive capacity of sows. These mainly include litter size, piglet birth weight, number of teats, milk production (litter weight at 21 days of age), and the number of piglets recovered at weaning. These traits are extremely important for pig farming. Good reproductive performance in sows means that each sow can produce more healthy piglets within a certain period, reducing breeding costs and improving production efficiency.

[0003] The number of mummies and stillbirths in pigs is of great significance for assessing sow reproductive efficiency and for pig breeding. By studying these traits, we can accelerate the transmission and fixation of superior genes, improve the reproductive capacity of pig herds, and provide a scientific basis for breeding and genetic improvement.

[0004] Therefore, the identification of genes related to the number of mummies and stillbirths in pigs can provide important clues for explaining the genetic mechanisms of fetal growth and development in pigs and other mammals, and provide a theoretical basis for the genetic improvement of reproductive traits in pigs.

[0005] In view of this, the present invention is hereby proposed. Summary of the Invention

[0006] The purpose of this invention is to overcome the shortcomings of the prior art and provide an SNP molecular marker related to the number of pig fetal deaths and its application.

[0007] To solve the above-mentioned technical problems, the present invention adopts the following technical solution:

[0008] In a first aspect, a substance for detecting SNP sites is provided for use in the preparation of a product for predicting the number of fetal deaths in pigs, wherein the SNP sites include one or more of the following: SNP sites rs318687930, rs337505213, rs321068825, and rs340473552.

[0009] Secondly, a kit for predicting the number of pig fetal deaths is provided, comprising at least one of the following primer pairs:

[0010] The primer pairs used to amplify SNP site rs318687930 have nucleotide sequences as shown in SEQ ID NO. 1 and 2, respectively; the primer pairs used to amplify SNP site rs340473552 have nucleotide sequences as shown in SEQ ID NO. 3 and 4, respectively; the primer pairs used to amplify SNP site rs321068825 have nucleotide sequences as shown in SEQ ID NO. 5 and 6, respectively; and the primer pairs used to amplify SNP site rs337505213 have nucleotide sequences as shown in SEQ ID NO. 7 and 8, respectively.

[0011] Thirdly, a method for predicting fetal mortality in pigs is provided, comprising predicting sows that meet at least one of (i) to (iv) as sows with low fetal mortality:

[0012] (i) The genotype of SNP locus rs318687930 is GG.

[0013] (ii) The genotype of SNP locus rs337505213 is CC;

[0014] (iii) The genotype of SNP locus rs321068825 is GG;

[0015] (iv) The genotype of SNP locus rs340473552 is CT.

[0016] Fourthly, a method for screening sows with a low number of dead piglets is provided, the method comprising screening sows with a low number of dead piglets predicted by the method described in the third aspect.

[0017] Fifthly, a breeding method for sows with low birth rate and low mortality rate is provided, the breeding method comprising acquiring at least one of the following genotypes in the sow:

[0018] (i) The genotype of SNP locus rs318687930 is GG.

[0019] (ii) The genotype of SNP locus rs337505213 is CC;

[0020] (iii) The genotype of SNP locus rs321068825 is GG;

[0021] (iv) The genotype of SNP locus rs340473552 is CT.

[0022] Compared with the prior art, the present invention has the following beneficial effects:

[0023] This invention utilizes low-depth resequencing and genome-wide association analysis to identify SNP molecular markers associated with fetal mortality in pigs, specifically the number of mummified fetuses and stillbirths. Four SNP loci, rs318687930, rs337505213, rs321068825, and rs340473552, were found to be associated. Sows with specific genotypes at these four loci exhibited lower rates of fetal mortality. These SNP molecular markers can be used to predict fetal mortality, screen sows with low rates of fetal mortality, and develop breeding methods for sows with low rates of fetal mortality. The application of these SNP loci can help improve sow reproductive performance and bring greater economic benefits to the pig farming industry. Attached Figure Description

[0024] To more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the specific embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0025] Figure 1 This is a genotype detection peak diagram obtained by capillary electrophoresis in an embodiment of the present invention. Detailed Implementation

[0026] The technical solution of the present invention will be clearly and completely described below with reference to the embodiments. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0027] cAMP response element binding protein 3 (CREB3 regulatory factor, CREBRF), also known as the Luman / CREB3 recruiting factor (LRF), is a regulator of the Luman / CREB3 protein (cyclic adenosinemonophosphate response element binding protein 3, Luman / CREB3). Studies have shown that CREBRF knockout mice have significantly lower prolactin levels than normal mice, impaired glucocorticoid signaling, and exhibit severe maternal behavioral defects, lacking the instinct to care for offspring. CREBRF gene expression is high in the ovary and uterus during estrus and postestrus, suggesting that CREBRF may be involved in cell differentiation, embryonic development, and implantation. Another study showed that CREBRF can mediate ERS pathway-mediated apoptosis of GCs and plays a crucial role in mouse follicle selection. CREBRF expression can be inhibited by E2 but induced by P4, and CREBRF can regulate decidualization during pregnancy by modulating the proliferation of mouse uterine stromal cells. Therefore, the CREBRF gene plays an important regulatory role in animal growth, development, and reproduction, especially in follicle growth and development, cell differentiation, embryonic development, and implantation. Furthermore, polymorphic changes at CREBRF gene SNP sites are correlated with estrogen levels, which in turn regulate sow reproductive efficiency. Since fetal mortality is an important indicator of sow reproductive traits, this invention investigated the correlation between CREBRF gene single nucleotide polymorphisms and fetal mortality.

[0028] This invention employs low-depth resequencing and genome-wide association analysis to analyze the association between CREBRF gene polymorphisms and important reproductive traits, and identifies SNP molecular markers in the porcine genome that are significantly associated with the number of pig fetal deaths. This invention discovered four SNP loci, rs318687930, rs337505213, rs321068825, and rs340473552, that are associated with the number of pig fetal deaths.

[0029] The porcine CREBRF gene SNP site rs318687930 is located at nucleotide position 51174074 on porcine chromosome 16 (reference genome is Sscrofa11.1). When the genotype of this SNP site is GG, the sow has a low birth rate and low fetal mortality.

[0030] The CREBRF gene SNP site rs337505213 is located at nucleotide position 51208314 on chromosome 16 of pigs (reference genome is Sscrofa11.1). When the genotype of this SNP site is CC, the sow has a low birth rate and low fetal mortality.

[0031] The CREBRF gene SNP site rs321068825 is located at nucleotide position 51195295 on chromosome 16 of pigs (reference genome is Sscrofa11.1). When the genotype of this SNP site is GG, the sow has a low birth rate and low fetal mortality.

[0032] The porcine CREBRF gene SNP site rs340473552 is located at nucleotide position 51177550 on porcine chromosome 16 (reference genome is Sscrofa11.1). When the genotype of this SNP site is CT, the sow has a low birth rate and low fetal mortality.

[0033] In this article, "fetal mortality" refers to the number of pig fetuses that die in utero. Depending on the time and specific circumstances, it can be further subdivided into different types. For example, it could include, but is not limited to, the number of mummified fetuses and / or stillbirths. "Low-yielding fetal mortality" refers to a number of fetal deaths that is lower than the average number of fetal deaths for that breed.

[0034] Based on the above findings, in a first aspect, an application is provided for detecting SNP sites in the preparation of a product for predicting the number of pig fetal deaths, wherein the SNP sites include one or more of the following: SNP sites rs318687930, rs337505213, rs321068825, and rs340473552.

[0035] In an optional implementation, the pig fetal death includes the number of mummified fetuses and / or the number of stillborn fetuses.

[0036] In an optional embodiment, the product includes a substance for detecting the SNP locus rs318687930, and the number of pig fetal deaths includes the number of primiparous mummified fetuses.

[0037] In an optional embodiment, the product includes a substance for detecting the SNP locus rs337505213, and the number of pig fetal deaths includes the number of primiparous mummified fetuses.

[0038] In an optional embodiment, the product includes a substance for detecting the SNP site rs321068825, and the number of pig fetal deaths includes the number of stillbirths at first birth.

[0039] In an optional embodiment, the product includes a substance for detecting the SNP site rs340473552, and the number of pig fetal deaths includes the number of multiparous stillbirths.

[0040] In an optional embodiment, the product includes a substance that detects SNP sites rs318687930, rs337505213, rs321068825, and rs340473552.

[0041] In optional embodiments, the substances used to detect SNP sites include, but are not limited to, one or more of the following: reagents for nucleic acid amplification, reagents for detecting nucleic acid amplification products, reagents for constructing sequencing libraries, and reagents for sequencing. More specifically, the substances used to detect SNP sites include, but are not limited to, primers, probes, enzymes for nucleic acid amplification reactions, fluorescent labels, buffer reagents, dNTPs, salts, etc. Depending on the specific detection method, those skilled in the art can select the above-mentioned reagents for nucleic acid amplification, reagents for detecting nucleic acid amplification products, reagents for constructing sequencing libraries, and reagents for sequencing according to the methods described in general and more specific textbooks, references, process manuals, product instructions, and standard documents. This invention does not impose any limitations on these selections.

[0042] In an optional embodiment, the substance for detecting SNP sites includes at least one of the following primer pairs: a primer pair for amplifying SNP site rs318687930, with nucleotide sequences as shown in SEQ ID NO. 1 and 2, respectively; a primer pair for amplifying SNP site rs340473552, with nucleotide sequences as shown in SEQ ID NO. 3 and 4, respectively; a primer pair for amplifying SNP site rs321068825, with nucleotide sequences as shown in SEQ ID NO. 5 and 6, respectively; and a primer pair for amplifying SNP site rs337505213, with nucleotide sequences as shown in SEQ ID NO. 7 and 8, respectively.

[0043] Secondly, a kit for predicting the number of fetal deaths in pigs is provided, the kit comprising at least one of the following primer pairs: a primer pair for amplifying SNP site rs318687930, with nucleotide sequences as shown in SEQ ID NO. 1 and 2, respectively; a primer pair for amplifying SNP site rs340473552, with nucleotide sequences as shown in SEQ ID NO. 3 and 4, respectively; a primer pair for amplifying SNP site rs321068825, with nucleotide sequences as shown in SEQ ID NO. 5 and 6, respectively; and a primer pair for amplifying SNP site rs337505213, with nucleotide sequences as shown in SEQ ID NO. 7 and 8, respectively.

[0044] Thirdly, a method for predicting fetal mortality in pigs is provided, the method comprising predicting sows that meet at least one of (i) to (iv) as sows with low fetal mortality:

[0045] (i) The genotype of SNP locus rs318687930 is GG.

[0046] (ii) The genotype of SNP locus rs337505213 is CC;

[0047] (iii) The genotype of SNP locus rs321068825 is GG;

[0048] (iv) The genotype of SNP locus rs340473552 is CT.

[0049] In an optional implementation, the method includes predicting sows that meet (i) and / or (ii) as sows with a low number of mummified litters:

[0050] (i) The genotype of SNP locus rs318687930 is GG.

[0051] (ii) The genotype of SNP locus rs337505213 is CC.

[0052] In an optional implementation, the method for predicting the number of low-birth-rate stillbirths in pigs includes predicting sows that meet (iii) and / or (iv) as sows with a low number of stillbirths:

[0053] (iii) The genotype of SNP locus rs321068825 is GG;

[0054] (iv) The genotype of SNP locus rs340473552 is CT.

[0055] The third aspect provides a method for predicting the number of low-birth-rate fetal deaths in pigs, which includes using one or more of the following SNP loci: rs318687930, rs337505213, rs321068825, and rs340473552 as the sole identification target; it can also be combined with other targets, such as other polymorphic molecular markers (e.g., SSR molecular markers, STR molecular markers, or InDel molecular markers), or other screening methods known in the art to assist in the prediction of the total number of piglets born.

[0056] Fourthly, a method for screening sows with a low number of dead piglets is provided, including screening sows with a low number of dead piglets predicted by the method described in the third aspect.

[0057] Fifthly, a breeding method for sows with low birth rate and low fetal mortality is provided, the breeding method comprising acquiring at least one of the following genotypes in the sow:

[0058] (i) The genotype of SNP locus rs318687930 is GG.

[0059] (ii) The genotype of SNP locus rs337505213 is CC;

[0060] (iii) The genotype of SNP locus rs321068825 is GG;

[0061] (iv) The genotype of SNP locus rs340473552 is CT.

[0062] The specific means by which a sow acquires a specific genotype can be implemented by those skilled in the art using conventional methods known in the art, and this invention does not limit this. In an optional embodiment, offspring with the target genotype are obtained by acquiring parents with a known genotype. In another optional embodiment, offspring with the target genotype are obtained through gene editing methods.

[0063] In an optional implementation, the pig in any of the above implementations is a Large White pig.

[0064] The present invention will be further illustrated below with specific embodiments. However, it should be understood that these embodiments are merely for the purpose of more detailed illustration and should not be construed as limiting the present invention in any way.

[0065] Example 1

[0066] I. Sample Collection

[0067] The experimental population in this embodiment consisted of 226 British Large White pigs from Rizhao Breeding Farm in Shandong, 165 Canadian Large White pigs from Xinjiang Tiankang Jiamei Breeding Branch, and 199 Danish Large White pigs from the great-grandparent breeding farm of Xinjiang Tiankang Animal Husbandry Technology Co., Ltd. A total of 590 Large White pigs were used for CREBRF gene SNP genotyping. Ear tissue samples were collected from each pig, placed in 75% alcohol, and stored at -20°C for DNA extraction.

[0068] II. Extraction and Library Construction of Pig Genomic DNA

[0069] (1) Cut an appropriate amount of pig ear tissue, cut it into pieces and put it into a 1.5mL Axgen tube.

[0070] (2) Take a 50mL BD centrifuge tube, mix proteinase K and lysis buffer to a final concentration of 0.4mg / mL evenly, and add 0.5mL lysis buffer to a 1.5mL centrifuge tube containing pig ear tissue for lysis.

[0071] (3) Place the centrifuge tubes evenly and parallel on the shaking plate of the constant temperature hybridization oven (tightly seal the tube caps to prevent liquid leakage). Incubate at 55°C for more than 6 hours (thorough mixing of the sample during digestion is very important. The criteria for judgment are the absence of obvious visible pig ear tissue and the milky consistency of the digested mixture).

[0072] (4) After the sample has been fully lysed, remove the centrifuge tubes, add 0.3 mL of saturated sodium chloride solution to each tube, mix thoroughly by inverting 6-8 times, and then place them on ice for 15 minutes.

[0073] (5) After the ice bath, centrifuge at 12,000 rpm at room temperature for 15 minutes. Carefully and slowly transfer the supernatant to a new 1.5 mL Axgen centrifuge tube (be careful to avoid pouring out the precipitate along with the supernatant, keep the pouring method consistent, and keep the amount of supernatant poured out in each tube the same).

[0074] (6) Add 0.7 mL of isopropanol (the amount of isopropanol added varies with the amount of supernatant poured out, and the two are equal in volume) to each tube, and invert until flocculent precipitate appears in the solution (if no flocculent precipitate appears, the solution can be placed in a -20°C refrigerator for 2 hours or in a 4°C refrigerator overnight).

[0075] (7) Centrifuge at 12000 rpm at room temperature for 15 minutes and remove the supernatant.

[0076] (8) Add 0.5 mL of 70% ethanol to each centrifuge tube and gently invert to thoroughly rinse the DNA that has precipitated above.

[0077] (9) Centrifuge at 10000 rpm for 30 seconds, then use a 200 μL micropipette to remove the ethanol from the centrifuge tube, leaving the precipitated DNA in the tube.

[0078] (10) Air dry DNA for 10 minutes.

[0079] (11) Pipette 0.1 mL of TE buffer into each tube to redissolve the DNA precipitate. Place the tube at 55°C for 2 hours and shake it several times to ensure that the DNA is fully dissolved.

[0080] (12) After the DNA was fully dissolved, the concentration of the extracted DNA was determined by UV spectrophotometer, and the quality of the extracted DNA was detected by agarose gel electrophoresis. The quality of the DNA was further tested using Qbuit, and qualified samples were used for library construction.

[0081] (13) Library construction: Sequencing libraries were prepared using the BGI library construction kit.

[0082] (14) Sequencing: After the library preparation is completed and the quality is checked, PE150 mode sequencing is performed using DNBSEQ-T7.

[0083] III. SNP chip genotyping and genotypic data quality control

[0084] DNA samples from 590 Large White pigs were sent to Beijing Gezhi Boya Biotechnology Co., Ltd. for 20× depth sequencing and low-depth resequencing.

[0085] Low-quality sequencing data was removed using the default parameters of fastp v0.23.2 to obtain clean reads. The clean reads were then aligned to the reference genome using the default parameters of bwa-mem v0.7.17. The alignment results were then converted into BAM files and sorted using Samtools software. Picard MarkDuplicates was used to remove duplicate reads from the sorted BAM files. Genomic variant detection was performed using GATK-HaplotypeCaller software, generating gvcf files for individual samples. GATK CombineGVCFs and GenotypeGVCFs were then used to merge and genotype the gvcf files. The filtering parameters for SNPs and Indels are shown in Table 1.

[0086] Table 1 Filtering Parameters

[0087] Filtering parameters SNP Indel QD ＜2.0 ＜2.0 QUAL ＜30.0 ＜30.0 MQ ＜40.0 ＜40.0 SOR ＞3.0 FS ＞60.0 ＞200.0 MQRankSum ＜-12.5 ReadPosRankSum ＜-8.0 ＜-20.0

[0088] IV. Data Processing and Analysis

[0089] (1) Phenotypic data analysis: Phenotypic data of the number of mummies and stillbirths of 590 Large White pigs were collected and organized in Excel. Descriptive statistics were performed on the phenotypic data of the number of mummies and stillbirths, and the sample size, mean, standard deviation, standard error, maximum value, minimum value and quartiles of each variable were calculated.

[0090] (2) Statistical Analysis: Excel 2021 was used to calculate various polymorphism indicators. The relevant formulas for calculating polymorphism indicators are as follows:

[0091] (2.1) Gene frequency (AF)

[0092]

[0093] (2.2) Genotype frequency (GF)

[0094]

[0095] (2.3) Genetic heterozygosity (He)

[0096]

[0097] (2.4) Effective number of alleles (Ne)

[0098]

[0099] (2.5) Polymorphic Information Content (PIC)

[0100]

[0101] (2.6) Correlation Analysis

[0102] Anova analysis was performed using the LSD method. Reproductive phenotypic characteristics of different genotypes were expressed as mean ± standard deviation. A linear model using PLINK software was used to perform association analysis between genotype and reproductive phenotype. The field effect was used as a covariate for correction. P ≤ 0.05 was considered statistically significant, and P ≤ 0.01 was considered extremely statistically significant.

[0103] V. Capillary electrophoresis detection of SNPs

[0104] (1) Determine the number of reactions N. During the test, a template-free control (nuclease-free pure water) should be tested simultaneously. N = number of samples to be tested (n) + template-free control (1) + 1.

[0105] (2) Place the enzyme mixture on ice, and thaw the remaining components at room temperature until completely melted. Mix with a vortex mixer for 10 seconds, and then centrifuge with a micro centrifuge for 10 seconds to concentrate the liquid at the bottom of the tube.

[0106] (3) Prepare the reaction system except for the template according to Table 2. Take one centrifuge tube, add each component, mix with a vortex mixer for 10s, centrifuge with a microcentrifuge for 10s, and aliquot 9μL into PCR reaction tubes. Primer sequences are shown in Table 3.

[0107] Table 2 Reaction system configuration

[0108] Serial Number Component Name Amount of standard system added (μL) Reaction number N and amount added (μL) 1 2.5×PCR reaction solution 4 4N 2 primer mixture 1 1N 3 Nuclease-free water 4 4N total 9 9N

[0109] Note: PCR products should be stored at 2–8℃ and tested within 24 hours, or stored at -20℃±5℃ and tested within 7 days. The number of freeze-thaw cycles should not exceed 3.

[0110] Table 3 Primer sequences

[0111]

[0112] (4) Add 1 μL of the sample to be tested to each of the pre-dispensed reaction tubes. Record the order of the numbers, mix using a vortex mixer for 10 s, and then centrifuge using a microcentrifuge for 10 s.

[0113] (5) Place each reaction tube in the reaction chamber of the PCR instrument and run the PCR program. The PCR amplification program is shown in Table 4.

[0114] Table 4 PCR Procedure

[0115]

[0116] (6) Electrophoresis detection of PCR products: Take an appropriate amount of PCR products and load them onto a 2% to 3% agarose gel for electrophoresis to detect whether the amplification is successful.

[0117] Capillary electrophoresis detection, results as follows Figure 1 As shown:

[0118] (1) The PCR amplification products were centrifuged at 3500 rpm for 2 min using a benchtop or plate centrifuge.

[0119] (2) Prepare a mixture of HiDi and Liz500. After mixing the mixture with a vortex mixer for 10 seconds, centrifuge it with a microcentrifuge for 10 seconds and dispense 9 μL into a 96-well plate. Add 1 μL of PCR product supernatant (stock solution or dilution) to each well.

[0120] (3) Cover with a rubber pad and centrifuge instantly using a benchtop or plate centrifuge;

[0121] (4) 95℃, denature for 5 min, then immediately ice bath for 3 min;

[0122] (5) Perform capillary electrophoresis using a gene analyzer. Select the "Fragment" electrophoresis method. Data analysis is performed using analytical software (Applied Biosystems).

[0123] VI. Results Analysis

[0124] Table 5

[0125]

[0126] Table 6

[0127]

[0128] Table 7

[0129]

[0130] Genotyping results show:

[0131] For the SNP (rs318687930) locus, 246 pigs had the GG genotype, and 186 pigs had the GA genotype; for the SNP (rs340473552) locus, 261 pigs had the CC genotype, and 144 pigs had the CT genotype; for the SNP (rs321068825) locus, 266 pigs had the GG genotype, and 140 pigs had the GA genotype; for the SNP (rs337505213) locus, 232 pigs had the CC genotype, and 198 pigs had the CT genotype.

[0132] Table 5 shows the allele and gene frequencies of the porcine CREBRF gene in a pig herd.

[0133] For the SNP (rs318687930) locus, the genotype frequency of GG was 0.4331, and the genotype frequency of GA was 0.3275. The genotype frequency of GG was higher than that of GA, and the GG allele was the dominant gene. For the SNP (rs340473552) locus, the genotype frequency of CC was 0.4595, and the genotype frequency of CT was 0.2535. The genotype frequency of CC was higher than that of CT, and the CC allele was the dominant gene. For the SNP (rs321068825) locus, the genotype frequency of GG was 0.4683, and the genotype frequency of GA was 0.2465. The genotype frequency of GG was higher than that of GA, and the GG allele was the dominant gene. For the SNP (rs337505213) locus, the genotype frequency of CC was 0.4085, and the genotype frequency of CT was 0.3486. The genotype frequency of CC was higher than that of CT, and the CC allele was the dominant gene.

[0134] Table 6 shows that at the SNP (rs318687930) locus, there were 246 GG genotypes and 186 GA genotypes in 590 Large White pigs. The CREBRF and the number of mummified primiparous pigs showed significant differences, with the GA genotype being more prevalent than the GG genotype. At the SNP (rs337505213) locus, there were 232 CC genotypes and 198 CT genotypes in 590 Large White pigs. The CREBRF and the number of mummified primiparous pigs also showed significant differences, with the CT genotype being more prevalent than the CC genotype.

[0135] Table 7 shows that at the SNP (rs340473552) locus, there were 261 CC genotypes and 144 CT genotypes in 590 Large White pigs. The CREBRF and the number of stillbirths in multiparous pigs were significantly different, with the CC genotype having a higher number than the CT genotype. At the SNP (rs321068825) locus, there were 266 GG genotypes and 140 GA genotypes in 590 Large White pigs. The CREBRF and the number of stillbirths in primiparous pigs were significantly different, with the GA genotype having a higher number than the GG genotype.

[0136] Association analysis of genotype and total litter size phenotypes was performed using a linear model with plink software, and the field effect was used as a covariate for adjustment. The results are shown in Tables 6 and 7:

[0137] The SNP (rs318687930) locus significantly affects the number of mummified primiparous piglets. The GA genotype has a significantly higher number of mummified primiparous piglets than the GG genotype. Therefore, in actual pig breeding, GG genotype pigs have fewer mummified primiparous piglets. The SNP (rs337505213) locus significantly affects the number of mummified primiparous piglets. The CT genotype has a significantly higher number of mummified and stillbirths than the CC genotype. Therefore, in actual pig breeding, CC genotype pigs have fewer mummified primiparous piglets. The SNP (rs340473552) locus significantly affects the number of stillbirths in multiparous pigs. The CC genotype has a significantly higher number of stillbirths in multiparous pigs than the CT genotype. Therefore, in actual pig breeding, CT genotype pigs have a lower number of stillbirths in multiparous pigs. The SNP (rs321068825) locus significantly affects the number of stillbirths in pigs after multiparous births. The number of stillbirths in primiparous births is significantly higher in the GA genotype than in the GG genotype. Therefore, in actual pig breeding, pigs with the GG genotype have a lower number of stillbirths in primiparous births.

[0138] In summary, determining the nucleotide sequence at the SNP (rs318687930) site of the porcine CREBRF gene can help identify whether a pig has the GA or GG genotype, thus aiding in the identification of mummified remains: the number of primiparous mummies with the GG genotype is significantly lower than that with the GA genotype. The GA genotype is a heterozygous combination of G and A at position 51174074 on porcine chromosome 16; the GG genotype is a homozygous combination of G at position 51174074 on porcine chromosome 16.

[0139] The nucleotide sequence at the SNP (rs337505213) site of the CREBRF gene in pigs can be used to determine whether an individual pig has the CT or CC genotype, thus aiding in the identification of mummified remains: the number of primiparous mummies with the CC genotype is significantly lower than that with the CT genotype. The CT genotype is a heterozygous combination of C and T at position 51208314 on pig chromosome 16; the CC genotype is a homozygous combination of C at position 51208314 on pig chromosome 16.

[0140] The nucleotide sequence at the SNP (rs340473552) site of the porcine CREBRF gene can be used to determine whether a pig has the CC or CT genotype, thus aiding in the identification of stillbirths: the CT genotype results in a significantly lower number of stillbirths than the CC genotype. The CT genotype is a heterozygous combination of C and T at position 51177550 on porcine chromosome 16; the CC genotype is a homozygous combination of C at position 51177550 on porcine chromosome 16.

[0141] The nucleotide sequence at the SNP (rs321068825) site of the CREBRF gene in pigs can be used to determine whether an individual pig has the GA or GG genotype, thus aiding in the identification of stillbirths at first birth: the number of stillbirths at first birth is significantly lower in the GG genotype than in the GA genotype. The GA genotype is a heterozygous combination of G and A at position 51195295 on chromosome 16 of pigs; the GG genotype is a homozygous combination of G at position 51195295 on chromosome 16 of pigs.

[0142] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some or all of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. The application of a substance for detecting SNP sites in the preparation of products for predicting the number of sow fetal deaths, characterized in that, The SNP locus is rs318687930, and the number of pig fetal deaths is the number of primiparous mummified fetuses; and / or, The SNP locus is rs337505213, and the number of pig fetal deaths is the number of primiparous mummified fetuses; and / or, The SNP locus is rs321068825, and the number of pig fetal deaths is the number of stillbirths in primiparous piglets; and / or, The SNP locus is rs340473552, and the number of pig fetal deaths is the number of stillbirths. The substances used to detect SNP sites are primers and / or probes; The pig in question is a Large White pig.

2. A breeding method for sows with a low birth rate and low fetal mortality rate, characterized in that, This includes acquiring at least one of the following genotypes in sows: (i) The genotype of SNP locus rs318687930 is GG, resulting in sows with a low number of primiparous mummies; (ii) The genotype of SNP locus rs337505213 is CC, resulting in sows with a low number of primiparous mummies; (iii) The genotype of SNP locus rs321068825 is GG, resulting in sows with a low number of stillbirths at first birth; (iv) The genotype of SNP locus rs340473552 is CT, resulting in sows with a low number of stillbirths. The pig in question is a Large White pig.

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