SNP (Single Nucleotide Polymorphism) molecular marker related to porcine newborn litter weight character and application of SNP molecular marker in character heterosis utilization

Abstract

The invention belongs to the technical field of pig molecular markers, and particularly discloses an SNP (Single Nucleotide Polymorphism) molecular marker related to a pig newborn litter weight character and application of the SNP molecular marker. Gene typing is carried out by utilizing a gene chip technology, whole genome association analysis is carried out based on SNP molecular markers, and four SNP molecular marker sites related to newborn litter weight characters are screened out through the analysis. The sites of the SNP molecular marker are located on a 10 # chromosome and a 15 # chromosome of a pig. Wherein the rs708832569 is located in an SUSD4 gene segment, the rs693520249 is located in a CYB5R1 gene segment, and the marker can be used for marker-assisted breeding of pig newborn litter weight traits and heterosis utilization of the pig newborn litter weight traits.

Description

Technical Field

[0001] This invention belongs to the field of porcine molecular marker technology, specifically relating to SNP molecular markers related to the birth litter weight trait in pigs and their applications. Background Technology

[0002] Birth weight in pigs refers to the sum of the weights of all surviving piglets in the same litter within 24 hours of birth, and is an important indicator for assessing sow reproductive performance (Ye et al., 2019). Studies have shown that piglets with low birth weight often exhibit decreased survival rates, slow growth during lactation, and poor fattening performance, while piglets with evenly distributed birth weight show significant advantages in colostrum intake, herd mortality control, and weaning rate (Jankowiak et al., 2020; Charneca et al., 2021).

[0003] Birth litter weight is influenced by both genetic factors (such as litter size and birth weight) and environmental factors (such as gestational nutrition and feeding management), with sow reproductive performance being the core determinant. The phenotypic and genetic correlations between birth litter weight and the number of live piglets in a litter are 0.831 and 0.572, respectively, indicating a high phenotypic correlation between the two traits. Selective breeding to increase the number of live piglets in a litter can effectively improve birth litter weight (Li Wenjing 2024). However, the number of live piglets in a litter is negatively correlated with weaning survival rate (-0.450). Increasing the number of live piglets in a litter requires combined with precise feeding management measures to synergistically optimize the overall reproductive performance of sows (Liu Jian et al. 2016). Placental development is a key factor determining fetal nutrient supply and growth potential. Sows with low birth litter weight exhibit delayed placental development in early pregnancy, and the crowded intrauterine environment further restricts fetal development (Moroni et al. 2022). In high-producing sows, placental morphological characteristics (such as weight and surface area) and umbilical cord length are closely related to fetal weight; piglets with low birth weight are usually accompanied by smaller placental volume and shorter umbilical cords (Lyderik et al 2023). Furthermore, nutritional regulation and precise feeding management during gestation have a significant impact on litter weight at birth. Appropriate nutritional intervention can improve sow body condition and enhance fetal development quality, but excessive supplementation may reduce the number of live piglets per litter due to increased metabolic load (Mallmann et al 2020).

[0004] Birth weight, as a complex quantitative trait influenced by multiple genes and environmental interactions, requires in-depth analysis of its genetic mechanisms using genome-wide association studies (GWAS) and multi-omics integration to optimize breeding strategies. Marker-assisted selection (MAS), based on molecular markers associated with the target trait, overcomes the limitations of traditional phenotypic selection methods, enabling precise screening of individuals with high genetic potential in early breeding populations, shortening generation intervals, and improving selection accuracy (Chakraborty et al 2022). Wei et al., through a genome-wide association study (GWAS) on Large White pigs, found significant associations between genes such as EGR2, BMPR1B, FSHR, and CENPE and birth weight, with CENPE showing significant correlations in transcriptome association analysis, co-location analysis, and Mendelian randomization analysis (Wei et al 2025). Zhang et al.'s GWAS study found significant associations between genes such as EPHB2 and SEMA4D and birth weight in Duroc pigs (Zhang et al 2019). A GWAS study by Sun et al. found that genes such as CAMK2A, NDST1, and RPS14 were significantly associated with birth litter weight in Large White pigs (Sun et al. 2023). Current research on birth litter weight in pigs mainly focuses on purebred pig populations, failing to fully reflect the characteristics of hybrid populations. Furthermore, traditional GWAS analyses primarily target additive genetic effects, with insufficient research on non-additive genetic effects in hybrid populations.

[0005] This invention collected 105,020 birth litter weight records from 26,857 Landrace and Large White crossbred sows. Through genome-wide association analysis with fitted dominant effects, four SNP markers significantly associated with birth litter weight were screened, providing a theoretical basis and application approach for marker-assisted selection in pigs. Summary of the Invention

[0006] The purpose of this invention is to overcome the shortcomings of the prior art by using gene chip technology for genotyping and performing genome-wide association analysis to fit the dominant effect of the pig's birth litter weight trait. Four SNP markers that are significantly associated with the pig's birth litter weight trait were screened out, and the genetic effects of the SNP markers were evaluated. This provides new SNP molecular marker resources for pig reproductive traits and the utilization of heterosis in reproductive traits.

[0007] To achieve the above objectives, the present invention adopts the following technical solution:

[0008] The applicant screened for SNP molecular markers that were significantly associated with the pig's birth litter weight trait through genome-wide association analysis, and obtained the nucleotide sequences of 100 bp upstream and downstream of each SNP based on the Ensmble database pig version 11.1 reference genome, as follows:

[0009] The nucleotide sequences containing the SNP1 marker are shown in SEQ ID NO. 1 and 2. The SNP1 marker is located at position 101 of the sequences, corresponding to position 19471012 on chromosome 10 of the pig genome, and the corresponding gene is... SUSD4 The accession number in the dbSNP database is rs708832569, the polymorphic site is T or A, and the favorable genotype is T / A;

[0010] The nucleotide sequences containing the SNP2 marker are shown in SEQ ID NO. 3 and 4. The SNP2 marker is located at position 101 of the sequences, corresponding to position 24930552 on chromosome 10 of the pig genome, and the corresponding gene is... CYB5R1 The accession number in the dbSNP database is rs693520249, the polymorphic site is G or A, and the favorable genotype is G / A;

[0011] The nucleotide sequences containing the SNP3 marker are shown in SEQ ID NO.5 and 6. The SNP3 marker is located at position 101 of the sequence, corresponding to position 112096 of chromosome 15 of the pig genome. The accession number in the dbSNP database is rs319349870. The polymorphic site is G or A, and the favorable genotype is G / A.

[0012] The nucleotide sequences containing the SNP4 marker are shown in SEQ ID NO.7 and 8. The SNP4 marker is located at position 101 of the sequence, corresponding to position 112123 of chromosome 15 of the pig genome. The accession number in the dbSNP database is rs330637216. The polymorphic site is G or A, and the favorable genotype is G / A.

[0013] Compared with the prior art, the present invention has the following beneficial effects:

[0014] It can be applied to the genetic improvement of piglet birth weight traits and the utilization of heterosis in hybrid sow reproductive traits, thereby increasing piglet birth weight, accelerating the breeding process, and improving production efficiency. Attached Figure Description

[0015] Figure 1 The Manhattan plot generated by this invention visualizes the results of GWAS analysis.

[0016] Figure 2The QQ graph generated by this invention compares the quantiles of the probability distributions of the actual -log10(P) value and the expected -log10(P) value, thereby comparing the two probability distributions to further determine the reliability of the GWAS results. Detailed Implementation

[0017] Example 1: Genotyping Detection and Data Processing

[0018] (1) DNA extraction

[0019] ① Ear tissues were collected from 26,857 Large White and Large White crossbred sows. The collected ear tissues were homogenized and placed in a glass homogenizer. An equal volume of a cell lysis buffer prepared with 100 mmol / L Tris-saturated phenol, 500 mmol / L disodium ethylenediaminetetraacetate (EDTA), 20 mmol / L sodium chloride (NaCl), 10% sodium dodecyl sulfate (SDS), and 20 μg / ml trypsin was added. Then, 10 ng / mL proteinase K was added, and the mixture was incubated at 65°C for 30 min. The centrifuge tubes were then slowly vortexed for 15 min, centrifuged at 12,000 rpm for 5 min, and the supernatant was transferred to another centrifuge tube.

[0020] ② Add equal volumes of phenol, chloroform, and isoamyl alcohol (volume ratio 25:24:1), shake to mix, centrifuge at 12000 rpm for 5 min, and then transfer the supernatant to another centrifuge tube.

[0021] ③ Add an equal volume of phenol, chloroform, and isoamyl alcohol (volume ratio 25:24:1), shake to mix, and centrifuge at 12000 rpm for 10 min. Transfer the supernatant to another centrifuge tube.

[0022] ④ Add 2 times the volume of pre-cooled anhydrous ethanol, let stand until the ethanol evaporates, pick out the DNA precipitate and dissolve the DNA in ultrapure water;

[0023] ⑤ DNA quality was detected using a DNA concentration analyzer and agarose gel electrophoresis.

[0024] (2) Genotyping detection

[0025] Based on the extracted DNA, genotyping was performed using the porcine 80K functional site gene chip from Wuhan Shadow Gene Technology Co., Ltd.

[0026] Example 2: Genome-wide association analysis of SNP molecular markers with litter weight in pigs

[0027] (1) Phenotypic correction

[0028] 105,020 birth litter weight records from 26,857 Large White and Large White crossbred sows were collected from a pig farm. Phenotypic data were processed according to the mean ± 3 standard deviations. The farrowing farm-farrowing year-farrowing season-parity were set as fixed effects. An R-package lme4 model was used to fit a single-trait repeatability model to correct for the influence of environmental factors on the phenotype. The sum of the breeding value and residuals was extracted from the model as the corrected phenotypic value.

[0029] (2) SNP molecular marker quality control

[0030] Based on microarray data, PLINK v1.9 software was used to perform quality control on the obtained SNP markers, removing SNPs with a site deletion rate greater than 10%, a sample deletion rate greater than 10%, and a minimum allele frequency less than 0.01. Finally, 178,746 autosomal SNPs and 26,857 samples were used for genome-wide association analysis.

[0031] (3) Genome-wide association analysis to fit dominant effects

[0032] The experimental pig herd used in this genome-wide association analysis consisted of Landrace-Landrace crossbred sows, comprising 26,857 individuals. Additive and dominant effect genome-wide association matrices were first constructed using the gmatrix module in GMAT software. Then, a genome-wide association analysis fitting the dominant effect of litter weight was performed using the remma module (non-additive test module), with the first three principal components used as covariates. The specific model is shown below:

[0033]

[0034] in It is a phenotypic vector; It is a fixed effects vector. Design a matrix for fixed effects; The correlation matrix is ​​the random effects. It is an additive SNP effect. It is a dominant SNP effect. It is an additive effects matrix. It is the dominance effect matrix. It is a random residual vector, which conforms to ,in It is the residual variance. It is an identity matrix.

[0035] Based on the GWAS results, the P-value for each SNP locus was calculated as -log10(P). Using the significance threshold formula -log10(1 / number of SNPs), this invention calculated that a -log10(P) value greater than or equal to 5.252236 for each SNP locus indicates a significant association between the SNP and the initial litter weight trait. Manhattan plots and QQ plots were then drawn using the CMplot package in R language. Figure 1 , Figure 2 ).

[0036] Table 1: Candidate SNP markers associated with litter weight identified based on GWAS

[0037]

[0038] Table 2: Genotype frequencies and mean litter weight of candidate SNP markers in the pig population

[0039]

[0040] Table 2 shows the genotype frequencies, mean litter weight, and standard errors of the four candidate SNP markers identified based on genome-wide association analysis in the pig population. For these four candidate SNP markers, samples with heterozygous genotypes showed higher litter weights compared to samples with homozygous genotypes. The favorable genotypes for the markers rs708832569, rs693520249, rs319349870, and rs330637216 are T / A. These SNP markers can be used alone or in combination for selective breeding of pigs with litter weight traits.

[0041] (4) Evaluation of the genetic effects of candidate SNP markers

[0042] Based on the genotype effect values ​​of candidate SNP markers, the additive effect (a) and dominant effect (d) are calculated as follows:

[0043]

[0044] Where AA and aa represent the effect values ​​of the two homozygous genotypes, respectively, and Aa represents the effect value of the heterozygous genotype. The additive effect reflects half of the difference between the two homozygous genotypes, while the dominant effect reflects the degree of deviation of the heterozygous genotype from the means of the two homozygous genotypes.

[0045] Table 3: Results of genetic effect assessment of candidate SNP markers

[0046]

[0047] Table 3 shows the calculated additive effect value, dominance effect value, and d / a ratio for four candidate SNP markers. The markers rs708832569, rs693520249, rs319349870, and rs330637216 showed higher dominance effect values, with the heterozygous genotype exhibiting a better effect than the two homozygous genotypes. These SNP markers have significant application value in effectively utilizing heterosis and can be used as candidate markers for breeding pig litter weight traits.

[0048] Main references:

[0049] [1] Li Wenjing. Estimation of genetic parameters of reproductive traits of large white sows in a national core pig breeding farm. Foreign Animal Husbandry (Pigs and Poultry), 2024, 44(04):59-62.

[0050] [2] Liu Jian, Wu Zhipeng, Zhong Tumu, Fu Jiping, Li Qingfei, Zhang Jinzhi. Correlation between litter size and birth weight of Large White sows and weaning litter weight and weaning survival rate. China Animal Husbandry Journal, 2016, 52(07):1-4.

[0051] [3] Ye Jian, Tan Cheng, Cai Gengyuan, Wu Zhenfang. Genetic assessment of litter weight traits in piglets. Journal of South China Agricultural University, 2019, 40(S1):72-75.

[0052] [4]Charneca R, Nunes JT, Freitas A, Le Dividich J. Effect of litterbirth weight standardization before first suckling on colostrum intake, passive immunization, pre-weaning survival, and growth of the piglets. Animal, 2021, 15(4):100184.

[0053] [5]Jankowiak H, Balogh P, Cebulska A, Vaclavkova E, Bocian M, ReszkaP. Impact of piglet birth weight on later rearing performance. Vet Med-Czech, 2020, 65(11):473-479.

[0054] [6]Moroni JL, Tsoi S, Wenger II, Tran C, Plastow GS, Charagu P, DyckMK. The influence of litter birth weight phenotype on embryonic and placentaldevelopment at day 30 of gestation in multiparous purebred Large White sows.Anim Reprod Sci, 2022, 244:107035.

[0055] [7]Lyderik KK, Østrup E, Bruun TS, Amdi C, Strathe AV. Fetal andplacental development in early gestation of hyper-prolific sows.Theriogenology, 2023, 197:259-266.

[0056] [8]Mallmann AL, Oliveira GS, Ulguim RR, Mellagi APG, Bernardi ML,Orlando UAD, Gonçalves MAD, Cogo RJ, Bortolozzo FP. Impact of feed intake inearly gestation on maternal growth and litter size according to body reservesat weaning of young parity sows. J Anim Sci, 2020, 98(3):skaa075.

[0057] [9]Chakraborty D, Sharma N, Kour S, Sodhi SS, Gupta MK, Lee SJ, SonYO. Applications of Omics Technology for Livestock Selection and Improvement.Front Genet, 2022, 13:774113.

[0058]

[10] Wei R, Zhang Z, Han H, Miao J, Yu P, Cheng H, Zhao W, Hou X, WangJ, He Y, Fu Y, Wang Z, Wang Q, Zhang Z, Pan Y. Integrative genomic analysisreveals shared loci for reproduction and production traits in Yorkshire pigs.BMC Genomics, 2025, 26(1):310.

[0059]

[11] Zhang Z, Chen Z, Ye S, He Y, Huang S, Yuan X, Chen Z, Zhang H, LiJ. Genome-Wide Association Study for Reproductive Traits in a Duroc PigPopulation. Animals (Basel), 2019, 9(10):732.

[0060]

[12] Sun J, Xiao J, Jiang Y, Wang Y, Cao M, Wei J, Yu T, Ding X, YangG. Genome-Wide Association Study on Reproductive Traits Using Imputation-Based Whole-Genome Sequence Data in Yorkshire Pigs. Genes (Basel), 2023, 14(4):861.

Claims

1. The application of SNP markers in the selection and breeding of pig litter weight, characterized in that, Includes at least one of the following SNP tags: Nucleotide sequences containing the SNP1 marker are shown in SEQ ID NO.1 and 2, where the SNP1 marker is located at position 101 of the sequence and the polymorphic site is either T or A. Nucleotide sequences containing the SNP2 marker are shown in SEQ ID NO.3 and 4, where the SNP2 marker is located at position 101 and the polymorphic site is G or A. Nucleotide sequences containing the SNP3 marker are shown in SEQ ID NO.5 and 6, where the SNP3 marker is located at position 101 of the sequence and the polymorphic site is G or A; Nucleotide sequences containing the SNP4 marker are shown in SEQ ID NO.7 and 8, where the SNP4 marker is located at position 101 of the sequence and the polymorphic site is G or A.

2. The application according to claim 1, characterized in that: The favorable genotypes for the SNP1 markers are T / A, the favorable genotypes for the SNP2 markers are G / A, the favorable genotypes for the SNP3 markers are G / A, and the favorable genotypes for the SNP4 markers are G / A. Samples with favorable genotypes exhibit high litter weight at birth.

3. The application according to claim 1, characterized in that, The pigs in question are of the Large White crossbred sow and the Large White crossbred sow.

4. The application of the kit in the selection and breeding of pig litter weight traits, characterized in that... The kit contains reagents for detecting polymorphic sites on porcine chromosome 10 or 15, wherein the polymorphic sites include at least one of the following: The polymorphic site at position 19471012 of chromosome 10 is either T or A; The polymorphic site at position 24930552 on chromosome 10 is either G or A. The polymorphic site at position 112096 of chromosome 15 is either G or A; The polymorphic site at position 112123 on chromosome 15 is either G or A. The reference genome version is Sscrofa 11.1.

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