SNP (Single Nucleotide Polymorphism) molecular marker related to healthy litter size of sow and application of SNP molecular marker

Abstract

The invention belongs to the technical field of pig molecular markers, and particularly discloses an SNP molecular marker related to the character of the number of healthy piglets born by a sow and application of the SNP molecular marker. Genetic typing and whole genome association analysis are carried out on 732 large white sows by using second-generation gene sequencing and gene chip technologies, an SNP site significantly related to the character of the number of healthy piglets born by the large white sows is screened out, the SNP site is located at the upstream of an SLC22A12 gene of a pig chromosome 2 and corresponds to the 7565970th nucleotide of a chromosome 2 of an international pig 11.1 version reference genome, and the SNP site is located at the upstream of the SLC22A12 gene of the chromosome 2 of the pig 11.1 version reference genome and is located at the upstream of the SLC22A12 gene of the chromosome 2 of the pig 11.1 version reference genome. The method can be used for character prediction of healthy litter size of sows or auxiliary breeding.

Description

Technical Field

[0001] The invention belongs to the technical field of pig molecular markers, and in particular relates to a SNP molecular marker on pig chromosome 2 related to the trait of healthy piglet number born by sows and an application thereof. Background Art

[0002] Increasing the number of live pigs and the number of piglets weaned by sows are important production goals in the industry, and the number of healthy piglets produced by sows per litter is closely related to this. For low-heritability reproductive traits such as the number of healthy piglets born by sows, the genetic basis is very complex, and genetic progress using traditional breeding methods is often slow. In order to better understand the genetic basis of litter size traits, it is necessary to screen important SNPs, chromosome regions, and candidate genes. In recent years, molecular biology tools such as marker-assisted selection and genomic selection have also become important animal breeding methods (Zhang et al, 2014), and have greatly improved breeding efficiency (Ding et al, 2021). The important SNPs related to traits can be identified through whole genome resequencing, gene chips and other technologies combined with genome-wide association analysis (GWAS), but reliable molecular markers are still very scarce.

[0003] The present invention conducts genome-wide association analysis on the healthy piglet number of Large White sows, screens out SNP sites that are significantly associated with the healthy piglet number trait of sows, and provides a theoretical basis and application approach for molecular marker-assisted selection breeding of pigs. Summary of the invention

[0004] The purpose of the present invention is to overcome the defects and shortcomings of the prior art, screen out SNP molecular markers that are significantly associated with the trait of healthy piglet number born by sows, provide new molecular marker resources for the trait of healthy piglet number born by sows, and provide a new application approach for marker-assisted selection breeding of pigs.

[0005] In order to achieve the above object, the technical solution of the present invention is as follows:

[0006] The present invention provides a method for screening molecular markers associated with the trait of healthy piglet number born by sows, the method comprising the following steps:

[0007] (1) Blood tissues were collected from 732 Large White pigs, DNA was extracted and quality tested;

[0008] (2) 611 samples were subjected to genome resequencing and 121 samples were subjected to gene chip sequencing;

[0009] (3) After chip data filling, it is merged with genome resequencing data and quality controlled;

[0010] (4) Deregression estimated breeding value (DEBV) of healthy piglets born by sows to correct for parity effects and reconstruct phenotypes;

[0011] (5) The present invention uses rMVP software to perform genome-wide association analysis based on the FarmCPU model.

[0012] SNP molecular markers significantly associated with the trait of healthy piglet birth in sows were screened through whole genome association analysis, and the nucleotide sequences 100bp upstream and downstream of each SNP were obtained based on the Ensmble database pig 11.1 version reference genome (Sus_scrofa.Sscrofa11.1-106), the SNP nucleotide sequence is shown in SEQ ID NO.1 or 2, the 101st base is G or A, and the allele mutation causes the above sequence to produce a nucleotide polymorphism, the site (chr2:7565970) is located 219bp upstream of the SLC22A12 gene, and the accession number in the dbSNP database is rs81359036.

[0013] The invention has the beneficial effects: compared with the traditional screening method, the invention has the outstanding advantages of accuracy and speed. Applying it to the selection and breeding of the trait of healthy piglets born by sows can increase the number of healthy piglets per litter of sows and increase the production income of pig farming enterprises. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] Figure 1 : This is a Manhattan plot produced by screening SNP molecular markers significantly associated with the trait of healthy piglet number in Large White sows.

[0015] Figure 2 : This is a QQ graph produced by screening SNP molecular markers significantly associated with the trait of healthy piglet number in Large White sows.

[0016] Figure 3 : This is the LDblock diagram of the SNP molecular marker screened by the present invention that is significantly associated with the healthy litter size trait of Large White sows and the SNP at the 5' end of the SLC22A12 gene. DETAILED DESCRIPTION

[0017] Example 1 Genotyping Detection

[0018] (1) Sample collection

[0019] Blood samples were collected from 121 French Large White pigs, 338 Canadian Large White pigs, and 273 Danish Large White sows in Anhui, Xinjiang, and Inner Mongolia, respectively.

[0020] (2) DNA extraction

[0021] ① Take 200 μL of whole blood, add an equal volume of cell lysis buffer composed of 100 mmol / L Tris-saturated phenol, 500 mmol / L disodium ethylenediaminetetraacetate (EDTA), 20 mmol / L sodium chloride (NaCL), 10% sodium dodecyl sulfate (SDS), 20 μg / ml pancreatic RNase, then add 10 ng / mL proteinase K, mix well, and place in a 65°C constant temperature water bath for 30 min;

[0022] ② Slowly shake the centrifuge tube for 15 minutes, centrifuge it at 12000 rpm for 5 minutes, and take the supernatant into another centrifuge tube;

[0023] ③ Add an equal volume of phenol-chloroform-isoamyl alcohol mixture (25:24:1), shake and mix, centrifuge at 12000 rpm for 5 min, and take the supernatant into another centrifuge tube;

[0024] ④ Add an equal volume of phenol-chloroform-isoamyl alcohol mixture (25:24:1), shake and mix, centrifuge at 12000 rpm for 10 min, and take the supernatant into another centrifuge tube;

[0025] ⑤ Add 2 times the volume of pre-cooled anhydrous ethanol, let it stand until the ethanol evaporates, pick out the DNA precipitate and use ultrapure water to dissolve the DNA;

[0026] ⑥ Use a DNA concentration meter and agarose gel electrophoresis to detect DNA quality.

[0027] (3) Genotyping

[0028] ① Based on the DNA extracted above, 611 samples were subjected to second-generation whole-genome resequencing using the DNBSEQ-T7 gene sequencer (the average sequencing depth was approximately 18×), the reference genome (Sus_scrofa.Sscrofa11.1-106) was aligned using the BWA software, and SNP calling was performed using the GATK software; the other 121 samples were genotyped using a 50K SNP whole-genome chip and filled using Beagle v5.4.

[0029] ② After merging the two genotyping files using BCFtools software, the obtained SNP molecular marker loci were quality controlled using PLINK v1.9 software to eliminate those with a detection rate less than 90%, a minimum allele frequency less than 0.05, and a Hardy-Weinberg equilibrium P value less than 1×10 -6 , filling SNPs with accuracy lower than 0.8, and finally obtaining data of 5,782,534 SNPs in 732 samples for subsequent analysis.

[0030] Example 2 Application of SNP Molecular Markers in Genome-wide Association Analysis of Healthy Piglet Number Traits in Large White Sows (1) Phenotypic Statistics and Reconstruction

[0031] The present invention collected data on the number of healthy piglets per litter of 732 sows. Some sows recorded data on multiple parities, and a total of 1,117 data were collected. The specific descriptive statistical results are as follows, see Table 1.

[0032] Table 1: Descriptive statistics of the phenotype of healthy piglets born in the Large White pig population

[0033]

[0034] As shown in Table 1, the coefficient of variation of the healthy piglet number phenotype is greater than 20%, indicating that this trait has a large selection space.

[0035] In order to eliminate the influence of kinship information in GWAS analysis and correct the parity effect, the present invention reconstructed the original healthy piglet phenotype and used the deregression estimated breeding values ​​(DEBVs) weighted by the estimated breeding values ​​(EBVs) as the response variable (Garrick et al, 2009; Ostersen et al, 2011). The present invention used the ssGBLUP method of HiBLUP software to estimate EBVs, and the model was as follows:

[0036] y=Xb+Zu+e

[0037] Where y is the original phenotypic vector; b represents fixed effects and covariates, including birth season, birth season, birthing condition, individual number, birthing age and the first three principal components; X is the association matrix; u is the random additive effect, Z is the association matrix between the additive effect and the phenotypic record; e is the residual vector. The weight coefficient (w i ) is calculated as follows:

[0038]

[0039] where h 2 is the heritability of the trait, is the reliability of the EBV of the i-th individual, c is the proportion of genetic variation that cannot be explained by genetic information, and in the present invention, c is set to 0.5.

[0040] (2) Genome-wide association analysis of healthy piglet number in Large White sows

[0041] The experimental pig herd used for the genome-wide association analysis in this example was Large White pigs (n=732). The FarmCPU model in the rMVP software was used to perform a genome-wide association analysis on the SNP molecular markers and the alternative phenotypes (DEBVs) of the healthy litter size trait of Large White sows. The FarmCPU model iteratively used a fixed effect model and a random effect model, and the fixed effect model was as follows:

[0042] y=M t b t +S j d j +e

[0043] Where y is the vector of DEBVs; M t is the genotype matrix of t pseudo-QTNs used as fixed effects; b t It is M t The relevant design matrix of S j is the jth marker to be tested, d j is the corresponding effect; e is the residual effect vector, A random effects model was used to select the most appropriate pseudo-QTN, which was:

[0044] y=u+e

[0045] where y and e are the same as in the fixed effects model; u is the genetic effect, where K is the relationship matrix defined by the pseudo-QTN.

[0046] The Manhattan plot based on the GWAS analysis results is shown in Figure 1 The Bonferroni correction threshold was used to detect significant SNPs in the whole genome, which was defined as 0.05 / N (N is the number of effective independent SNPs inferred by simpleM software, which is 2963141). The QQ plot is shown in Figure 2 .Depend on Figure 1 It can be seen that a total of 6 SNP sites were detected. The present invention only focuses on the SNP site located at the first position of chromosome 2 (the SNP indicated by the arrow in the figure). This SNP site is closely linked to multiple SNP sites in the 5' UTR and exons of the SLC22A12 gene, and 3 of the SNP sites will cause non-synonymous mutations in the coding region (see Figure 3 ), so this SNP site is very likely to act together with the surrounding SNP sites that cause non-synonymous mutations on the structure and function of the SLC22A12 protein, thereby providing a possible SNP marker for the genetic interpretation of the sow litter size trait. The basic genetic parameter information of this SNP site is shown in Table 2.

[0047] Table 2: Information on candidate SNP loci for healthy piglets in Large White sows based on GWAS

[0048]

[0049] Table 2 Description: GWAS results log10(1 / P)>7.772782 indicate significant association.

[0050] As shown in Table 2, the selected candidate SNP site (rs81359036) is significantly correlated with the number of healthy piglets born by Large White sows. The present invention has statistically analyzed some information of different genotypes of the SNP site in the population, as shown in Table 3.

[0051] Table 3: Different genotype frequencies and phenotypic values ​​of healthy piglets in candidate SNP loci in Large White sows

[0052]

[0053] As shown in Table 3, for the above SNP site (rs81359036), the number of healthy offspring produced by individuals homozygous for the minor allele (AA genotype) is lower than that of individuals with the other two genotypes.

[0054] Main references:

[0055] Ding, R., Qiu, Y., Zhuang, Z., Ruan, D., Wu, J., Zhou, S., Ye, J., Cao, L., Hong, L., Xu, Z., Zheng, E., Li, Z., Wu, Z., & Yang, J. (2021). Genome-wide association studies reveal polygenic genetic architecture of litter traits in Durocpigs.Theriogenology,173,269–278.

[0056] Garrick,DJ,Taylor,JF,&Fernando,RL(2009).Deregressing estimatedbreeding values ​​and weighting information for genomic regressionanalyses.Genetics,selection,evolution:GSE,41(1),55.

[0057] Ostersen,T.,Christensen,O.F.,Henryon,M.,Nielsen,B.,Su,G.,&Madsen,P.(2011).Deregressed EBV as the response variable yield more reliable genomicpredictions than traditional EBV in pure-bred pigs.Genetics,selection,evolution:GSE,43(1),38.Zhang,Z.,Ober,U.,Erbe,M.,Zhang,H.,Gao,N.,He,J.,Li,J.,&Simianer,H.(2014).Improving the accuracy of whole genome prediction forcomplex traits using the results of genome wide association studies.PloS one,9(3),e93017.。

Claims

1. A SNP molecular marker associated with the trait of healthy piglets born to sows, characterized in that: The nucleotide sequence of the SNP molecular marker is shown in SEQ ID NO. 1 or 2, and the 101st nucleotide is G or A.

2. A kit for detecting the trait of healthy piglets born by sows, characterized in that: The kit contains reagents for detecting nucleotide No. 7565970 of chromosome 2 of sow, and the reference genome version is Sus_scrofa.Sscrofa11.1-106.

3. Use of the SNP molecular marker according to claim 1 or the kit according to claim 2 in predicting the number of healthy piglets born by sows or in assisting breeding.

4. The use according to claim 3, characterized in that: Sows with AA genotype produced fewer healthy piglets than sows with GG or GA genotypes.

5. The use according to claim 3, characterized in that: The breed of the pig is Large White pig.

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