Functional site combination for predicting litter size traits of landrace and application of functional site combination

Abstract

The invention discloses a functional site combination for predicting sow reproductive traits and application thereof.The functional site combination comprises 12232 SNP loci, ear tissues of Changbai breeding pigs from a certain pig farm in the south of China are collected, gene chip sequencing and whole genome re-sequencing data are used, and the functional site combination is used for predicting the reproductive traits of sows. A large number of SNP markers are obtained by using a genotype filling technology, functional marker information related to the breeding traits of the landrace sows is screened in combination with multi-omics information, noise sites in filling data are removed, and finally the 10K functional site applied to the breeding traits of the landrace sows is formed. The SNP molecular marker related to the breeding traits of the landrace sows is screened out, a new molecular marker development basis is provided for prediction and genetic improvement of the breeding traits related to the landrace sows, and the SNP molecular marker has important significance in improving the breeding and breeding efficiency of pigs.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of pig molecular marker screening technology, genomic breeding and functional genomics, and particularly relates to a functional site combination for predicting sow reproductive traits and application thereof. BACKGROUND

[0002] At present, in the field of genomics, improving the association between sites and target excellent traits can improve the accuracy of whole genome selection using chips. By screening sites with strong correlation with reproductive traits, the customization of low-density functional chips can be facilitated, thereby realizing the application of molecular marker-assisted breeding, detecting excellent trait site signals, and rapidly evaluating animal reproductive capacity and the like.

[0003] Preselecting SNPs with higher genetic variation contribution to reproductive traits helps to improve the genomic prediction accuracy of gene chips for reproductive traits and the detection efficiency of GWAS. In order to distinguish these SNP sites, it is best to obtain information other than the analyzed traits to find out the sites that may affect the phenotype. XIANG et al. proposed the evaluation method of FAETH score in 2019, which aims to sort SNP sites by their contribution to gene regulation, evolution and 34 kinds of complex trait variation. Their research provides a method and analysis framework for quantifying the importance of sequence variation (RUIDONG XIANG et al. 2019).

[0004] The reproductive traits of sows are the basis for developing good strain propagation, and genetic improvement can significantly improve reproductive efficiency and economic benefits. Sow reproductive traits belong to low heritability traits. Effective molecular markers can help improve the prediction ability of sow genomic selection. Landrace pigs are widely used as paternal lines in hybrid production systems, and genetic improvement of Landrace pigs mainly focuses on growth and carcass traits rather than reproductive traits, so there is a huge genetic improvement space for Landrace pig reproductive performance. As a low heritability trait, sow reproductive traits are more efficient than traditional breeding methods in molecular marker-assisted breeding. Good molecular markers help to improve the prediction accuracy of whole genome selection and accelerate the genetic improvement effect of sow reproductive traits.

[0005] Therefore, it is necessary to mine functional sites related to sow reproductive traits through whole genome association analysis combined with various functional information of SNPs. SUMMARY

[0006] The present application aims to overcome the deficiencies of the prior art, and provides a functional site combination for predicting the reproductive traits of Landrace pigs and an application thereof, which combines the genetic contribution of SNPs to the reproductive traits of Landrace pigs with the results of whole-genome association analysis of the reproductive traits, and screens functional sites that are significant for the reproductive traits. The present application obtains a large number of SNP markers by collecting ear tissues of Landrace pigs from a certain pig farm in southern China, through gene chip sequencing and whole-genome resequencing data, and using genotype filling technology, combines multi-omics information to screen functional marker information related to the reproductive traits of Landrace sows, eliminates noise sites in the filled data, and finally forms a 10K gene site applied to the reproductive traits of Landrace sows. The present application screens SNP molecular markers related to the reproductive traits of Landrace sows, and provides new molecular markers for predicting and genetically improving the related reproductive traits of Landrace pigs, which has important significance for improving the breeding and reproductive efficiency of pigs.

[0007] To achieve the above-mentioned object, the technical scheme designed by the present application is as follows:

[0008] The present application provides a functional site combination for the reproductive traits of sows, which comprises 12232 SNP sites, and the site information thereof is specifically as shown in Table 2.

[0009] The present application also provides a screening method for the functional site combination for the reproductive traits of sows, comprising the following steps:

[0010] 1) Gene chip sequencing is performed on each individual in the sow population, and a part of the individuals are randomly selected for whole-genome resequencing, and the sequencing depth is 30x;

[0011] 2) Genotyping is performed by using the resequencing data, and the genotype data of the chip sequencing population is filled to the whole-genome level by using the genotype filling technology, so as to obtain whole-genome SNPs;

[0012] 3) The reproductive trait phenotypes of the Landrace sow population are collected, and individuals with less than 3 total litter size and less than 0.3 kg birth weight are eliminated;

[0013] 4) The filled data are quality controlled, and sites with less than 0.05 maf are eliminated, and the genotype data after quality control are used for whole-genome association analysis with the collected reproductive traits, so as to screen relevant associated sites;

[0014] 5) The filled data are quality controlled, and sites with less than 0.01 maf are eliminated, and the genotype data after quality control are used to quantify the contribution of whole-genome SNPs to the reproductive traits of Landrace sows according to the FAETH framework, and the SNP sites with high FAETH ranking are screened, and the sites with P value less than 10-5 in the relevant associated sites (the results of whole-genome association analysis) screened in step 4 are combined, so as to obtain the functional sites for the reproductive traits of Landrace sows.

[0015] Further, in the step 1), the sow is a Landrace sow.

[0016] Still further, in the step 3), the reproductive trait phenotype includes total litter size, live litter size, stillbirth number, gestation age and birth weight traits

[0017] The application also provides an application of the functional site combination in excellent reproductive trait screening, pig reproductive trait improvement and improvement of pig breeding and reproductive efficiency.

[0018] The application also provides a probe combination for detecting the functional site combination, which contains probes for detecting the 12232 SNP sites.

[0019] The application also provides a 10K liquid chip for pig reproductive trait prediction and screening, which contains the probe combination.

[0020] The application also provides a system for detecting the functional site combination, and the detection method of the system is to detect the 12232 SNP sites contained in the genome of the to-be-detected breed by sequencing.

[0021] The application also provides an application of the 10K liquid chip or the system in excellent reproductive trait screening.

[0022] The application also provides an application of the 10K liquid chip or the system in pig reproductive trait improvement and improvement of pig breeding and reproductive efficiency.

[0023] The application has the following beneficial effects:

[0024] 1. The application is based on the genotype filling data and related data of Landrace sows, combined with multi-omics data analysis and screening of SNP sites that have a great contribution to the reproductive traits of Landrace sows, and finally obtains SNP sites that have a great contribution to the reproductive traits of Landrace sows, thereby providing a new method for predicting the reproductive traits of Landrace sows and improving the breeding accuracy of reproductive traits.

[0025] 2. The SNP markers screened by the application can be applied to whole genome association analysis and genome selection related to the reproductive traits of Landrace pigs, thereby providing new molecular marker resources for molecular marker assisted selection of the reproductive traits of Landrace pigs.

[0026] 3. The application can improve the accuracy of genomic breeding of the reproductive traits of Landrace sows, accelerate the genetic progress of genomic selection of the reproductive traits of Landrace sows, has significant economic benefits, and is extremely valuable in pig molecular breeding. BRIEF DESCRIPTION OF DRAWINGS

[0027] Figure 1 This is a schematic diagram of the overall technical process of the present invention. Detailed Implementation

[0028] The present invention will now be described in further detail with reference to specific embodiments, so that those skilled in the art can understand it.

[0029] Example 1

[0030] The screening method for functional loci of reproductive traits in Landrace sows includes the following steps:

[0031] Step 1: Collect tail tissue samples from Landrace sows for gene chip sequencing; select a portion of the samples for whole-genome resequencing to obtain a series of sequencing data. Use the whole-genome resequencing data to fill the gene chip data at the whole-genome level. Perform quality control on the filling results, retaining SNP sites with DR2>0.8 and maf>0.01.

[0032] Step 2: Record the total number of piglets born, the number of live piglets born, the number of stillbirths, the gestational age, and the phenotypic data of all sequenced sows, and remove individuals with a total number of piglets born less than 3 and a birth weight less than 0.3 kg.

[0033] Step 3: Genome-wide association analysis (GWAS) was performed using genome filling data and reproductive trait-related phenotypes to screen loci significantly associated with reproductive traits. In this step, the GWAS employed a mixed linear model and a FarmCPU model in rMVP software. Fixed effects included farm, gestation season, strain, and parity. The Bonferroni method was used to correct for significance thresholds: a significance threshold of 0.05 / N at the genome-wide level and 1 / N at the chromosome level (where N is the number of SNPs involved in the analysis).

[0034] Step 4: Based on the functional annotation of the pig whole genome and existing ChIP-seq data, combined with studies on the conservation of animal genome evolution and theories of linkage disequilibrium, SNP loci at the whole genome level were divided into 6 categories and 22 sets. The GBLUP method was used to estimate the average heritability of each SNP set in the five reproductive traits of total litter size, live litter size, stillbirth size, birth weight, and gestation time.

[0035] Step 5: Based on the FAETH scoring framework and SNP classification, the relative importance of SNPs to reproductive traits was quantified (RUIDONG XIANG et al., 2019). Genome-wide SNPs were divided into 6 categories, totaling 22 sets. Five reproductive traits were selected: total litter size, live birth size, stillbirth size, gestational age, and birth weight. First, the heritability of the five reproductive traits was calculated using all SNPs (all SNPs, a total of 11,332,071 SNPs). and the average heritability of 5 reproductive traits The second step involves calculating the average heritability of four sets (MAF_q1, MAF_q2, MAF_q3, and MAF_q4) within the MAF category, using the MAF category as an example, for SNP classifications covering the entire genome. The corresponding set Divide by the number of SNPs in the set to obtain the per-variant heritability of each SNP in the set. That is, the average per-variant heritability of all SNPs in the MAF classification. Other classifications follow the same principle. The third step involves classifying SNPs that do not cover the entire genome (QTLs, genomic regulatory regions, and conserved regions). Taking the QTL classification as an example, genome-wide SNPs are divided into QTL sets and non-QTL sets. For QTL set SNPs, the heritability of the five reproductive traits of the QTL set is calculated. and average heritability For non-QTL set SNPs, their corresponding heritability Depend on The average heritability was obtained and calculated. Then and Divide each by the number of SNPs in the set to obtain the corresponding per-variant. and per-variant per-variant As the average heritability of non-QTL SNPs within QTL categories, this yields the average heritability of all SNPs across QTL categories at the genome-wide level. The same logic applies to genomic regulatory regions and conserved regions. Ultimately, each SNP at the genome-wide level will have 6 per-variants. By calculating the per-variant of each SNP across its 6 categories The average of these values ​​is the FAETH score.

[0036] Step 6: Based on the FAETH score of whole-genome SNPs, the top 10K SNP sites were extracted and combined with SNP sites with P-values ​​less than 10⁻⁵ in the results of genome-wide association analysis based on gene filling. The resulting functional loci of reproductive traits in Landrace sows were obtained after merging.

[0037] The reference genome and genome-wide association analysis results in this invention are based on pig genome version 11.1 (https: / / ftp.ensembl.org / pub / release-113 / gtf / sus_scrofa / ).

[0038] Based on the above screening method, tail tissue samples from different Landrace sows were collected to screen for reproductive trait loci in Landrace sows, as detailed below:

[0039] A total of 7130 tail tissue samples were collected from Landrace sows for 80K liquid-phase microarray capture sequencing, and 140 tail tissue samples from these sows were selected for high-depth resequencing. Using the resequencing data from these 140 Landrace sows as a reference panel, the remaining microarray sequencing individuals were filled to the whole genome level using Beagle 5.4 software (http: / / faculty.washington.edu / browning / beagle / beagle.html). Beagle software outputs the correlation square (DR2) between the filled genotype and the true genotype in the filling results, reflecting the accuracy of the filling results. Therefore, SNPs with a DR2 greater than 0.8 in the filling results were retained for subsequent analysis.

[0040] After quality control, loci with a maf value less than 0.05 were removed from the imputed data. Genome-wide association analysis was then performed on total litter size, live litter size, stillbirth size, and birth weight traits. A mixed linear model using rMVP and a FarmCPU model were used, with farm, calving season, and strain as fixed effects.

[0041] The imputed data underwent further quality control, and loci with a maf value less than 0.01 were removed, retaining a total of 11,332,071 loci at the whole-genome level. All SNP loci were divided into 6 categories and 22 sets, as shown in Table 1. The per-variant distribution of each SNP at the whole-genome level, comprising 6 categories, was calculated using the GBLUP method. By calculating the per-variant of each SNP across its 6 categories The average value is the FAETH score. Subsequently, the top 10K FAETH scores were extracted and combined with SNPs with P-values ​​less than 10⁻⁵ in the genome-wide association analysis based on gene filling. The final result was 12,232 SNPs for reproductive traits in Landrace sows. Their site information is shown in Table 2 below.

[0042] Table 1 SNP Classification Set Information

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[0045] Table 2. Locus information of SNP sites

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[0071] Example 2: 10K liquid phase chip for predicting and screening reproductive traits in pigs

[0072] Based on the SNP locus information obtained in Example 1, a 10K liquid phase chip was developed for predicting and screening pig reproductive traits, as detailed below:

[0073] The 10K liquid phase chip includes probes that detect the aforementioned 12,232 SNP sites.

[0074] Example 3: Application of the above-mentioned 10K liquid-phase chip or sequencing system to the functional loci of reproductive traits in Landrace sows in genome breeding.

[0075] To verify the validity of the functional site set obtained by the above 10K liquid-phase chip or sequencing system, a commercial SNP chip site and a set of randomly selected SNP sites from the whole genome were used as controls.

[0076] The sequencing system was used to detect the 12,232 SNP sites mentioned above in the genome of the sow breed being tested, using the Illumina sequencing platform and the Q-T7B sequencing instrument.

[0077] Individuals from the same farm in Example 1 were selected as the validation population, comprising 1664 Landrace sows. The GBLUP method was used to estimate the breeding values ​​of total litter size, live litter size, and stillbirth size in the validation population. The Pearson correlation coefficient between the estimated breeding values ​​and the true phenotype was calculated using five-fold cross-validation to determine the accuracy of the estimated breeding values.

[0078] The results are shown in Table 3: the accuracy of the estimated breeding values ​​for traits such as total litter size, live litter size, and stillbirth size was significantly improved compared to the Illumina Pig 50K chip and randomly selected loci. This demonstrates the effectiveness of the functional loci screened by the aforementioned 10K liquid-phase chip or sequencing system.

[0079] Table 3. Accuracy of estimated breeding values ​​for total litter size, live litter size, and stillbirths at different loci within the same population.

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[0081] All other parts not described in detail are existing technologies. Although the above embodiments have provided a detailed description of the present invention, they are only some embodiments of the present invention, not all embodiments. People can obtain other embodiments based on these embodiments without creative effort, and these embodiments all fall within the protection scope of the present invention.

Claims

1. A combination of functional loci for a sow's reproductive trait, characterized in that: The functional locus combination contains 12,232 SNP loci, and their locus information is as follows:

2. A method for screening functional locus combinations of sow reproductive traits as described in claim 1, characterized in that: Includes the following steps: 1) Gene chip sequencing was performed on each individual in the sow population, and a portion of the individuals were randomly selected for whole-genome resequencing at a sequencing depth of 30x; 2) Genotyping was performed using resequencing data, and genotype filling technology was used to fill the genotype data of the microarray sequencing population to the whole genome level to obtain whole genome SNPs; 3) Collect reproductive phenotypic data of Landrace sows and remove individuals with a total litter size of less than 3 and a birth weight of less than 0.3 kg; 4) Perform quality control on the filled data, remove loci with a maf value less than 0.05, and use the quality-controlled genotype data to perform genome-wide association analysis with the collected reproductive traits to screen out relevant associated loci; 5) Perform quality control on the filled data, remove sites with a maf value less than 0.01, and use the quality-controlled genotype data to quantify the contribution of whole-genome SNPs to the reproductive traits of Landrace sows according to the FAETH framework. Select the top-ranked SNP sites in FAETH and merge them with sites with a p-value less than 10-5 among the related sites selected in step 4 to obtain the functional sites of reproductive traits in Landrace sows.

3. The screening method according to claim 2, characterized in that: In step 1), the sow is a Landrace sow.

4. The screening method according to claim 2, characterized in that: In step 3), the reproductive phenotypic includes total number of offspring, number of live offspring, number of stillbirths, gestational age, and birth weight.

5. The application of the functional site combination of claim 1 in the screening of superior reproductive traits, improvement of pig reproductive traits and improvement of pig breeding and reproductive efficiency.

6. A probe assembly for detecting the functional site combination of claim 1, characterized in that: The probe assembly contains probes for detecting the 12,232 SNP sites as described in claim 1.

7. A 10K liquid phase chip for predicting and screening reproductive traits in pigs, characterized in that: The 10K liquid phase chip includes the probe assembly as described in claim 5.

8. A system for detecting the combination of functional sites as described in claim 1, characterized in that: The detection method of the system is to detect the 12,232 SNP sites described in claim 1 in the genome of the variety to be tested by sequencing.

9. The application of the 10K liquid phase chip of claim 7 or the system of claim 8 in the screening of superior reproductive traits.

10. The application of the 10K liquid phase chip of claim 7 or the system of claim 8 in the improvement of pig reproductive traits and the enhancement of pig breeding and reproductive efficiency.

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