Application of snp molecular marker related to residual feed intake of large white pig

Abstract

The application belongs to the technical field of animal molecular breeding, and particularly relates to application of a SNP molecular marker related to residual feed intake of large white pigs, a sequence of the SNP molecular marker is at least one of nucleotide sequences shown in SEQ ID NO. 1 to SEQ ID NO. 10, and the application refers to any one of the following: identifying residual feed intake of large white pigs; improving feed utilization efficiency of offspring of large white pigs. Through GWAS analysis, 10 SNP sites related to residual feed intake traits of large white pigs subjected to local breeding are accurately identified, the number of genetic markers related to feed utilization efficiency traits of large white pigs is enriched, and an important foundation is laid for carrying out domestic local molecular breeding and genome selection of large white pigs.

Description

Technical Field

[0001] This invention belongs to the field of animal molecular breeding technology, specifically relating to the application of a SNP molecular marker related to the remaining feed intake of Large White pigs. Background Technology

[0002] Feed costs are the largest single input in pig farming, accounting for 60% to 75% of total farming costs, far exceeding other expenditures such as veterinary drugs, labor, and facility depreciation. The growth, development, reproduction, body maintenance, and even the functioning of the immune system in pigs are highly dependent on a continuous and sufficient supply of feed. Feed quality and feed utilization efficiency directly determine the economic benefits of the pig farming industry. my country is the world's largest producer and consumer of pork. This massive consumption base keeps the number of pigs in stock and slaughtered at consistently high levels, resulting in a substantial total demand for feed. Therefore, obtaining higher livestock product output per unit of feed input, i.e., improving feed efficiency (FE), has become one of the most direct and economical ways to alleviate the supply-demand imbalance of raw materials and reduce farming costs. Furthermore, improving feed utilization efficiency also helps reduce the amount of feed required per unit of weight gain, thereby reducing the total amount of manure generated and potential greenhouse gas emissions.

[0003] From a genetic breeding perspective, feed utilization efficiency is a typical quantitative trait, simultaneously regulated by genetic factors and non-genetic factors such as feeding management, environmental temperature, and diet composition. Compared to improvements brought about by environmental management measures, which are often temporary and limited by specific feeding conditions, the improvements obtained through genetic selection are cumulative and transferable, continuing to play a role in offspring populations. Therefore, it is recognized as the most fundamental technical approach to improving feed utilization efficiency. Commonly used indicators of feed utilization efficiency include feed conversion ratio (FCR) and residual feed intake (RFI). RFI represents the difference between actual feed intake and the predicted feed intake required to sustain life and growth, reflecting the metabolic differences determined by an individual's genetic background. A negative RFI indicates that the individual consumes less feed to achieve the same weight gain and body composition goals, with feed utilization efficiency higher than the population average; conversely, a positive RFI indicates that the individual has problems with feed waste or low metabolic efficiency. RFI eliminates basal metabolic requirements related to growth and body weight composition, and can more purely reflect the genetic differences in feed utilization among individual animals. In recent years, it has been widely used in international pig breeding practices.

[0004] Genomic variation is a crucial genetic basis for individual differences in pigs. Single nucleotide polymorphisms (SNPs), the most common type of mutation, account for over 90% of genomic polymorphisms and are a major factor contributing to phenotypic differences. Feed utilization efficiency in pigs is also influenced by genetic variation. Screening and identifying relevant candidate genes or gene mutation sites can help improve feed utilization efficiency through marker-assisted selection, accelerating the process of genetic improvement in pigs.

[0005] Currently, methods for locating genetic variations in complex traits in pigs mainly rely on candidate gene methods and genome-wide association studies (GWAS). Candidate gene methods primarily target the discovery of single nucleotide polymorphisms (SNPs) associated with the target trait in known functional genes. This mainly employs an RFLP-PCR strategy, involving PCR amplification and enzyme digestion of DNA samples from each pig, followed by association analysis based on linkage disequilibrium principles to obtain relevant loci. However, this method has relatively low screening efficiency. GWAS, on the other hand, is a powerful method for discovering SNP markers associated with the target trait across the entire genome and has become the mainstream approach for genetic analysis of important economic traits in pigs. GWAS can identify SNP markers in known genes and also screen for SNP markers in new, unknown genes.

[0006] There are still many problems and shortcomings in the current field of screening genetic markers related to pig feed utilization efficiency traits, mainly in the following three aspects: (1) The accumulation of known genetic markers is far from sufficient to support efficient breeding. In recent years, scholars at home and abroad have reported several candidate genes and molecular marker loci related to feed utilization efficiency in different varieties and hybrid combinations. However, feed utilization efficiency, as a typical quantitative trait, is controlled by a large number of minor genes, and the contribution of each locus to the phenotype is extremely limited. In comparison, the candidate markers that have been successfully located and validated so far are far from sufficient to support precise and efficient molecular breeding practices in terms of quantity, effect size of a single locus, and cross-population applicability. It is still very urgent to continue to carry out in-depth research and validation of relevant genetic markers.

[0007] (2) The resolution of genotyping strategies based on conventional SNP chips is insufficient. Although chips (such as 60K or 80K SNP chips) widely used in current pig genome selection breeding have played an important role in genome-wide association analysis and genome prediction, their marker density is still sparse relative to the pig genome. The low marker density means that a large number of genomic regions are in coverage gaps, especially some low-frequency variations, structural variations, and important sites located in regions whose functions were unknown during chip design. This leads to insufficient statistical power of association analysis, and many truly causal genetic variations are difficult to capture and locate effectively.

[0008] (3) Genetic markers are highly specific to breeds and populations, especially in domestically bred populations where their discovery is insufficient. The effectiveness of genetic markers often depends heavily on the linkage disequilibrium structure and allele frequency distribution of a specific breed or population. Even within the same breed, there are significant differences in breeding history, population genetic structure, and inbreeding degree between different countries or regions. This results in a significant reduction in the applicability and predictive accuracy of molecular markers identified in imported populations in domestically bred populations, making it difficult to directly serve the molecular genetic improvement of feed utilization efficiency in domestic pig breeding populations.

[0009] Therefore, developing an application technology for tracking the remaining feed intake of Large White pigs has become a key technical problem that urgently needs to be solved in this field. Summary of the Invention

[0010] The purpose of this invention is to provide an application of SNP molecular markers related to the remaining feed intake of Large White pigs, thereby solving the problems existing in the prior art.

[0011] The technical solution adopted in this invention is: This invention provides an application of SNP molecular markers related to residual feed intake in Large White pigs, wherein the SNP molecular markers are at least one of the following 1) to 10): 1) The nucleotide sequence shown in SEQ ID NO.1 has a C or T nucleotide at position 101 bp; 2) The nucleotide sequence shown in SEQ ID NO.2 has a T or C nucleotide at the 101 bp position; 3) In the nucleotide sequence shown in SEQ ID NO.3, the nucleotide at position 101 bp is either A or T; 4) The nucleotide sequence shown in SEQ ID NO.4 has a C or T nucleotide at position 101 bp; 5) The nucleotide sequence shown in SEQ ID NO.5 has a C or G nucleotide at the 101 bp position; 6) In the nucleotide sequence shown in SEQ ID NO.6, the nucleotide at position 101 bp is either A or C; 7) The nucleotide sequence shown in SEQ ID NO.7 has a T or C nucleotide at the 101 bp position; 8) The nucleotide sequence shown in SEQ ID NO.8 has a T or C nucleotide at the 101 bp position; 9) In the nucleotide sequence shown in SEQ ID NO.9, the nucleotide at position 101 bp is either T or C; 10) In the nucleotide sequence shown in SEQ ID NO.10, the nucleotide at position 101 bp is either A or T; The application refers to any one of the following (1) and (2): (1) Determine the remaining feed intake of the Large White pig; (2) Improve the feed utilization efficiency of Large White pig offspring.

[0012] Preferably, the method for determining the remaining feed intake of Large White pigs is as follows: Genomic DNA was extracted from the Large White pigs to be tested and sequenced. Determine the genotype of this Large White pig at position 101 bp in SEQ ID NO.1~SEQ ID NO.10; If the genotype is at least one of the following a~j, then the Large White pig is low residual feed intake, where low residual feed intake means that the residual feed intake is not higher than -0.10 kg; a. The genotype at position 101bp of SEQ ID NO.1 is CT; b. The genotype at 101bp of SEQ ID NO.2 is TC; c. The genotype at 101bp of SEQ ID NO.3 is AT; d. The genotype at position 101bp of SEQ ID NO.4 is CT; e. The genotype at position 101bp of SEQ ID NO.5 is CG; f. The genotype at 101bp of SEQ ID NO.6 is AC; g. The genotype at SEQ ID NO. 7, position 101bp is TC; h, the genotype at SEQ ID NO. 101bp is TC; i. The genotype at 101bp of SEQ ID NO.9 is TC; j. The genotype at 101bp of SEQ ID NO.10 is AT.

[0013] Preferably, the method for improving feed utilization efficiency in Large White pig offspring is as follows: Genomic DNA was extracted from the Large White pigs to be tested and sequenced. Determine the genotype of this Large White pig at position 101 bp in SEQ ID NO.1~SEQ ID NO.10; By selecting Large White pigs carrying at least one of the genotypes shown in A to J below as parents for breeding, the feed utilization efficiency of Large White pig offspring can be improved. A. The genotype at position 101bp of SEQ ID NO.1 is CT; B. The genotype at SEQ ID NO.2, position 101bp, is TC; C. The genotype at 101bp of SEQ ID NO.3 is AT; D. The genotype at position 101bp of SEQ ID NO.4 is CT; E. The genotype at position 101bp of SEQ ID NO.5 is CG; F, the genotype at 101bp of SEQ ID NO.6 is AC; G, the genotype at SEQ ID NO. 7 at position 101 is TC; H, the genotype at position 101bp of SEQ ID NO.8 is TC; I. The genotype at 101bp of SEQ ID NO.9 is TC; J, the genotype at position 101bp of SEQ ID NO.10 is AT.

[0014] Preferably, the genomic DNA is derived from any one of the ear tissue, hair follicles, and blood of Large White pigs.

[0015] Compared with the prior art, the beneficial effects of the present invention are: This invention provides an application of SNP molecular markers related to the remaining feed intake of Large White pigs. The sequence of the SNP molecular marker is at least one of the nucleotide sequences shown in SEQ ID NO.1 to SEQ ID NO.10. The application refers to any one of the following (1) and (2): (1) identifying the remaining feed intake of Large White pigs; (2) improving the feed utilization efficiency of Large White pig offspring. Through GWAS analysis, this invention accurately identified 10 SNP loci related to the remaining feed intake trait in Large White pigs that affect local breeding, enriching the number of genetic markers related to the feed utilization efficiency trait in Large White pigs, and laying an important foundation for carrying out domestic local molecular breeding and genome selection of Large White pigs.

[0016] This invention provides 10 SNP loci that significantly influence the residual feed intake trait in Large White pigs. Specifically: The chr8_88658614 locus is located at position 88658614 on chromosome 8 of the pig genome (Sus_scrofa.11.1). The reference base for this locus is C, and the mutation here is a C-to-T change. The residual feed intake of the CC genotype is greater than that of the CT genotype, indicating that individuals with the CT genotype have higher feed utilization efficiency. The chr8_88658668 locus is located at position 88658668 on chromosome 8 of the pig genome (Sus_scrofa.11.1). The reference base for this locus is T, and the mutation here is a T-to-C change. The residual feed intake of the TT genotype is greater than that of the TC genotype. The residual feed intake for the TC genotype indicates higher feed utilization efficiency. The chr8_88660846 locus is located at position 88660846 on chromosome 8 of the pig genome (Sus_scrofa.11.1). The reference genome base for this locus is A, and the mutation here is an A-to-T change. The residual feed intake for the AA genotype is greater than that for the AT genotype, indicating higher feed utilization efficiency for the AT genotype. The chr8_88660859 locus is located at position 88660859 on chromosome 8 of the pig genome (Sus_scrofa.11.1). The reference genome base for this locus is C, and the mutation here is... The C mutation to T, where the remaining feed intake of the CC genotype is greater than that of the CT genotype, indicates that individuals with the CT genotype have higher feed utilization efficiency; the chr8_88661193 locus is located at the base position 88661193 on chromosome 8 of the pig genome (Sus_scrofa.11.1). The base position of this locus in the reference genome is C. The mutation here is a C to G, where the remaining feed intake of the CC genotype is greater than that of the CG genotype, indicating that individuals with the CG genotype have higher feed utilization efficiency; the chr8_88661860 locus is located at the base position 88661860 on chromosome 8 of the pig genome (Sus_scrofa.11.1). At this locus, the reference genome base is A, and the mutation here is A changing to C. The remaining feed intake of the AA genotype is greater than that of the AC genotype, indicating that individuals with the AC genotype have higher feed utilization efficiency. The chr8_88662571 locus is located at position 88662571 on chromosome 8 of the pig genome (Sus_scrofa.11.1). The reference genome base for this locus is T, and the mutation here is T changing to C. The remaining feed intake of the TT genotype is greater than that of the TC genotype, indicating that individuals with the TC genotype have higher feed utilization efficiency. The chr8_88663076 locus is located on chromosome 8 of the pig genome (Sus_scrofa.11).1) At the base position 88663076 on chromosome 8, the base of the reference genome at this position is T. The variation here is a T mutation to C. Among them, the remaining feed intake of the TT genotype is greater than that of the TC genotype, indicating that the feed utilization efficiency of individuals with the TC genotype is higher. The rs1111031671 locus is located at position 88810769 on chromosome 8 of the pig genome (Sus_scrofa.11.1). The reference base for this locus is T, and the mutation here is a T-to-C mutation. The remaining feed intake of the TT genotype is greater than that of the TC genotype, indicating that individuals with the TC genotype have higher feed utilization efficiency. The chr11_14489743 locus is located at position 14489743 on chromosome 11 of the pig genome (Sus_scrofa.11.1). The reference base for this locus is A, and the mutation here is an A-to-T mutation. The remaining feed intake of the AA genotype is greater than that of the AT genotype, indicating that individuals with the AT genotype have higher feed utilization efficiency. The variance of the residual feed intake phenotype explained by the 10 significant loci was 13.44%. In actual breeding processes, retaining individuals carrying superior genotypes is beneficial for screening individuals with high feed utilization efficiency for breeding, improving the accuracy of early selection for the feed utilization efficiency trait in Large White pigs, and has good economic benefits and broad application prospects. Attached Figure Description

[0017] Figure 1 The results of agarose gel electrophoresis analysis of genomic DNA extracted from ear tissue of Large White pigs. Lanes 1 to 21 contain 21 different samples.

[0018] Figure 2 Linkage disequilibrium analysis for Large White pig populations.

[0019] Figure 3 GWAS analysis of residual feed intake traits in Large White pigs. A: Manhattan plot; B: QQ plot.

[0020] Figure 4 Association analysis was performed on different genotypes at 10 SNP loci with remaining feed intake. A~J are, in order: chr8_88658614, chr8_88658668, chr8_88660846, chr8_88660859, chr8_88661193, chr8_88661860, chr8_88662571, chr8_88663076, rs1111031671, and chr11_14489743. Detailed Implementation

[0021] The present invention will be further illustrated below with specific embodiments, but these embodiments do not limit the scope of the invention. Modifications or substitutions to the details and form of the technical solutions of the present invention may be made without departing from the spirit and scope of the invention, but all such modifications or substitutions fall within the protection scope of the present invention.

[0022] The inventive concept of this invention is as follows: In the identification of genetic markers for feed utilization efficiency, the number of genetic markers for Large White pigs remains insufficient, traditional microarray screening strategies struggle to capture all key variations, and genetic markers exhibit strong breed and population specificity, particularly in domestically bred populations where their discovery is inadequate. This invention aims to provide a genetic marker for residual feed intake traits in domestically bred Large White pig populations and its application. Specifically, this invention aims to improve the accuracy of identifying genetic markers for feed utilization efficiency traits in domestically bred Large White pig populations by using a genome sequencing full-coverage strategy to fill in SNPs across the entire genome and then performing GWAS analysis, thereby screening and identifying molecular markers related to residual feed intake.

[0023] This invention provides 10 SNP loci that significantly affect the residual feed intake trait in Large White pigs, of which 9 SNP loci are located on chromosome 8 and 1 SNP locus is located on chromosome 11, described below: (1) The chr8_88658614 locus is located at the base of chromosome 88658614 in the pig genome (Sus_scrofa.11.1). The base of the reference genome at this locus is C. The mutation here is C to T. The remaining feed intake of the CC genotype is greater than that of the CT genotype, indicating that the feed utilization efficiency of individuals with the CT genotype is higher.

[0024] (2) The chr8_88658668 locus is located at the base of chromosome 88658668 in the pig genome (Sus_scrofa.11.1). The base of the reference genome at this locus is T. The variation here is T mutated to C. The remaining feed intake of the TT genotype is greater than that of the TC genotype, indicating that the feed utilization efficiency of the TC genotype individuals is higher.

[0025] (3) The chr8_88660846 locus is located at the base of chromosome 88660846 in the pig genome (Sus_scrofa.11.1). The base of the reference genome at this locus is A. The variation here is A mutated to T. Among them, the remaining feed intake of AA genotype is greater than that of AT genotype, indicating that the feed utilization efficiency of AT genotype individuals is higher.

[0026] (4) The chr8_88660859 locus is located at the base position 88660859 on chromosome 8 of the pig genome (Sus_scrofa.11.1). The base of the reference genome at this locus is C. The variation here is C mutated to T. Among them, the remaining feed intake of CC genotype is greater than that of CT genotype, indicating that the feed utilization efficiency of CT genotype individuals is higher.

[0027] (5) The chr8_88661193 locus is located at the base of chromosome 88661193 in the pig genome (Sus_scrofa.11.1). The base of the reference genome at this locus is C. The variation here is C to G. Among them, the remaining feed intake of CC genotype is greater than that of CG genotype, indicating that the feed utilization efficiency of CG genotype individuals is higher.

[0028] (6) The chr8_88661860 locus is located at the base of chromosome 88661860 in the pig genome (Sus_scrofa.11.1). The base of the reference genome at this locus is A. The variation here is A mutated to C. The remaining feed intake of the AA genotype is greater than that of the AC genotype, indicating that the feed utilization efficiency of the AC genotype individuals is higher.

[0029] (7) The chr8_88662571 locus is located at the base of chromosome 88662571 in the pig genome (Sus_scrofa.11.1). The base of the reference genome at this locus is T. The variation here is T mutated to C. The remaining feed intake of the TT genotype is greater than that of the TC genotype, indicating that the feed utilization efficiency of the TC genotype individuals is higher.

[0030] (8) The chr8_88663076 locus is located at the base of chromosome 88663076 in the pig genome (Sus_scrofa.11.1). The base of the reference genome at this locus is T. The variation here is a T mutation to C. The remaining feed intake of the TT genotype is greater than that of the TC genotype, indicating that the feed utilization efficiency of the TC genotype individuals is higher.

[0031] (9) The chr8_88810769 (rs1111031671) locus is located at the base of chromosome 88810769 in the pig genome (Sus_scrofa.11.1). The base of the reference genome at this locus is T. The variation here is a T mutation to C. The remaining feed intake of the TT genotype is greater than that of the TC genotype, indicating that the feed utilization efficiency of the TC genotype individuals is higher.

[0032] (10) The chr11_14489743 locus is located at the base of chromosome 11, 14489743 in the pig genome (Sus_scrofa.11.1). The base of the reference genome at this locus is A. The variation here is A mutated to T. Among them, the remaining feed intake of the AA genotype is greater than that of the AT genotype, indicating that the feed utilization efficiency of the AT genotype individuals is higher.

[0033] In actual breeding processes, preserving individuals carrying superior genotypes is beneficial for breeding new strains with low residual feed intake (i.e., screening for high feed utilization efficiency), improving the accuracy of early selection of feed utilization efficiency traits, and has good economic benefits and broad application prospects.

[0034] To enable those skilled in the art to better understand and implement the technical solutions of this invention, the invention will be further described below with reference to specific embodiments. In the description of this invention, unless otherwise specified, all reagents used are commercially available, and all methods used are conventional techniques in the art.

[0035] The formula for calculating the remaining feed intake according to the present invention is as follows: .

[0036] Wherein, 𝑅𝐹𝐼: remaining feed intake (kg); 𝐷𝐹𝐼: average daily feed intake (kg); Station: the measurement station where each individual is located; 𝛽1 and 𝛽2 are partial regression coefficients; 𝑀𝐵𝑊: the mean weight at the beginning and end of the measurement to the power of 0.75; 𝐴𝐷𝐺: average daily weight gain (kg).

[0037] Example 1: Application of SNP molecular markers related to residual feed intake in Large White pigs, as detailed below: 1. Experimental methods.

[0038] 1.1 Sample collection and genomic DNA preparation.

[0039] Phenotypic data collection and cleaning were performed on feed utilization efficiency traits of the Large White pig population, and DNA was extracted from the collected ear tissue.

[0040] 1.1.1 Phenotypic data collection.

[0041] The Bos Intelligent Measurement Station is used to measure the breeding pigs in the pig farm. When the pigs enter the measurement equipment, the equipment door closes automatically, the equipment recognizes the pig's electronic ear tag, and then opens the feed trough door. The measurement equipment will automatically record the weight of feed (g), feeding time (s), and remaining feed weight (g) of each pig's feeding each time. The feeding records of the pigs are statistically analyzed every day, and all data is automatically uploaded to the cloud system corresponding to the measurement equipment and stored.

[0042] 1.1.2. Phenotypic data cleaning.

[0043] Quality control was conducted based on factors such as feed intake (18g), feeding duration (60s), feeding rate (18g / min~66g / min), body weight (median corrected for daily weight), and number of feedings per day (2 times / day~15 times / day).

[0044] 1.1.3 The average daily feed intake (DFI), average daily gain (ADG), metabolic birth weight (MBW) at the midpoint of the experiment, and fixed effects were estimated using a linear regression model.

[0045] 1.1.4 DNA extraction.

[0046] Genomic DNA was extracted from porcine ear tissue using a fully automated nucleotide extractor (Bayer) and its accompanying kit. The extracted DNA was then examined using 2% agarose gel electrophoresis to detect degradation, and DNA concentration was determined using a NanoDrop 2000 ultra-micro spectrophotometer. Samples that passed the above DNA quality tests were then used for library construction and sequencing.

[0047] 1.2 Sequencing of pig genomic DNA samples.

[0048] Samples that passed quality control were sent to Wuhan Shadow Gene Technology Co., Ltd. for 2× low-depth resequencing (BGI T7 genome sequencing platform). Raw sequencing data were quality controlled using fastp (v0.23.4), with the main quality control parameter being "-q 20".

[0049] 1.3 SNP typing and filling.

[0050] The quality-controlled FASTQ files were aligned to the pig reference genome (Sus_scrofa.Sscrofa.11.1) using BWA (v0.7.17) software. Then, samtools (v1.22.1) was used to sort, deduplicate, remove redundancy, and index the obtained BAM files, resulting in pre-processed BAM files. Genetic variations were detected and genotyped using GATK 4.5's Haplotype Caller, Genotype GVCFs, and CombineGVCFs tools. The Haplotype Caller tool was used to detect variations and generate GVCF files for each sample. These GVCF files record variation information for all loci, preparing for joint genotyping. The GVCF files from all samples were merged using GLnexus software, and joint genotyping was performed to obtain VCF files containing the original SNP variation information. The SelectVariants tool was used to extract SNP variation sites from the original VCF files, and Variant was used to further refine the data. The Filtration tool was used to strictly filter SNPs, with the following filtering parameters: "QUAL < 30.0 || QD < 2.0 || FS > 60.0 || SOR > 3.0 || MQRankSum < -12.5 || ReadPosRankSum < -8.0". Population SNP filtering was performed using PLINK (v1.9) software. The filtering conditions were as follows: SNP detection rate of over 90%; minimum allele frequency (MAF) threshold set to 0.01. Then, genotyping was performed using Beagle 5.5 software combined with high-depth (>10×) Large White pig population genome data downloaded from the NCBI database. The filled data retained R... 2 Sites with a value ≥0.6 were then filtered using the same criteria in PLINK, and the resulting high-quality SNP sites were used for subsequent analysis.

[0051] 1.4 Chaining Disequilibrium (LD) Analysis.

[0052] PopLDdecay software was used to evaluate the degree of genome-wide linkage disequilibrium (LD) in a population, aiming to assess the efficiency and accuracy of association analysis.

[0053] 1.5 Genome-wide association analysis (GWAS).

[0054] GEMMA was used to perform genome-wide association analysis (GWAS) on feed utilization efficiency traits, with batch number, age at measurement, and weight gain during the measurement period as covariates. Boferroni correction was used to adjust the p-values ​​of the GWAS analysis. Because Boferroni correction is very strict, the effective number N of independent tests was calculated using the R package simpleM (https: / / github.com / LTibbs / SimpleM), with a threshold of 1 / N for the GWAS signal. The significance of each SNP was assessed using a likelihood ratio test. The genomic inflation factor (λ) for the test statistics was calculated using R (v4.3) software as the ratio between the median of the observed p-value distribution and the theoretical median. It was ensured that there was no significant stratification in the population, and that the results were not false positives due to population structure. The mixed linear model is as follows:

[0055] .

[0056] In the above model, y Indicates phenotypic value; W It is an n x (w + 1) matrix that includes the intercept and covariates; Then it is a vector of (w + 1) × 1, representing the effect size of the covariate; Gs It is an n × 1 vector representing the genotype of a certain locus. The value of each item is usually 0, 1, or 2 (the copy number of the allele). gamma This is a scalar, representing the effect size of the genotype at the target locus; g This is due to the accumulation effect; epsilon It represents the residual.

[0057] 2. Results.

[0058] 2.1 Phenotypic data collection and ear tissue sample DNA preparation.

[0059] (1) 234,377 feeding records of 673 Large White pigs (weight range of 25kg to 115kg during fattening period) were collected using the Bos Intelligent Measurement Station. Quality control was carried out based on conditions such as feed intake (18g), feeding duration (60s), feeding rate (18g / min to 66g / min), weight (median corrected for daily weight), and number of feedings per day (2 times / day to 15 times / day). After cleaning, 138,908 data points were obtained, and the number of samples that met the conditions was 360.

[0060] (2) The final residual intake (RFI) ranged from -0.42 kg to 0.59 kg, as shown in Table 1, by estimating the average daily feed intake (DFI), average daily gain (ADG), metabolic birth weight (MBW) at the midpoint of the experiment and the fixed effect based on the linear regression model.

[0061] Table 1. Descriptive statistics of remaining feed intake of 360 Large White pigs (3) Genomic DNA was extracted from pig ear tissue using a fully automated nucleotide extractor (Zhongke Bayer) and its accompanying reagent kit. Since low-quality DNA can affect sequencing results, 2% agarose gel electrophoresis was used to detect DNA degradation. The electrophoresis results are shown below. Figure 1 The DNA sample bands were clear and undegraded. Detection using an ultra-micro spectrophotometer showed that the lowest concentration of DNA in the extracted ear tissue samples was 108.75 ng / μL, the highest was 1559.51 ng / μL, and the average was 526.84 ng / μL. OD 260 / 280 The minimum value was 1.65, the maximum value was 2.11, and the average value was 1.83. These test results indicate that the DNA extracted from the ear tissue of the Large White pig population is of good quality and meets the requirements for library construction and sequencing.

[0062] 2.2 Sample sequencing.

[0063] 360 qualified samples were sent to Wuhan Shadow Gene Technology Co., Ltd. for 2× low-depth resequencing (BGI T7 genome sequencing platform). The raw sequencing data were quality controlled using fastp (v0.23.4), with the main quality control parameter being "-q 20".

[0064] 2.3 SNP typing.

[0065] Following the method described in section 1.3 above, a total of 2,274,704 high-quality SNP sites were obtained for subsequent analysis.

[0066] 2.4 Chaining Imbalance Analysis.

[0067] PopLDdecay software was used to evaluate the degree of genome-wide linkage disequilibrium (LD) in a population, aiming to assess the efficiency and accuracy of association analysis.

[0068] 2.5 Genome-wide association analysis.

[0069] The calculated λ value for the residual feed intake trait in this population was 0.97, indicating that there was no obvious stratification in the population and no false positives were produced due to population structure.

[0070] 2.6 Chaining Imbalance Analysis.

[0071] Depend on Figure 2 It can be seen that in linkage disequilibrium (LD) analysis, as the marker distance between paired SNPs increases, r... 2 The value tends to decrease, and r is observed in the first 100Kb range. 2 The value shows a rapid downward trend. In the study population, the linkage disequilibrium was at approximately 70 kb when r... 2 The value decayed to 0.2.

[0072] 2.7 GWAS signal identification.

[0073] GWAS analysis results are shown below Figure 3 This indicates that nine significant SNP signals are focused on chromosome 8 of the Large White pig, and one significant locus is located on chromosome 11. The QQ plot further confirms the reliability of the analysis results. Detailed information on the 10 loci is shown in Table 2.

[0074] Table 2. Remaining feed intake signal peak locations in the Large White pig population. Note: "-" in Table 2 indicates that this item is not available.

[0075] The nucleotide sequences containing the 10 SNP sites in Table 2 are shown in SEQ ID NO.1 to SEQ ID NO.10, with the 101st bp (in bold) in SEQ ID NO.1 to SEQ ID NO.10 being the mutation site.

[0076] SEQ ID NO.1: AATGAGTCACACTCCCAGGTAGATATCAGAGAGTCTGGAAAATGTGGTCTATCTGGATAGCTGCTTCTCAGGATTGACTGATACTTTGTAATGAGAAACACGAAATTGTGGTGAGTAATTGCTTTTCTCAGCCATTCACATCTGAATCTAGGAATTCTTGTTATAAAAAAAAAATGTTTCATCGAGATATTGTATTACCTT.

[0077] SEQ ID NO.2: GGATAGCTGCTTCTCAGGATTGACTGATACTTTGTAATGAGAAACACGAAATTGTGGTGAGTAATTGCTTTTCTCAGCCATTCACATCTGAATCTAGGAATTCTTGTTATAAAAAAAAAATGTTTCATCGAGATATTGTATTACCTTGGAGTACTTTAGACAAAATCCTGAGGAAAATGATAACATTCAAAAAAGTCTACT。

[0078] SEQ ID NO.3: TTTGTACCAGTTATAAACAATTTTAGGAATATCCTAAGTATAGGCAATTACAGAATTACTCAGATTGTTCTATCAGAAAATTTGTCACCTTCAGGTGTTCTAAACTCTCTGGAGCATCAAGCTAGCTTTATTCACTCTGTTTTCATAGCAATCGTCTTTTTAGCCAACATGAAGCACTGAAAACAATGCTCATTTCTCATAC。

[0079] SEQ ID NO.4: AAAACAATTTTAGGAATATCCTAAGTATAGGCAATTACAGAATTACTCAGATTGTCTATCAGAAAATTTGTCACCTTCAGGTGTTCTAAACTCTTCTGGAGCATCAAGCTAGCTTTATTCACTCTGTTTTCATAGCAATCGTCTTTTTAGCCAACATGAAGCACTGAAAACAATGCTCATTTCTCATACTCCATCATAGAGT。

[0080] SEQ ID NO.5: TAGTACATGTTTGTCAGTATGTAAGGATCTGACACAAAACAGCTGTGACATCATGGACATGATATGTCACGAATGTGGAACTTAGAGTTGGAAGATCTGGCTTCAAGTCCCAGCTCTCTCATTTACTACCTTGTGACTTTGGCCAGTCACTTAACCTCTCTAAGCCTTGGTTCCCATGTTTGAAAATGATGGTATTATACC。

[0081] SEQ ID NO.6: ACATCTTGTTAATCATAAATGCATAAACATTTGCAAGAGAGTGTTGTAGGCATGAATCATTTTTGTTCAGCTTAAAGACAATGCTTTTGTTGCACTTAGAATTTCTGGATATTTGACAATAATACAGGCTTTGAAATATCAGTGGCCTACCAGTTCCTTCAATTCCTTTTATTATCATGTGCCATTTGCCTTAATCTTGGG。

[0082] SEQ ID NO.7: CATCCAGGGAGATTTATTCAGTGAGCCTCTTTTTTTTTTTTTTTTTTTAATTAAACATAAACTAATATTTCCCAGAGTTCCGGTCATGGCTCAGTGAAAATGAATCTGATTATTATCCATGAGGACACAGTTCCATCCCTGGCCTCACTCAGCGAGTTAAGGATCTGTGTTGCCCTGATCTGTGGTGTAGGTCGCAGACTA。

[0083] SEQ ID NO.8: AAACATTATATTCCACAATTACATTTTCTCTGAAAATTAATGGAGTTTGAGGAGGCACATGCATAAGAGAGAGAGGGTACACTCTACACTTCAGAGGCTTTAATGCTCTGACTTCAAGGTAGGATAGATTGGTGGCTGGGTTTTGGGTTTCCACTTACCAGCTGTGCATCCTTGAACAGTTATTAAAACTCTCTACTTCAT。

[0084] SEQ ID NO.9: TGGGCCGCTCCCATGGCATATGGAGGTTCCTAGGCTAGGGGTTGAATCGGAGCTGCAGCCACAGGCCTACGCCAGAGCCACAGCAACGCGGGATCCGAGCTGTGTCTGCAACCTACACCACAGCTCTTGGCAACGCCGGATCGTTAACCCACTGAGCAAGGTCAGGGACCAAACCTGCAACCTCATGGTTCCTAGTCGGAT。

[0085] SEQ ID NO.10: GTATGGAATTTACTTTTTATCATTTTCTACCAGAGCAGCTCCACTCTCTAAGCAAGTAAATCCATACAAGGACCATTTCTTTCACAAAAGATGAAAAATAAGCATAAGTTCCAGAATTAAGGTTGGTATTAGAATCGATGAGAGAAGAGGAACAGAGAGTAGTTTAATGGGGTAGAGCTTTAAGGATAAAGAAAGACTCCA.

[0086] 2.8 Correlation analysis between SNP loci and residual feed intake phenotype.

[0087] Association analysis between genotypes and residual feed intake at 10 significant loci was performed using R software. The results are shown in Table 3. Since the number of homozygous mutants in this resource population was only 1-2, statistical analysis was not feasible, and their trait effects could not be reliably evaluated. To ensure the accuracy and reliability of the experimental data, this invention only used wild-type homozygous and heterozygous genotypes with sufficient samples for phenotypic association analysis. The association analysis diagram between genotypes and phenotypes at significant loci is shown below. Figure 4 As shown.

[0088] Table 3. Association analysis of genotypes at 10 SNP loci with residual feed intake trait From Table 3 and Figure 4 It was found that the correlation between the 10 SNP loci and the remaining feed intake of pigs was extremely significant (P<0.0001).

[0089] 1) The remaining food intake of the CC genotype at the chr8_88658614 locus was 0.2±0.01, while that of the CT genotype was -0.15±0.03. The remaining food intake of the CT genotype was significantly lower than that of the CC genotype. 2) The remaining food intake of the TT genotype at the chr8_88658668 locus was 0.02±0.01, while that of the TC genotype was -0.15±0.03. The remaining food intake of the TC genotype was significantly lower than that of the TT genotype. 3) The remaining food intake of the AA genotype at the chr8_88660846 locus was 0.02±0.01, while that of the AT genotype was -0.15±0.03. The remaining food intake of the AT genotype was significantly lower than that of the AA genotype. 4) The remaining food intake of the CC genotype at the chr8_88660859 locus was 0.02±0.01, while that of the CT genotype was -0.15±0.03. The remaining food intake of the CT genotype was significantly lower than that of the CC genotype. 5) The remaining food intake of the CC genotype at the chr8_88661193 locus was 0.02±0.01, while that of the CG genotype was -0.15±0.03. The remaining food intake of the CG genotype was significantly lower than that of the CC genotype. 6) The remaining food intake of the AA genotype at the chr8_88661860 locus was 0.02±0.01, while that of the AC genotype was -0.15±0.03. The remaining food intake of the AC genotype was significantly lower than that of the AA genotype. 7) The remaining food intake of the TT genotype at the chr8_88662571 locus was 0.02±0.01, while that of the TC genotype was -0.15±0.03. The remaining food intake of the TC genotype was significantly lower than that of the TT genotype. 8) The remaining food intake of the TT genotype at the chr8_88663076 locus was 0.02±0.01, while that of the TC genotype was -0.15±0.03. The remaining food intake of the TC genotype was significantly lower than that of the TT genotype. 9) The remaining food intake of the TT genotype at the rs1111031671 locus was 0.02±0.01, while that of the TC genotype was -0.12±0.02. The remaining food intake of the TC genotype was significantly lower than that of the TT genotype. 10) The remaining food intake of the AA genotype at the chr11_14489743 locus was 0.02±0.01, while that of the AT genotype was -0.17±0.03. The remaining food intake of the AT genotype was significantly lower than that of the AA genotype.

[0090] The residual feed intake of mutant genotypes at each SNP site was lower than that of the reference genotype, indicating that mutant genotypes have higher feed utilization efficiency.

[0091] We used R software to perform multi-locus joint effects analysis on the genotyping data of 10 SNP loci and the residual feed intake (RFI) phenotypic data of 360 individuals using an additive linear model. The 10 SNPs were additively encoded with 0 / 1 / 2 allele doses, and after matching individual phenotypes, a joint regression model was constructed to test the overall genetic effect of the 10 SNPs and calculate the phenotypic variance explained. The results showed that the joint additive effect of the 10 SNPs significantly affected residual feed intake. The specific model is as follows:

[0092] .

[0093] in, Let be the phenotypic value of the i-th individual; mu It is the group mean; G i The combined genotype effect of the i-th individual; e i Let be the random residual effect of the i-th individual.

[0094] The results showed that the combined additive effect of the 10 SNPs made a highly significant contribution to the phenotypic variation in residual feed intake (P < 2.54 × 10⁻⁻⁴). 8 The additive effect values ​​for each SNP site are shown in Table 4 below.

[0095] Table 4. Additive effect values ​​of each SNP locus Under the additive linear model, the sum of squares explained by the 10 SNPs was 1.69173, the sum of squares of the residuals was 10.89953, and the total sum of squares of the traits was 12.59127. The calculated variance of the residual feed intake phenotype explained by this marker combination was 13.44% (1.69173 / 12.59127*100%). In practical breeding, retaining individuals carrying superior genotypes is beneficial for screening individuals with high feed utilization efficiency, improving the accuracy of early selection, and has good economic benefits and broad application prospects.

[0096] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0097] The embodiments described above are merely examples of several implementations of the present invention, and while the descriptions are relatively specific and detailed, they should not be construed as limiting the scope of the invention. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of the present invention, and these modifications and improvements all fall within the scope of protection of the present invention.

Claims

1. The application of a SNP molecular marker associated with residual feed intake in Large White pigs, characterized in that, The SNP molecular marker is at least one of the following 1) to 10): 1) The nucleotide sequence shown in SEQ ID NO.1 has a C or T nucleotide at position 101 bp; 2) The nucleotide sequence shown in SEQ ID NO.2 has a T or C nucleotide at the 101 bp position; 3) In the nucleotide sequence shown in SEQ ID NO.3, the nucleotide at position 101 bp is either A or T; 4) The nucleotide sequence shown in SEQ ID NO.4 has a C or T nucleotide at position 101 bp; 5) The nucleotide sequence shown in SEQ ID NO.5 has a C or G nucleotide at the 101 bp position; 6) In the nucleotide sequence shown in SEQ ID NO.6, the nucleotide at position 101 bp is either A or C; 7) The nucleotide sequence shown in SEQ ID NO.7 has a T or C nucleotide at the 101 bp position; 8) The nucleotide sequence shown in SEQ ID NO.8 has a T or C nucleotide at the 101 bp position; 9) In the nucleotide sequence shown in SEQ ID NO.9, the nucleotide at position 101 bp is either T or C; 10) In the nucleotide sequence shown in SEQ ID NO.10, the nucleotide at position 101 bp is either A or T; The application refers to any one of the following (1) and (2): (1) Determine the remaining feed intake of the Large White pig; (2) Improve the feed utilization efficiency of Large White pig offspring.

2. The application as described in claim 1, characterized in that, The method for determining the remaining feed intake of Large White pigs is as follows: Genomic DNA was extracted from the Large White pigs to be tested and sequenced. Determine the genotype of this Large White pig at position 101 bp in SEQ ID NO.1~SEQ ID NO.10; If the genotype is at least one of the following a~j, then the Large White pig is low residual feed intake, where low residual feed intake means that the residual feed intake is not higher than -0.10 kg; a. The genotype at position 101bp of SEQ ID NO.1 is CT; b. The genotype at 101bp of SEQ ID NO.2 is TC; c. The genotype at 101bp of SEQ ID NO.3 is AT; d. The genotype at position 101bp of SEQ ID NO.4 is CT; e. The genotype at position 101bp of SEQ ID NO.5 is CG; f. The genotype at 101bp of SEQ ID NO.6 is AC; g. The genotype at SEQ ID NO. 7, position 101bp is TC; h, the genotype at SEQ ID NO. 101bp is TC; i. The genotype at 101bp of SEQ ID NO.9 is TC; j. The genotype at 101bp of SEQ ID NO.10 is AT.

3. The application as described in claim 1, characterized in that, The following methods can be used to improve feed utilization efficiency in Large White pig offspring: Genomic DNA was extracted from the Large White pigs to be tested and sequenced. Determine the genotype of this Large White pig at position 101 bp in SEQ ID NO.1~SEQ ID NO.10; By selecting Large White pigs carrying at least one of the genotypes shown in A to J below as parents for breeding, the feed utilization efficiency of Large White pig offspring can be improved. A. The genotype at position 101bp of SEQ ID NO.1 is CT; B. The genotype at SEQ ID NO.2, position 101bp, is TC; C. The genotype at 101bp of SEQ ID NO.3 is AT; D. The genotype at position 101bp of SEQ ID NO.4 is CT; E. The genotype at position 101bp of SEQ ID NO.5 is CG; F, the genotype at 101bp of SEQ ID NO.6 is AC; G, the genotype at SEQ ID NO. 7 at position 101 is TC; H, the genotype at position 101bp of SEQ ID NO.8 is TC; I. The genotype at 101bp of SEQ ID NO.9 is TC; J, the genotype at position 101bp of SEQ ID NO.10 is AT.

4. The application as described in claim 2 or claim 3, characterized in that, The genomic DNA was derived from any one of the ear tissue, hair follicles, or blood of the Large White pig.

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