Application of SNP (Single Nucleotide Polymorphism) molecular marker influencing feed conversion rate of large white pigs

Abstract

The invention belongs to the technical field of animal molecular breeding, and particularly relates to application of an SNP molecular marker influencing the feed conversion rate of large white pigs, the SNP molecular marker is at least one of the following: a nucleotide sequence shown as SEQ ID NO.1, nucleotide at the 101bp site is C or T; in the nucleotide sequence as shown in SEQ ID NO.3, the nucleotide at the 101bp site is G or A; the application refers to any one of the following steps: identifying the feed conversion rate of the large white pigs; the feed utilization rate of large white pig offspring is improved. Two brand-new SNP molecular markers are identified on a large white pig for the first time and are remarkably related to the feed conversion rate. Based on the marker, early and accurate feed efficiency identification and breeding can be performed on large white pigs, and by screening individuals carrying excellent genotypes as parents, offspring with lower feed conversion rate can be effectively bred.

Description

Technical Field

[0001] This invention belongs to the field of animal molecular breeding technology, specifically relating to the application of SNP molecular markers that affect the feed conversion rate of Large White pigs. Background Technology

[0002] With global economic development and continued population growth, the livestock industry plays a crucial role in ensuring meat supply. Pigs are one of the world's most raised livestock, and pig farming is an important component of my country's animal husbandry industry and a pillar industry of domestic meat production. my country is the world's largest producer and consumer of pork, with a large population base and persistently high demand for pork. At the same time, with the continuous expansion of large-scale pig farming, cost control has become an increasingly important concern in the industry. Feed input alone accounts for 50% to 85% of the total cost of pig farming, making it the largest contributor compared to other costs such as veterinary drugs and labor. Currently, compound feed is widely used in pig farming, leading to a year-on-year increase in demand for crops such as corn and soybeans, while my country's arable land resources are limited. Pig feed utilization efficiency is influenced by both genetic factors and environmental factors such as feeding management, but continuous improvement can be achieved through genetic selection. Therefore, improving pig feed utilization efficiency through effective breeding methods has become a key focus of current and future pig breeding work. Improving the efficiency of pigs' feed utilization not only helps reduce grain consumption, but also reduces manure and greenhouse gas emissions, which has significant economic, ecological and social benefits.

[0003] Pigs obtain energy through feed intake to meet their needs for life and growth; the weight of feed ingested is called feed intake. Feed utilization efficiency mainly reflects a pig's ability to convert and utilize feed, and commonly used indicators include feed conversion ratio (FCR) and residual feed intake. Although their definitions and calculation methods differ, both are based on assessing feed utilization efficiency through changes in feed intake and body weight. Feed conversion ratio (FCR) is the ratio of the total weight of feed consumed to the total increase in animal body weight during the measurement period; in pigs, it is also called the "feed-to-meat ratio" and is the reciprocal of feed utilization efficiency. The lower the FCR value, the higher the feed utilization efficiency and the lower the breeding cost. Studies have shown that the heritability estimates of traits related to feed utilization efficiency are between 0.27 and 0.46. A study on "Junmu No. 1 White Pig" showed that the heritability of residual feed intake was approximately 0.15, indicating that the pig feed utilization efficiency trait is a genetically low-to-medium heritability trait. 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.

[0004] 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 single nucleotide polymorphisms (SNPs) associated with the target trait within known functional genes. This mainly employs RFLP-PCR, 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.

[0005] There are still many problems and shortcomings in the current field of screening genetic markers related to pig feed utilization efficiency: (1) The number of relevant genetic markers is still very insufficient. To date, the relevant candidate genes or genetic markers that have been screened and identified are: Yorkshire (Large White) pig AHR_rs339939442, Duroc × (Landrace × Yorkshire) AIF1L , ASS1 and QRFP Mutations in genes, porcine Orexin (G516-A516), and chromosome 263045504 (GA) and 235291491 (CT) in Large White pigs are among the identified genetic markers. However, feed utilization efficiency in pigs is generally considered a quantitative trait, controlled by multiple genes with minor effects. Currently, the number of relevant candidate genes or genetic markers discovered is still very limited. Existing markers are insufficient in terms of quantity, effect size, and universality to support a breeding revolution, necessitating further screening of relevant genetic markers.

[0006] (2) The effectiveness of screening and identifying relevant genetic markers based on small population samples is limited. The cost of accurately measuring the feed efficiency of individual pigs is extremely high, which limits the ability to obtain high-precision data from large samples. Small population samples, such as a few hundred pigs, are slightly insufficient in terms of accuracy in identification, making it difficult to discover rare and minor variations. Most variation sites that are statistically "correlated" are prone to false negatives or false positives.

[0007] (3) Screening and identification strategies based on traditional chip technology are difficult to capture all key variations. The coverage density of mainstream chips related to pig genome selection breeding, such as 60K or 80K SNP chips, is limited, making it difficult to capture all key variations on the pig genome. During the analysis process, a large amount of unknown information is easily missed.

[0008] (4) Genetic markers are highly specific to varieties and populations, especially in domestically bred populations where their discovery is insufficient. Markers found in one variety in other varieties often fail in other varieties. Similarly, even within the same variety, there are differences in the genetic background of domestic and foreign populations, resulting in poor applicability of related genetic variations to domestically bred populations and hindering the molecular genetic improvement of related traits.

[0009] Therefore, developing an application technology for marking feed conversion ratio in 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 that affect the feed conversion rate of Large White pigs, which solves the problems of insufficient number of genetic markers for pig feed utilization efficiency, low identification accuracy, and lack of genetic markers for domestically bred populations in the prior art.

[0011] The technical solution adopted in this invention is: This invention provides an application of SNP molecular markers that affect feed conversion ratio in Large White pigs, wherein the SNP molecular markers are at least one of the following ① and ②: ①The nucleotide sequence shown in SEQ ID NO.1 has a C or T nucleotide at position 101 bp; ②The nucleotide sequence shown in SEQ ID NO.3 has a nucleotide at position 101 bp that is either G or A; The application refers to any one of the following (1) and (2): (1) To determine the feed conversion ratio of Large White pigs; (2) Improve the feed utilization rate of offspring of Large White pigs.

[0012] Preferably, the method for determining the feed conversion ratio 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 the Large White pig at 101 bp of SEQ ID NO.1 or SEQ ID NO.3; If the genotype is at least one of A) and B) below, then the Large White pig has a low feed conversion ratio, which means that the feed conversion ratio is not higher than 2.61; A) The genotype at 101bp of SEQ ID NO.1 is TT; B) The genotype at 101bp of SEQ ID NO.3 is AA.

[0013] Preferably, the method for improving feed utilization 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 the Large White pig at 101 bp of SEQ ID NO.1 or SEQ ID NO.3; By selecting Large White pig individuals carrying at least one of the genotypes shown in a) and c) as parents for breeding, the feed utilization rate of Large White pig offspring can be improved. a) The genotype at 101bp of SEQ ID NO.1 is TT; b) The genotype at 101bp of SEQ ID NO.3 is AA.

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

[0015] Preferably, the feed conversion ratio refers to: The ratio of the total weight of feed consumed by Large White pigs during the fattening period to the total weight gain of the Large White pigs.

[0016] Compared with the prior art, the beneficial effects of the present invention are: This invention provides an application of SNP molecular markers affecting feed conversion ratio in Large White pigs. The SNP molecular markers are at least one of the following ① and ②: ① the nucleotide sequence shown in SEQ ID NO.1, where the nucleotide at the 101bp site is C or T; ② the nucleotide sequence shown in SEQ ID NO.3, where the nucleotide at the 101bp site is G or A. The application refers to any one of the following (1) and (2): (1) identifying the feed conversion ratio of Large White pigs; (2) improving the feed utilization rate of Large White pig offspring. This invention identifies two novel SNP molecular markers on chromosome 6 of Large White pigs for the first time, namely rs1112948356 and chr6_8065911, which are significantly correlated with feed conversion ratio. Based on these markers, early and precise feed efficiency identification and breeding of Large White pigs can be carried out. By selecting individuals carrying superior genotypes as parents, offspring with lower feed conversion ratios can be effectively bred. This method is based on large-scale local population validation, with reliable results, simple operation, and easy integration into existing breeding systems. It can significantly reduce feed costs and improve economic efficiency, while also having a positive impact on saving grain and promoting the green development of animal husbandry. Attached Figure Description

[0017] Figure 1 This is a partial result of agarose gel electrophoresis detection of genomic DNA from pig ear tissue.

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

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

[0020] Figure 4 Association analysis of two loci with different genotypes on chromosome 6 of Large White pigs and feed conversion rate. A: chr6_8048592; B: chr6_8065911. Specific implementation mode

[0021] The present invention will be further described below through specific embodiments, but it does not limit the scope of the present invention. Modifications or substitutions can be made to the details and forms of the technical solutions of the present invention without departing from the spirit and scope of the present invention, but these modifications or substitutions all fall within the protection scope of the present invention.

[0022] The inventive concept of the present invention is as follows: In view of the problems existing in the identification of genetic markers for feed utilization efficiency in Large White pig populations, such as the still insufficient number of genetic markers, the limited efficacy of screening and identifying relevant genetic markers based on small population samples, the difficulty of traditional chip technology screening and identification strategies to capture all key variations, and the strong specificity of genetic markers for breeds and populations, especially the lack of exploration in domestic local breeding populations. The present invention aims to provide a genetic marker for feed utilization efficiency traits in local Large White pig populations and its application. Specifically, the present invention aims to perform low-depth (2×) genome sequencing on a local Large White pig population selected through breeding, combined with genome-wide SNP imputation for GWAS analysis, so as to improve the accuracy of identifying genetic markers for pig feed utilization efficiency traits and screen and identify the number of SNP loci related to feed utilization efficiency traits.

[0023] The present invention provides two SNP loci that have a significant impact on the feed conversion rate of Large White pigs, both of which are located on chromosome 6 of the pig genome (Sus_scrofa.11.1). They are described as follows:

[0024] (1) The rs1112948356 locus is located at the base of position 8048592 on chromosome 6 of the pig genome (Sus_scrofa.11.1). The base of the reference genome at this locus is C, and the variation here is the mutation of C to T. Among them, the feed conversion rate of the TT genotype < the feed conversion rate of the CT genotype < the feed conversion rate of the CC genotype, indicating that the feed-to-meat ratio of individuals with the TT genotype is the smallest and the feed utilization efficiency is the highest.

[0025] (2) The chr6_8065911 locus is located at the base of the 8,065,911th site on chromosome 6 of the pig genome (Sus_scrofa.11.1). The base of the reference genome at this site is G, and the mutation here is from G to A. Among them, the feed conversion efficiency of the AA genotype < the feed conversion efficiency of the GA genotype < the feed conversion efficiency of the GG genotype, indicating that the AA genotype individuals have the smallest feed-to-meat ratio and the highest feed utilization efficiency.

[0026] In actual breeding, retaining individuals carrying excellent genotypes is conducive to screening new strains with high feed utilization efficiency, improving the accuracy of early selection for feed utilization efficiency traits, and having good economic benefits and broad application prospects.

[0027] In order to enable those skilled in the art to better understand and implement the technical solutions of the present invention, the present invention will be further described below in conjunction with specific embodiments. In the description of the present invention, unless otherwise specified, all reagents used are commercially available, and all methods used are conventional techniques in the art.

[0028] The abbreviation list of the present invention is shown in Table 1.

[0029] Table 1 Abbreviation List Explanation of relevant terms in the present invention: Feed conversion rate: The ratio of the total weight of feed consumed during the fattening period to the total increase in animal body weight.

[0030] Feed-to-meat ratio: The weight of feed consumed per 1 kg increase in body weight during the fattening period.

[0031] The feed conversion rate and the feed-to-meat ratio are reciprocal to each other.

[0032] Example 1 Application of an SNP molecular marker affecting the feed conversion rate of Yorkshire pigs, specifically as follows: 1. Method.

[0033] 1.1. Sample collection and genomic DNA preparation.

[0034] Collect and clean the phenotypic data of the feed utilization efficiency trait for the Yorkshire pig resource population, and extract and quality-check the DNA from the collected ear tissues.

[0035] (1) Phenotypic data collection.

[0036] 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.

[0037] (2) Phenotypic data cleaning.

[0038] 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 (3~20 times / day).

[0039] (3) DNA extraction.

[0040] Low-quality DNA can affect sequencing results. Genomic DNA was extracted from pig ear tissue using an automated nucleotide extractor and its accompanying kit. 2% agarose gel electrophoresis was used to detect DNA degradation, and a NanoDrop 2000 micro-spectrophotometer was used to determine DNA concentration. Samples that passed the DNA quality check were used for library construction and sequencing.

[0041] 1.2 Sequencing of pig genomic DNA samples.

[0042] Samples that passed quality control were sent to Wuhan Yingzi Gene Technology Co., Ltd. for 2× low-depth resequencing. Raw sequencing data were quality controlled using fastp (v0.23.4), with the main quality control parameter being "-q 20".

[0043] 1.3 SNP typing and filling.

[0044] The quality-controlled FASTQ files were aligned to the pig reference genome (Sus_scrofa.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 the Haplotype Caller, Genotype GVCFs, and CombineGVCFs tools in GATK 4.2. The Haplotype Caller tool was used to detect variations and generate GVCF files for each sample, recording variation information for all loci, preparing for joint genotyping. The CombineGVCFs tool was used to merge the GVCF files of all samples, and the GenotypeGVCFs tool was used for joint genotyping, resulting in 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 tools were used to further refine the extraction process. The Filtration tool was used to rigorously filter SNPs, with the following filter 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: individual detection rate of ≥ 90%; SNP detection rate of ≥ 90%; minimum allele frequency threshold set to 0.05. Then, Beagle 5.5 software was used, combined with high-depth (10×) Large White pig population genome data downloaded from the NCBI database, to perform genotyping. The resulting high-quality SNP loci were used for subsequent analysis.

[0045] 1.4 Chaining Imbalance Analysis.

[0046] PopLDdecay software was used to evaluate the degree of genome-wide linkage disequilibrium in a population, aiming to assess the efficiency and accuracy of association analysis.

[0047] 1.5 Genome-wide association analysis.

[0048] 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 was used to correct for p-values ​​in the GWAS analysis. The threshold for the GWAS signal was 1 / N. The genomic expansion factor (λ) was calculated using R (v4.3) software as the ratio between the observed p-value distribution and the theoretical median. It was ensured that the population did not exhibit significant stratification, and that the results were not false positives due to population structure. The mixed linear model is as follows:

[0049] .

[0050] In the above model, y Indicates phenotypic value; W It is an n x (w + 1) matrix; it 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). This is a scalar, representing the effect size of the genotype at the target locus. This is due to the accumulation effect. This is the residual.

[0051] 2. Results.

[0052] 2.1 Phenotypic data collection and ear tissue sample DNA preparation.

[0053] (1) 8,800,735 feeding records were collected from 3,541 Large White pigs using the Boss Intelligent Measurement Station. The weight range during the fattening period was 35 kg to 120 kg. Quality control was performed based on feed intake (18 g), feeding duration (60 s), feeding rate (18 g / min to 66 g / min), weight (median corrected for daily), and number of feedings per day (3 to 20 times / day). After cleaning, 6,532,568 data points were obtained, and the number of samples meeting the criteria was 3,231. The final feed conversion ratio (FCR) ranged from 1.76 to 3.51.

[0054] (2) Genomic DNA was extracted from pig ear tissue using an automated nucleotide extractor and its accompanying kit. Low DNA quality can affect sequencing results; therefore, 2% agarose gel electrophoresis was used to detect DNA degradation. The electrophoresis results are shown below. Figure 1 As shown in the image, the genomic DNA master band of the extracted tissue sample is clear and undegraded. Figure 1The 21 lanes represent the detection results of a portion of the samples. Detection results using an ultra-micro spectrophotometer showed that the lowest DNA concentration was 98.75 ng / μL, the highest was 1159.50 ng / μL, and the average concentration of the population sample was 416.50 ng / μL. OD 260 / 280 The minimum value was 1.60, the maximum value was 2.09, and the average value was 1.79. The above test results indicate that the DNA quality of the experimental population is high and meets the requirements for library construction and sequencing.

[0055] 2.2 Sample sequencing.

[0056] 3231 qualified samples were sent to Wuhan Shadow Gene Technology Co., Ltd. for 2× low-depth resequencing. The raw sequencing data were quality controlled using fastp (v0.23.4), with the main quality control parameter being "-q 20".

[0057] 2.3 SNP typing.

[0058] Following the method described in section 1.3 above, a total of 997,854 high-quality SNP sites were obtained for subsequent analysis.

[0059] 2.4 Chaining Imbalance Analysis.

[0060] PopLDdecay software was used to evaluate the degree of genome-wide linkage disequilibrium in a population, aiming to assess the efficiency and accuracy of association analysis.

[0061] 2.5 Genome-wide association analysis.

[0062] This invention uses batch size, age at measurement, and weight gain during the measurement period as covariates. Boferroni was used to correct the p-values ​​of the GWAS analysis. The threshold for the GWAS signal was 1 / N, where N equals 70820. The genomic expansion factor (λ) was calculated using R software as the ratio between the observed p-value distribution and the theoretical median. The calculated λ value for the feed utilization efficiency trait in this population was 1.014, indicating no significant stratification within the population and no false positives due to population structure.

[0063] 2.6 Chaining Imbalance Analysis.

[0064] Depend on Figure 2 It can be seen that in linkage disequilibrium 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 is at approximately 100 kb when r... 2 The value decayed to 0.2.

[0065] 2.7 GWAS signal identification.

[0066] Depend on Figure 3 As can be seen, two signal peaks were observed on pig chromosome 6, and the QQ plot further confirmed the reliability of the analysis results. Detailed information on the two loci is shown in Table 2.

[0067] Table 2. Information on feed conversion ratio signal peaks identified on chromosome 6 of Large White pigs. The nucleotide sequence of the SNP containing the C→T mutation site at position 8048592 on chromosome 6 is shown in SEQ ID NO.1 and SEQ ID NO.2.

[0068] SEQ ID NO.1: TGCTGAAGTGGGAAGAATAATTGGACCAAATAGTCATGCGATTAATGCAAACAGAGAGAACTCATCTGTTCCGAGTACAGTAAATGCACTGCTGAAGACGCGGAGAGCTTGCTTTCTGTTTTATTCTTGGGCTGGGGAACAAATGTTGCTGAGTTCACTGCCACAGATTCCTGTGTTTCTTCCACGGGGCGGAGACCTTAAA.

[0069] SEQ ID NO.2: TGCTGAAGTGGGAAGAATAATTGGACCAAATAGTCATGCGATTAATGCAAACAGAGAGAACTCATCTGTTCCGAGTACAGTAAATGCACTGCTGAAGACGTGGAGAGCTTGCTTTCTGTTTTATTCTTGGGCTGGGGAACAAATGTTGCTGAGTTCACTGCCACAGATTCCTGTGTTTCTTCCACGGGGCGGAGACCTTAAA.

[0070] The nucleotide sequence of the SNP containing the G→A mutation site at position 8065911 on chromosome 6 is shown in SEQ ID NO.3 and SEQ ID NO.4.

[0071] SEQ ID NO.3: TTTAGTGGCTGTGGGGCCCTGCTGCCTCCCAGGAGAGGACCAGCCTTCTAACGGAGCTCCTGCATTTTGGAGCTAGACGGTCTCGTGGAGTGACTGTTTGGAGTATTAAATGACTTACTGGATGCAGGGGTCTTTTGACCAAGGGTTCTGGCCCAGAACAAGAGCTAAGGAAGCTGCCGTGGAGAAGAGCTCGTGCTCATG.

[0072] SEQ ID NO.4: TTTAGTGGCTGTGGGGCCCTGCTGCCTCCCAGGAGAGGACCAGCCTTCTAACGGAGCTCCTGCATTTTGGAGCTAGACGGTCTCGTGGAGTGACTGTTTGAAGTATTAAATGACTTACTGGATGCAGGGGTCTTTTGACCAAGGGTTCTGGCCCAGAACAAGAGCTAAGGAAGCTGCCGTGGAGAAGAGCTCGTGCTCATG.

[0073] 2.8 Correlation analysis between SNP sites and feed conversion ratio phenotype.

[0074] The significance of different genotypes and feed conversion ratio traits was tested using R software, and the results were visualized. The results are shown in Table 3. Figure 4 The results showed that the two loci located on chromosome 6, chr6_8048592_C>T and chr6_8065911_G>A, both had a highly significant impact on the feed conversion ratio trait.

[0075] Table 3 Association analysis between different genotypes and phenotypes at two loci From Table 3 and Figure 4 It was found that two SNP loci were significantly associated with feed conversion ratio in Large White pigs, namely: (1) The feed conversion ratio of the CC genotype at the chr6_8048592 (rs1112948356) locus was 2.82±0.31, the feed conversion ratio of the CT genotype was 2.69±0.29, and the feed conversion ratio of the TT genotype was 2.61±0.34. The feed conversion ratio of the TT genotype was significantly lower than that of the CT and CC genotypes, indicating that the TT genotype individuals had the lowest feed conversion ratio and the highest feed utilization efficiency.

[0076] (2) The feed conversion ratio of the GG genotype at the chr6_8065911 locus was 2.82±0.32, the feed conversion ratio of the GA genotype was 2.75±0.29, and the feed conversion ratio of the AA genotype was 2.59±0.33. The feed conversion ratio of the AA genotype was significantly lower than that of the GA and GG genotypes, indicating that the AA genotype individuals had the lowest feed conversion ratio and the highest feed utilization efficiency.

[0077] Furthermore, the SNP loci of this invention were estimated and analyzed using an additive linear model. The model fitting results showed that the phenotypic variance of feed conversion efficiency explained by the rs1112948356 and chr6_8065911 loci was 6.98% and 8.75%, respectively.

[0078] In actual breeding, preserving individuals carrying superior genotypes is beneficial for screening new strains with high feed utilization efficiency (i.e., low feed conversion rate), improving the accuracy of early selection, and has good economic benefits and broad breeding application prospects.

[0079] 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.

[0080] 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 an SNP molecular marker affecting feed conversion ratio in Large White pigs, characterized in that, The SNP molecular marker is at least one of the following ① and ②: ①The nucleotide sequence shown in SEQ ID NO.1 has a C or T nucleotide at position 101 bp; ②The nucleotide sequence shown in SEQ ID NO.3 has a nucleotide at position 101 bp that is either G or A; The application refers to any one of the following (1) and (2): (1) To determine the feed conversion ratio of Large White pigs; (2) Improve the feed utilization rate of offspring of Large White pigs.

2. The application as described in claim 1, characterized in that, The method for determining the feed conversion ratio 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 the Large White pig at 101 bp of SEQ ID NO.1 or SEQ ID NO.3; If the genotype is at least one of A) and B) below, then the Large White pig has a low feed conversion ratio, which means that the feed conversion ratio is not higher than 2.61; A) The genotype at 101bp of SEQ ID NO.1 is TT; B) The genotype at 101bp of SEQ ID NO.3 is AA.

3. The application as described in claim 1, characterized in that, The methods to improve feed utilization in Large White pig offspring are as follows: Genomic DNA was extracted from the Large White pigs to be tested and sequenced. Determine the genotype of the Large White pig at 101 bp of SEQ ID NO.1 or SEQ ID NO.3; By selecting Large White pig individuals carrying at least one of the genotypes shown in a) and c) as parents for breeding, the feed utilization rate of Large White pig offspring can be improved. a) The genotype at 101bp of SEQ ID NO.1 is TT; b) The genotype at 101bp of SEQ ID NO.3 is AA.

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.

5. The application as described in claim 1, characterized in that, The feed conversion rate refers to: The ratio of the total weight of feed consumed by Large White pigs during the fattening period to the total weight gain of the Large White pigs.

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