KR20110139011A - Single nucleotide polymorphism (snp) markers associated with intramuscular fat contents trait in pig and their methods for evaluation - Google Patents

Abstract

PURPOSE: A biomarker for diagnosing the content of pork marbling is provided to determine the content of pork marbling. CONSTITUTION: An SNP biomarker for determining the content of pork marbling contains one among sequences of sequence numbers 1-30. A method for selecting the SNP biomarker comprises: a step of determining SNPs relating to pork marbling content; a step of testing correlation with QTL(quantitative trait loci); and a step of analyzing the characteristic with QTL. A breeding pig is selected using the SNP biomarker. A kit for determining breeding pigs contains the SNP biomarker.

Description

Single nucleotide polymorphism (SNP) markers associated with intramuscular fat contents trait in pig and their methods for evaluation}

The present invention relates to a new biomarker for diagnosing intramuscular fat content of pigs and a method of selecting the same.

Livestock breeding has repeatedly performed a series of processes for selecting high-quality individuals and producing later generations using selected livestocks, and then testing these later generations for high-quality livestock selection. Therefore, in carrying out the related continuous process, various breeding techniques are put in place according to a predetermined strategy (breeding scheme). In the past, statistical methods are used to estimate breeding value based on phenotypic information expressed in the breeding process. The selection has been set as the default. Thus, in order to obtain more useful livestock for people, it is necessary to select good breeding stocks for the production of the next generation of livestock. Animal traits (eg, milk yield, weight, etc.) for improvement through selection are quantitative traits that are mostly affected by a large number of genes. Quantitative traits are generally not only affected by a large number of genes, but also by a number of environmental factors. Therefore, in quantitative traits, it is much more difficult than the qualitative trait to follow up the individual gene action or characteristics that influence it. Therefore, statistical methods are used as a powerful means to study the traits of quantitative traits, and studies have been conducted by various scholars to effectively estimate the genetic factors affecting quantitative traits from various environmental factors. The use of molecular genetic techniques to improve livestock could enable the study of the genetic predisposition of individuals at the DNA level, and the genes involved in the target trait, namely major genes or quantitative trait loci. Direct selection of QTL (Quanttitative Trait Loci) or selection of genetic markers associated with quantitative trait loci (QTL) can provide a tool to realize genetic predisposition. Rather than relying solely on phenotypic information, additional use of molecular genetic information could further accelerate genetic improvement.

Information at the DNA level provides important information not only for producers, but also for breeders, in selecting specific key variants. This DNA information can be used for selection of quantitative traits called marker-assisted selection (MAS). In addition, the molecular markers enhance the selection accuracy of breeders and allow selection of gender-restricted traits, and can be very useful for conductor traits such as meat quality. To date, several genes or markers are actually used in the pig industry.

Genes and Markers Used in the Swine Industry Gene, marker Related traits, fields of use Remarks Paternity - Non-exclusive use HAL Flesh Non-exclusive use ESR, PRLR, RBP4 Mountain embroidery Exclusive Use (PIC) KIT White hair Exclusive Use (PIC) MC1R Red / black hair Exclusive Use (PIC) MC4R Growth, obesity Exclusive Use (PIC) FUT1 Edema ( E. coli F18) Exclusive Use (PIC / ITH Switzerland) RN Flesh Non-exclusive use
(Uppsala, INRA, Kiel) AFABP, HFABP Muscle fat Non Exclusive (IPG) PRKAG3 Flesh Exclusive (PIC) CAST year Exclusive (PIC) IGF2 Conductor composition Exclusive Use (Seghers)

Until now, a selection index based on phenotypic values has been used as a conventional method for selecting longitudinal axes. However, in recent years, marker help selection (MAS) is effectively used not only for traits controlled by single genes but also for traits controlled by quantitative trait loci (QTL). It can be confirmed and reported through simulation. Recently, the genome project has been used to calculate the index including genomic information in the test results when selecting breeders in cattle and chickens. In line with this global trend, from 2009 onwards, when the United States and Canada announce cow breeders, the genome genetic evaluation (GBLUP) is adopted as an official record. have.

Specifically, in 2010, swine genome detoxification was completed and high density genomic information was disclosed. In addition, high-density SNP chips have been produced for major livestock such as cattle and pigs. Indeed, various sow companies have developed single nucleotide polymorphisms (SNPs) of genes such as HAL, ESR, PRLR, KIT, RBP4, MCIR, MC4R, RN, AFABP, HFABP and IGF2. It is used to improve sows.

Accordingly, the present inventors have made efforts to develop a biomarker for diagnosing pig intramuscular fat content that can be used for marker-assisted selection (MAS) when selecting pig breeding pigs. Single base polymorphisms (SNPs) associated with fat content were determined to test their association with quantitative trait loci (QTL), and based on these results, a single quantitative thickness could be determined by analyzing traits of intramuscular fat content in pigs. The present invention has been successfully completed by selecting and providing base polymorphic (SNP) biomarkers.

It is an object of the present invention to provide a biomarker for diagnosing pig intramuscular fat content.

Another object of the present invention is to provide a method for selecting the biomarker.

Still another object of the present invention is to provide a method for selecting sows using the biomarker.

Another object of the present invention is to provide a diagnostic kit for determining the pig muscle fat content comprising the biomarker.

In order to achieve the above object, the present invention provides a monobasic polymorphic biomarker for determining the pig muscle fat content comprising one or more of the nucleotide sequence of SEQ ID NO: 1 to SEQ ID NO: 30.

In addition, the present invention comprises the steps of (1) determining the monobasic polymorphisms (SNPs) associated with the pig muscle fat content; (2) assaying for association with quantitative trait locus (QTL); And (3) analyzing the pig intramuscular fat content trait based on the results.

The present invention also provides a method for selecting sows using the single base polymorphic biomarker.

In another aspect, the present invention provides a diagnostic kit for determining the sows comprising the single base polymorphic biomarker.

In the case of using the monomorphic polymorphic biomarker according to the present invention, it is possible to measure the genetic ability 25 to 35% more accurately than the selection effect by phenotypic evaluation, thereby dramatically increasing the genetic capacity improvement of the sows, and the content of muscle fat in the current meat quality This is one of the important factors in evaluating the quality of livestock, which can greatly contribute to the domestic development of good sows. Thus, according to the global trend in breeder improvement, the monobasic polymorphism genotype associated with intramuscular fat content found in this study will be very effective as a genetic DNA marker for pig selection in the future.

Figure 1 shows a QTL plot (chromosome-wise) for the pig muscle fat content.
Figure 2 shows the location of SNPs associated with intramuscular fat content on porcine chromosomes.

Hereinafter, the present invention will be described in detail.

The present invention provides a biomarker capable of determining the economic trait of a pig using a plurality of single nucleotide polymorphisms (SNPs) corresponding to quantitative trait loci (QTL).

The present invention is to analyze the association with economic traits for a large number of single nucleotide polymorphisms present in the entire genome, in contrast to simply finding single nucleotide polymorphisms in conventional methods and analyzing traits.

Specifically, the present invention is a monobasic polymorphic biomarker ALGA0002965 comprising a nucleotide sequence of SEQ ID NO: 1, a monobasic polymorphic biomarker ASGA0003596 comprising a nucleotide sequence of SEQ ID NO: 2, a monobasic polymorphism comprising a nucleotide sequence of SEQ ID NO: 3 Biomarker MARC0105148, single nucleotide polymorphism biomarker comprising nucleotide sequence of SEQ ID NO: 4 Single nucleotide polymorphic biomarker INRA0003847 comprising nucleotide sequence of SEQ ID NO: 5, single nucleotide polymorphic biomarker comprising nucleotide sequence of SEQ ID NO: 6 MARC0081058, a monobasic polymorphic biomarker ALGA0005765 comprising the nucleotide sequence of SEQ ID NO: 7, a monobasic polymorphic biomarker ALGA0005768 comprising the nucleotide sequence of SEQ ID NO: 8, a monobasic polymorphic biomarker H3GA0003071, comprising the nucleotide sequence of SEQ ID NO: 9, Monobasic polymorphism comprising the nucleotide sequence of SEQ ID NO: 10 Biomarker MARC0013086, monobasic polymorphic biomarker comprising the nucleotide sequence of SEQ ID NO: 11 Monobasic polymorphic biomarker ALGA0035721, comprising the nucleotide sequence of SEQ ID NO: 12 Monobasic polymorphic biomarker comprising the nucleotide sequence of SEQ ID NO: 13 M1GA0017062, monobasic polymorphic biomarker DIAS0000860 comprising the nucleotide sequence of SEQ ID NO: 14, monobasic polymorphic biomarker DIAS0000861 comprising the nucleotide sequence of SEQ ID NO: 15, monobasic polymorphic biomarker ASGA0055250, comprising the nucleotide sequence of SEQ ID NO: 16, Single base polymorphic biomarker ASGA0101283 comprising the nucleotide sequence of SEQ ID NO: 17, Single base polymorphic biomarker H3GA0052996 comprising the nucleotide sequence of SEQ ID NO: 18, single base polymorphic biomarker ASGA0056733, SEQ ID NO: Single salt comprising 20 nucleotide sequences Polymorphic biomarker ASGA0056791, a monobasic polymorphic biomarker comprising the nucleotide sequence of SEQ ID NO: 21 polymorphic biomarker ALGA0069052, a monobasic polymorphic biomarker comprising the nucleotide sequence of SEQ ID NO: 22, H3GA0035918 Single base polymorphic biomarker ALGA0069045 comprising the nucleotide sequence of marker MARC0084121, SEQ ID NO: 24 Single base polymorphic biomarker ALGA0069061 comprising the nucleotide sequence of SEQ ID NO: 25 Single base polymorphic biomarker ALGA0069141 comprising the nucleotide sequence of SEQ ID NO: 26 , Polynucleotide biomarker H3GA0035984 comprising the nucleotide sequence of SEQ ID NO: 27 mononucleotide polymorphic biomarker ISU10000889, comprising the nucleotide sequence of SEQ ID NO: 28, mononucleotide polymorphic biomarker ALGA0069995 or the sequence Contains the nucleotide sequence of number 30 Provides a single nucleotide polymorphism biomarker MARC0029973. The monobasic polymorphic biomarker of the present invention is preferably used in combination comprising one or more of the nucleotide sequences of SEQ ID NO: 1 to SEQ ID NO: 30.

In addition, the present invention comprises the steps of (1) determining the monobasic polymorphisms (SNPs) associated with the pig muscle fat content; (2) assaying for association with quantitative trait locus (QTL); And (3) analyzing the pig intramuscular fat content trait based on the results.

In addition, the present invention provides a method for selecting the sows using at least one monobasic polymorphic biomarker of the base sequence of SEQ ID NO: 1 to SEQ ID NO: 30.

In addition, the present invention provides a diagnostic kit for the determination of sows comprising at least one monobasic polymorphic biomarker of the nucleotide sequence of SEQ ID NO: 1 to SEQ ID NO: 30, characterized in that it is determined by determining the pig muscle fat content It is done.

When using the molecular label according to the present invention, it is possible to measure the genetic ability 25 to 35% more accurate than the selection effect by phenotypic evaluation, which can dramatically increase the genetic capacity improvement of the sows, and the content of muscle fat in the present is to evaluate the meat quality. Since it is one of the important factors, it can greatly contribute to domestic fostering of excellent sows. Thus, according to the global trend in breeder improvement, the monobasic polymorphism genotype associated with intramuscular fat content found in this study will be very effective as a genetic DNA marker for pig selection in the future.

Hereinafter, the present invention will be described in more detail with reference to Examples. However, the following examples are only for illustrating the present invention in more detail, but the scope of the present invention is not limited thereto.

Example : Single Base Polymorphism Analysis

In the present invention, genes that regulate quantitative trait loci (QTL) and their variants were analyzed to select biomarkers associated with pig intramuscular fat content and single nucleotide polymorphisms (SNPs) were investigated as follows.

First, DNA was extracted from the blood of 551 pigs containing pork belly content using Wizard Genomic DNA Purification Kit (Promega, Madison, Wis., USA), and a total of 62,163 SNPs. SNP genotyping was performed using an array chip consisting of information (iSelect Infinium Porcine ArrayChips; Illumina, San Diego, CA, USA).

All SNP data obtained after genotyping were subjected to chi-square test of the R / SNPassoc package for the frequency of Hardy-Weinberg equilibrium (HWE) and minor alleles (MAF). Were excluded (HWE; P <0.05, MAF; <10%). In addition, single marker regression analysis was used to test the association between QTL and SNP, and the additive effect on the markers was evaluated. In addition, the mixed linear LD regression model using the ASReml package was analyzed using the following equation (1).

Equation 1

y = Xb + Za + e

Where y is the phenotype vector for fixed effects with gender and age in the carcase, X is the design matirx, b is the regression vector for the single SNP genotype, and Z is the frequency matrix for the animal effect , And e mean the vector for the residual.

Then, for statistical inference, the false discovery rate (FDR) suggested by Benjamin and Hochberg (1995) for the complex hypothesis test was used in the calculation and all significant values were 5% chromosome. Calculated at the (chromosome-wise) FDR level.

As a result, as shown in FIG. 2, Table 2 and Table 3, SNPs having significant significance in the pig muscle fat content of 62,163 SNPs present in the total porcine genome were 9, A total of 30 samples were identified (2, 7, 12) (chromosome-wise P <0.05). These genotypes can be used to predict the proportion of high and low levels of intramuscular fat. It seems to be effective.

In the embodiment of the present invention, it was confirmed that the selection effect can be enhanced when a diagnostic kit including one or more of the nucleotide sequences of SEQ ID NO: 1 to SEQ ID NO: 30 is used as a single base polymorphic biomarker.

Sequence information for each SNP SNPs order SEQ ID NO: ALGA0002965 CTTTAAAGAGATAAAGTGTATGGTATGTGAATTATAGCTCAATAAAGCCGCCACTAAAAARAAAGGAAGTAAAAGAAGGGAGGAAGGAATAAAACGGAAAAGGAAAAAGGATAAAGAGAAG One ASGA0003596 ACAATGGGAACTTCAAGATGTGAAGCATTATATTGAGGTAAAAGCTTGTCCTAGTGGAAGM] TTTAAAAAAATGTCTAATCACAAAATACTAGGGATGTAGTGTTTCCATTAAGAGAATGGA 2 MARC0105148 TGTGTTCTTCATGTACAGAGCTCACNAAMRTTTCTATAGAAGGCAGAATTTTCAGGATGGRGGGAAAAGAGACTGAGTTCTTACTGACAGGAAGCACCTCAATGATTCAGCTGGAAAGATT 3 MARC0029668 AAGGCAAAAGAAACTTCTGAGAAGAGGGGAGAAAATAATCTTCTCAGGTGAAATAATCCARTTTGTTCCTCTTCAATGCTCACATTCCCAAGGTGGATCATTTGCTAAATCATAAAGGAGG 4 INRA0003847 GATTATTGTGTTCAAGGGATAAAATCAAACTTGACGATTTTAGCAGGGAACTGCAAACTAYAGAAAAGTGACTTAACAGATGTGCCTATGTGTGGAGGGGGAAAAATCCAGAAGTGAAAAT 5 MARC0081058 CCTCACCACCCCCCTGGGTCCYCAGCCACGTGCCCCTCACTCAGGCTCCACCTGGACATCAGTGGAAAAAGCTGGGAACTTT 6 ALGA0005765 CGGGATGACCAAGGAAGGCCTTACTGAGAAGCTGAAAATCAAGGAAGTTAGAAACCACCAYACATTCATATGCAGGAAGGAACATCCAGGAAGATGAGAAAAGGCCCAAAGGCCCAGAGAA 7 ALGA0005768 GTCTCCTAACCTGCCTATAGGGTGCCTCCTCTTTGAGAGCTGTCCAGAGTACAACAGAATYCCGGGCAGTAGATTCTGGCAAAAGCATACCCACCCTGTGGAGAATGCTGTTGGAAGCCAG 8 H3GA0003071 TATGGAAGGATTCGCACTTTTCTCTGCGGGGTGTCAAAGGATATACAGAGATGGGAGGCAMGTAATCTGATGTGTCATTTAAGAGGCCCCTGACAGCTGAAGTATCGACAGTGTGTGGCCG 9 MARC0013086 TGATATATATAATCTCCTTATTCTCTGAGTTTTCTTGCCTTTACTTAGTGACTACGTTGCMGACACTTAGTATACTTCCTCTCTTTTCATTCTCACAACAGTTCAAGWGAAGGGGACTTAT 10 ALGA0035721 TCTCGTACTGACACAACTGGATTTGGGCGGCATAACTGAGTGATAGAAAAGCTGGCTGCKYGACAGTGACAGAGTGACACCGAGAGGTCAGTGGGCCCGCAGATGTGAATTAATTTGTCCC 11 ALGA0066693 CTCTCTGGGACAGTTTCCTCACTGGTAAAGCAGGGGTAGCATTTCCCACCTTGCCTGACARTTGTCACAGGCACCATAGTTAGGGCACCCAGCTTGTACACACTGGGTGCTCCTTTGCTGT 12 M1GA0017062 GGGGTCCCTGGCTCAGCTGGAACACAGGGATATTGACTAGGAAGCCGGTTAACAGGAAACYTGCCACTCCCTGGGAGACGTCAGCCACTTTCCAACCACCTCCCTCCAGCCTTCCCCCTTG 13 DIAS0000860 TTTCTCCTCCAGCTCCTTCCGGCGAGCCTCGGATCTGGCCAGTTCTTCCTTGGTTCTCTCRAAGTCCTCCTTCATGGTGGCCATCTCTTTCTCCGCCTCCGCGCTCTTGAGCAGGGGCTTA 14 DIAS0000861 CAGCAGGTTCCTCCCCAGGAGCCACACCTCCCGCAGCACCACCGCCCCNCACCTGGTGCCRGGGGACCACGTACCCGGCTGGAGGTGAAGTCTCGGGTCTTTGCGCGAAGCTTATTGACCT 15 ASGA0055250 AACGAAGAGGAGGAAGAGCCTCATAGGTGAAGGAAAGAGTCAGTACAGTTTGAGAAGCTCRGGAGGCTGGATGCTGAGGGAAGTGCATATGCTGGGTGTGGAGTGGTGTCCAGGGGCGGAA 16 ASGA0101283 NNNNNNNNNNNNNNNNNNNNNNNNNNNNNCTGGTGGCTCAGAGATTCGCTCTGCAAACACYATCATGAAAGACATCTACGGAATAGAGAGGGTGGCCAGCGCCCAGGCAGTGCCTGGGCAG 17 H3GA0052996 NNNNNNNNNNNNNNNNNNNCTCTCAGACCCGCGTGGCCTCTAGCGCCGAGAGCGCTGGGCKTTCTCAGAGGTGGATGTTAAGTCAGGAAATCAAGGTCTGGTCACGTGGGGGAGGAGCATG 18 ASGA0056733 CCTCTTCATTAACACCTCTCAGTTCAGTTCCATCAGGGCCACTTTCAGTGAAAGGGACCAYAATCAAGACCTTAAAAATGCCCGTCTTTGGAGCTTGGGAAATGTGTTAATGTAATTGCAA 19 ASGA0056791 CAGGGCCCTTTTTTTAAAAATGGTATTAAAAGTTTCAAGATGACAATAGAAGAGCATTGARCCAAGTATAGGGCCCTTCTAACTGCAGAGCTCTATGACCACATGGATTGCATGCCCATAA 20 ALGA0069052 TCACCTTCTGCTGCAAAGGTATATGATGGGAGCTGGACGGCTAAAATCAATCAAAATGGARCCAGGAACTAAACTAAATTCATGCAGTTCATCTCGCAGACAGGGATCATTCAAACCATGG 21 H3GA0035918 GTGGGTCAGCAGTAACAAACCCGACTAATATCCGTGAGAGTGCAGCAGTAACAAACCTCAYATCCCTGGCCTTGCTCAGTGGGTTAAGGATCTGGTGATGCCGAGAGCTATGGTGTAGGTC 22 MARC0084121 CTCCAAACCGAATGCAGTCTCTTGGTCAACGAGTTCAGCAATAGCTATATAAAACAGCTCRGGTTTGGTAACGTTGCACTWGTACGTTGRGCTCTCTGTCCTGATGTTCCAAGCTTTTGAT 23 ALGA0069045 CAGGAAAGGAAGGCTCCAGAATGTCCGCGATGCCCATGGTCAGCTGAGCAAAGATGGGGARCAGGCTGTCGACACCATCAGACCTGAGTTCAGAGTCTTGGGTGCTAAAGGTGCAAACTCA 24 ALGA0069061 GGACCAGTGGGTGACTGATGCATATTTTCTCCTGAATGTTAACCCACCAGCTTGGAGCTGRGTGGTAGGAGAAGGAAAAGGAAGGACTGAAAATCTAGGATGCTGGCCTCGAGACCACCTC 25 ALGA0069141 CGGTGGCTTAAAGAATCCAGTGTTTGCTGCAGCTGCACTGTAGGTTTTGGATCTGATCTCYAGCCCTGATTCCTGGCCTCGGAACTTCATATGCCAGTGGGGCAGCCAAAAAAGAAAAAGA 26 H3GA0035984 ACAGTGCCTGTTTATCACTGAGCTTGGGCCACCCTCCAGGCACTGCATTAAGTACATTACRYGAATGATCTTGCACGCAGAAATTACACAAGGTCAGTGTTCCCCAGAGACAGACCTCAAG 27 ISU10000889 ACGGGATTTTTCTTGGCCTTGGAAATTTCTAGTAATGCCCTGTGCCTCTGTTTCCATCCARTGCTGAGTGTTGTAGGACCAGGGATGGGGTCACTGCTGGGGTTGGGGACATGTGGCAGAG 28 ALGA0069995 TCAGGAATCTTCATCATCAACCTTCTGGTTCCAACCAATCTGAGCTCTATGTGCTGTAATYTGCATGTAGTCACCATCCACCACCTGGGTAGGTGGAGTTCTTAGTTTCTACAGAACAACT 29 MARC0029973 CCTCTATTTTTARCACATTGCCTAAATGAGCCTGTGTAATAGTCCATATCTTTCTTAGGGGACTCCCTGCTCT 30

Information on SNPs Associated with Pig Muscle Fat Content SNPs chromosome location F-value ^{1 )} P-value ^{2 )} Expected value ^{3 )} R2 ^{4 )} ALGA0002965 One 45667782 27.78 1.998E-07 4.835 0.12641 ASGA0003596 One 82326046 24.8 8.692E-07 4.839 0.12278 MARC0105148 One 82368197 24.81 8.644E-07 4.839 0.12278 MARC0029668 One 116271379 14.18 0.0001853 1.26 0.03447 INRA0003847 One 117037484 13.03 0.0003365 1.23 0.03205 MARC0081058 One 118411914 24.76 8.866E-07 4.839 0.12274 ALGA0005765 One 124600282 11.89 0.0006104 -1.182 0.00218 ALGA0005768 One 125041690 12.36 0.0004773 -1.201 0.00201 H3GA0003071 One 163144236 21.37 4.789E-06 -5.427 0.04339 MARC0013086 6 30915907 25.03 7.753E-07 2.129 0.12055 ALGA0035721 6 55436680 15.47 9.535E-05 1.341 0.08711 ALGA0066693 12 43465065 20.86 6.27E-06 4.424 0.13034 M1GA0017062 12 52061341 17.6 3.215E-05 1.033 0.04701 DIAS0000860 12 52147581 18.09 2.507E-05 1.009 0.04893 DIAS0000861 12 52424062 17.34 3.672E-05 0.9367 0.05149 ASGA0055250 12 52530438 25.34 6.68E-07 1.137 0.06439 ASGA0101283 12 54635126 15.38 9.984E-05 -1.272 0.00065 H3GA0052996 12 54641285 14.09 0.0001942 0.779 0.04617 ASGA0056733 13 20044505 13.56 0.0002555 -0.8741 0.00119 ASGA0056791 13 20735999 17.85 2.834E-05 1.011 0.04343 ALGA0069052 13 20962808 18.63 1.905E-05 1.023 0.04465 H3GA0035918 13 20997312 16.1 6.9E-05 0.9577 0.03955 MARC0084121 13 21019224 15.93 7.531E-05 -0.9556 0.0012 ALGA0069045 13 21058687 16.71 5.051E-05 -0.9704 0.00167 ALGA0069061 13 21170070 17.53 3.331E-05 0.9912 0.04266 ALGA0069141 13 22226811 21.66 4.151E-06 1.472 0.04472 H3GA0035984 13 22345579 15.98 7.345E-05 -1.34 0.00053 ISU10000889 13 24782678 13.92 0.0002119 -1.187 0.0004 ALGA0069995 13 39548763 14.22 0.0001816 1.346 0.034 MARC0029973 13 52102943 15.09 0.0001159 1.098 0.0392

1) F-value: F-statistic

2) P-value: Significance value according to F-statistic

3) Estimated value: Estimated value of each SNP for intramuscular fat traits (e.g., ALGA0002965 can expect 4.835% increase in intramuscular fat content)

4) R2: The goodness of fit of the model (e.g., 0.12641 describes about 12% of the phenotype of the intramuscular fat content of the SNP).

In the case of using the monomorphic polymorphic biomarker according to the present invention, it is possible to measure the genetic ability 25 to 35% more accurately than the selection effect by phenotypic evaluation, thereby dramatically increasing the genetic capacity improvement of the sows, and the content of muscle fat in the current meat quality This is one of the important factors in evaluating the quality of livestock, which can greatly contribute to the domestic development of good sows. Therefore, according to the global trend in breeder improvement, the monobasic polymorphism genotype associated with intramuscular fat content found in this study is highly effective as a genetic DNA marker for pig selection in the future.

<110> REPUBLIC OF KOREA (MANAGEMENT: RURAL DEVELOPMENT ADMINISTRATION) <120> Single nucleotide polymorphism (SNP) markers associated with          intramuscular fat contents trait in pig and their methods for          evaluation <130> pa100021 <160> 30 <170> KopatentIn 1.71 <210> 1 <211> 121 <212> DNA <213> Artificial Sequence <220> <223> Artificial <400> 1 ctttaaagag ataaagtgta tggtatgtga attatagctc aataaagccg ccactaaaaa 60 raaaggaagt aaaagaaggg aggaaggaat aaaacggaaa aggaaaaagg ataaagagaa 120 g 121 <210> 2 <211> 121 <212> DNA <213> Artificial Sequence <220> <223> Artificial <400> 2 acaatgggaa cttcaagatg tgaagcatta tattgaggta aaagcttgtc ctagtggaag 60 mtttaaaaaa atgtctaatc acaaaatact agggatgtag tgtttccatt aagagaatgg 120 a 121 <210> 3 <211> 121 <212> DNA <213> Artificial Sequence <220> <223> Artificial <400> 3 tgtgttcttc atgtacagag ctcacnaamr tttctataga aggcagaatt ttcaggatgg 60 rgggaaaaga gactgagttc ttactgacag gaagcacctc aatgattcag ctggaaagat 120 t 121 <210> 4 <211> 121 <212> DNA <213> Artificial Sequence <220> <223> Artificial <400> 4 aaggcaaaag aaacttctga gaagagggga gaaaataatc ttctcaggtg aaataatcca 60 rtttgttcct cttcaatgct cacattccca aggtggatca tttgctaaat cataaaggag 120 g 121 <210> 5 <211> 121 <212> DNA <213> Artificial Sequence <220> <223> Artificial <400> 5 gattattgtg ttcaagggat aaaatcaaac ttgacgattt tagcagggaa ctgcaaacta 60 yagaaaagtg acttaacaga tgtgcctatg tgtggagggg gaaaaatcca gaagtgaaaa 120 t 121 <210> 6 <211> 82 <212> DNA <213> Artificial Sequence <220> <223> Artificial <400> 6 cctcaccacc cccctgggtc cycagccacg tgcccctcac tcaggctcca cctggacatc 60 agtggaaaaa gctgggaact tt 82 <210> 7 <211> 121 <212> DNA <213> Artificial Sequence <220> <223> Artificial <400> 7 cgggatgacc aaggaaggcc ttactgagaa gctgaaaatc aaggaagtta gaaaccacca 60 yacattcata tgcaggaagg aacatccagg aagatgagaa aaggcccaaa ggcccagaga 120 a 121 <210> 8 <211> 121 <212> DNA <213> Artificial Sequence <220> <223> Artificial <400> 8 gtctcctaac ctgcctatag ggtgcctcct ctttgagagc tgtccagagt acaacagaat 60 yccgggcagt agattctggc aaaagcatac ccaccctgtg gagaatgctg ttggaagcca 120 g 121 <210> 9 <211> 121 <212> DNA <213> Artificial Sequence <220> <223> Artificial <400> 9 tatggaagga ttcgcacttt tctctgcggg gtgtcaaagg atatacagag atgggaggca 60 mgtaatctga tgtgtcattt aagaggcccc tgacagctga agtatcgaca gtgtgtggcc 120 g 121 <210> 10 <211> 121 <212> DNA <213> Artificial Sequence <220> <223> Artificial <400> 10 tgatatatat aatctcctta ttctctgagt tttcttgcct ttacttagtg actacgttgc 60 mgacacttag tatacttcct ctcttttcat tctcacaaca gttcaagwga aggggactta 120 t 121 <210> 11 <211> 121 <212> DNA <213> Artificial Sequence <220> <223> Artificial <400> 11 tctcgtactg acacaactgg atttgggcgg cataactgag tgatagaaaa gctggctgck 60 ygacagtgac agagtgacac cgagaggtca gtgggcccgc agatgtgaat taatttgtcc 120 c 121 <210> 12 <211> 121 <212> DNA <213> Artificial Sequence <220> <223> Artificial <400> 12 ctctctggga cagtttcctc actggtaaag caggggtagc atttcccacc ttgcctgaca 60 rttgtcacag gcaccatagt tagggcaccc agcttgtaca cactgggtgc tcctttgctg 120 t 121 <210> 13 <211> 121 <212> DNA <213> Artificial Sequence <220> <223> Artificial <400> 13 ggggtccctg gctcagctgg aacacaggga tattgactag gaagccggtt aacaggaaac 60 ytgccactcc ctgggagacg tcagccactt tccaaccacc tccctccagc cttccccctt 120 g 121 <210> 14 <211> 121 <212> DNA <213> Artificial Sequence <220> <223> Artificial <400> 14 tttctcctcc agctccttcc ggcgagcctc ggatctggcc agttcttcct tggttctctc 60 raagtcctcc ttcatggtgg ccatctcttt ctccgcctcc gcgctcttga gcaggggctt 120 a 121 <210> 15 <211> 121 <212> DNA <213> Artificial Sequence <220> <223> Artificial <400> 15 cagcaggttc ctccccagga gccacacctc ccgcagcacc accgccccnc acctggtgcc 60 rggggaccac gtacccggct ggaggtgaag tctcgggtct ttgcgcgaag cttattgacc 120 t 121 <210> 16 <211> 121 <212> DNA <213> Artificial Sequence <220> <223> Artificial <400> 16 aacgaagagg aggaagagcc tcataggtga aggaaagagt cagtacagtt tgagaagctc 60 rggaggctgg atgctgaggg aagtgcatat gctgggtgtg gagtggtgtc caggggcgga 120 a 121 <210> 17 <211> 121 <212> DNA <213> Artificial Sequence <220> <223> Artificial <400> 17 nnnnnnnnnn nnnnnnnnnn nnnnnnnnnc tggtggctca gagattcgct ctgcaaacac 60 yatcatgaaa gacatctacg gaatagagag ggtggccagc gcccaggcag tgcctgggca 120 g 121 <210> 18 <211> 121 <212> DNA <213> Artificial Sequence <220> <223> Artificial <400> 18 nnnnnnnnnn nnnnnnnnnc tctcagaccc gcgtggcctc tagcgccgag agcgctgggc 60 kttctcagag gtggatgtta agtcaggaaa tcaaggtctg gtcacgtggg ggaggagcat 120 g 121 <210> 19 <211> 121 <212> DNA <213> Artificial Sequence <220> <223> Artificial <400> 19 cctcttcatt aacacctctc agttcagttc catcagggcc actttcagtg aaagggacca 60 yaatcaagac cttaaaaatg cccgtctttg gagcttggga aatgtgttaa tgtaattgca 120 a 121 <210> 20 <211> 121 <212> DNA <213> Artificial Sequence <220> <223> Artificial <400> 20 cagggccctt tttttaaaaa tggtattaaa agtttcaaga tgacaataga agagcattga 60 rccaagtata gggcccttct aactgcagag ctctatgacc acatggattg catgcccata 120 a 121 <210> 21 <211> 121 <212> DNA <213> Artificial Sequence <220> <223> Artificial <400> 21 tcaccttctg ctgcaaaggt atatgatggg agctggacgg ctaaaatcaa tcaaaatgga 60 rccaggaact aaactaaatt catgcagttc atctcgcaga cagggatcat tcaaaccatg 120 g 121 <210> 22 <211> 121 <212> DNA <213> Artificial Sequence <220> <223> Artificial <400> 22 gtgggtcagc agtaacaaac ccgactaata tccgtgagag tgcagcagta acaaacctca 60 yatccctggc cttgctcagt gggttaagga tctggtgatg ccgagagcta tggtgtaggt 120 c 121 <210> 23 <211> 121 <212> DNA <213> Artificial Sequence <220> <223> Artificial <400> 23 ctccaaaccg aatgcagtct cttggtcaac gagttcagca atagctatat aaaacagctc 60 rggtttggta acgttgcact wgtacgttgr gctctctgtc ctgatgttcc aagcttttga 120 t 121 <210> 24 <211> 121 <212> DNA <213> Artificial Sequence <220> <223> Artificial <400> 24 caggaaagga aggctccaga atgtccgcga tgcccatggt cagctgagca aagatgggga 60 rcaggctgtc gacaccatca gacctgagtt cagagtcttg ggtgctaaag gtgcaaactc 120 a 121 <210> 25 <211> 121 <212> DNA <213> Artificial Sequence <220> <223> Artificial <400> 25 ggaccagtgg gtgactgatg catattttct cctgaatgtt aacccaccag cttggagctg 60 rgtggtagga gaaggaaaag gaaggactga aaatctagga tgctggcctc gagaccacct 120 c 121 <210> 26 <211> 121 <212> DNA <213> Artificial Sequence <220> <223> Artificial <400> 26 cggtggctta aagaatccag tgtttgctgc agctgcactg taggttttgg atctgatctc 60 yagccctgat tcctggcctc ggaacttcat atgccagtgg ggcagccaaa aaagaaaaag 120 a 121 <210> 27 <211> 121 <212> DNA <213> Artificial Sequence <220> <223> Artificial <400> 27 acagtgcctg tttatcactg agcttgggcc accctccagg cactgcatta agtacattac 60 rygaatgatc ttgcacgcag aaattacaca aggtcagtgt tccccagaga cagacctcaa 120 g 121 <210> 28 <211> 121 <212> DNA <213> Artificial Sequence <220> <223> Artificial <400> 28 acgggatttt tcttggcctt ggaaatttct agtaatgccc tgtgcctctg tttccatcca 60 rtgctgagtg ttgtaggacc agggatgggg tcactgctgg ggttggggac atgtggcaga 120 g 121 <210> 29 <211> 121 <212> DNA <213> Artificial Sequence <220> <223> Artificial <400> 29 tcaggaatct tcatcatcaa ccttctggtt ccaaccaatc tgagctctat gtgctgtaat 60 ytgcatgtag tcaccatcca ccacctgggt aggtggagtt cttagtttct acagaacaac 120 t 121 <210> 30 <211> 73 <212> DNA <213> Artificial Sequence <220> <223> Artificial <400> 30 cctctatttt tarcacattg cctaaatgag cctgtgtaat agtccatatc tttcttaggg 60 gactccctgc tct 73

Claims (5)

A monobasic polymorphic biomarker for determining pig intramuscular fat content comprising at least one of the nucleotide sequences of SEQ ID NO: 1 to SEQ ID NO: 30.
(1) determining monobasic polymorphisms (SNPs) associated with pig intramuscular fat content; (2) assaying for association with quantitative trait locus (QTL); And (3) analyzing the pig intramuscular fat content trait based on these results.
A method of selecting sows using the monobasic polymorphic biomarker of claim 1.
A diagnostic kit for determining a sow comprising the monobasic polymorphic biomarker of claim 1.
The method of claim 4, wherein
A diagnostic kit, characterized in that it is determined by determining the pig muscle fat content.

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