CN114150068B - SNP (Single nucleotide polymorphism) marker related to pig backfat thickness and application thereof - Google Patents
SNP (Single nucleotide polymorphism) marker related to pig backfat thickness and application thereof Download PDFInfo
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Abstract
The invention discloses a molecular marker related to pig backfat thickness, an obtaining method and application thereof, and a method and a system for predicting pig backfat thickness. The molecular marker is SNP marker, which is located at 161,686,082bp of chromosome 2 of international pig genome 10.2 version reference sequence, and has T/G polymorphism, and the corresponding genotypes are GG genotype, TG genotype and TT genotype; backfat thickness of pigs with genotype TT is significantly lower than those with genotypes TG and GG. The molecular marker related to the backfat thickness of the pig disclosed by the invention can be used for early breeding of the pig, reduces the breeding cost, shortens the breeding period and quickens the genetic progress, and can be directly identified to screen the pig strain with lower backfat thickness, so that the excellent pig variety with low backfat thickness can be accurately and efficiently bred.
Description
Technical Field
The invention belongs to the technical field of molecular biology, and relates to a molecular marker, in particular to an SNP marker related to pig backfat thickness and application thereof.
Background
In the modern pig breeding production process, backfat thickness is an important index for measuring lean meat percentage, health of breeding sow and other characters, so that selecting the breeding pigs meeting production requirements is an important target for pig breeding work. A large number of researches show that the backfat thickness and the lean meat percentage are obviously inversely related, and the thinner the backfat is, the higher the lean meat percentage is, and the thin backfat high lean meat percentage is an important breeding direction in the production process of live pigs. In addition, the pig reproductive performance and the backfat thickness are directly related, and the sow with the backfat thickness of 13.5-18.5mm can be selected to improve the reproductive performance of the sow to a certain extent. The backfat thickness property of the pigs is quantitative property determined by the polygenic loci, and the integral reproductive performance of the pig group can be improved and the requirements of people on meat products and breeding work can be met by identifying and screening loci related to the backfat thickness property of the pigs.
At present, genetic breeding in pig farms mainly adopts phenotype selection, and the phenotype selection has the defects of long breeding period, high false positive rate, easiness in being influenced by feeding environment and the like, and can cause the problems of gene misselection, mispanning and the like.
Therefore, there is a need to discover SNP markers with definite functions and remarkable effects, realize early selection of backfat thickness traits, accelerate genetic progress, and improve backfat thickness traits of pigs.
Disclosure of Invention
In order to overcome the problems, the inventor of the invention has conducted intensive research and provides a molecular marker related to the pig backfat thickness, an obtaining method and application thereof, and a method and system for predicting the pig backfat thickness. The molecular marker can be used for early breeding of pigs, reduces breeding cost, shortens breeding period, accelerates genetic progress, can be used for screening pig strains with lower backfat thickness by directly identifying the marker, and can accurately and efficiently select good pig varieties with low backfat thickness, thereby completing the invention.
In particular, it is an object of the present invention to provide the following aspects:
the invention provides a molecular marker related to pig backfat thickness, wherein the molecular marker is an SNP marker, which is positioned at 161,686,082bp on chromosome 2 of international pig genome 10.2 version reference sequence, and has T/G polymorphism.
Wherein, alleles of SNP markers at 161,686,082bp on chromosome 2 of the 10.2 version reference sequence of the international pig genome are G and T, the corresponding genotypes are three, namely GG genotype, TG genotype and TT genotype,
preferably, the backfat thickness of the swine with genotype TT of SNP markers located at 161,686,082bp on chromosome 2 of version 10.2 reference sequence of the international swine genome is significantly lower than that of swine with genotypes TG and GG.
The invention also provides a method for obtaining the molecular marker, wherein the method comprises the following steps:
step 1, selecting pig groups, and extracting genome DNA;
step 2, determining the phenotype;
step 3, genotyping is carried out;
and 4, carrying out genome-wide association analysis of the phenotypic character.
Wherein in step 1, the pig species in the pig population is selected from one or more of Duroc pigs, long white pigs and large white pigs.
Wherein in step 3, the genotyping is performed by one or more of direct sequencing, restriction fragment length polymorphism polymerase chain reaction, time-of-flight mass spectrometry, and chip technology.
The invention also provides a method for predicting the backfat thickness of the pig, wherein the method comprises the step of predicting the backfat thickness of the pig to be detected by detecting the SNP marker of the pig to be detected;
preferably, the method comprises the steps of:
step I, extracting genome DNA of a pig to be detected;
step II, amplifying the genome DNA to obtain a PCR product;
and III, sequencing the PCR product to determine the backfat thickness of the pig.
The invention also provides a system for predicting pig backfat thickness, wherein the system comprises:
the amplification unit is used for amplifying the genome DNA of the pig to be detected;
a sequencing unit connected to the amplification unit for sequencing the amplified product;
and the prediction unit is connected with the sequencing unit and is used for predicting the pig backfat thickness according to the sequencing result.
The invention also provides application of the molecular marker or the SNP marker obtained by the method or the system for predicting the pig backfat thickness in the aspect of identifying the pig backfat thickness or screening low backfat thickness pig varieties.
The invention also provides application of the molecular marker or the SNP marker obtained by the method or the system for predicting the backfat thickness of the pig in pig breeding.
Wherein the application comprises the steps of:
step i, obtaining genome DNA of pigs;
step ii, detecting the genotype of the SNP marker of the pig at 161,686,082bp on chromosome 2 of the version 10.2 reference sequence of the genome of the international pig;
step iii, selecting low backfat thickness pigs as breeding pigs according to genotypes to carry out breeding.
The invention has the beneficial effects that:
(1) The molecular marker related to the backfat thickness of the pig can be used for early breeding of the pig, so that the breeding cost is reduced, the breeding period is shortened, the genetic progress is accelerated, and SNP markers for auxiliary breeding of the molecular marker are enriched;
(2) The molecular marker related to the pig backfat thickness provided by the invention can be used for screening pig strains with lower backfat thickness by directly identifying the marker, so that the economic benefit and the social value of breeding enterprises and the whole pig breeding industry are improved;
(3) The method for predicting the backfat thickness of the pig provided by the invention is simple to operate, has high prediction accuracy, and can provide scientific basis for molecular marker-assisted selection of the production traits of the pig.
Drawings
FIG. 1 shows a Manhattan diagram of a whole genome correlation analysis in example 1 of the present invention;
FIG. 2 is a box plot showing the gene effect in example 2 of the present invention.
Detailed Description
The invention is further illustrated by the following preferred embodiments and examples. The features and advantages of the present invention will become more apparent from the description.
The word "exemplary" is used herein to mean "serving as an example, embodiment, or illustration. Any embodiment described herein as "exemplary" is not necessarily to be construed as preferred or advantageous over other embodiments.
With the rapid development of molecular biology, the tremendous enrichment of SNP molecular markers and the rapid improvement of computer computing power, the whole genome association analysis technology has become a common means for identifying key genes and loci affecting economic traits. Whole genome association analysis techniques have become a common means of identifying key genes and loci that affect economic traits.
In the invention, the high-density SNP typing chip is preferably adopted to carry out association analysis on tens of thousands of loci and corresponding phenotypes on the pig chromosome, so that SNP loci which are obviously associated with the target traits are found, and the early selection of backfat thickness traits is realized by typing specific loci of the pig group to be detected, so that the feeding cost can be greatly saved, the generation interval can be reduced, and the genetic progress can be accelerated.
In a first aspect of the invention there is provided a molecular marker associated with pig backfat thickness, said molecular marker being a SNP marker located at position 161,686,082bp on chromosome 2 of version 10.2 reference sequence of the international pig genome, in which there is a T/G polymorphism.
According to a preferred embodiment of the present invention, the alleles of SNP markers located at 161,686,082bp on chromosome 2 of version 10.2 reference sequence of the International pig genome are G and T, and the corresponding genotypes are GG genotype, TG genotype and TT genotype respectively,
preferably, the backfat thickness of pigs with SNP locus genotype TT is significantly lower than those with genotypes TG and GG.
Wherein the GG genotype is homozygote with the base G at the site, the TT genotype is homozygote with the base T at the site, and the TG genotype is heterozygote with the bases T and G at the site.
The inventor researches and discovers that the backfat thickness of the TT genotype individuals of the SNP marker of the pig is obviously lower than that of individuals with genotypes TG and GG, so that the meat quality characters of the pig can be genetically evaluated according to the genotype of the SNP locus. It can also be determined that the SNP markers located at 161,686,082bp on chromosome 2 of the international swine genome version 10.2 reference sequence are closely related to the swine backfat thickness property, can be effectively used for molecular marker assisted breeding of swine, and has the advantages of early screening, time saving, low cost and high accuracy.
In order to eliminate the mis-panning and mis-selection of the excellent genes of pigs by the factors of feeding environment, feed, diseases and the like in the phenotype selection, the SNP loci need to be genotyped so as to enhance the accuracy of target selection.
The genotyping method has various methods, such as a direct sequencing method, a restriction fragment length polymorphism polymerase chain reaction, a time-of-flight mass spectrum, a chip technology and the like, and the high-density SNP chip technology is preferably adopted for genotyping, so that a large number of SNPs can be typed in a short time period, the efficiency is high, and the cost is low.
Preferably, SNP 80K chip (Neogen_POPOP80K) from Neuguer is used for genotyping in the present invention.
In a second aspect of the present invention, there is provided a method for obtaining the above SNP marker, comprising the steps of:
step 1, selecting pig groups, and extracting genome DNA.
In the present invention, a pig group composed of Duroc pigs, long white pigs, and big white pigs, for example, a group composed of 1173 pigs is preferably selected, wherein Duroc boars 23, duroc sow 177, long white boar 15, long white sow 363, big white boar 2, and big white sow 593 are selected.
Extracting genome DNA of pig by using the method or kit commonly used in the prior art, preferably collecting pig ear tissue to extract genome DNA, detecting DNA quality by using an ultraviolet spectrophotometer and gel electrophoresis, and storing the detected qualified DNA at-20 ℃ for subsequent typing determination.
And step 2, measuring the phenotype.
In the invention, the phenotype is preferably the live backfat thickness of the pig, and the specific measurement method comprises the following steps:
and when the weight of the pig individual is in the range of 85-105kg, measuring the backfat thickness of the individual, and correcting the phenotype data of the collected data by using a genetic evaluation character measurement procedure of a Hebei province local standard (DB 13/T2065-2014) file "production performance measurement technical procedure in a pig farm".
The backfat thickness in millimeters at the 3-4 intercostal position was measured using a B-mode scan. Finally, the weight of the body weight is converted into a living body backfat thickness reaching 100kg according to the following correction formula (the calculation method is as follows, and the correction coefficient for correcting the backfat thickness is referred to in Table 1):
corrected backfat thickness (mm) =measured backfat thickness (mm) ×cf
Wherein:
cf=a ++a ++ [ B× (actual measurement) body weight (kg) -100) ] }
Table 1, backfat thickness correction table for gilts
Note that: A. b is the backfat thickness correction coefficient of different pig species
Quality control of the measured phenotypic trait data: individuals with a loss of phenotype values were cleared, and individuals with a deviation from the mean value of greater than 3 standard deviations were cleared.
And 3, genotyping.
In the invention, the genotyping method is selected from one or more of a direct sequencing method, a restriction fragment length polymorphism polymerase chain reaction, a time-of-flight mass spectrum and a chip technology, preferably a high-density SNP chip technology is adopted for genotyping, and a large number of SNPs can be typed in a short time period, so that the efficiency is high and the cost is low.
Preferably, the Neogen_POPOP80K chip of Newton's company is used for genotyping and quality control of the genotyping data.
The quality control is as follows: removing SNP loci with genotype detection rate less than 95%; clearing individuals with detection rate less than 95%; less than 1% of individuals with minimal allele frequencies (Minimum Allele Frequency, MAF) are cleared; clearing SNP loci with a Hardy-Wenberg equilibrium (Hardy-Weinberg Equilibrium, HWE) chi-square test P value less than 1.0E-4; the SNP site on the sex chromosome is cleared.
And 4, carrying out genome-wide association analysis of the phenotypic character.
According to a preferred embodiment of the present invention, the statistical analysis model used for the whole gene association analysis is as follows:
y=Xβ+Zμ+e
wherein y is the observed phenotype value; beta is an unknown value containing fixed effects, including genetic markers, population structure (Q matrix) and intercept; μ is the unknown value of the random additive genetic effect from multiple background QTLs of an individual or line; x and Z are known design matrices; e is the residual vector that is not observed.
In the invention, an analysis software package adopted for carrying out the whole-gene association analysis is an R language package GAPIT Version 3, and a statistical model of the software package is a compressed mixed linear model. GAPIT was designed to accurately perform GWAS and genome predictions on large datasets. The hybrid linear model (Mixed Liner Model, MLM) includes fixed and random effects, the model takes population structure as fixed effect, and incorporates individuals into random effect for individual affinity matrix construction.
Based on the mixed linear model, correction backfat thickness correlation analysis is carried out on all typing SNP loci, and SNP loci (G/T; chr2:161,686,082) are obviously related to the backfat thickness characters of pigs.
Further, the genotype data and the phenotype data are subjected to a difference significance test, so that genotype types which are significantly related to low backfat thickness can be obtained.
In a third aspect of the invention, there is provided a method of predicting backfat thickness in pigs, the method comprising: and predicting the backfat thickness of the pig to be tested by detecting the SNP marker in the first aspect.
Preferably, the method comprises the steps of:
step I, extracting genome DNA of a pig to be detected;
step II, amplifying the genome DNA to obtain a PCR product;
and III, sequencing the PCR product to determine the backfat thickness of the pig.
In the step II, the primers for PCR amplification are P1 and P2, and the nucleotide sequences of the primers are respectively shown in SEQ ID NO:1 and SEQ ID NO: 2.
In step III, preferably, the pig backfat thickness with the nucleotide at the SNP marker being the base T is lower than the pig backfat thickness with the nucleotide being the base G.
By adopting the method, the backfat thickness of the pig can be accurately and efficiently predicted.
In a fourth aspect of the invention, there is provided a system for predicting backfat thickness of a pig, the system comprising:
the amplification unit is used for amplifying the genome DNA of the pig to be detected;
a sequencing unit connected to the amplification unit for sequencing the amplified product;
and the prediction unit is connected with the sequencing unit and is used for predicting the pig backfat thickness according to the sequencing result.
In a fifth aspect, the invention provides the use of a SNP marker according to the first aspect or a SNP marker obtained by the method according to the second aspect or a system for predicting pig backfat thickness according to the fourth aspect for identifying pig backfat thickness or for screening low backfat thickness pig breeds.
In a sixth aspect, the invention provides the use of a SNP marker as defined in the first aspect or a SNP marker obtained by a method as defined in the second aspect or a system for predicting pig backfat thickness as defined in the fourth aspect in pig breeding.
Wherein the pig is preferably Duroc pig, changbai pig or Dabai pig.
Preferably, the application comprises the steps of:
step i, obtaining genome DNA of pigs;
step ii, detecting the genotype of the SNP marker of the pig at 161,686,082bp on chromosome 2 of the version 10.2 reference sequence of the genome of the international pig;
step iii, selecting low backfat thickness pigs as breeding pigs according to genotypes to carry out breeding.
Wherein, the individuals with genotype TT of SNP markers at 161,686,082bp on chromosome 2 of the 10.2 version reference sequence of the international pig genome are selected as breeding pigs, and the individuals with genotype TG and GG of the SNP loci are eliminated, so that the frequency of genotype TT of the loci is increased by generations in the process of subculture, thereby reducing backfat thickness.
Examples
The invention is further described below by means of specific examples, which are however only exemplary and do not constitute any limitation on the scope of protection of the invention.
EXAMPLE 1 identification of SNP markers
1. Test population
The experimental pig population used in this example was 1,173 pigs from the Hebei American Shen stock pig farm, wherein, duroc boar was 23, duroc sow was 177, white boar was 15, white sow was 363, white boar was 2, and white sow was 593.
2. Backfat thickness measurement and correction
The live backfat thickness (Backfat Thickness, BFT) is measured when the weight of the individual pigs is in the range of 85-105kg, and the backfat thickness at the 3 rd to 4 th intercostal positions of the individual pigs in the group is measured by adopting B ultrasonic scanning, and the backfat thickness is measured in millimeter units. Then, the collected data is subjected to phenotype data correction by adopting a genetic evaluation character measurement procedure of Hebei province local standard (DB 13/T2065-2014) file "production performance measurement technical procedure in pig farm", and the living backfat thickness of the pig reaching 100kg body weight is calculated according to the following correction formula:
corrected backfat thickness (mm) =measured backfat thickness (mm) ×cf
Wherein: cf=a ++a ++ [ B× (actual measurement) body weight (kg) -100) ];
the correction coefficient (A, B) is shown in the above table 1.
3. DNA extraction and SNP typing
3.1 genomic DNA extraction
In the embodiment, a DP1902 model cell/tissue genome DNA extraction kit of Beijing Baitaike biotechnology Co is adopted to extract DNA from pig ear tissues, an ultraviolet spectrophotometer and gel electrophoresis are used for DNA quality detection, and the DNA which is qualified in detection is stored at the temperature of minus 20 ℃ for subsequent typing determination.
3.2 genotyping
And taking the DNA which is qualified in detection, and carrying out genotyping by utilizing a Neogen_POR80K chip of New York corporation.
4. Quality control of phenotypic and genotypic data
4.1, quality control criteria for phenotypic data:
clearing individuals with a loss of phenotype values; individuals with deviations from the mean that were greater than 3 standard deviations were cleared.
4.2, filtration criteria for SNP chip typing: removing SNP loci with genotype detection rate less than 95%; clearing individuals with detection rate less than 95%; less than 1% of individuals with minimal allele frequencies (Minimum Allele Frequency, MAF) are cleared; clearing SNP loci with a Hardy-Wenberg equilibrium (Hardy-Weinberg Equilibrium, HWE) chi-square test P value less than 1.0E-4; the SNP site on the sex chromosome is cleared.
5. Whole genome correlation analysis of pig backfat thickness
The whole genome association analysis is carried out by adopting an R language package GAPIT Version 3 (developed by Washington university), and the statistical model of the software package is a compressed mixed linear model. The hybrid linear model (Mixed Liner Model, MLM) includes fixed and random effects, the model takes population structure as fixed effect, and incorporates individuals into random effect for individual affinity matrix construction. The statistical analysis model is as follows:
y=Xβ+Zμ+e
wherein y is the observed phenotype value; beta is an unknown value containing fixed effects, including genetic markers, population structure (Q matrix) and intercept; μ is the unknown value of the random additive genetic effect from multiple background QTLs of an individual or line; x and Z are known design matrices; e is the residual vector that is not observed.
Based on the mixed linear model, correction backfat thickness association analysis is carried out on all typing SNP loci by adopting GAPIT statistical analysis software, and the statistical analysis model is the same as the above.
The results are shown in FIG. 1, and as can be seen from FIG. 1: SNP locus 2_161686082 (G/T; chr2:161,686,082) is significantly associated with the pig backfat thickness trait (corrected p-value of 3.14E-03).
Example 2 correlation analysis of SNP locus 2_161686082 (G/T) different genotypes with backfat thickness
1. Test population
The test pig population used in this example was the same as in example 1.
2. Backfat thickness measurement and correction
The backfat thickness measurement and correction method used in this example was the same as in example 1.
3. SNP detection
3.1 genomic DNA extraction
The genomic DNA extraction method used in this example was the same as that used in example 1.
3.2 genotyping
Taking qualified DNA, detecting the genotype of each individual by using a Neogen_POR80K chip of New Youzu corporation, extracting the sequence of a polymorphic site (2_161686082) by R language, and counting the genotype frequency and gene frequency distribution, wherein the result is shown in Table 2:
TABLE 2
As can be seen from Table 2, GG genotype is the dominant genotype of the experimental population and G is the dominant allele.
4. Genotype and backfat thickness correlation analysis
The difference significance test is carried out on the genotype data and the phenotype data by using Rstudio software by using a Kruskal-Wallis method, P-value is less than 0.01, the difference is very significant, and the result is shown in Table 3; and drawing a box line graph by using the ggplot2, ggpubr and maggittr function packages of the R language, wherein the result is shown in fig. 2.
TABLE 3 Table 3
As can be seen from table 3 and fig. 2, there is a significant difference in corrected backfat thickness for pigs of the three genotypes. Backfat thickness of TT-genotype pigs was significantly lower than those of TG and GG genotypes at 100kg body weight. The individual backfat thickness of TT genotype at site 2_161686082 is 2.12mm less than backfat thickness of GG type. The SNP locus can be used as a molecular marker for screening the backfat thickness of pigs and applied to the molecular breeding process of pigs
The invention has been described in detail in connection with the specific embodiments and exemplary examples thereof, but such description is not to be construed as limiting the invention. It will be understood by those skilled in the art that various equivalent substitutions, modifications or improvements may be made to the technical solution of the present invention and its embodiments without departing from the spirit and scope of the present invention, and these fall within the scope of the present invention.
SEQUENCE LISTING
<110> Shenzhen agricultural genome research institute of China academy of agricultural sciences
<120> SNP marker related to pig backfat thickness and application thereof
<130> 2020
<160> 2
<170> PatentIn version 3.5
<210> 1
<211> 21
<212> DNA
<213> amplification primer P1 (Artificial sequence)
<400> 1
ggacggttaa caagatgagg g 21
<210> 2
<211> 22
<212> DNA
<213> amplification primer P2 (Artificial sequence)
<400> 2
accatttcct ttgtagcctg tg 22
Claims (5)
1. The application of a primer for detecting SNP molecular markers in the aspect of identifying pig backfat thickness or screening low backfat thickness pig breeds is characterized in that the SNP molecular markers are positioned at 161686082bp of chromosome 2 of international pig genome 10.2 version reference sequence and have T/G polymorphism;
the backfat thickness of the pig with the genotype of TT of the SNP locus is lower than that of the pig with the genotype of TG or GG;
the pig breeds are white pig, white pig and Duroc pig.
2. The use according to claim 1, wherein the primers are P1 and P2, the nucleotide sequences of which are set forth in SEQ ID NOs: 1 and SEQ ID NO: 2.
3. The application of a primer for detecting SNP molecular markers in pig backfat thickness breeding is characterized in that the SNP molecular markers are positioned at 161686082bp of a 10.2 version reference sequence number 2 chromosome of an international pig genome and have T/G polymorphism;
the backfat thickness of the pig with the genotype of TT of the SNP locus is lower than that of the pig with the genotype of TG or GG;
the pig breeds are white pig, white pig and Duroc pig.
4. The use according to claim 3, wherein the primers are P1 and P2, the nucleotide sequences of which are set forth in SEQ ID NOs: 1 and SEQ ID NO: 2.
5. The use according to claim 3, wherein,
the application comprises the following steps:
step i, obtaining genome DNA of pigs;
step ii, detecting the genotype of the SNP marker of the pig at 161686082bp on the chromosome 2 of the version 10.2 reference sequence of the genome of the pig;
step iii, selecting low backfat thickness pigs as breeding pigs according to genotypes to carry out breeding.
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CN108330197A (en) * | 2018-03-06 | 2018-07-27 | 华南农业大学 | A kind of and relevant SNP marker of Duroc kind fat thickness at back of pig and application thereof |
CN109929935A (en) * | 2017-12-15 | 2019-06-25 | 北京康普森生物技术有限公司 | A kind of method and its application based on rs80995809 Genotyping identification fat thickness at back of pig |
KR102081569B1 (en) * | 2018-12-11 | 2020-02-26 | 대한민국 | SNP marker for predicting backfat thickness of pig |
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CN109929935A (en) * | 2017-12-15 | 2019-06-25 | 北京康普森生物技术有限公司 | A kind of method and its application based on rs80995809 Genotyping identification fat thickness at back of pig |
CN108330197A (en) * | 2018-03-06 | 2018-07-27 | 华南农业大学 | A kind of and relevant SNP marker of Duroc kind fat thickness at back of pig and application thereof |
KR102081569B1 (en) * | 2018-12-11 | 2020-02-26 | 대한민국 | SNP marker for predicting backfat thickness of pig |
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