CN114521533B - Black pig core group re-selection breeding method - Google Patents
Black pig core group re-selection breeding method Download PDFInfo
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- CN114521533B CN114521533B CN202210169410.3A CN202210169410A CN114521533B CN 114521533 B CN114521533 B CN 114521533B CN 202210169410 A CN202210169410 A CN 202210169410A CN 114521533 B CN114521533 B CN 114521533B
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- A—HUMAN NECESSITIES
- A01—AGRICULTURE; FORESTRY; ANIMAL HUSBANDRY; HUNTING; TRAPPING; FISHING
- A01K—ANIMAL HUSBANDRY; CARE OF BIRDS, FISHES, INSECTS; FISHING; REARING OR BREEDING ANIMALS, NOT OTHERWISE PROVIDED FOR; NEW BREEDS OF ANIMALS
- A01K67/00—Rearing or breeding animals, not otherwise provided for; New breeds of animals
- A01K67/02—Breeding vertebrates
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02P—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
- Y02P60/00—Technologies relating to agriculture, livestock or agroalimentary industries
- Y02P60/80—Food processing, e.g. use of renewable energies or variable speed drives in handling, conveying or stacking
- Y02P60/87—Re-use of by-products of food processing for fodder production
Abstract
The invention discloses a re-breeding method for a core group of black-capped pigs. Determining the genetic relationship among individuals in the black-cap pig group by using SNP chip data, extracting the genome DNA of all the pigs, and obtaining 65000 SNPs locus information of the black-cap pigs in the group; analyzing the meat quality related genes and molecular marker genotypes of the black-cap pig population; determining an MBLUP breeding value estimation model by utilizing SNP chip data and molecular markers; determining a comprehensive selection index method of black-cap pigs and selecting core group individuals; the invention adopts a new scientific technology, utilizes SNP chip data to determine the genetic relationship among individuals in the black-capped pig group, extracts the genome DNA of all the breeding pigs, and utilizes PLINK software to carry out quality control on the result data through data modeling, thereby greatly improving the breeding accuracy and greatly improving the breeding quality of the black-capped pigs regardless of the number or the meat quality.
Description
Technical Field
The invention relates to the technical field of livestock breeding, in particular to a re-breeding method for a core group of black-capped pigs.
Background
The Zaozhuang area concentrates the feeding of black-cover pigs, and belongs to local high-quality breeds. The shoal black-cover pig feed has compact body type, coarse feed resistance, fresh and tender meat quality and unique taste, along with the increasing improvement of the living standard of people, the requirements of people on the meat quality are higher and higher, the pursuit on the meat nutrition and the taste is more prominent, and the breeding growth speed and the lean meat yield of the shoal black-cover pig are obviously lagged behind the development of the times. At present, a more traditional breeding mode is adopted, for example, a method commonly used in the pig breeding practice in China at present is a closed group subculture breeding method, the principle is that a plurality of basic groups of ancestry are firstly selected and collected, then the livestock group is closed, and the breeding selection is carried out in the closed group according to the production performance, the physical appearance and the ancestry source. Compared with more scientific chip data collection and gene analysis breeding, the method is obviously lagged behind, and the success probability and quality of breeding can not meet the requirements.
Disclosure of Invention
The invention aims to provide a re-breeding method for a core group of black-cap pigs, which adopts a new scientific technology to breed so as to solve the technical problems.
In order to achieve the purpose, the invention adopts the following technical scheme:
a re-selection and breeding method for a core group of black cap pigs comprises the following steps:
step 1, determining the genetic relationship among individuals in a black-cap pig group by using SNP chip data, extracting the genome DNA of all pigs, and obtaining 65000 SNPs locus information of the black-cap pigs in the group;
step 2, analyzing meat quality related genes and molecular marker genotypes of the black-cover pig groups;
selecting all candidate genes and molecular markers thereof related to the meat quality traits and the growth traits, and performing correlation analysis on the candidate genes and the molecular markers by combining the existing growth speed, feed conversion rate phenotype data and meat shape phenotype data which is conjectured by using backfat thickness and eye muscle area in an auxiliary way, thereby determining the molecular markers and the dominant genotypes thereof which can be used for selecting black-cap pigs, and making a specialized chip which can be used for identifying the excellent growth traits and the meat quality shapes of the black-cap pigs for subsequent molecular breeding;
step 3, determining SNP chip data and an MBLUP breeding value estimation model of the molecular marker;
according to the group genetic relationship estimated by the chip data, a genetic relationship matrix is constructed, the molecular markers and the typing results thereof are combined, and the MBLUP technology is adopted to estimate the individual breeding value, wherein the model is as follows:
wherein y is a phenotype measurement vector; u is a random vector of a breeding value, the mean value of the random vector is 0, the variance covariance matrix is A sigma u2, and A is a genetic relationship matrix; v is a fixed molecular marker effect vector, the genotype is known, e is an error vector, the mean value is 0, and the variance covariance matrix is I sigma e2; z and Q are corresponding incidence matrixes;
step 4, determining the black-capped pigs by using a comprehensive selection index method and selecting core group individuals;
selecting 50-th-rank boars and 300 sows to form a 0-generation breeding core group according to the individual numerical value, carrying out locked breeding after the core group is formed, introducing no external blood in the midway, and making offspring records; in order to shorten the generation interval and accelerate the genetic progress, a basic frame of first-birth seed reservation for one generation of a year is implemented, the hybridization is completed in 30 days, the performance of a new generation of the breeding is measured under the same period and the same conditions, individuals with genetic defects, body types and obvious growth and development defects are eliminated, the seeds are selected and reserved preferentially, the seed reservation rate is determined according to the group scale and the updating rate, the male swine is compatible with the ancestry, the male swine of each family is selected in principle, but the same amount of the seeds of each family is reserved, the number of the male sows of each generation is basically the same as the basic group scale, the half and whole sibling mating is limited, and the replacement swine needs to be put into use after the seed performance is strictly measured.
Preferably, before the analysis in the step 1, quality control is carried out on the result data by utilizing PLINK software, the detection rate of removing SNP is less than 95 percent, the frequency of the minimum allele is less than 1 percent, and the extreme mismatching with the Hardy-Weinberg equilibrium testP<10 -6 And SNP sites and individual detection rates without chromosomal position information<90% of individuals.
The invention has the beneficial effects that: the invention adopts a new scientific technology, utilizes SNP chip data to determine the genetic relationship among individuals in the black-capped pig group, extracts the genome DNA of all the breeding pigs, and utilizes PLINK software to carry out quality control on the result data through data modeling, thereby greatly improving the breeding accuracy and greatly improving the breeding quality of the black-capped pigs regardless of the number or the meat quality.
Detailed Description
The technical solutions in the embodiments of the present invention are clearly and completely described below, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
The genetic relationship among individuals in the Zaozhuang black-cap pig group is determined by using 60K SNP chip data, the experimental group of the research is from 660 black-cap pig breeding pigs of Shandong Futeng food Co., ltd, the genome DNA of all the breeding pigs is extracted, and 65000 SNPs site information of the black-cap pigs in the group is obtained by using Illumina Porcine 60K SNP chip. Before analysis, quality control is carried out on the result data by utilizing PLINK software, and the detection rate of removing SNP is less than95%, minimum allele frequency less than 1%, extreme non-compliance with the Hardy-Weinberg equilibrium testP<10 -6 And SNP sites and individual detection rates without chromosomal position information<90% of individuals.
Analyzing the meat quality related genes and molecular marker genotypes of the Zaozhuang black-cover pig group;
the method comprises the steps of selecting all candidate genes and molecular markers thereof related to meat quality traits and growth traits through documents and databases, carrying out correlation analysis on the candidate genes and the molecular markers by combining phenotype data such as existing growth speed, feed conversion rate and the like and meat shape phenotype data which is obtained by utilizing backfat thickness and eye muscle area to assist in conjecture, determining the molecular markers and the dominant genotypes thereof which can be used for black-cover pig group selection, and making a specialized chip which can be used for identifying excellent growth traits and meat shape of black-cover pigs for subsequent molecular breeding.
Determining SNP chip data and an MBLUP breeding value estimation model of a molecular marker;
according to the group genetic relationship estimated by the chip data, a genetic relationship matrix is constructed, the molecular markers and the typing results thereof are combined, and the MBLUP technology is adopted to estimate the individual breeding value, wherein the model is as follows: wherein y is a phenotype measurement vector; u is a random vector of breeding values, the mean value is 0, and the variance covariance matrix is A sigma u2 (A is a genetic relationship matrix); v is the fixed molecular marker effect vector (genotype known), e is the error vector with mean 0 and covariance matrix I σ e2, and Z, Q are the corresponding correlation matrices.
Determining and selecting individual of core group by using black pig comprehensive selection index method;
according to the individual numerical value, selecting 50-th-rank boars and 300 sows to form a 0-generation breeding core group, carrying out locked breeding after the core group is formed, introducing no external blood in the midway, and making offspring records. In order to shorten the generation interval and accelerate the genetic progress, a basic framework of first generation and first fetus seed reservation is implemented. The mating is completed in 30 days, and the performance of the new generation is measured under the same period and approximately the same conditions. Eliminating individuals with genetic defect, body type and obvious growth and development defect, and selecting and reserving seeds preferentially, wherein the seed reserving rate is determined according to the population scale and the updating rate. The boars should be of bloody origin, and in principle, boars of each family are selected (but not the same amount of breed of each family). The number of the sows in each generation is basically the same as the scale of the basic group, and half-and-full-sibling mating is limited. The replacement pig needs to be put into use after strictly measuring the breeding performance.
Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that changes, modifications, substitutions and alterations can be made in these embodiments without departing from the principles and spirit of the invention, the scope of which is defined in the appended claims and their equivalents.
Claims (2)
1. The re-selection and breeding method of the black-cap pig core group is characterized by comprising the following steps:
step 1, determining the genetic relationship among individuals in a black-cap pig group by using SNP chip data, extracting the genomic DNA of all pigs, and obtaining 65000 SNPs site information of the black-cap pigs in the group;
step 2, analyzing meat quality related genes and molecular marker genotypes of black-capped pig groups;
selecting all candidate genes and molecular markers thereof related to meat quality traits and growth traits, performing correlation analysis on the candidate genes and the molecular markers by combining the existing growth speed, feed conversion rate phenotype data and meat quality trait phenotype data which is conjectured by the aid of backfat thickness and eye muscle area, determining the molecular markers and the dominant genotypes thereof which can be used for black-capped pig group selection, and making a specialized chip which can be used for identifying the excellent growth traits and the meat quality traits of the black-capped pigs for subsequent molecular breeding;
step 3, determining an MBLUP breeding value estimation model by utilizing SNP chip data and molecular markers; according to the group genetic relationship estimated by the chip data, a genetic relationship matrix is constructed, the molecular markers and the typing results thereof are combined, and the MBLUP technology is adopted to estimate the individual breeding value, wherein the model is as follows:
wherein y is a phenotype measurement vector; u is a random vector of breeding values, the mean value of the random vector is 0, the variance covariance matrix is A sigma u2, and A is a genetic relationship matrix; v is a fixed molecular marker effect vector, the genotype is known, e is an error vector, the mean value is 0, and the variance covariance matrix is I sigma e2;
step 4, determining the black-cover pigs by using a comprehensive selection index method and selecting core group individuals;
selecting 50-th-rank boars and 300 sows to form a 0-generation breeding core group according to the individual numerical value, carrying out locked breeding after the core group is formed, introducing no external blood in the midway, and making offspring records; in order to shorten the generation interval and accelerate the genetic progress, a basic frame of first-birth seed reservation for one generation of a year is implemented, the hybridization is completed in 30 days, the performance of a new generation of the breeding is measured under the same period and the same conditions, individuals with genetic defects, body types and obvious growth and development defects are eliminated, the seeds are selected and reserved preferentially, the seed reservation rate is determined according to the group scale and the updating rate, the male swine is compatible with the ancestry, the male swine of each family is selected in principle, but the same amount of the seeds of each family is reserved, the number of the male sows of each generation is basically the same as the basic group scale, the half and whole sibling mating is limited, and the replacement swine needs to be put into use after the seed performance is strictly measured.
2. The method of claim 1, wherein before analysis in step 1, quality control is performed on the result data by using PLINK software, the detection rate of removed SNPs is less than 95%, the minimum allele frequency is less than 1%, and the extreme mismatching hardship-weinberg balance test is performedP<10 -6 And SNP sites and individual detection rates without chromosomal position information<90% of individuals.
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Patent Citations (9)
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| WO2005015989A1 (en) * | 2003-08-04 | 2005-02-24 | Monsanto Technology Llc | Method for genetic improvement of terminal boars |
| WO2008025093A1 (en) * | 2006-09-01 | 2008-03-06 | Innovative Dairy Products Pty Ltd | Whole genome based genetic evaluation and selection process |
| WO2015092151A1 (en) * | 2013-12-19 | 2015-06-25 | Genoscoper Oy | Method and arrangement for matching mammals by comparing genotypes |
| CN105010233A (en) * | 2015-08-11 | 2015-11-04 | 吉林康大食品有限公司 | Method for breeding high-reproductive-performance breeding rabbits through SNP assistant selection breeding technology |
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