Method for rapidly evaluating genome breeding value and application

A genome and breeding value technology, applied in the field of bioinformatics, can solve problems such as exponential increase of calculation time, affecting the efficiency of genome breeding value evaluation, implementation difficulties, etc., and achieve the effect of speeding up calculation

Inactive Publication Date: 2014-07-09
CHINA AGRI UNIV
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Problems solved by technology

[0004] At present, there are still difficulties in the implementation of the method of estimating the genome breeding value based on the combination of genome information and pedigree information, mainly reflected in (1) how to select individuals without SNP genotypes to join the reference population. Inappropriate addition of pedigree information will not only fail to improve the genome breeding value The accuracy of the estimation, and the exponential increase of the calculation time, cannot meet the needs of actual breed

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  • Method for rapidly evaluating genome breeding value and application
  • Method for rapidly evaluating genome breeding value and application
  • Method for rapidly evaluating genome breeding value and application

Examples

Experimental program
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Effect test

Embodiment 1

[0029] see figure 1 , this embodiment provides a method for quickly estimating the genome breeding value, comprising the following steps,

[0030] 1) Obtaining data, the data comes from 5974 Chinese Holstein cows, born between 2004 and 2012, all cows were tested for Illunima50K SNP chip genotype, and the milk yield and milk protein amount of 5 milk production traits , milk protein rate, milk fat amount, and milk fat rate were estimated by traditional breeding values. And edit the SNP chip data, a total of 47,160 SNPs were used for analysis; according to the pedigree information of 5,974 cows with SNP genotypes, the data of 10 generations were traced upwards, including 130,852 individuals, which were used for the construction of the kinship matrix A array; the reliability of traditional breeding values ​​was selected The breeding values ​​of 5 milk production traits of individuals higher than 0.45 were used as phenotypes to generate the final phenotype data files.

[0031] 2)...

Embodiment 2

[0056] 7) Repeat step 6) to estimate the genomic breeding values ​​of other 4 milk production traits such as milk protein amount. Embodiment 2 uses real data to evaluate the calculation speed and accuracy of this method

[0057] Using the data in Example 1, use the present invention to calculate and construct the H matrix and the inversion method, and compare the calculation time with the traditional symmetric matrix inversion and the R language ginv function. At the same time, compared with the traditional GBLUP method that only uses genome information, the accuracy of predicting genome breeding value is compared. In Example 1, 541 cows born after 2008 and 2008 with 5974 SNP genotypes were selected, and their traditional breeding value was correlated with the genome breeding value as a standard to measure the accuracy of genome breeding value prediction. The higher the correlation, the higher the explanation The more accurate the genome breeding value is estimated, the bette...

Embodiment 3

[0067] Embodiment 3 simulation data

[0068] The simulation data is an outbred population simulated by QTL-MAS Workshop using LDSO software in 2011. It is constructed by simulating 1000 generations of historical groups with 1000 individuals per generation, and 30 generations of contemporary groups with 150 individuals per generation. The data used in the analysis is the last generation data, a total of 20 male animal lines, each male animal mated with 100 female animals, and each female animal produced 15 offspring. 9990 SNP markers are evenly distributed on 5 chromosomes, each chromosome is 1 Morgen in length, and 1998 SNP markers are evenly distributed.

[0069] The specific data information provided by the simulation data are: pedigree files, SNP marker files, and phenotype files, where the phenotype files are the phenotype values ​​of 10 individuals in each 15 full-sibling offspring, and the other 5 individuals to verify the individual. Also provides the true breeding va...

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Abstract

The invention belongs to the field of bioinformatics and provides a method for rapidly evaluating a genome breeding value. The method includes single nucleotide polymorphism (SNP) chip data edition; arrangement of genealogy files; construction of a matrix A by genealogy information, selection of individuals with SNP genotypes from the matrix A, and construction of a submatrix A22 according to matrix A elements among the individuals; construction of a matrix G by using high-density SNP chip information, and rapid construction of the matrix G by using a DGEMM process in a public open-source LAPACK math library; construction of a matrix H, calling of DGETRF and DGETRI matrixes in the public open-source LAPACK math library to obtain an inverse subprogram, rapid obtaining of inverse matrixes of the matrix A, the matrix A22 and the matrix G, and further solving of an inverse matrix G according to the partitioning inverse matrixes; solving of the genome breeding value of the individuals through a mixed model equation set. According to the method, calculation speeds for evaluating the genome breeding value by means of the comprehensive genealogy information and genome information can be accelerated, and applications of the genome selection to the field of animal breeding can be boosted.

Description

technical field [0001] The invention belongs to the technical field of bioinformatics, and in particular relates to a method and application for quickly estimating genome breeding values ​​by using pedigree information and genome information. Background technique [0002] In the field of livestock and poultry breeding, artificial selection plays a pivotal role in breed breeding and trait improvement. Since 2007, with the advent of genome-wide high-density SNP chips of various livestock and poultry, genome selection has been widely used in the field of livestock and poultry breeding, especially dairy cattle breeding. [0003] The widespread application of genomic selection is inseparable from the development of corresponding computational methods. Based on the variance of SNP effects, genomic selection calculation methods are mainly divided into two categories: BLUP-type methods and BAYES-type methods. Whether it is the BAYES method or the BLUP method, it is based on the SN...

Claims

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Application Information

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IPC IPC(8): G06F19/24
Inventor 丁向东李秀金张勤王胜
Owner CHINA AGRI UNIV
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