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Method for determining optimal SNP quantity as well as performing genome selective breeding on production performance of large yellow croakers through selection markers

A technology for genome selection and production performance, applied in the fields of genomics, biochemical equipment and methods, biological systems, etc., can solve the problem of inaccurate estimates of breeding values, and achieve the effect of saving breeding costs and reducing costs.

Active Publication Date: 2017-11-10
JIMEI UNIV
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  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

Although the BLUP method has achieved great success in animal breeding, the method still has its limitations, because the traditional method can only treat the genome information as a "black box", and the transmission information of alleles can only be determined by inference. Impossible to make direct observations, which may lead to inaccurate estimates of breeding values
However, there is no report on genomic selective breeding for meat quality traits of large yellow croaker

Method used

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  • Method for determining optimal SNP quantity as well as performing genome selective breeding on production performance of large yellow croakers through selection markers
  • Method for determining optimal SNP quantity as well as performing genome selective breeding on production performance of large yellow croakers through selection markers
  • Method for determining optimal SNP quantity as well as performing genome selective breeding on production performance of large yellow croakers through selection markers

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Experimental program
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Effect test

Embodiment 1

[0042] Example 1 Determination of SNP Screening Quantity

[0043] Experimental material: The experimental data is large yellow croaker, which was bred in Jinling Aquatic Technology Co., Ltd., Ningde City, Fujian Province. 30 male fishes and 30 female fishes were mixed in a tank. By injecting luteinizing hormone-releasing hormone A3 (LRH-A3), all parent fishes released sperm or eggs at almost the same time, so all offspring had the same age. When the offspring reached the age of 2, 176 individuals (including 61 males and 115 females) were randomly selected as the test material of this study, that is, the reference group, and the research trait was n-3 high unsaturated fatty acid content (n3-HUFA) .

[0044] Phenotype (n-3 high unsaturated fatty acid content) determination method: "The extraction of total lipids adopts the Folch method, and after total lipids are extracted, 50% KOH and ethanol are used for saponification and then heated with 7% BF3 and methanol (methanol) The ...

Embodiment 2

[0074] Embodiment 2: The meat quality character screening experiment of 197 fish

[0075] Experimental material: The experimental data is large yellow croaker, which was bred in Jinling Aquatic Technology Co., Ltd., Ningde City, Fujian Province. 30 male fishes and 30 female fishes were mixed in a tank. By injecting luteinizing hormone-releasing hormone A3 (LRH-A3), all parent fishes released sperm or eggs at almost the same time, so all offspring had the same age. When the offspring reached the age of 2, 197 individuals (including 89 males and 108 females) were randomly selected.

[0076] The 12 SNP sites of these 197 fish were determined, and the genome breeding value GEBV was calculated by the GBLUP method (the solution equation set is shown in the R language package "EMMREML", version 3.1.). The 4 males and 5 females with the highest genome breeding value GEBV were selected as the breeding group, and 181 individuals (84 males and 97 females) were randomly selected from the...

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Abstract

The invention discloses a method for determining optimal SNP quantity as well as performing genome selective breeding on production performance of large yellow croakers through selection markers. The method comprises the following steps: performing phenotype determination and genomic sequencing on the production performance of individuals of a reference group to obtain SNP locus; screening out the qualified SNP locus and supplementing the deleted genotype; dividing the reference group into a training set and a validation set to perform hybridization validation; screening the SNP locus most remarkably associated with the character through single marker analysis, and then calculating GEBV of individuals of the validation set only by using the locus and through a GBLUP method; further obtaining breeding value estimation accuracy under each screening SNP quantity; finally determining the optimal quantity of SNP screening; and according to the optimal quantity, calculating the GEBV by the GBLUP method, further obtaining the breeding value estimation accuracy and performing genome selective breeding according to the value size. By the method, the genomic selection cost on the production performance of the large yellow croakers can be reduced remarkably.

Description

technical field [0001] The invention relates to the field of genome selection breeding, in particular to a method for determining the optimal SNP quantity and performing genome selection breeding on the production performance of large yellow croaker through screening markers. Background technique [0002] The traditional breeding value estimation method is mainly carried out through phenotype and pedigree records, and this method is called Best Linear Unbiased Prediction (BLUP). Although the BLUP method has achieved great success in animal breeding, the method still has its limitations, because the traditional method can only treat the genome information as a "black box", and the transmission information of alleles can only be determined by inference. Direct observations cannot be made, which may lead to inaccurate estimates of breeding values. With the development of high-throughput sequencing technology, it is entirely possible to obtain high-density SNP markers in animal...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): C12Q1/68G06F19/12G06F19/18G06F19/22
CPCC12Q1/6888C12Q2600/124C12Q2600/156G16B5/00G16B20/00G16B30/00
Inventor 王志勇董林松肖世俊
Owner JIMEI UNIV
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