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A genomic selection method for genetic improvement of complex traits

A technology for genome selection and genetic improvement, applied in the field of genome selection for genetic improvement of complex traits, can solve the problem of lack of distinction and integration of major genes and minor genes for complex traits, neglect of major genes and minor genes, selection methods and efficiency Differences and other issues, to achieve the effects of easy model expansion, high predictive power, and high genome selection accuracy

Active Publication Date: 2022-05-27
ZHEJIANG UNIV
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Problems solved by technology

[0004] However, the existing prediction models and strategies based on genomic selection lack the distinction and integration of major and minor genes for complex traits. It means that the main effect gene effect and the minor effect gene effect are not included in the calculation of breeding value

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  • A genomic selection method for genetic improvement of complex traits
  • A genomic selection method for genetic improvement of complex traits
  • A genomic selection method for genetic improvement of complex traits

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Embodiment Construction

[0060] Under the mixed linear model framework, we believe that major-effect genes in complex traits are often the genes involved in the most core link of trait occurrence, with larger gene effects, which are more in line with the assumption of fixed effects; correspondingly, minor-effect genes are often involved in the occurrence of traits. In the modification link, the gene effect is smaller, which is more in line with the assumption of random effect. However, both major and minor genes have more or less influence on the phenotypic value, so it is necessary to jointly incorporate the estimation of the breeding value of the full model to improve the precision of genome selection.

[0061] Therefore, we propose a new strategy for genome selection to analyze the genetic structure of complex traits, that is, for the genetic characteristics of complex traits, the whole genome selection model includes both the main genes identified by GWAS as fixed effects and the overall GBLUP. Th...

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Abstract

The invention discloses a genome selection method for genetic improvement of complex traits, comprising the following steps: (1) establishment of a statistical genetic model; (2) main effect gene positioning; (3) genetic parameter estimation; (4) individual-based Genome-wide selection of breeding values. Compared with the prior art, the beneficial effects of the present invention are: a) Compared with the model hypothesis of GBLUP, the model hypothesis proposed by the application is more in line with the law of biological inheritance and has higher predictive power, that is, has a higher genome Selection accuracy; b) The present invention is based on a mixed linear model, which has great flexibility and facilitates model expansion.

Description

technical field [0001] The invention relates to the technical field of computational biology, in particular to a genome selection method for genetic improvement of complex traits. Background technique [0002] Most human diseases and agronomic traits are complex traits affected by polygenic and non-genetic factors. The accurate analysis and prediction of these complex traits is of great significance to improve disease diagnosis rate and crop quality. For more accurate prediction of complex traits, Meuwissen et al. (Meuwissen THE, Hayes BJ, and Goddard ME. Prediction of total genetic value using genome-wide densemarker maps. Genetics, 157(4):1819-1829. (2001) ) first proposed Genomic Selection (GS), a statistical method for predicting phenotypic values ​​of traits based on genome-wide information. Unlike molecular marker-assisted selection (MAS), the ultimate goal of genomic selection is not just to find a certain or part of the key genes (or major genes) associated with tra...

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G16B5/00G16B20/00
CPCG16B5/00G16B20/00
Inventor 徐海明张齐心刘臣涛朱天能
Owner ZHEJIANG UNIV
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