Multi-omics genome combined genetic evaluation method and device

By integrating multi-omics data using the FSBLUP method and optimizing omics weights and grid search-cross-validation using adaptive binary search, the problem of insufficient prediction accuracy of multi-omics data in breeding was solved, achieving efficient and accurate evaluation of breeding values, especially showing excellent performance in low heritability traits.

CN121506245APending Publication Date: 2026-02-10CHINA AGRI UNIV
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Patent Information

Application Number
CN202511433956.5
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2025-10-09
Publication Date
2026-02-10

AI Technical Summary

Technical Problem

Existing technologies struggle to effectively integrate multi-omics data, resulting in insufficient prediction accuracy in livestock and poultry breeding, particularly for traits with low heritability and those requiring slaughter for measurement. Furthermore, existing models do not assume independence from biological hierarchical regulatory mechanisms, and their classification standards lack universality.

Method used

We employ the optimal linear unbiased prediction method based on fusion similarity matrix (FSBLUP), dynamically optimize omics weights through an adaptive binary search algorithm, and construct a multi-omics fusion similarity matrix by combining a grid search-cross-validation system. This enables the analysis of the genetic contribution of information at various levels and integrates data from the genome, transcriptome, proteome, metabolome, and microbiome.

Benefits of technology

It significantly improves the accuracy of breeding value estimation, especially in low heritability traits. The prediction accuracy of piglet number, age per 100 kg and backfat thickness in pig breeding farms is improved by more than 25%. The computational efficiency is more than 10 times higher than that of Bayesian models, providing a precise breeding scheme for complex traits.

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Abstract

The invention relates to the technical field of biological information, and particularly discloses a multi-omics genome combined genetic assessment method and device. According to the method, multi-source data such as a genome, a transcriptome, a proteome, a metabolome, a microbiome and a high-throughput phenotype are integrated by constructing a multi-omics fusion similar matrix, an adaptive dichotomy is adopted to optimize omics weights, a grid search and cross validation system is introduced, and global optimal estimation of parameters is achieved. Verification of the method on livestock and poultry breeding and plant breeding data shows that the prediction accuracy of complex characters can be remarkably improved, and particularly, the prediction precision in low heritability characters is remarkably improved. The invention further provides a corresponding device which comprises a data acquisition module, a matrix construction module, a parameter optimization module and a breeding value calculation module, comprehensive utilization of multi-omics information can be efficiently achieved, and the accuracy and calculation efficiency of breeding value estimation are improved.
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