基于元共祖的基因组联合育种模拟研究

doi:10.11843/j.issn.0366-6964.2022.07.014

Abstract

Abstract: This study aimed to apply the single-step genomic best linear unbiased prediction with metafounders (MF-SSGBLUP) to joint genomic breeding and compare it with other classical genomic selection methods. QMSim software was used to simulate 3 dairy cattle populations with independent pedigrees; The generalized least squares (GLS) and naïve (NAI) methods were used to estimate the ancestral relationship matrix Γ between different populations. MF-SSGBLUP, SSGBLUP and BLUP were used respectively to joint breeding for the simulated populations, and the performance of each method in estimating genetic parameters and breeding values was evaluated. For different heritabilities, the Γ matrix obtained by GLS was slightly lower than that obtained by NAI method in diagonal elements, but there was no significant difference in non-diagonal elements. The correlation coefficient in diagonal elements between the genomic and genetic relationship matrices based on metafounders (0.750-0.775) was higher than that between genomic and traditional relationship matrices (0.508-0.572). The deviations of heritability estimates by MF-SSGBLUP (0.138, 0.140, 0.297 and 0.298) from the current population heritability (0.107 and 0.296) were smaller than those of the other two methods (0.145, 0.173, 0.273 and 0.340). Correspondingly, the accuracies of estimated breeding values by MF-SSGBLUP (0.888-0.908) were higher than that by SSGBLUP (0.863-0.876) and BLUP (0.854-0.871). The results showed that MF-SSGBLUP had less biased estimates of genetic parameters and breeding values with higher accuracies. Based on the simulation results, the MF-SSGBLUP performed better than other classical genomic selection methods in joint breeding.

Key words: genomic selection, metafounder, joint genomic breeding, SSGBLUP, simulation research

CLC Number:

S823.91

PANG Zhixu, ZHANG Hongzhi, QIAO Liying, WANG Wannian, PAN Yangyang, LIU Wenzhong. Simulation Study on Joint Genomic Breeding Using Metafounders[J]. Acta Veterinaria et Zootechnica Sinica, 2022, 53(7): 2172-2181.

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Simulation Study on Joint Genomic Breeding Using Metafounders

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