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Genomic prediction in pigs using data from a commercial crossbred population: insights from the Duroc x (Landrace x Yorkshire) three-way crossbreeding system

Genetics selection evolution (Paris), 2023-03, Vol.55 (1), p.21-21, Article 21 [Peer Reviewed Journal]

2023. The Author(s). ;COPYRIGHT 2023 BioMed Central Ltd. ;The Author(s) 2023. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;2023. This work is licensed under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. ;Distributed under a Creative Commons Attribution 4.0 International License ;The Author(s) 2023 ;ISSN: 1297-9686 ;ISSN: 0999-193X ;EISSN: 1297-9686 ;DOI: 10.1186/s12711-023-00794-2 ;PMID: 36977978

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  • Title:
    Genomic prediction in pigs using data from a commercial crossbred population: insights from the Duroc x (Landrace x Yorkshire) three-way crossbreeding system
  • Author: Liu, Siyi ; Yao, Tianxiong ; Chen, Dong ; Xiao, Shijun ; Chen, Liqing ; Zhang, Zhiyan
  • Subjects: Accuracy ; Animal breeding ; Animals ; Bayes Theorem ; Bayesian analysis ; Breeding of animals ; Cross-breeding ; Dam engineering ; Females ; Genetic aspects ; Genome ; Genomes ; Genomics ; Genotype ; Genotype & phenotype ; Genotypes ; Genotyping ; Heritability ; Hogs ; Hybridization, Genetic ; Life Sciences ; Livestock ; Males ; Mathematical models ; Models, Genetic ; Optimization ; Performance enhancement ; Performance prediction ; Phenotype ; Phenotypes ; Prediction models ; Swine
  • Is Part Of: Genetics selection evolution (Paris), 2023-03, Vol.55 (1), p.21-21, Article 21
  • Description: Genomic selection is widely applied for genetic improvement in livestock crossbreeding systems to select excellent nucleus purebred (PB) animals and to improve the performance of commercial crossbred (CB) animals. Most current predictions are based solely on PB performance. Our objective was to explore the potential application of genomic selection of PB animals using genotypes of CB animals with extreme phenotypes in a three-way crossbreeding system as the reference population. Using real genotyped PB as ancestors, we simulated the production of 100,000 pigs for a Duroc x (Landrace x Yorkshire) DLY crossbreeding system. The predictive performance of breeding values of PB animals for CB performance using genotypes and phenotypes of (1) PB animals, (2) DLY animals with extreme phenotypes, and (3) random DLY animals for traits of different heritabilities ([Formula: see text] = 0.1, 0.3, and 0.5) was compared across different reference population sizes (500 to 6500) and prediction models (genomic best linear unbiased prediction (GBLUP) and Bayesian sparse linear mixed model (BSLMM)). Using a reference population consisting of CB animals with extreme phenotypes showed a definite predictive advantage for medium- and low-heritability traits and, in combination with the BSLMM model, significantly improved selection response for CB performance. For high-heritability traits, the predictive performance of a reference population of extreme CB phenotypes was comparable to that of PB phenotypes when the effect of the genetic correlation between PB and CB performance ([Formula: see text]) on the accuracy obtained with a PB reference population was considered, and the former could exceed the latter if the reference size was large enough. For the selection of the first and terminal sires in a three-way crossbreeding system, prediction using extreme CB phenotypes outperformed the use of PB phenotypes, while the optimal design of the reference group for the first dam depended on the percentage of individuals from the corresponding breed that the PB reference data comprised and on the heritability of the target trait. A commercial crossbred population is promising for the design of the reference population for genomic prediction, and selective genotyping of CB animals with extreme phenotypes has the potential for maximizing genetic improvement for CB performance in the pig industry.
  • Publisher: France: BioMed Central Ltd
  • Language: English;German
  • Identifier: ISSN: 1297-9686
    ISSN: 0999-193X
    EISSN: 1297-9686
    DOI: 10.1186/s12711-023-00794-2
    PMID: 36977978
  • Source: Hyper Article en Ligne (HAL) (Open Access)
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    Alma/SFX Local Collection
    Springer Nature OA/Free Journals
    ProQuest Central
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