ArticleGenetics, selection, evolution : GSE2019
Validation of genomic predictions for body weight in broilers using crossbred information and considering breed-of-origin of alleles.
Article in Genetics, selection, evolution : GSE, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 18 papers.
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Who cites it
18 citing papers in PubMed.
- Balancing gain and diversity: Optimal contribution selection for sustainable genetic improvement in sugarcane.The plant genome · 2026Review
- Leveraging data from commercial cattle for genetic improvement- an international perspective.Journal of animal science · 2025Review
- Confidence intervals for validation statistics with data truncation in genomic prediction.Genetics, selection, evolution : GSE · 2024Article
- Concurrently mapping quantitative trait loci associations from multiple subspecies within hybrid populations.Heredity · 2023Article
- Multi-breed genomic evaluation for tropical beef cattle when no pedigree information is available.Genetics, selection, evolution : GSE · 2023Article
- Segregation between breeds and local breed proportions in genetic and genomic models for crossbreds.Genetics, selection, evolution : GSE · 2023Article
- Validation with single-step SNPBLUP shows that evaluations can continue using a single mean of genotyped individuals, even with multiple breeds.Genetics, selection, evolution : GSE · 2023Article
- Realized genomic selection across generations in a reciprocal recurrent selection breeding program ofFrontiers in plant science · 2023Article
- Impact of genomic preselection on subsequent genetic evaluations with ssGBLUP using real data from pigs.Genetics, selection, evolution : GSE · 2022Article
- Genotyping and phenotyping strategies for genetic improvement of meat quality and carcass composition in swine.Genetics, selection, evolution : GSE · 2022Article
- Improving the Accuracy of Multi-Breed Prediction in Admixed Populations by Accounting for the Breed Origin of Haplotype Segments.Frontiers in genetics · 2022Article
- Review: optimizing genomic selection for crossbred performance by model improvement and data collection.Journal of animal science · 2021Review
- Selective genotyping and phenotypic data inclusion strategies of crossbred progeny for combined crossbred and purebred selection in swine breeding.Journal of animal science · 2021Article
- The Genetic Basis of Tomato Aroma.Genes · 2021Review
- Impact of inclusion rates of crossbred phenotypes and genotypes in nucleus selection programs.Journal of animal science · 2020Article
- Optimizing genomic reference populations to improve crossbred performance.Genetics, selection, evolution : GSE · 2020Article
- Assessment of sire contribution and breed-of-origin of alleles in a three-way crossbred broiler dataset.Poultry science · 2019Article
- Correction to: Validation of genomic predictions for body weight in broilers using crossbred information and considering breed-of-origin of alleles.Genetics, selection, evolution : GSE · 2019Article
Corrections and comments
- Erratum issued
Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundPig and poultry breeding programs aim at improving crossbred (CB) performance. Selection response may be suboptimal if only purebred (PB) performance is used to compute genomic estimated breeding values (GEBV) because the genetic correlation between PB and CB performance ([Formula: see text]) is often lower than 1. Thus, it may be beneficial to use information on both PB and CB performance. In addition, the accuracy of GEBV of PB animals for CB performance may improve when the breed-of-origin of alleles (BOA) is considered in the genomic relationship matrix (GRM). Thus, our aim was to compare scenarios where GEBV are computed and validated by using (1) either CB offspring averages or individual CB records for validation, (2) either a PB or CB reference population, and (3) a GRM that either accounts for or ignores BOA in the CB individuals. For this purpose, we used data on body weight measured at around 7 (BW7) or 35 (BW35) days in PB and CB broiler chickens and evaluated the accuracy of GEBV based on the correlation GEBV with phenotypes in the validation population (validation correlation).
resultsWith validation on CB offspring averages, the validation correlation of GEBV of PB animals for CB performance was lower with a CB reference population than with a PB reference population for BW35 ([Formula: see text] = 0.96), and about equal for BW7 ([Formula: see text] = 0.80) when BOA was ignored. However, with validation on individual CB records, the validation correlation was higher with a CB reference population for both traits. The use of a GRM that took BOA into account increased the validation correlation for BW7 but reduced it for BW35.
conclusionsWe argue that the benefit of using a CB reference population for genomic prediction of PB animals for CB performance should be assessed either by validation on CB offspring averages, or by validation on individual CB records while using a GRM that accounts for BOA in the CB individuals. With this recommendation in mind, our results show that the accuracy of GEBV of PB animals for CB performance was equal to or higher with a CB reference population than with a PB reference population for a trait with an [Formula: see text] of 0.8, but lower for a trait with an [Formula: see text] of 0.96. In addition, taking BOA into account was beneficial for a trait with an [Formula: see text] of 0.8 but not for a trait with an [Formula: see text] of 0.96.
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