ArticleGenetics, selection, evolution : GSE2013
Efficiency of genomic selection in an established commercial layer breeding program.
Article in Genetics, selection, evolution : GSE, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.
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17 citing papers in PubMed.
- Stochastic simulations to optimize genomic selection for laying hens: Impact of generation interval and genotyping in the context of extended laying period.Poultry science · 2026Article
- Application of optimal contribution selection, trait distribution management, and group selection in layer chickens.Genetics, selection, evolution : GSE · 2026Article
- Analysis of different genotyping and selection strategies in laying hen breeding programs.Genetics, selection, evolution : GSE · 2025Article
- GOplan: an R package for animal breeding program design via integrating Gene Flow and Bayesian optimization methods.G3 (Bethesda, Md.) · 2025Article
- Sustainable high-yield farming is essential for bending the curve of biodiversity loss.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2025Review
- Whole-genome sequencing identifies potential candidate genes for egg production traits in laying ducks (Anas platyrhynchos).Scientific reports · 2023Article
- Assessment of long-term trends in genetic mean and variance after the introduction of genomic selection in layers: a simulation study.Frontiers in genetics · 2023Article
- Applications of Omics Technology for Livestock Selection and Improvement.Frontiers in genetics · 2022Review
- The role of BAMBI in regulating adipogenesis and myogenesis and the association between its polymorphisms and growth traits in cattle.Molecular biology reports · 2020Article
- High-Throughput Sequencing With the Preselection of Markers Is a Good Alternative to SNP Chips for Genomic Prediction in Broilers.Frontiers in genetics · 2020Article
- A survey of functional genomic variation in domesticated chickens.Genetics, selection, evolution : GSE · 2018Article
- Revolutionize livestock breeding in the future: an animal embryo-stem cell breeding system in a dish.Journal of animal science and biotechnology · 2018Review
- Genomic prediction of survival time in a population of brown laying hens showing cannibalistic behavior.Genetics, selection, evolution : GSE · 2016Article
- Accuracy of imputation using the most common sires as reference population in layer chickens.BMC genetics · 2015Article
- Response and inbreeding from a genomic selection experiment in layer chickens.Genetics, selection, evolution : GSE · 2015Article
- Upweighting rare favourable alleles increases long-term genetic gain in genomic selection programs.Genetics, selection, evolution : GSE · 2015Article
- Genomic selection needs to be carefully assessed to meet specific requirements in livestock breeding programs.Frontiers in genetics · 2015Article
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7 authors.
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No grant is acknowledged in the PubMed record.
Abstract
backgroundIn breeding programs for layers, selection of hens and cocks is based on recording phenotypic data from hens in different housing systems. Genomic information can provide additional information for selection and/or allow for a strong reduction in the generation interval. In this study, a typical conventional layer breeding program using a four-line cross was modeled and the expected genetic progress was derived deterministically with the software ZPLAN+. This non-genomic reference scenario was compared to two genomic breeding programs to determine the best strategy for implementing genomic information in layer breeding programs.
resultsIn scenario I, genomic information was used in addition to all other information available in the conventional breeding program, so the generation interval was the same as in the reference scenario, i.e. 14.5 months. Here, we assumed that either only young cocks or young cocks and hens were genotyped as selection candidates. In scenario II, we assumed that breeders of both sexes were used at the biologically earliest possible age, so that at the time of selection only performance data of the parent generation and genomic information of the selection candidates were available. In this case, the generation interval was reduced to eight months. In both scenarios, the number of genotyped male selection candidates was varied between 800 and 4800 males and two sizes of the calibration set (500 or 2000 animals) were considered. All genomic scenarios increased the expected genetic gain and the economic profit of the breeding program. In scenario II, the increase was much more pronounced and even in the most conservative implementation led to a 60% improvement in genetic gain and economic profit. This increase was in all cases associated with higher breeding costs.
conclusionsWhile genomic selection is shown to have the potential to improve genetic gain in layer breeding programs, its implementation remains a business decision of the breeding company; the possible extra profit for the breeding company depends on whether the customers of breeding stock are willing to pay more for improved genetic quality.
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