ArticleGenetics, selection, evolution : GSE2020
Optimizing genomic reference populations to improve crossbred performance.
Article in Genetics, selection, evolution : GSE, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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13 citing papers in PubMed, 34 citations in OpenAlex.
- Methods to detect selection history in a population under ongoing directional selection.Genetics · 2026Article
- Restructuring breeding programs 2: Assortative mating for improved commercial genetic gain when using optimum contribution selection and diversity introduction.Genetics, selection, evolution : GSE · 2026Article
- Genetic Evaluation of Beef Sires Using a Beef-on-Dairy Crossbred Reference Population.Journal of animal breeding and genetics = Zeitschrift fur Tierzuchtung und Zuchtungsbiologie · 2026Article
- Genomic selection for growth and wood properties in multi-generation hybrid populations ofHorticulture research · 2025Article
- Practical Considerations When Using Mendelian Sampling Variances for Selection Decisions in Genomic Selection Programs.Journal of animal breeding and genetics = Zeitschrift fur Tierzuchtung und Zuchtungsbiologie · 2025Article
- Improved genomic prediction accuracy by genetic relatedness using a crossbred pig population.Translational animal science · 2025Article
- Optimizing purebred selection to improve crossbred performance.Frontiers in genetics · 2024Article
- 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 : GSE · 2023Article
- Challenges and Opportunities for Developing More Generalizable Polygenic Risk Scores.Annual review of biomedical data science · 2022Review
- Genotyping and phenotyping strategies for genetic improvement of meat quality and carcass composition in swine.Genetics, selection, evolution : GSE · 2022Article
- Building a Calibration Set for Genomic Prediction, Characteristics to Be Considered, and Optimization Approaches.Methods in molecular biology (Clifton, N.J.) · 2022Article
- Purebred-crossbred genetic parameters for reproductive traits in swine.Journal of animal science · 2021Article
- Review: optimizing genomic selection for crossbred performance by model improvement and data collection.Journal of animal science · 2021Review
Corrections and comments
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Authors and funding
3 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundIn pig and poultry breeding, the objective is to improve the performance of crossbred production animals, while selection takes place in the purebred parent lines. One way to achieve this is to use genomic prediction with a crossbred reference population. A crossbred reference population benefits from expressing the breeding goal trait but suffers from a lower genetic relatedness with the purebred selection candidates than a purebred reference population. Our aim was to investigate the benefit of using a crossbred reference population for genomic prediction of crossbred performance for: (1) different levels of relatedness between the crossbred reference population and purebred selection candidates, (2) different levels of the purebred-crossbred correlation, and (3) different reference population sizes. We simulated a crossbred breeding program with 0, 1 or 2 multiplication steps to generate the crossbreds, and compared the accuracy of genomic prediction of crossbred performance in one generation using either a purebred or a crossbred reference population. For each scenario, we investigated the empirical accuracy based on simulation and the predicted accuracy based on the estimated effective number of independent chromosome segments between the reference animals and selection candidates.
resultsWhen the purebred-crossbred correlation was 0.75, the accuracy was highest for a two-way crossbred reference population but similar for purebred and four-way crossbred reference populations, for all reference population sizes. When the purebred-crossbred correlation was 0.5, a purebred reference population always resulted in the lowest accuracy. Among the different crossbred reference populations, the accuracy was slightly lower when more multiplication steps were used to create the crossbreds. In general, the benefit of crossbred reference populations increased when the size of the reference population increased. All predicted accuracies overestimated their corresponding empirical accuracies, but the different scenarios were ranked accurately when the reference population was large.
conclusionsThe benefit of a crossbred reference population becomes larger when the crossbred population is more related to the purebred selection candidates, when the purebred-crossbred correlation is lower, and when the reference population is larger. The purebred-crossbred correlation and reference population size interact with each other with respect to their impact on the accuracy of genomic estimated breeding values.
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