ArticleEvolutionary applications2021
How to achieve a higher selection plateau in forest tree breeding? Fostering heterozygote × homozygote relationships in optimal contribution selection in the case study of
Article in Evolutionary applications, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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5 citing papers in PubMed.
- Balancing gain and diversity: Optimal contribution selection for sustainable genetic improvement in sugarcane.The plant genome · 2026Review
- Evolutionary computing to assemble standing genetic diversity and achieve long-term genetic gain.The plant genome · 2024Article
- Mate selection: A useful approach to maximize genetic gain and control inbreeding in genomic and conventional oil palm (Elaeis guineensis Jacq.) hybrid breeding.PLoS computational biology · 2023Article
- Genome-wide genotyping data renew knowledge on genetic diversity of a worldwide alfalfa collection and give insights on genetic control of phenology traits.Frontiers in plant science · 2023Article
- How to achieve a higher selection plateau in forest tree breeding? Fostering heterozygote × homozygote relationships in optimal contribution selection in the case study ofEvolutionary applications · 2021Article
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3 authors.
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Abstract
In breeding, optimal contribution selection (OCS) is one of the most effective strategies to balance short- and long-term genetic responses, by maximizing genetic gain and minimizing global coancestry. Considering genetic diversity in the selection dynamic-through coancestry-is undoubtedly the reason for the success of OCS, as it avoids preliminary loss of favorable alleles. Originally formulated with the pedigree relationship matrix, global coancestry can nowadays be assessed with one of the possible formulations of the realized genomic relationship matrix. Most formulations were optimized for genomic evaluation, but few for the management of coancestry. We introduce here an alternative formulation specifically developed for genomic OCS (GOCS), intended to better control heterozygous loci, and thus better account for Mendelian sampling. We simulated a multigeneration breeding program with mate allocation and under GOCS for twenty generations, solved with quadratic programming. With the case study of
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