ArticleTAG. Theoretical and applied genetics. Theoretische und angewandte Genetik2023
Genomic selection strategies for clonally propagated crops.
Article in TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 34 papers.
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Who cites it
34 citing papers in PubMed.
- Balancing gain and diversity: Optimal contribution selection for sustainable genetic improvement in sugarcane.The plant genome · 2026Review
- From family trials to genomic mate allocation: statistical and genomic strategies to accelerate sugarcane genetic improvement.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2026Review
- Scalable medium-density genotyping platforms for cultivar identification, pedigree authentication, marker-assisted and genomic selection, and other applications in strawberry.G3 (Bethesda, Md.) · 2026Article
- Integrating genomic selection into potato breeding: A comparison of genotyping platforms and cross-environmental predictions.The plant genome · 2026Article
- Advancing Wheat Productivity Through Nutrient Interactions, Fertilizer Practices, and Genetic Improvement.Life (Basel, Switzerland) · 2026Review
- Sparse testcrossing for early-stage genomic prediction of general combining ability to increase genetic gain in maize hybrid breeding programs.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2026Article
- Article
- Exploring intra-varietal variation for complex traits in grapevine (Vitis vinifera L.).TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2025Article
- AdaptiveGS: an explainable genomic selection framework based on adaptive stacking ensemble machine learning.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2025Article
- Integrating molecular genetics with plant breeding to deliver impact.Plant physiology · 2025Review
- Exploiting historical agronomic data to develop genomic prediction strategies for early clonal selection in the Louisiana sugarcane variety development program.The plant genome · 2025Article
- SimpleMating: R-package for prediction and optimization of breeding crosses using genomic selection.The plant genome · 2025Article
- Within-family genomic selection in strawberry: Optimization of marker density, trial design, and training set composition.The plant genome · 2025Article
- Optimal implementation of genomic selection in clone breeding programs exemplified in potato: II. Effect of selection strategy and cross-selection method on long-term genetic gain.The plant genome · 2025Article
- Evaluation of crossbreeding strategies for improved adaptation and productivity in African smallholder cattle farms.Genetics, selection, evolution : GSE · 2025Article
- Genomic Predicted cross performance: a tool for optimizing parental combinations in breeding programs.Database : the journal of biological databases and curation · 2025Article
- Genetic architecture and genomic prediction of vase life in carnation.Frontiers in plant science · 2025Article
- Genetic diversity ofFrontiers in plant science · 2025Article
- Integrating multi-layered biological priors to improve genomic prediction accuracy in beef cattle.Biology direct · 2024Article
- Genomic-inferred cross-selection methods for multi-trait improvement in a recurrent selection breeding program.Plant methods · 2024Article
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Authors and funding
6 authors.
Funding
Abstract
key messageFor genomic selection in clonally propagated crops with diploid (-like) meiotic behavior to be effective, crossing parents should be selected based on genomic predicted cross-performance unless dominance is negligible. For genomic selection (GS) in clonal breeding programs to be effective, parents should be selected based on genomic predicted cross-performance unless dominance is negligible. Genomic prediction of cross-performance enables efficient exploitation of the additive and dominance value simultaneously. Here, we compared different GS strategies for clonally propagated crops with diploid (-like) meiotic behavior, using strawberry as an example. We used stochastic simulation to evaluate six combinations of three breeding programs and two parent selection methods. The three breeding programs included (1) a breeding program that introduced GS in the first clonal stage, and (2) two variations of a two-part breeding program with one and three crossing cycles per year, respectively. The two parent selection methods were (1) parent selection based on genomic estimated breeding values (GEBVs) and (2) parent selection based on genomic predicted cross-performance (GPCP). Selection of parents based on GPCP produced faster genetic gain than selection of parents based on GEBVs because it reduced inbreeding when the dominance degree increased. The two-part breeding programs with one and three crossing cycles per year using GPCP always produced the most genetic gain unless dominance was negligible. We conclude that (1) in clonal breeding programs with GS, parents should be selected based on GPCP, and (2) a two-part breeding program with parent selection based on GPCP to rapidly drive population improvement has great potential to improve breeding clonally propagated crops.
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