ArticleTAG. Theoretical and applied genetics. Theoretische und angewandte Genetik2016
Model training across multiple breeding cycles significantly improves genomic prediction accuracy in rye (Secale cereale L.).
Article in TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 46 papers.
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Who cites it
46 citing papers in PubMed.
- Review
- Rapid cycling genomic selection in maize landraces: a step toward closing the yield gap.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2025Article
- Genomic selection: Essence, applications, and prospects.The plant genome · 2025Review
- Diversity of cereal rye (Secale cereale) germplasm in the Southeast United States.The plant genome · 2025Article
- Portability of genomic predictions trained on sparse factorial designs across two maize silage breeding cycles.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2024Article
- Accelerating genetic gains for quantitative resistance to verticillium wilt through predictive breeding in strawberry.The plant genome · 2024Article
- Influence of the mating design on the additive genetic variance in plant breeding populations.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2023Article
- Training set designs for prediction of yield and moisture of maize test cross hybrids with unreplicated trials.Frontiers in plant science · 2023Article
- Prediction of additive, epistatic, and dominance effects using models accounting for incomplete inbreeding in parental lines of hybrid rye and sugar beet.Frontiers in plant science · 2023Article
- Realized genomic selection across generations in a reciprocal recurrent selection breeding program ofFrontiers in plant science · 2023Article
- Genomic prediction using information across years with epistatic models and dimension reduction via haplotype blocks.PloS one · 2023Article
- Improving Yield and Yield Stability in Winter Rye by Hybrid Breeding.Plants (Basel, Switzerland) · 2022Review
- The Potential of Genome-Wide Prediction to Support Parental Selection, Evaluated with Data from a Commercial Barley Breeding Program.Plants (Basel, Switzerland) · 2022Article
- Building a Calibration Set for Genomic Prediction, Characteristics to Be Considered, and Optimization Approaches.Methods in molecular biology (Clifton, N.J.) · 2022Article
- Genomic Prediction Can Provide Precise Estimates of the Genotypic Value of Barley Lines Evaluated in Unreplicated Trials.Frontiers in plant science · 2022Article
- Combining NDVI and Bacterial Blight Score to Predict Grain Yield in Field Pea.Frontiers in plant science · 2022Article
- Formation of Potential Heterotic Groups of Oat Using Variation at Microsatellite Loci.Plants (Basel, Switzerland) · 2021Article
- Improved genomic prediction of clonal performance in sugarcane by exploiting non-additive genetic effects.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2021Article
- Correlational selection in the age of genomics.Nature ecology & evolution · 2021Review
- Early prediction of biomass in hybrid rye based on hyperspectral data surpasses genomic predictability in less-related breeding material.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2021Article
Corrections and comments
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Authors and funding
11 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
key messageGenomic prediction accuracy can be significantly increased by model calibration across multiple breeding cycles as long as selection cycles are connected by common ancestors. In hybrid rye breeding, application of genome-based prediction is expected to increase selection gain because of long selection cycles in population improvement and development of hybrid components. Essentially two prediction scenarios arise: (1) prediction of the genetic value of lines from the same breeding cycle in which model training is performed and (2) prediction of lines from subsequent cycles. It is the latter from which a reduction in cycle length and consequently the strongest impact on selection gain is expected. We empirically investigated genome-based prediction of grain yield, plant height and thousand kernel weight within and across four selection cycles of a hybrid rye breeding program. Prediction performance was assessed using genomic and pedigree-based best linear unbiased prediction (GBLUP and PBLUP). A total of 1040 S
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