ArticleTAG. Theoretical and applied genetics. Theoretische und angewandte Genetik2021
Strategies and considerations for implementing genomic selection to improve traits with additive and non-additive genetic architectures in sugarcane breeding.
Article in TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.
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Who cites it
18 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
- Exploiting historical agronomic data to develop genomic prediction strategies for early clonal selection in the Louisiana sugarcane variety development program.The plant genome · 2025Article
- Machine learning for genomic and pedigree prediction in sugarcane.The plant genome · 2024Article
- Sparse testing designs for optimizing predictive ability in sugarcane populations.Frontiers in plant science · 2024Article
- Sugarcane breeding: a fantastic past and promising future driven by technology and methods.Frontiers in plant science · 2024Article
- Genomic prediction with machine learning in sugarcane, a complex highly polyploid clonally propagated crop with substantial non-additive variation for key traits.The plant genome · 2023Article
- Genomic prediction of hybrid performance for agronomic traits in sorghum.G3 (Bethesda, Md.) · 2023Article
- Evaluation of a Sugarcane (Plants (Basel, Switzerland) · 2023Article
- Evaluating the impact of modeling the family effect for clonal selection in potato-breeding programs.Frontiers in plant science · 2023Article
- A first look at the ability to use genomic prediction for improving the ratooning ability of sugarcane.Frontiers in plant science · 2023Article
- Haplotype blocks for genomic prediction: a comparative evaluation in multiple crop datasets.Frontiers in plant science · 2023Article
- Optimising clonal performance in sugarcane: leveraging non-additive effects via mate-allocation strategies.Frontiers in plant science · 2023Article
- Integrated Approach in Genomic Selection to Accelerate Genetic Gain in Sugarcane.Plants (Basel, Switzerland) · 2022Review
- Genomic prediction with allele dosage information in highly polyploid species.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2022Article
- Recent Advances in Sugarcane Genomics, Physiology, and Phenomics for Superior Agronomic Traits.Frontiers in genetics · 2022Review
- Accuracy of genomic prediction of complex traits in sugarcane.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2021Article
- Genomic Selection in Sugarcane: Current Status and Future Prospects.Frontiers in plant science · 2021Review
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7 authors.
Funding
Abstract
key messageSimulations highlight the potential of genomic selection to substantially increase genetic gain for complex traits in sugarcane. The success rate depends on the trait genetic architecture and the implementation strategy. Genomic selection (GS) has the potential to increase the rate of genetic gain in sugarcane beyond the levels achieved by conventional phenotypic selection (PS). To assess different implementation strategies, we simulated two different GS-based breeding strategies and compared genetic gain and genetic variance over five breeding cycles to standard PS. GS scheme 1 followed similar routines like conventional PS but included three rapid recurrent genomic selection (RRGS) steps. GS scheme 2 also included three RRGS steps but did not include a progeny assessment stage and therefore differed more fundamentally from PS. Under an additive trait model, both simulated GS schemes achieved annual genetic gains of 2.6-2.7% which were 1.9 times higher compared to standard phenotypic selection (1.4%). For a complex non-additive trait model, the expected annual rates of genetic gain were lower for all breeding schemes; however, the rates for the GS schemes (1.5-1.6%) were still greater than PS (1.1%). Investigating cost-benefit ratios with regard to numbers of genotyped clones showed that substantial benefits could be achieved when only 1500 clones were genotyped per 10-year breeding cycle for the additive genetic model. Our results show that under a complex non-additive genetic model, the success rate of GS depends on the implementation strategy, the number of genotyped clones and the stage of the breeding program, likely reflecting how changes in QTL allele frequencies change additive genetic variance and therefore the efficiency of selection. These results are encouraging and motivate further work to facilitate the adoption of GS in sugarcane breeding.
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