ArticleBMC genetics2013
Genomic selection in sugar beet breeding populations.
Article in BMC genetics, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 50 papers.
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Who cites it
50 citing papers in PubMed, 118 citations in OpenAlex.
- Revisiting the Molecular Roadmap for Sugar Crops: Genome Reading, Trait Writing and Variety Redesigning.Plant biotechnology journal · 2026Review
- Experimental evaluation of effectiveness of genomic selection for resistance to northern corn leaf blight in maize.Journal of applied genetics · 2025Article
- How Rice Responds to Temperature Changes and Defeats Heat Stress.Rice (New York, N.Y.) · 2024Review
- 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
- Genomic selection for spot blotch in bread wheat breeding panels, full-sibs and half-sibs and index-based selection for spot blotch, heading and plant height.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2022Article
- The performance of phenomic selection depends on the genetic architecture of the target trait.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2022Article
- Genome-wide association study and genomic prediction of white rust resistance in USDA GRIN spinach germplasm.Horticulture research · 2022Article
- Genomic Prediction of Complex Traits in an Allogamous Annual Crop: The Case of Maize Single-Cross Hybrids.Methods in molecular biology (Clifton, N.J.) · 2022Article
- Training set design in genomic prediction with multiple biparental families.The plant genome · 2021Article
- 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
- Genomic Prediction and Selection for Fruit Traits in Winter Squash.G3 (Bethesda, Md.) · 2020Article
- Revisiting hybrid breeding designs using genomic predictions: simulations highlight the superiority of incomplete factorials between segregating families over topcross designs.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2020Article
- Integrating molecular markers into metabolic models improves genomic selection for Arabidopsis growth.Nature communications · 2020Article
- Molecular tracking of multiple disease resistance in a winter wheat diversity panel.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2020Article
- Genomic prediction of fruit texture and training population optimization towards the application of genomic selection in apple.Horticulture research · 2020Article
- Evaluation of genomic selection methods for predicting fiber quality traits in Upland cotton.Molecular genetics and genomics : MGG · 2020Article
- Microbial Inoculation for Productivity Improvements and Potential Biological Control in Sugar Beet Crops.Frontiers in plant science · 2020Article
- Understanding the Impact of Cultivar, Seed Origin, and Substrate on Bacterial Diversity of the Sugar Beet Rhizosphere and Suppression of Soil-Borne Pathogens.Frontiers in plant science · 2020Article
- Advancing crested wheatgrass [Agropyron cristatum (L.) Gaertn.] breeding through genotyping-by-sequencing and genomic selection.PloS one · 2020Article
- Accuracy of genomic selection for grain yield and agronomic traits in soft red winter wheat.BMC genetics · 2019Article
Corrections and comments
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Authors and funding
5 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundGenomic selection exploits dense genome-wide marker data to predict breeding values. In this study we used a large sugar beet population of 924 lines representing different germplasm types present in breeding populations: unselected segregating families and diverse lines from more advanced stages of selection. All lines have been intensively phenotyped in multi-location field trials for six agronomically important traits and genotyped with 677 SNP markers.
resultsWe used ridge regression best linear unbiased prediction in combination with fivefold cross-validation and obtained high prediction accuracies for all except one trait. In addition, we investigated whether a calibration developed based on a training population composed of diverse lines is suited to predict the phenotypic performance within families. Our results show that the prediction accuracy is lower than that obtained within the diverse set of lines, but comparable to that obtained by cross-validation within the respective families.
conclusionsThe results presented in this study suggest that a training population derived from intensively phenotyped and genotyped diverse lines from a breeding program does hold potential to build up robust calibration models for genomic selection. Taken together, our results indicate that genomic selection is a valuable tool and can thus complement the genomics toolbox in sugar beet breeding.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.