ArticleGenetics2012
Maximizing the reliability of genomic selection by optimizing the calibration set of reference individuals: comparison of methods in two diverse groups of maize inbreds (Zea mays L.).
Article in Genetics, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 168 papers.
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Who cites it
168 citing papers in PubMed.
- Improving grain yield prediction in Southern US oat germplasm using genomics information and environmental covariates.The plant genome · 2026Article
- Genomic selection in timothy (Phleum pratense L.): a comprehensive evaluation of prediction models, multi-trait strategies, and forward validation across Norwegian environments.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2026Article
- Unveiling the interactions between design optimization, modeling strategies, and spatial analysis in genomic selection.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2026Article
- Evolutionary structure constrains genomic prediction accuracy more than model complexity in mango (Mangifera indica L.).G3 (Bethesda, Md.) · 2026Article
- Impact of scale parameter for marker variance prior in some Bayesian whole-genome regression methods.Mammalian genome : official journal of the International Mammalian Genome Society · 2026Article
- Optimizing training sets for genomic selection to identify superior genotypes across multiple environments.G3 (Bethesda, Md.) · 2026Article
- Advances in tea breeding in Japan: from traditional methods to genomic approaches.Breeding science · 2026Article
- Targeted expansion of a barley genebank core collection facilitates the discovery of disease resistance loci.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2026Article
- Article
- Derivation of prediction error variance for non-genotyped individuals in genomic selection.Frontiers in genetics · 2026Article
- Statistics and data science unlock the predictive power of quantitative genetics.Frontiers in plant science · 2026Review
- Optimising the Use of Cryopreserved Genetic Resources for the Selection and Conservation of Animal Populations.Journal of animal breeding and genetics = Zeitschrift fur Tierzuchtung und Zuchtungsbiologie · 2026Article
- A public mid-density genotyping platform for cultivated cranberry (Vaccinium macrocarpon Aiton).The plant genome · 2025Article
- Assessment of genomic prediction capabilities of transcriptome data in a barley multi-parent RIL population.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2025Article
- Genomic prediction in Persian walnut: Optimization levers according to genetic architecture of complex traits.The plant genome · 2025Article
- Genomic selection: Essence, applications, and prospects.The plant genome · 2025Review
- Multi-trait/environment sparse genomic prediction using the SFSI R-package.The plant genome · 2025Article
- Leveraging historical trials to predict Fusarium head blight resistance in spring wheat breeding programs.The plant genome · 2025Article
- Optimization of sparse phenotyping strategy in multi-environmental trials in maize.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2025Article
- Optimizing training sets to identify superior genotypes in hybrid populations.Frontiers in plant science · 2025Article
108 more citing papers are in PubMed but not listed here.
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Authors and funding
20 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Genomic selection refers to the use of genotypic information for predicting breeding values of selection candidates. A prediction formula is calibrated with the genotypes and phenotypes of reference individuals constituting the calibration set. The size and the composition of this set are essential parameters affecting the prediction reliabilities. The objective of this study was to maximize reliabilities by optimizing the calibration set. Different criteria based on the diversity or on the prediction error variance (PEV) derived from the realized additive relationship matrix-best linear unbiased predictions model (RA-BLUP) were used to select the reference individuals. For the latter, we considered the mean of the PEV of the contrasts between each selection candidate and the mean of the population (PEVmean) and the mean of the expected reliabilities of the same contrasts (CDmean). These criteria were tested with phenotypic data collected on two diversity panels of maize (Zea mays L.) genotyped with a 50k SNPs array. In the two panels, samples chosen based on CDmean gave higher reliabilities than random samples for various calibration set sizes. CDmean also appeared superior to PEVmean, which can be explained by the fact that it takes into account the reduction of variance due to the relatedness between individuals. Selected samples were close to optimality for a wide range of trait heritabilities, which suggests that the strategy presented here can efficiently sample subsets in panels of inbred lines. A script to optimize reference samples based on CDmean is available on request.
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