ArticleThe plant genome2021
Genomic selection of parents and crosses beyond the native gene pool of a breeding program.
Article in The plant genome, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
3 citing papers in PubMed.
- Genomic prediction in a small barley population can benefit from training on related populations.G3 (Bethesda, Md.) · 2025Article
- Haplotype-tagged SNPs improve genomic prediction accuracy for Fusarium head blight resistance and yield-related traits in wheat.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2023Article
- Genomic selection of parents and crosses beyond the native gene pool of a breeding program.The plant genome · 2021Article
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Genomic selection has become a valuable tool for selecting cultivar candidates in many plant breeding programs. Genomic selection of elite parents and crossing combinations with germplasm developed outside a breeding program has, however, hardly been explored until now. The aim of this study was to assess the potential of this method for commonly ranking and selecting elite germplasm developed within and beyond a given breeding program. A winter wheat (Triticum aestivum L.) population consisting of 611 in-house and 87 externally developed lines was used to compare training population compositions and statistical models for genomically predicting baking quality in this framework. Augmenting training populations with lines from other breeding programs had a larger influence on the prediction ability than adding in-house generated lines when aiming to commonly rank both germplasm sets. Exploiting preexisting information of secondary correlated traits resulted likewise in more accurate predictions both in empirical analyses and simulations. Genotyping germplasm developed beyond a given breeding program is moreover a convenient way to clarify its relationships with a breeder's own germplasm because pedigree information is oftentimes not available for this purpose. Genomic predictions can thus support a more informed diversity management, especially when integrating simply to phenotype correlated traits to partly circumvent resource reallocations for a costly phenotyping of germplasm from other programs.
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