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Genomic selection for quantitative adult plant stem rust resistance in wheat

Author: Rutkoski, J.
Author: Poland, J.E
Author: Singh, R.P.
Author: Huerta-Espino, J.
Author: Bhavani, S.
Author: Barbier, H.
Author: Rouse, M.N.
Author: Jannink, J.L.
Author: Sorrells, M.E.
Year: 2014
ISSN: 1940-3372
Abstract: Quantitative adult plant resistance (APR) to stem rust (Puccinia graminis f. sp. tritici) is an important breeding target in wheat (Triticum aestivum L.) and a potential target for genomic selection (GS). To evaluate the relative importance of known APR loci in applying GS, we characterized a set of CIMMYT germplasm at important APR loci and on a genome-wide profile using genotyping-by-sequencing (GBS). Using this germplasm, we describe the genetic architecture and evaluate prediction models for APR using data from the international Ug99 stem rust screening nurseries. Prediction models incorporating markers linked to important APR loci and seedling phenotype scores as fixed effects were evaluated along with the classic prediction models: Multiple linear regression (MLR), Genomic best linear unbiased prediction (G-BLUP), Bayesian Lasso (BL), and Bayes Cπ (BCπ). We found the Sr2 region to play an important role in APR in this germplasm. A model using Sr2 linked markers as fixed effects in G-BLUP was more accurate than MLR with Sr2 linked markers (p-value = 0.12), and ordinary G-BLUP (p-value = 0.15). Incorporating seedling phenotype information as fixed effects in G-BLUP did not consistently increase accuracy. Overall, levels of prediction accuracy found in this study indicate that GS can be effectively applied to improve stem rust APR in this germplasm, and if genotypes at Sr2 linked markers are available, modeling these genotypes as fixed effects could lead to better predictions.
Format: PDF
Language: English
Publisher: Crop Science Society of America
Copyright: CIMMYT manages Intellectual Assets as International Public Goods. The user is free to download, print, store and share this work. In case you want to translate or create any other derivative work and share or distribute such translation/derivative work, please contact indicating the work you want to use and the kind of use you intend; CIMMYT will contact you with the suitable license for that purpose.
Type: Article
Place of Publication: United States
Issue: 3
Volume: 7
DOI: 10.3835/plantgenome2014.02.0006
Keywords: Quantitative Adult Plant Resistance
Keywords: APR
Keywords: Stem Rust
Keywords: Genomic Selection
Agrovoc: WHEAT
Agrovoc: RUSTS
Related Datasets:
Related Datasets:
Related Datasets:
Journal: The Plant Genome

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  • Wheat
    Wheat - breeding, phytopathology, physiology, quality, biotech

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