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Genomic prediction and genome-wide association studies of flour yield and alveograph quality traits using advanced winter wheat breeding material

Author: Kristensen, P.S.
Author: Jensen, J.
Author: Andersen, J.P.
Author: Guzman, C.
Author: Orabi, J.
Author: Jahoor, A.
Year: 2019
ISSN: 2073-4425
URI: https://hdl.handle.net/10883/20547
Abstract: Use of genetic markers and genomic prediction might improve genetic gain for quality traits in wheat breeding programs. Here, flour yield and Alveograph quality traits were inspected in 635 F6 winter wheat breeding lines from two breeding cycles. Genome-wide association studies revealed single nucleotide polymorphisms (SNPs) on chromosome 5D significantly associated with flour yield, Alveograph P (dough tenacity), and Alveograph W (dough strength). Additionally, SNPs on chromosome 1D were associated with Alveograph P and W, SNPs on chromosome 1B were associated with Alveograph P, and SNPs on chromosome 4A were associated with Alveograph L (dough extensibility). Predictive abilities based on genomic best linear unbiased prediction (GBLUP) models ranged from 0.50 for flour yield to 0.79 for Alveograph W based on a leave-one-out cross-validation strategy. Predictive abilities were negatively affected by smaller training set sizes, lower genetic relationship between lines in training and validation sets, and by genotype–environment (G×E) interactions. Bayesian Power Lasso models and genomic feature models resulted in similar or slightly improved predictions compared to GBLUP models. SNPs with the largest effects can be used for screening large numbers of lines in early generations in breeding programs to select lines that potentially have good quality traits. In later generations, genomic predictions might be used for a more accurate selection of high quality wheat lines.
Format: PDF
Language: English
Publisher: MDPI
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 CIMMYT-Knowledge-Center@cgiar.org 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: Basel (Switzerland)
Pages: art. 669
Issue: 9
Volume: 10
DOI: 10.3390/genes10090669
Agrovoc: WHEAT
Agrovoc: PLANT BREEDING
Agrovoc: BAKING CHARACTERISTICS
Agrovoc: FLOURS
Agrovoc: MARKER-ASSISTED SELECTION
Related Datasets: https://www.mdpi.com/2073-4425/10/9/669/s1
Journal: Genes


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

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