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    Predicting Hybrid Performances for Quality Traits through Genomic-Assisted Approaches in Central European Wheat

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    Type
    Article
    Authors
    Liu, Guozheng
    Zhao, Yusheng
    Gowda, Manje
    Longin, C. Friedrich H.
    Reif, Jochen C.
    Mette, Michael F.
    KAUST Department
    Biological and Environmental Science and Engineering (BESE) Division
    Center for Desert Agriculture
    Date
    2016-07-06
    Permanent link to this record
    http://hdl.handle.net/10754/617507
    
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    Abstract
    Bread-making quality traits are central targets for wheat breeding. The objectives of our study were to (1) examine the presence of major effect QTLs for quality traits in a Central European elite wheat population, (2) explore the optimal strategy for predicting the hybrid performance for wheat quality traits, and (3) investigate the effects of marker density and the composition and size of the training population on the accuracy of prediction of hybrid performance. In total 135 inbred lines of Central European bread wheat (Triticum aestivum L.) and 1,604 hybrids derived from them were evaluated for seven quality traits in up to six environments. The 135 parental lines were genotyped using a 90k single-nucleotide polymorphism array. Genome-wide association mapping initially suggested presence of several quantitative trait loci (QTLs), but cross-validation rather indicated the absence of major effect QTLs for all quality traits except of 1000-kernel weight. Genomic selection substantially outperformed marker-assisted selection in predicting hybrid performance. A resampling study revealed that increasing the effective population size in the estimation set of hybrids is relevant to boost the accuracy of prediction for an unrelated test population.
    Citation
    Predicting Hybrid Performances for Quality Traits through Genomic-Assisted Approaches in Central European Wheat 2016, 11 (7):e0158635 PLOS ONE
    Sponsors
    The wheat data set for this research was generated within the HYWHEAT project funded by Bundesministerium für Bildung und Forschung (Grant ID: FKZ0315945D). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
    Publisher
    Public Library of Science (PLoS)
    Journal
    PLoS ONE
    DOI
    10.1371/journal.pone.0158635
    Additional Links
    http://dx.plos.org/10.1371/journal.pone.0158635
    ae974a485f413a2113503eed53cd6c53
    10.1371/journal.pone.0158635
    Scopus Count
    Collections
    Articles; Biological and Environmental Science and Engineering (BESE) Division; Center for Desert Agriculture

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