Literature DB >> 27225454

Genetic control of protein content and sedimentation volume in European winter wheat cultivars.

Tobias Würschum1, Willmar L Leiser2, Ebrahim Kazman3, C Friedrich H Longin2.   

Abstract

KEY MESSAGE: Breeding of bread wheat in the last decades has maintained a high baking quality despite the intensive selection for grain yield. The quality trait sedimentation volume but not protein content is mainly controlled by the Glu - A1, Glu - B1, Glu - D1, Gli - B1 , and Pinb - D1 loci which are differentially used in varieties from different European origins. Protein content and sedimentation volume are two important quality traits in wheat breeding. In this study, we used a panel of 407 European winter wheat cultivars to dissect the genetic architecture of both traits and to assess the potential of genomics-assisted breeding. All lines were phenotyped in multi-location field trials, genotyped by a genotyping-by-sequencing approach, and assessed for the alleles at the Glu-A1, Glu-B1, Glu-D1, Gli-B1, and Pinb-D1 candidate loci. Our analyses revealed no effect of the candidate loci on protein content, but a strong effect on sedimentation volume, with Glu-B1 and Gli-B1 explaining 24.6 and 19.5 % of the genotypic variance, respectively. The genome-wide scan identified three quantitative trait loci (QTL) for protein content which jointly explained only 18.5 % of the genotypic variance. In contrast, four QTL were detected for sedimentation volume most likely identifying the Glu-B1 and Gli-B1 candidate loci and explaining approximately 60 % of the genotypic variance. We observed differences for both traits between countries of origin of the cultivars, accompanied by corresponding geographic differences in QTL allele frequencies. Furthermore, a genome-wide prediction approach resulted in a higher predictive ability for both traits as compared to marker-assisted selection based on the identified QTL. Taken together, our results illustrate a different genetic architecture of the two quality traits and show the potential of their genomics-assisted improvement.

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Year:  2016        PMID: 27225454     DOI: 10.1007/s00122-016-2732-0

Source DB:  PubMed          Journal:  Theor Appl Genet        ISSN: 0040-5752            Impact factor:   5.699


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