Improving the baking quality of bread wheat by genomic selection in early generations

Abstract

Gungor, Huseyin/0000-0001-6708-6337; Epure, Doru-Gabriel/0000-0002-6209-2794; Buerstmayr, Hermann/0000-0002-0748-2351; Michel, Sebastian/0000-0001-6636-2694WOS: 000423400100017PubMed: 29063161Genomic selection shows great promise for pre-selecting lines with superior bread baking quality in early generations, 3 years ahead of labour-intensive, time-consuming, and costly quality analysis. The genetic improvement of baking quality is one of the grand challenges in wheat breeding as the assessment of the associated traits often involves time-consuming, labour-intensive, and costly testing forcing breeders to postpone sophisticated quality tests to the very last phases of variety development. The prospect of genomic selection for complex traits like grain yield has been shown in numerous studies, and might thus be also an interesting method to select for baking quality traits. Hence, we focused in this study on the accuracy of genomic selection for laborious and expensive to phenotype quality traits as well as its selection response in comparison with phenotypic selection. More than 400 genotyped wheat lines were, therefore, phenotyped for protein content, dough viscoelastic and mixing properties related to baking quality in multi-environment trials 2009-2016. The average prediction accuracy across three independent validation populations was r = 0.39 and could be increased to r = 0.47 by modelling major QTL as fixed effects as well as employing multi-trait prediction models, which resulted in an acceptable prediction accuracy for all dough rheological traits (r = 0.38-0.63). Genomic selection can furthermore be applied 2-3 years earlier than direct phenotypic selection, and the estimated selection response was nearly twice as high in comparison with indirect selection by protein content for baking quality related traits. This considerable advantage of genomic selection could accordingly support breeders in their selection decisions and aid in efficiently combining superior baking quality with grain yield in newly developed wheat varieties.University of Natural Resources and Life Sciences Vienna (BOKU); EUEuropean Union (EU) [E! 6399, E! 8959]Open access funding provided by University of Natural Resources and Life Sciences Vienna (BOKU). We like to thank Maria Burstmayr and her team for the tremendous work when extracting the DNA of several hundred wheat lines each year, Herbert Hetzendorfer for managing the collection of the phenotypic data, and Monika Opalo for screening the germplasm with regard to the Glu-1 loci. This research was funded by the EU Eurostars projects "E! 6399 Genomic selection of wheat varieties for robustness, yield and quality" and "E! 8959 Genomic selection for nitrogen use efficiency in wheat". We thank the anonymous reviewers for their valuable comments and suggestions for improving the manuscript