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

KEY MESSAGE: Genomic 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. ABSTRACT: The genetic improvement of baking quality is one of the grand challenges in wh...

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Autores principales: Michel, Sebastian, Kummer, Christian, Gallee, Martin, Hellinger, Jakob, Ametz, Christian, Akgöl, Batuhan, Epure, Doru, Löschenberger, Franziska, Buerstmayr, Hermann
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Berlin Heidelberg 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5787228/
https://www.ncbi.nlm.nih.gov/pubmed/29063161
http://dx.doi.org/10.1007/s00122-017-2998-x
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author Michel, Sebastian
Kummer, Christian
Gallee, Martin
Hellinger, Jakob
Ametz, Christian
Akgöl, Batuhan
Epure, Doru
Löschenberger, Franziska
Buerstmayr, Hermann
author_facet Michel, Sebastian
Kummer, Christian
Gallee, Martin
Hellinger, Jakob
Ametz, Christian
Akgöl, Batuhan
Epure, Doru
Löschenberger, Franziska
Buerstmayr, Hermann
author_sort Michel, Sebastian
collection PubMed
description KEY MESSAGE: Genomic 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. ABSTRACT: 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. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1007/s00122-017-2998-x) contains supplementary material, which is available to authorized users.
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spelling pubmed-57872282018-02-02 Improving the baking quality of bread wheat by genomic selection in early generations Michel, Sebastian Kummer, Christian Gallee, Martin Hellinger, Jakob Ametz, Christian Akgöl, Batuhan Epure, Doru Löschenberger, Franziska Buerstmayr, Hermann Theor Appl Genet Original Article KEY MESSAGE: Genomic 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. ABSTRACT: 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. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1007/s00122-017-2998-x) contains supplementary material, which is available to authorized users. Springer Berlin Heidelberg 2017-10-23 2018 /pmc/articles/PMC5787228/ /pubmed/29063161 http://dx.doi.org/10.1007/s00122-017-2998-x Text en © The Author(s) 2017 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
spellingShingle Original Article
Michel, Sebastian
Kummer, Christian
Gallee, Martin
Hellinger, Jakob
Ametz, Christian
Akgöl, Batuhan
Epure, Doru
Löschenberger, Franziska
Buerstmayr, Hermann
Improving the baking quality of bread wheat by genomic selection in early generations
title Improving the baking quality of bread wheat by genomic selection in early generations
title_full Improving the baking quality of bread wheat by genomic selection in early generations
title_fullStr Improving the baking quality of bread wheat by genomic selection in early generations
title_full_unstemmed Improving the baking quality of bread wheat by genomic selection in early generations
title_short Improving the baking quality of bread wheat by genomic selection in early generations
title_sort improving the baking quality of bread wheat by genomic selection in early generations
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5787228/
https://www.ncbi.nlm.nih.gov/pubmed/29063161
http://dx.doi.org/10.1007/s00122-017-2998-x
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