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Merging Genomics and Transcriptomics for Predicting Fusarium Head Blight Resistance in Wheat
Genomic selection with genome-wide distributed molecular markers has evolved into a well-implemented tool in many breeding programs during the last decade. The resistance against Fusarium head blight (FHB) in wheat is probably one of the most thoroughly studied systems within this framework. Aside f...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7832326/ https://www.ncbi.nlm.nih.gov/pubmed/33477759 http://dx.doi.org/10.3390/genes12010114 |
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author | Michel, Sebastian Wagner, Christian Nosenko, Tetyana Steiner, Barbara Samad-Zamini, Mina Buerstmayr, Maria Mayer, Klaus Buerstmayr, Hermann |
author_facet | Michel, Sebastian Wagner, Christian Nosenko, Tetyana Steiner, Barbara Samad-Zamini, Mina Buerstmayr, Maria Mayer, Klaus Buerstmayr, Hermann |
author_sort | Michel, Sebastian |
collection | PubMed |
description | Genomic selection with genome-wide distributed molecular markers has evolved into a well-implemented tool in many breeding programs during the last decade. The resistance against Fusarium head blight (FHB) in wheat is probably one of the most thoroughly studied systems within this framework. Aside from the genome, other biological strata like the transcriptome have likewise shown some potential in predictive breeding strategies but have not yet been investigated for the FHB-wheat pathosystem. The aims of this study were thus to compare the potential of genomic with transcriptomic prediction, and to assess the merit of blending incomplete transcriptomic with complete genomic data by the single-step method. A substantial advantage of gene expression data over molecular markers has been observed for the prediction of FHB resistance in the studied diversity panel of breeding lines and released cultivars. An increase in prediction ability was likewise found for the single-step predictions, although this can mostly be attributed to an increased accuracy among the RNA-sequenced genotypes. The usage of transcriptomics can thus be seen as a complement to already established predictive breeding pipelines with pedigree and genomic data, particularly when more cost-efficient multiplexing techniques for RNA-sequencing will become more accessible in the future. |
format | Online Article Text |
id | pubmed-7832326 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-78323262021-01-26 Merging Genomics and Transcriptomics for Predicting Fusarium Head Blight Resistance in Wheat Michel, Sebastian Wagner, Christian Nosenko, Tetyana Steiner, Barbara Samad-Zamini, Mina Buerstmayr, Maria Mayer, Klaus Buerstmayr, Hermann Genes (Basel) Article Genomic selection with genome-wide distributed molecular markers has evolved into a well-implemented tool in many breeding programs during the last decade. The resistance against Fusarium head blight (FHB) in wheat is probably one of the most thoroughly studied systems within this framework. Aside from the genome, other biological strata like the transcriptome have likewise shown some potential in predictive breeding strategies but have not yet been investigated for the FHB-wheat pathosystem. The aims of this study were thus to compare the potential of genomic with transcriptomic prediction, and to assess the merit of blending incomplete transcriptomic with complete genomic data by the single-step method. A substantial advantage of gene expression data over molecular markers has been observed for the prediction of FHB resistance in the studied diversity panel of breeding lines and released cultivars. An increase in prediction ability was likewise found for the single-step predictions, although this can mostly be attributed to an increased accuracy among the RNA-sequenced genotypes. The usage of transcriptomics can thus be seen as a complement to already established predictive breeding pipelines with pedigree and genomic data, particularly when more cost-efficient multiplexing techniques for RNA-sequencing will become more accessible in the future. MDPI 2021-01-19 /pmc/articles/PMC7832326/ /pubmed/33477759 http://dx.doi.org/10.3390/genes12010114 Text en © 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Michel, Sebastian Wagner, Christian Nosenko, Tetyana Steiner, Barbara Samad-Zamini, Mina Buerstmayr, Maria Mayer, Klaus Buerstmayr, Hermann Merging Genomics and Transcriptomics for Predicting Fusarium Head Blight Resistance in Wheat |
title | Merging Genomics and Transcriptomics for Predicting Fusarium Head Blight Resistance in Wheat |
title_full | Merging Genomics and Transcriptomics for Predicting Fusarium Head Blight Resistance in Wheat |
title_fullStr | Merging Genomics and Transcriptomics for Predicting Fusarium Head Blight Resistance in Wheat |
title_full_unstemmed | Merging Genomics and Transcriptomics for Predicting Fusarium Head Blight Resistance in Wheat |
title_short | Merging Genomics and Transcriptomics for Predicting Fusarium Head Blight Resistance in Wheat |
title_sort | merging genomics and transcriptomics for predicting fusarium head blight resistance in wheat |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7832326/ https://www.ncbi.nlm.nih.gov/pubmed/33477759 http://dx.doi.org/10.3390/genes12010114 |
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