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Article

Merging Genomics and Transcriptomics for Predicting Fusarium Head Blight Resistance in Wheat

1
Institute of Biotechnology in Plant Production (IFA-Tulln), University of Natural Resources and Life Sciences Vienna, 3430 Tulln, Austria
2
PGSB Plant Genome and Systems Biology, Helmholtz Center Munich, German Research Center for Environmental Health, 85764 Neuherberg, Germany
3
Research Unit Environmental Simulation (EUS) at the Institute of Biochemical Plant Pathology (BIOP), Helmholtz Zentrum München, 85764 Neuherberg, Germany
4
Saatzucht Edelhof GmbH, 3910 Zwettl, Austria
*
Author to whom correspondence should be addressed.
Genes 2021, 12(1), 114; https://doi.org/10.3390/genes12010114
Received: 17 December 2020 / Revised: 14 January 2021 / Accepted: 16 January 2021 / Published: 19 January 2021
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. View Full-Text
Keywords: wheat; Fusarium head blight; genomic prediction; omics-based prediction; transcriptomics wheat; Fusarium head blight; genomic prediction; omics-based prediction; transcriptomics
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MDPI and ACS Style

Michel, S.; Wagner, C.; Nosenko, T.; Steiner, B.; Samad-Zamini, M.; Buerstmayr, M.; Mayer, K.; Buerstmayr, H. Merging Genomics and Transcriptomics for Predicting Fusarium Head Blight Resistance in Wheat. Genes 2021, 12, 114. https://doi.org/10.3390/genes12010114

AMA Style

Michel S, Wagner C, Nosenko T, Steiner B, Samad-Zamini M, Buerstmayr M, Mayer K, Buerstmayr H. Merging Genomics and Transcriptomics for Predicting Fusarium Head Blight Resistance in Wheat. Genes. 2021; 12(1):114. https://doi.org/10.3390/genes12010114

Chicago/Turabian Style

Michel, Sebastian, Christian Wagner, Tetyana Nosenko, Barbara Steiner, Mina Samad-Zamini, Maria Buerstmayr, Klaus Mayer, and Hermann Buerstmayr. 2021. "Merging Genomics and Transcriptomics for Predicting Fusarium Head Blight Resistance in Wheat" Genes 12, no. 1: 114. https://doi.org/10.3390/genes12010114

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