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...
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| Format: | Article |
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MDPI AG
2021-01-01
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| Series: | Genes |
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| Online Access: | https://www.mdpi.com/2073-4425/12/1/114 |
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| author | Sebastian Michel Christian Wagner Tetyana Nosenko Barbara Steiner Mina Samad-Zamini Maria Buerstmayr Klaus Mayer Hermann Buerstmayr |
| author_facet | Sebastian Michel Christian Wagner Tetyana Nosenko Barbara Steiner Mina Samad-Zamini Maria Buerstmayr Klaus Mayer Hermann Buerstmayr |
| author_sort | Sebastian Michel |
| collection | DOAJ |
| 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. |
| first_indexed | 2024-03-09T04:23:27Z |
| format | Article |
| id | doaj.art-f65614334c9f4611a631f7deea65b05a |
| institution | Directory Open Access Journal |
| issn | 2073-4425 |
| language | English |
| last_indexed | 2024-03-09T04:23:27Z |
| publishDate | 2021-01-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Genes |
| spelling | doaj.art-f65614334c9f4611a631f7deea65b05a2023-12-03T13:45:03ZengMDPI AGGenes2073-44252021-01-0112111410.3390/genes12010114Merging Genomics and Transcriptomics for Predicting Fusarium Head Blight Resistance in WheatSebastian Michel0Christian Wagner1Tetyana Nosenko2Barbara Steiner3Mina Samad-Zamini4Maria Buerstmayr5Klaus Mayer6Hermann Buerstmayr7Institute of Biotechnology in Plant Production (IFA-Tulln), University of Natural Resources and Life Sciences Vienna, 3430 Tulln, AustriaInstitute of Biotechnology in Plant Production (IFA-Tulln), University of Natural Resources and Life Sciences Vienna, 3430 Tulln, AustriaPGSB Plant Genome and Systems Biology, Helmholtz Center Munich, German Research Center for Environmental Health, 85764 Neuherberg, GermanyInstitute of Biotechnology in Plant Production (IFA-Tulln), University of Natural Resources and Life Sciences Vienna, 3430 Tulln, AustriaInstitute of Biotechnology in Plant Production (IFA-Tulln), University of Natural Resources and Life Sciences Vienna, 3430 Tulln, AustriaInstitute of Biotechnology in Plant Production (IFA-Tulln), University of Natural Resources and Life Sciences Vienna, 3430 Tulln, AustriaPGSB Plant Genome and Systems Biology, Helmholtz Center Munich, German Research Center for Environmental Health, 85764 Neuherberg, GermanyInstitute of Biotechnology in Plant Production (IFA-Tulln), University of Natural Resources and Life Sciences Vienna, 3430 Tulln, AustriaGenomic 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.https://www.mdpi.com/2073-4425/12/1/114wheatFusarium head blightgenomic predictionomics-based predictiontranscriptomics |
| spellingShingle | Sebastian Michel Christian Wagner Tetyana Nosenko Barbara Steiner Mina Samad-Zamini Maria Buerstmayr Klaus Mayer Hermann Buerstmayr Merging Genomics and Transcriptomics for Predicting Fusarium Head Blight Resistance in Wheat Genes wheat Fusarium head blight genomic prediction omics-based prediction transcriptomics |
| 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 | wheat Fusarium head blight genomic prediction omics-based prediction transcriptomics |
| url | https://www.mdpi.com/2073-4425/12/1/114 |
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