Haplotype-based genome-wide association increases the predictability of leaf rust (Puccinia triticina) resistance in wheat
© The Author(s) 2020. Published by Oxford University Press on behalf of the Society for Experimental Biology. All rights reserved. For permissions, please email: journals.permissionsoup.com.
| Veröffentlicht in: | Journal of experimental botany. - 1985. - 71(2020), 22 vom: 31. Dez., Seite 6958-6968 |
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| Weitere Verfasser: | , , , |
| Format: | Online-Aufsatz |
| Sprache: | English |
| Veröffentlicht: |
2020
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| Zugriff auf das übergeordnete Werk: | Journal of experimental botany |
| Schlagworte: | Journal Article Research Support, Non-U.S. Gov't Association mapping FH-based GWAS SNP-based GWAS functional haplotype hybrid wheat independent validation leaf rust predictability |
| Zusammenfassung: | © The Author(s) 2020. Published by Oxford University Press on behalf of the Society for Experimental Biology. All rights reserved. For permissions, please email: journals.permissionsoup.com. Resistance breeding is crucial for sustainable control of wheat leaf rust and single nucleotide polymorphism (SNP)-based genome-wide association studies (GWAS) are widely used to dissect leaf rust resistance. Unfortunately, GWAS based on SNPs often explained only a small proportion of the genetic variation. We compared SNP-based GWAS with a method based on functional haplotypes (FH) considering epistasis in a comprehensive hybrid wheat mapping population composed of 133 parents plus their 1574 hybrids and characterized with 626 245 high-quality SNPs. In total, 2408 and 1 139 828 significant associations were detected in the mapping population by using SNP-based and FH-based GWAS, respectively. These associations mapped to 25 and 69 candidate regions, correspondingly. SNP-based GWAS highlighted two already-known resistance genes, Lr22a and Lr34-B, while FH-based GWAS detected associations not only on these genes but also on two additional genes, Lr10 and Lr1. As revealed by a second hybrid wheat population for independent validation, the use of detected associations from SNP-based and FH-based GWAS reached predictabilities of 11.72% and 22.86%, respectively. Therefore, FH-based GWAS is not only more powerful for detecting associations, but also improves the accuracy of marker-assisted selection compared with the SNP-based approach |
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| Beschreibung: | Date Completed 14.05.2021 Date Revised 14.05.2021 published: Print Dryad: 10.5061/dryad.3n5tb2rf3 Citation Status MEDLINE |
| ISSN: | 1460-2431 |
| DOI: | 10.1093/jxb/eraa387 |