Haplotype-based genome-wide association increases the predictability of leaf rust (Puccinia triticina) resistance in wheat
Functional haplotypes constructed based on epistatic interactions increased the predictability of leaf rust resistance in hybrid wheat as compared with single-marker effect estimates. Abstract Resistance breeding is crucial for sustainable control of wheat leaf rust and single nucleotide polymorphis...
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Veröffentlicht in: | Journal of experimental botany 2020-12, Vol.71 (22), p.6958-6968 |
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Sprache: | eng |
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Zusammenfassung: | Functional haplotypes constructed based on epistatic interactions increased the predictability of leaf rust resistance in hybrid wheat as compared with single-marker effect estimates.
Abstract
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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ISSN: | 0022-0957 1460-2431 |
DOI: | 10.1093/jxb/eraa387 |