Integrating high-throughput phenotyping with multiple complementary GWAS models reduces method-dependent bias and enables reliable identification of novel loci and elite germplasm for durable yellow and leaf rust resistance in wheat. The causal agents of yellow and leaf rust in wheat, Puccinia striiformis f. sp. tritici and Puccinia triticina, pose a serious threat to grain yield and quality worldwide. Growing durable resistant wheat cultivars is an effective protection measure contributing to sustainable agriculture. Many of the known resistance genes, however, have been overcome due to the high genetic diversity and adaptability of pathogen populations. Therefore, the present study aimed to identify novel loci associated with yellow rust and leaf rust in a genome-wide association study using 1984 spring wheat accessions from the German Federal ex situ Genebank. Phenotypic data obtained from a detached-leaf assay were combined with 90,283 genotyping-by-sequencing genome-wide markers. Six significant peak marker-trait associations were identified for yellow rust and leaf rust, respectively. These are located on chromosomes 1D, 2B, 3B, 4A, 4B, 4D, 5A, 6B, and 7D. Six candidate genes were identified close to the identified loci. These findings may be valuable for identifying and deploying genetic resources to broaden the genetic basis of resistance and safeguard durability of resistance against yellow and leaf rust.
Behnaz Soleimani, Anne-Kathrin Pfrieme, Ulrike Beukert et al.· Theoretical and Applied Gene...· 0 citations
Proper analysis of phenotypic data is essential for reliable genomic prediction (GP) and sustained genetic gain in breeding programs. In this study, we used phenotypic and genotypic data generated from the winter wheat breeding program of Deutsche Saatveredelung AG (DSV), Lippstadt, Germany, comprising 1,941 genotypes and 6,335 SNP markers across three traits: grain yield, plant height, and heading date. We evaluated the impact of different two-stage analysis strategies: one using the environment (year × location combination) as the analysis unit (TS-S1) and the other using the breeding stage as the analysis unit (TS-S2), each with and without accounting for breeding-stage effects (-YesBS and -NoBS), on the computation of best linear unbiased estimates (BLUEs) and genome-wide prediction ability (PA), defined as the correlation between BLUEs and predicted values. The performance of these 4 different second stage models (TS-S1-NoBS, TS-S1-YesBS, TS-S2-NoBS, and TS-S2-YesBS) were evaluated using the extended genomic best linear prediction (EGBLUP) model under 5-fold cross validation (5-fold CV), leave one year out cross validation (LOY-CV) and leave one breeding stage out cross validation (LOBS-CV) scenarios. In the presence of the strong breeding stage effect ignoring the breeding stage in the model resulted in biased BLUEs and overestimated prediction abilities in the 5-fold CV, and underestimated prediction abilities in the LOY-CV and LOBS-CV. These unstable prediction abilities are driven by confounded environmental effects in the BLUEs due to omission of the breeding-stage effect. In contrast, models that accounted for the breeding stage produced more reliable BLUEs and more stable prediction results across all cross-validation scenarios, with TS-S1-YesBS performing best overall. Overall, our findings demonstrate that breeding stage effects mainly arise from differences in growing conditions and must be adequately considered. Therefore, including breeding stage in phenotypic models is critical to obtaining unbiased BLUEs and ensuring accurate genomic prediction and selection decisions.
Ravindra Reddy Gundala, Georg Witte, Jost Doernte et al.· Frontiers in Plant Science· 0 citations
A new approach to identify environment-specific quantitative trait loci (QTL) using GWAS and the validated resistance gene Yr27 was identified as sole candidate gene for one QTL region of particular relevance for Central European wheat.
Jiao-Jiao Wang, Renate H. Schmidt, Guoliang Li et al.· Theoretical and Applied Gene...· 1 citation
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