ArticleTAG. Theoretical and applied genetics. Theoretische und angewandte Genetik2023
Toward combining qualitative race-specific and quantitative race-nonspecific disease resistance by genomic selection.
Article in TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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Who cites it
10 citing papers in PubMed.
- A built-in brake for plant immunity: Resistance (R) protein-mediated immunity is fine-tuned byScience advances · 2026Article
- Genetic dissection of southern corn leaf blight resistance in sweet corn through genome-wide association studies and genomic selection.The plant genome · 2026Article
- Genome-Wide Association and Transcriptome Analyses Identify OsCBP606 as a Calmodulin-Mediated Susceptibility Gene to Magnaporthe oryzae in Rice.Rice (New York, N.Y.) · 2026Article
- Quantitive disease resistance (QDR): The alternative to "all-or-nothing" strategy in plant immunity.The Plant cell · 2025Article
- Molecular Insights into Rice Immunity: Unveiling Mechanisms and Innovative Approaches to Combat Major Pathogens.Plants (Basel, Switzerland) · 2025Review
- The Role of Genetic Resistance in Rice Disease Management.International journal of molecular sciences · 2025Review
- Dissecting adult plant resistance to stem rust through multi-model GWAS in a diverse barley germplasm panel.Frontiers in plant science · 2025Article
- Fine mapping of powdery mildew resistance gene PmXNM in a Chinese wheat landrace Xiaonanmai.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2024Article
- Fine-mapping ofFrontiers in plant science · 2024Article
- Comparison of linear and semi-parametric models incorporating genomic, pedigree, and associated loci information for the prediction of resistance to stripe rust in an Austrian winter wheat breeding program.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2023Article
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4 authors.
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No grant is acknowledged in the PubMed record.
Abstract
key messageA novel genomic selection strategy offers the unique opportunity to develop qualitative race-specific resistant varieties that possess high levels of the more durable quantitative race-nonspecific resistance in their genetic background. Race-specific qualitative resistance genes (R-genes) are conferring complete resistance in many pathosystems, but are frequently overcome by new virulent pathogen races. Once the deployed R-genes are overcome, a wide variation of quantitative disease resistance (QDR) can be observed in a set of previously race-specific, i.e., completely resistant genotypes-a phenomenon known as "vertifolia effect." This race-nonspecific QDR is considered to be more durable in the long term, but provides merely a partial protection against pathogens. This simulation study aimed to detangle race-specific R-gene-mediated resistance of pending selection candidates and the QDR in their genetic background by employing different genomic selection strategies. True breeding values that reflected performance data for rust resistance in wheat were simulated, and used in a recurrent genomic selection based on several prediction models and training population designs. Using training populations that were devoid of race-specific R-genes was thereby pivotal for an efficient improvement of QDR in the long term. Marker-assisted preselection for the presence of R-genes followed by a genomic prediction for accumulating the many small to medium effect loci underlying QDR in the genetic background of race-specific resistant genotypes appeared furthermore to be a promising approach to select simultaneously for both types of resistance. The practical application of such a knowledge-driven genomic breeding strategy offers the opportunity to develop varieties with multiple layers of resistance, which have the potential to prevent intolerable crop losses under epidemic situations by displaying a high level of QDR even when race-specific R-genes have been overcome by evolving pathogen populations.
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