Genomic Prediction for Fusarium Head Blight Resistance in the Hard Red Spring Wheat Uniform Regional Scab Nursery - Archive ouverte HAL Accéder directement au contenu
Poster De Conférence Année : 2023

Genomic Prediction for Fusarium Head Blight Resistance in the Hard Red Spring Wheat Uniform Regional Scab Nursery

Résumé

Fusarium Head Blight (FHB) is one of the major threatening diseases for wheat in the United States. Genetic progress through breeding has been observed but the phenotypic evaluation of FHB in the field remains tedious. Genomic studies suggest a rather complex genetic architecture with many genes with minor effects involved. For almost 20 years, the Uniform Regional Scab Nursery evaluated breeding lines, mainly from Montana, South Dakota, North Dakota State University, as well as the University of Minnesota. FHB resistance and other related traits were evaluated in 5 locations and for 30 lines each year on average with 9 locations in total. The experimental design was highly unbalanced since almost all lines are evaluated for one year (across all locations for that year). A subset of these lines has recently been genotyped by two genotypic arrays of 90k and 3k markers. Genomic prediction is a statistical method relying on all available genetic markers to predict the trait of interest, we implemented it to assess its efficiency in predicting FHB susceptibility. Filters were applied to discard lines and SNPs with too much missing data, imputation was done with Beagle and the minor allele frequency threshold was of 5%, leading to 288 lines genotyped for 53k SNPs. Traits were incidence, severity, disease, visual scabby kernel, DON concentration, and heading date, they were accounted for environmental effects with a linear mixed model. Genomic prediction was fitted by cross-validation and predictive ability was measured as the Pearson correlation between predicted and observed value in the validation set. The best two methods among the seven tested were rrBLUP (ridge-regression Best Linear Unbiased Predictor) and RKHS (Reproducing Kernel Hilbert Space) across all traits, with an average predictive ability of 0.61 and 0.62, respectively. Highest accuracy was obtained for VSK trait with 0.75. Then, we compared the impact of marker density on the predictive ability. We found that predictive ability plateaued with 500 to 3k SNPs, depending on the trait. Finally, we used successively each breeding population (from the different breeding programs) as validation set, to test the impact of decreasing genetic relatedness. In almost all cases, predictive ability decreased when predicted within a specific breeding program, but various patterns were observed. Finally, those insights demonstrated a clear interest in using genomic prediction in wheat breeding programs. The density of markers needed is small, thus allowing to use the low-cost 3k genotypic array.
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Dates et versions

hal-04332481 , version 1 (11-12-2023)

Identifiants

  • HAL Id : hal-04332481 , version 1

Citer

Charlotte Brault, Emily Conley, Jason Fiedler, James Anderson. Genomic Prediction for Fusarium Head Blight Resistance in the Hard Red Spring Wheat Uniform Regional Scab Nursery. Fusarium Head Blight Forum 2023, Dec 2023, Cincinnati (Ohio, USA), United States. ⟨hal-04332481⟩
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