Comparing wMAS, GWAS, and genomic prediction for selecting powdery mildew-resistant spring barley genotypes
Su Myat Noe
Comparing wMAS, GWAS, and genomic prediction for selecting powdery mildew-resistant spring barley genotypes - London (United Kingdom) : BioMed Central Ltd., 2025.
Peer review Open Access
Background: Barley is one of the most widely cultivated cereals worldwide, and powdery mildew is among the major diseases threatening global barley production. Our study evaluated 370 spring barley breeding lines under controlled greenhouse growth conditions. Results: Using genome-wide association study (GWAS), 21 quantitative trait loci (QTL) were identified associated with seedling-stage powdery mildew resistance. Of these, eight were newly identified in this study. Genetic merit was also calculated using major-effect markers, and a positive correlation (> 0.7) was observed between the genetic merit and BLUP (AUDPC) values in both the two subpopulations of two- and six-row barley. While evaluating the performance of genomic prediction (GP) models, a GWAS-incorporated GP model consistently outperformed the Standard GP model in both subpopulations demonstrating the advantage of incorporating major-effect markers for a more accurate prediction. Our analysis of genotype selection patterns revealed a notable degree of agreement among the tested methods. In the two-row subpopulation, a large number of genotypes were exclusively selected by weighted marker-assisted selection (wMAS) revealing the dominance of major-effect QTL. In contrast, the six-row subpopulation had a smaller wMAS-exclusive group, suggesting a more polygenic background, which was captured by genomic prediction. Additionally, genomics-based methods consistently identified resistant genotypes that were overlooked by phenotypic selection, showing their ability to detect hidden genetic potential. Conclusions: Overall, GWAS-incorporated GP model demonstrated the best performance among the evaluated methods, suggesting this approach is the most effective with a potential to contribute to efficient breeding of powdery mildew resistance in spring barley.
Text in English
1471-2164
https://doi.org/10.1186/s12864-025-12395-y
Genome-wide association studies
Marker-assisted selection
Genomics
Forecasting
Barley
Powdery mildews
Best linear unbiased predictor
Comparing wMAS, GWAS, and genomic prediction for selecting powdery mildew-resistant spring barley genotypes - London (United Kingdom) : BioMed Central Ltd., 2025.
Peer review Open Access
Background: Barley is one of the most widely cultivated cereals worldwide, and powdery mildew is among the major diseases threatening global barley production. Our study evaluated 370 spring barley breeding lines under controlled greenhouse growth conditions. Results: Using genome-wide association study (GWAS), 21 quantitative trait loci (QTL) were identified associated with seedling-stage powdery mildew resistance. Of these, eight were newly identified in this study. Genetic merit was also calculated using major-effect markers, and a positive correlation (> 0.7) was observed between the genetic merit and BLUP (AUDPC) values in both the two subpopulations of two- and six-row barley. While evaluating the performance of genomic prediction (GP) models, a GWAS-incorporated GP model consistently outperformed the Standard GP model in both subpopulations demonstrating the advantage of incorporating major-effect markers for a more accurate prediction. Our analysis of genotype selection patterns revealed a notable degree of agreement among the tested methods. In the two-row subpopulation, a large number of genotypes were exclusively selected by weighted marker-assisted selection (wMAS) revealing the dominance of major-effect QTL. In contrast, the six-row subpopulation had a smaller wMAS-exclusive group, suggesting a more polygenic background, which was captured by genomic prediction. Additionally, genomics-based methods consistently identified resistant genotypes that were overlooked by phenotypic selection, showing their ability to detect hidden genetic potential. Conclusions: Overall, GWAS-incorporated GP model demonstrated the best performance among the evaluated methods, suggesting this approach is the most effective with a potential to contribute to efficient breeding of powdery mildew resistance in spring barley.
Text in English
1471-2164
https://doi.org/10.1186/s12864-025-12395-y
Genome-wide association studies
Marker-assisted selection
Genomics
Forecasting
Barley
Powdery mildews
Best linear unbiased predictor