ArticleFrontiers in plant science2018
Evaluation of the Potential for Genomic Selection to Improve Spring Wheat Resistance to Fusarium Head Blight in the Pacific Northwest.
Article in Frontiers in plant science, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers.
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25 citing papers in PubMed, 69 citations in OpenAlex.
- Genome-wide association mapping of native QTLs for Fusarium head blight resistance in US winter wheat.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2026Article
- Genetic and molecular approaches for Fusarium wilt resistance in garden pea: advances and future outlook.Plant molecular biology · 2025Review
- Integrating genomics, phenomics, and deep learning improves the predictive ability for Fusarium head blight-related traits in winter wheat.The plant genome · 2024Article
- Evaluation of eight Bayesian genomic prediction models for three micronutrient traits in bread wheat (Triticum aestivum L.).The plant genome · 2023Article
- Haplotype-tagged SNPs improve genomic prediction accuracy for Fusarium head blight resistance and yield-related traits in wheat.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2023Article
- Genomic selection to improve husk tightness based on genomic molecular markers in maize.Frontiers in plant science · 2023Article
- Editorial: Machine learning on understanding the epigenetic mechanisms underlying plant adaptation and domestication.Frontiers in plant science · 2023Article
- Patterns of genetic variation and QTLs controlling grain traits in a collection of global wheat germplasm revealed by high-quality SNP markers.BMC plant biology · 2022Article
- Comparison of single-trait and multi-trait genomic predictions on agronomic and disease resistance traits in spring wheat.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2022Article
- Article
- Multi-trait genomic selection can increase selection accuracy for deoxynivalenol accumulation resulting from fusarium head blight in wheat.The plant genome · 2022Article
- Maladaptation of U.S. corn and soybeans to a changing climate.Scientific reports · 2021Article
- Multi-Trait Multi-Environment Genomic Prediction of Agronomic Traits in Advanced Breeding Lines of Winter Wheat.Frontiers in plant science · 2021Article
- GPTransformer: A Transformer-Based Deep Learning Method for Predicting Fusarium Related Traits in Barley.Frontiers in plant science · 2021Article
- Updating the Breeding Philosophy of Wheat to Fusarium Head Blight (FHB): Resistance Components, QTL Identification, and Phenotyping-A Review.Plants (Basel, Switzerland) · 2020Review
- Assessment of the Potential for Genomic Selection To Improve Husk Traits in Maize.G3 (Bethesda, Md.) · 2020Article
- Methodical Considerations and Resistance Evaluation againstMicroorganisms · 2020Article
- Denser Markers and Advanced Statistical Method Identified More Genetic Loci Associated with Husk Traits in Maize.Scientific reports · 2020Article
- Germplasms, genetics and genomics for better control of disastrous wheat Fusarium head blight.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2020Review
- Training Population Design With the Use of Regional Fusarium Head Blight Nurseries to Predict Independent Breeding Lines for FHB Traits.Frontiers in plant science · 2020Article
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Authors and funding
7 authors at 4 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Fusarium Head Blight (FHB) has emerged in spring wheat production in Pacific Northwest during the last decade due to factors including climate changes, crop rotations, and tillage practices. A breeding population with 170 spring wheat lines was established and screened over a 2-year period in multiple locations for FHB incidence (INC), severity (SEV), and deposition of the mycotoxin, deoxynivalenol (DON). A genome-wide association study suggested that the detectable number of genetic loci and effects are limited for marker-assisted selection. In conjunction with the success of breeding on FHB resistance in other programs, genomic selection (GS) was suggested as a better option. To evaluate the prediction accuracy of GS in the current breeding population, we conducted a variety of validations by varying proportions of testing populations and cohorts based on both FHB resistance and market class, including soft white spring (SWS), hard white spring (HWS), and hard red spring (HRS). We found that INC had higher heritability, higher correlation across years and locations, and higher prediction accuracy than SEV and DON. Prediction accuracy varied among the scenarios that restricted the testing population to a certain cohort. For a small set of newly developed or introduced lines (<17), prediction accuracy will be about 60% if the lines have similar genetic relationships as those among the current 170-line training population. However, we expect a lower prediction accuracy if new lines are selected for a specific characteristic, such as FHB resistance or market class. With the exception of DON in the SWS lines, the current training population is capable of making reasonably accurate predictions for FHB-resistant lines in most of the major market classes. For SWS, adding more lines or further phenotyping is required to improve prediction accuracy. These results demonstrate the potential and challenges of GS, especially for developing FHB-resistant varieties in the SWS market class.
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