ArticleTAG. Theoretical and applied genetics. Theoretische und angewandte Genetik2023
Haplotype-tagged SNPs improve genomic prediction accuracy for Fusarium head blight resistance and yield-related traits in wheat.
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 23 papers.
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Who cites it
23 citing papers in PubMed, 27 citations in OpenAlex.
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- Genetic dissection of cold stress tolerance and yield potential under cold stress in nested synthetic wheat (Triticum aestivum L.) introgression libraries using multi-locus genome-wide association and haplotype analysis.Functional & integrative genomics · 2026Article
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- Genome-wide-association-analysis-based identification of genetic loci and candidate genes associated with seedling emergence rate in super-sweet corn (Zea mays L.).BMC plant biology · 2026Article
- Haplotype applications in genomic selection.Genome biology · 2026Review
- A multi-locus genome-wide association study uncovers candidate genes for alkali tolerance in maize (Zea Mays L.) seedlings.BMC genomics · 2025Article
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- Integrating multi-omics and machine learning for disease resistance prediction in legumes.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2025Review
- Genomic Prediction and Heritability Estimation for Daughter Pregnancy Rate in U.S. Holstein Cows Using SNP, Epistasis and Haplotype Effects.International journal of molecular sciences · 2025Article
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- SPDC-HG: An accelerator of genomic hybrid breeding in maize.Plant biotechnology journal · 2025Article
- Exploiting historical agronomic data to develop genomic prediction strategies for early clonal selection in the Louisiana sugarcane variety development program.The plant genome · 2025Article
- Genome-wide association study and genomic prediction of root system architecture traits in Sorghum (Sorghum bicolor (L.) Moench) at the seedling stage.BMC plant biology · 2025Article
- Beyond the genome: the role of functional markers in contemporary plant breeding.Frontiers in plant science · 2025Review
- Quantitative Trait Locus Mapping Combined with RNA Sequencing Identified Candidate Genes for Resistance to Powdery Mildew in Bitter Gourd (International journal of molecular sciences · 2024Article
- Single- and multi-trait genomic prediction and genome-wide association analysis of grain yield and micronutrient-related traits in ICARDA wheat under drought environment.Molecular genetics and genomics : MGG · 2023Article
- Comparison of the Accuracy of Epistasis and Haplotype Models for Genomic Prediction of Seven Human Phenotypes.Biomolecules · 2023Article
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Authors and funding
5 authors at 3 institutions in 2 countries.
Funding
Abstract
key messageLinkage disequilibrium (LD)-based haplotyping with subsequent SNP tagging improved the genomic prediction accuracy up to 0.07 and 0.092 for Fusarium head blight resistance and spike width, respectively, across six different models. Genomic prediction is a powerful tool to enhance genetic gain in plant breeding. However, the method is accompanied by various complications leading to low prediction accuracy. One of the major challenges arises from the complex dimensionality of marker data. To overcome this issue, we applied two pre-selection methods for SNP markers viz. LD-based haplotype-tagging and GWAS-based trait-linked marker identification. Six different models were tested with preselected SNPs to predict the genomic estimated breeding values (GEBVs) of four traits measured in 419 winter wheat genotypes. Ten different sets of haplotype-tagged SNPs were selected by adjusting the level of LD thresholds. In addition, various sets of trait-linked SNPs were identified with different scenarios from the training-test combined and only from the training populations. The BRR and RR-BLUP models developed from haplotype-tagged SNPs had a higher prediction accuracy for FHB and SPW by 0.07 and 0.092, respectively, compared to the corresponding models developed without marker pre-selection. The highest prediction accuracy for SPW and FHB was achieved with tagged SNPs pruned at weak LD thresholds (r
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