ArticleFrontiers in plant science2023
Genomic prediction with haplotype blocks in wheat.
Article in Frontiers in plant science, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.
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Who cites it
17 citing papers in PubMed.
- Efficiency under epistasis of haplotype-based genomic selection for pure line breeding.Heredity · 2026Article
- OptimGS: a dual integrative genomic prediction framework for improving cold stress tolerance in wheat.Briefings in bioinformatics · 2026Article
- Mining QTLs and candidate genes in bread wheat associated with kernel hardness through GWAS.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2026Article
- Next-Generation Genotyping: Innovations Driving Plant Genomic Improvement.Life (Basel, Switzerland) · 2026Review
- Exploring the potential of naked barley to manage deoxynivalenol accumulation from Fusarium head blight.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2026Article
- Haplotype applications in genomic selection.Genome biology · 2026Review
- Haplotype-based autoencoders can reduce the dataset dimension and estimate haplotype block effects in different crop species.BMC bioinformatics · 2025Article
- PotatoMASH is a cost-effective marker system for genomic prediction in potato based on short-read haplotypes.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2025Article
- 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
- Enhancing Genomic Prediction Accuracy of Reproduction Traits in Rongchang Pigs Through Machine Learning.Animals : an open access journal from MDPI · 2025Article
- Mining genomic regions associated with stomatal traits and their candidate genes in bread wheat through genome-wide association study (GWAS).TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2025Article
- DeepHapNet: a haplotype assembly method based on RetNet and deep spectral clustering.Briefings in bioinformatics · 2024Article
- Wheat improvement through advances in single nucleotide polymorphism (SNP) detection and genotyping with a special emphasis on rust resistance.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2024Review
- Haplotype-based association mapping of genomic regions associated with Zymoseptoria tritici resistance using 217 diverse wheat genotypes.BMC plant biology · 2024Article
- Genomic prediction for sugarcane diseases including hybrid Bayesian-machine learning approaches.Frontiers in plant science · 2024Article
- Genomic prediction within and across maize landrace derived populations using haplotypes.Frontiers in plant science · 2024Article
- 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
14 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Haplotype blocks might carry additional information compared to single SNPs and have therefore been suggested for use as independent variables in genomic prediction. Studies in different species resulted in more accurate predictions than with single SNPs in some traits but not in others. In addition, it remains unclear how the blocks should be built to obtain the greatest prediction accuracies. Our objective was to compare the results of genomic prediction with different types of haplotype blocks to prediction with single SNPs in 11 traits in winter wheat. We built haplotype blocks from marker data from 361 winter wheat lines based on linkage disequilibrium, fixed SNP numbers, fixed lengths in cM and with the R package HaploBlocker. We used these blocks together with data from single-year field trials in a cross-validation study for predictions with RR-BLUP, an alternative method (RMLA) that allows for heterogeneous marker variances, and GBLUP performed with the software GVCHAP. The greatest prediction accuracies for resistance scores for
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