ArticleG3 (Bethesda, Md.)2022
Development of the Wheat Practical Haplotype Graph database as a resource for genotyping data storage and genotype imputation.
Article in G3 (Bethesda, Md.), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.
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16 citing papers in PubMed.
- A haplotype-layered GWAS identifies a multi-trait grain mold resistance hub on sorghum chromosome 5.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2026Article
- Next-Generation Genotyping: Innovations Driving Plant Genomic Improvement.Life (Basel, Switzerland) · 2026Review
- Skim-sequencing for genomic selection in wheat: a comparison of marker platforms.The plant genome · 2026Article
- Identification of stripe rust adult plant resistance genes in the hard winter wheat cultivar Baker's Ann.The plant genome · 2026Article
- Integration and imputation of GBS-derived and DArTseq-derived SNP markers in assessing genetic diversity of bread wheat genotypes.BMC genomics · 2026Article
- Haplotype applications in genomic selection.Genome biology · 2026Review
- Pathogenic and Genetic Diversity ofJournal of fungi (Basel, Switzerland) · 2025Article
- Developing pangenomes for large and complex plant genomes and their representation formats.Journal of advanced research · 2025Review
- Interaction of plant-derived metabolites and rhizobiome functions enhances drought stress tolerance.Genome biology · 2025Article
- Benchmarking of low coverage sequencing workflows for precision genotyping in eggplant.BMC plant biology · 2025Article
- PidTools: Algorithm and web tools for crop pedigree identification analysis.Computational and structural biotechnology journal · 2024Article
- Skim exome capture genotyping in wheat.The plant genome · 2023Article
- All families of transposable elements were active in the recent wheat genome evolution and polyploidy had no impact on their activity.The plant genome · 2023Article
- Genomic selection for agronomic traits in a winter wheat breeding program.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2023Article
- The Practical Haplotype Graph, a platform for storing and using pangenomes for imputation.Bioinformatics (Oxford, England) · 2022Article
- High-Density Mapping of Quantitative Trait Loci Controlling Agronomically Important Traits in Quinoa (Frontiers in plant science · 2022Article
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40 authors.
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Abstract
To improve the efficiency of high-density genotype data storage and imputation in bread wheat (Triticum aestivum L.), we applied the Practical Haplotype Graph (PHG) tool. The Wheat PHG database was built using whole-exome capture sequencing data from a diverse set of 65 wheat accessions. Population haplotypes were inferred for the reference genome intervals defined by the boundaries of the high-quality gene models. Missing genotypes in the inference panels, composed of wheat cultivars or recombinant inbred lines genotyped by exome capture, genotyping-by-sequencing (GBS), or whole-genome skim-seq sequencing approaches, were imputed using the Wheat PHG database. Though imputation accuracy varied depending on the method of sequencing and coverage depth, we found 92% imputation accuracy with 0.01× sequence coverage, which was slightly lower than the accuracy obtained using the 0.5× sequence coverage (96.6%). Compared to Beagle, on average, PHG imputation was ∼3.5% (P-value < 2 × 10-14) more accurate, and showed 27% higher accuracy at imputing a rare haplotype introgressed from a wild relative into wheat. We found reduced accuracy of imputation with independent 2× GBS data (88.6%), which increases to 89.2% with the inclusion of parental haplotypes in the database. The accuracy reduction with GBS is likely associated with the small overlap between GBS markers and the exome capture dataset, which was used for constructing PHG. The highest imputation accuracy was obtained with exome capture for the wheat D genome, which also showed the highest levels of linkage disequilibrium and proportion of identity-by-descent regions among accessions in the PHG database. We demonstrate that genetic mapping based on genotypes imputed using PHG identifies SNPs with a broader range of effect sizes that together explain a higher proportion of genetic variance for heading date and meiotic crossover rate compared to previous studies.
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