ArticleThe plant genome2020
A sorghum practical haplotype graph facilitates genome-wide imputation and cost-effective genomic prediction.
Article in The plant genome, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 45 papers, 1 of them a synthesis that pooled it.
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Who cites it
45 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Data Integration, Imputation, and Meta-analysis for Genome-Wide Association Studies.Methods in molecular biology (Clifton, N.J.) · 2022Pooled it
- Identification and Fine Mapping of a MYB-like Transcription Factor Regulating Yellow Grain inPlants (Basel, Switzerland) · 2026Article
- Next-Generation Genotyping: Innovations Driving Plant Genomic Improvement.Life (Basel, Switzerland) · 2026Review
- Accessing crop genetic diversity via pangenomics.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2026Review
- Skim-sequencing for genomic selection in wheat: a comparison of marker platforms.The plant genome · 2026Article
- Haplotype applications in genomic selection.Genome biology · 2026Review
- Developing pangenomes for large and complex plant genomes and their representation formats.Journal of advanced research · 2025Review
- Genotype and environment synergistically determine the polyphenolic composition and functional activity of highbush blueberries.Scientific reports · 2025Article
- Breeding perspectives on tackling trait genome-to-phenome (G2P) dimensionality using ensemble-based genomic prediction.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2025Review
- Review
- The role of pangenomics in orphan crop improvement.Nature communications · 2025Review
- Review
- Genomic resources, opportunities, and prospects for accelerated improvement of millets.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2024Review
- Omics-driven utilization of wild relatives for empowering pre-breeding in pearl millet.Planta · 2024Review
- Skim exome capture genotyping in wheat.The plant genome · 2023Article
- Advances in genomic characterization of Urochloa humidicola: exploring polyploid inheritance and apomixis.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2023Article
- The Progression in Developing Genomic Resources for Crop Improvement.Life (Basel, Switzerland) · 2023Review
- Exploring the sorghum race level diversity utilizing 272 sorghum accessions genomic resources.Frontiers in plant science · 2023Article
- Graph-based pangenomics maximizes genotyping density and reveals structural impacts on fungal resistance in melon.Nature communications · 2022Article
- Development and validation of an optimized marker set for genomic selection in southern U.S. rice breeding programs.The plant genome · 2022Article
Corrections and comments
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Authors and funding
21 authors.
Funding
Abstract
Successful management and utilization of increasingly large genomic datasets is essential for breeding programs to accelerate cultivar development. To help with this, we developed a Sorghum bicolor Practical Haplotype Graph (PHG) pangenome database that stores haplotypes and variant information. We developed two PHGs in sorghum that were used to identify genome-wide variants for 24 founders of the Chibas sorghum breeding program from 0.01x sequence coverage. The PHG called single nucleotide polymorphisms (SNPs) with 5.9% error at 0.01x coverage-only 3% higher than PHG error when calling SNPs from 8x coverage sequence. Additionally, 207 progenies from the Chibas genomic selection (GS) training population were sequenced and processed through the PHG. Missing genotypes were imputed from PHG parental haplotypes and used for genomic prediction. Mean prediction accuracies with PHG SNP calls range from .57-.73 and are similar to prediction accuracies obtained with genotyping-by-sequencing or targeted amplicon sequencing (rhAmpSeq) markers. This study demonstrates the use of a sorghum PHG to impute SNPs from low-coverage sequence data and shows that the PHG can unify genotype calls across multiple sequencing platforms. By reducing input sequence requirements, the PHG can decrease the cost of genotyping, make GS more feasible, and facilitate larger breeding populations. Our results demonstrate that the PHG is a useful research and breeding tool that maintains variant information from a diverse group of taxa, stores sequence data in a condensed but readily accessible format, unifies genotypes across genotyping platforms, and provides a cost-effective option for genomic selection.
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