ArticleG3 (Bethesda, Md.)2022
Genome-wide imputation using the practical haplotype graph in the heterozygous crop cassava.
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 11 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
11 citing papers in PubMed.
- Haplotype applications in genomic selection.Genome biology · 2026Review
- AI-integrated digital breeding for crop improvement.Frontiers in plant science · 2026Review
- Genome-Wide, High-Density Genotyping Approaches for Plant Germplasm Characterisation (Methods and Applications).International journal of molecular sciences · 2025Review
- Developing pangenomes for large and complex plant genomes and their representation formats.Journal of advanced research · 2025Review
- Missing genotype imputation in non-model species using self-organizing maps.Molecular ecology resources · 2025Article
- Imputation strategies for genomic prediction using nanopore sequencing.BMC biology · 2023Article
- Construction of a strawberry breeding core collection to capture and exploit genetic variation.BMC genomics · 2023Article
- Skim exome capture genotyping in wheat.The plant genome · 2023Article
- The Practical Haplotype Graph, a platform for storing and using pangenomes for imputation.Bioinformatics (Oxford, England) · 2022Article
- Pangenomes as a Resource to Accelerate Breeding of Under-Utilised Crop Species.International journal of molecular sciences · 2022Review
- Expanding Gene-Editing Potential in Crop Improvement with Pangenomes.International journal of molecular sciences · 2022Review
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Genomic applications such as genomic selection and genome-wide association have become increasingly common since the advent of genome sequencing. The cost of sequencing has decreased in the past two decades; however, genotyping costs are still prohibitive to gathering large datasets for these genomic applications, especially in nonmodel species where resources are less abundant. Genotype imputation makes it possible to infer whole-genome information from limited input data, making large sampling for genomic applications more feasible. Imputation becomes increasingly difficult in heterozygous species where haplotypes must be phased. The practical haplotype graph (PHG) is a recently developed tool that can accurately impute genotypes, using a reference panel of haplotypes. We showcase the ability of the PHG to impute genomic information in the highly heterozygous crop cassava (Manihot esculenta). Accurately phased haplotypes were sampled from runs of homozygosity across a diverse panel of individuals to populate PHG, which proved more accurate than relying on computational phasing methods. The PHG achieved high imputation accuracy, using sparse skim-sequencing input, which translated to substantial genomic prediction accuracy in cross-validation testing. The PHG showed improved imputation accuracy, compared to a standard imputation tool Beagle, especially in predicting rare alleles.
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Registered trials
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