ArticleGenetics, selection, evolution : GSE2014
Imputation of sequence level genotypes in the Franches-Montagnes horse breed.
Article in Genetics, selection, evolution : GSE, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
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Who cites it
15 citing papers in PubMed.
- An increased number of heterozygous calls in the AxiomTM Equine Genotyping Array.G3 (Bethesda, Md.) · 2026Article
- Comparison between SNP array and imputed data to estimate population structure and ROH hotspots in horse breeds.BMC genomics · 2025Article
- Predicted genetic burden and frequency of phenotype-associated variants in the horse.Scientific reports · 2024Article
- Development and validation of a horse reference panel for genotype imputation.Genetics, selection, evolution : GSE · 2022Article
- Article
- Adapting Genotyping-by-Sequencing and Variant Calling for Heterogeneous Stock Rats.G3 (Bethesda, Md.) · 2020Article
- Article
- Sequence imputation from low density single nucleotide polymorphism panel in a black poplar breeding population.BMC genomics · 2019Article
- The horse Y chromosome as an informative marker for tracing sire lines.Scientific reports · 2019Article
- Imputation from SNP chip to sequence: a case study in a Chinese indigenous chicken population.Journal of animal science and biotechnology · 2018Article
- Highly accurate sequence imputation enables precise QTL mapping in Brown Swiss cattle.BMC genomics · 2017Article
- Developing a 670k genotyping array to tag ~2M SNPs across 24 horse breeds.BMC genomics · 2017Article
- Evaluation of the accuracy of imputed sequence variant genotypes and their utility for causal variant detection in cattle.Genetics, selection, evolution : GSE · 2017Article
- Article
- Genotype imputation in the domestic dog.Mammalian genome : official journal of the International Mammalian Genome Society · 2016Article
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8 authors.
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No grant is acknowledged in the PubMed record.
Abstract
backgroundA cost-effective strategy to increase the density of available markers within a population is to sequence a small proportion of the population and impute whole-genome sequence data for the remaining population. Increased densities of typed markers are advantageous for genome-wide association studies (GWAS) and genomic predictions.
methodsWe obtained genotypes for 54 602 SNPs (single nucleotide polymorphisms) in 1077 Franches-Montagnes (FM) horses and Illumina paired-end whole-genome sequencing data for 30 FM horses and 14 Warmblood horses. After variant calling, the sequence-derived SNP genotypes (~13 million SNPs) were used for genotype imputation with the software programs Beagle, Impute2 and FImpute.
resultsThe mean imputation accuracy of FM horses using Impute2 was 92.0%. Imputation accuracy using Beagle and FImpute was 74.3% and 77.2%, respectively. In addition, for Impute2 we determined the imputation accuracy of all individual horses in the validation population, which ranged from 85.7% to 99.8%. The subsequent inclusion of Warmblood sequence data further increased the correlation between true and imputed genotypes for most horses, especially for horses with a high level of admixture. The final imputation accuracy of the horses ranged from 91.2% to 99.5%.
conclusionsUsing Impute2, the imputation accuracy was higher than 91% for all horses in the validation population, which indicates that direct imputation of 50k SNP-chip data to sequence level genotypes is feasible in the FM population. The individual imputation accuracy depended mainly on the applied software and the level of admixture.
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