ArticleGenetics, selection, evolution : GSE2014
Imputation of non-genotyped individuals based on genotyped relatives: assessing the imputation accuracy of a real case scenario in dairy cattle.
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 8 papers.
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Who cites it
8 citing papers in PubMed.
- Inclusion of imputed genotypes from non-genotyped dairy cattle in a Thai multibreed genomic-polygenic evaluation.Animal bioscience · 2025Article
- Evaluation of low-density SNP panels and imputation for cost-effective genomic selection in four aquaculture species.Frontiers in genetics · 2023Article
- Imputation of non-genotyped F1 dams to improve genetic gain in swine crossbreeding programs.Journal of animal science · 2022Article
- Assessing accuracy of genotype imputation in the Afrikaner and Brahman cattle breeds of South Africa.Tropical animal health and production · 2022Article
- Identification of genomic regions affecting production traits in pigs divergently selected for feed efficiency.Genetics, selection, evolution : GSE · 2021Article
- Genotype Imputation to Improve the Cost-Efficiency of Genomic Selection in Rabbits.Animals : an open access journal from MDPI · 2021Article
- Accuracy of genotype imputation in Labrador Retrievers.Animal genetics · 2018Article
- Accuracy of genome-wide imputation in Braford and Hereford beef cattle.BMC genetics · 2014Article
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4 authors.
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Abstract
backgroundImputation of genotypes for ungenotyped individuals could enable the use of valuable phenotypes created before the genomic era in analyses that require genotypes. The objective of this study was to investigate the accuracy of imputation of non-genotyped individuals using genotype information from relatives.
methodsGenotypes were simulated for all individuals in the pedigree of a real (historical) dataset of phenotyped dairy cows and with part of the pedigree genotyped. The software AlphaImpute was used for imputation in its standard settings but also without phasing, i.e. using basic inheritance rules and segregation analysis only. Different scenarios were evaluated i.e.: (1) the real data scenario, (2) addition of genotypes of sires and maternal grandsires of the ungenotyped individuals, and (3) addition of one, two, or four genotyped offspring of the ungenotyped individuals to the reference population.
resultsThe imputation accuracy using AlphaImpute in its standard settings was lower than without phasing. Including genotypes of sires and maternal grandsires in the reference population improved imputation accuracy, i.e. the correlation of the true genotypes with the imputed genotype dosages, corrected for mean gene content, across all animals increased from 0.47 (real situation) to 0.60. Including one, two and four genotyped offspring increased the accuracy of imputation across all animals from 0.57 (no offspring) to 0.73, 0.82, and 0.92, respectively.
conclusionsAt present, the use of basic inheritance rules and segregation analysis appears to be the best imputation method for ungenotyped individuals. Comparison of our empirical animal-specific imputation accuracies to predictions based on selection index theory suggested that not correcting for mean gene content considerably overestimates the true accuracy. Imputation of ungenotyped individuals can help to include valuable phenotypes for genome-wide association studies or for genomic prediction, especially when the ungenotyped individuals have genotyped offspring.
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