ArticlePloS one2014
Improvement of prediction ability for genomic selection of dairy cattle by including dominance effects.
Article in PloS one, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 46 papers.
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Who cites it
46 citing papers in PubMed.
- Consequences of ignoring dominance genetic effects from genomic selection model for discrete threshold traits.Scientific reports · 2025Article
- Genomic Analysis of Reproductive Trait Divergence in Duroc and Yorkshire Pigs: A Comparison of Mixed Models and Selective Sweep Detection.Veterinary sciences · 2025Article
- Genomic Prediction of Semen Traits in Boars Incorporating Biological Interactions.International journal of molecular sciences · 2024Article
- Exploring genomic inbreeding and selection signatures in a commercial Brangus herd through functional annotation.Journal of applied genetics · 2024Article
- MAGE: metafounders-assisted genomic estimation of breeding value, a novel additive-dominance single-step model in crossbreeding systems.Bioinformatics (Oxford, England) · 2024Article
- Investigating the impact of non-additive genetic effects in the estimation of variance components and genomic predictions for heat tolerance and performance traits in crossbred and purebred pig populations.BMC genomic data · 2023Article
- Genomic studies of the additive and dominant genetic control on production traits of Euterpe edulis fruits.Scientific reports · 2023Article
- Increasing genomic prediction accuracy for unphenotyped full-sib families by modeling additive and dominance effects with large datasets in white spruce.Frontiers in plant science · 2023Article
- Non-additive QTL mapping of lactation traits in 124,000 cattle reveals novel recessive loci.Genetics, selection, evolution : GSE · 2022Article
- How to achieve a higher selection plateau in forest tree breeding? Fostering heterozygote × homozygote relationships in optimal contribution selection in the case study ofEvolutionary applications · 2021Article
- Evaluation of Bayesian alphabet and GBLUP based on different marker density for genomic prediction in Alpine Merino sheep.G3 (Bethesda, Md.) · 2021Article
- An assessment of genomic connectedness measures in Nellore cattle.Journal of animal science · 2020Article
- Inbreeding depression across the genome of Dutch Holstein Friesian dairy cattle.Genetics, selection, evolution : GSE · 2020Article
- Long-term exposure to particulate air pollution and brachial artery flow-mediated dilation in the Old Order Amish.Environmental health : a global access science source · 2020Article
- Estimation of additive and non-additive genetic variance component for growth traits in Adani goats.Tropical animal health and production · 2020Article
- De novo mutations across 1,465 diverse genomes reveal mutational insights and reductions in the Amish founder population.Proceedings of the National Academy of Sciences of the United States of America · 2020Article
- Genomic Prediction of Additive and Dominant Effects on Wool and Blood Traits in Alpine Merino Sheep.Frontiers in veterinary science · 2020Article
- Genomic Prediction and Association Analysis with Models Including Dominance Effects for Important Traits in Chinese Simmental Beef Cattle.Animals : an open access journal from MDPI · 2019Article
- A targeted genotyping approach to enhance the identification of variants for lactation persistency in dairy cows.Journal of animal science · 2019Article
- Allele substitution and dominance effects of CD166/ALCAM gene polymorphisms for endoparasite resistance and test-day traits in a small cattle population using logistic regression analyses.Mammalian genome : official journal of the International Mammalian Genome Society · 2019Article
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4 authors.
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Abstract
Dominance may be an important source of non-additive genetic variance for many traits of dairy cattle. However, nearly all prediction models for dairy cattle have included only additive effects because of the limited number of cows with both genotypes and phenotypes. The role of dominance in the Holstein and Jersey breeds was investigated for eight traits: milk, fat, and protein yields; productive life; daughter pregnancy rate; somatic cell score; fat percent and protein percent. Additive and dominance variance components were estimated and then used to estimate additive and dominance effects of single nucleotide polymorphisms (SNPs). The predictive abilities of three models with both additive and dominance effects and a model with additive effects only were assessed using ten-fold cross-validation. One procedure estimated dominance values, and another estimated dominance deviations; calculation of the dominance relationship matrix was different for the two methods. The third approach enlarged the dataset by including cows with genotype probabilities derived using genotyped ancestors. For yield traits, dominance variance accounted for 5 and 7% of total variance for Holsteins and Jerseys, respectively; using dominance deviations resulted in smaller dominance and larger additive variance estimates. For non-yield traits, dominance variances were very small for both breeds. For yield traits, including additive and dominance effects fit the data better than including only additive effects; average correlations between estimated genetic effects and phenotypes showed that prediction accuracy increased when both effects rather than just additive effects were included. No corresponding gains in prediction ability were found for non-yield traits. Including cows with derived genotype probabilities from genotyped ancestors did not improve prediction accuracy. The largest additive effects were located on chromosome 14 near DGAT1 for yield traits for both breeds; those SNPs also showed the largest dominance effects for fat yield (both breeds) as well as for Holstein milk yield.
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