ArticleG3 (Bethesda, Md.)2017
Benefits of Dominance over Additive Models for the Estimation of Average Effects in the Presence of Dominance.
Article in G3 (Bethesda, Md.), 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.
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Who cites it
19 citing papers in PubMed.
- Genomic prediction of feed efficiency in boars by deep learning.G3 (Bethesda, Md.) · 2026Article
- Evaluating effect of different dominance genotype encodings on genome-wide association studies and genomic selection.Animal bioscience · 2025Article
- HLA loci heterozygosity modulates genetic risk in idiopathic inflammatory myopathies.Annals of the rheumatic diseases · 2025Article
- Improvement in genetic evaluation of quantitative traits in sheep by enriching genetic model with dominance effects.Scientific reports · 2025Article
- Identifying candidate genetic variants for egg number by analyzing over 1,000 fully sequenced layers.GigaScience · 2025Article
- Pharmacogenetic and clinical risk factors for bevacizumab-related gastrointestinal hemorrhage in prostate cancer patients treated on CALGB 90401 (Alliance).The pharmacogenomics journal · 2024Article
- polyGBLUP: a modified genomic best linear unbiased prediction improved the genomic prediction efficiency for autopolyploid species.Briefings in bioinformatics · 2024Article
- Improving hybrid rice breeding programs via stochastic simulations: number of parents, number of hybrids, tester update, and genomic prediction of hybrid performance.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2023Article
- Genomic studies of the additive and dominant genetic control on production traits of Euterpe edulis fruits.Scientific reports · 2023Article
- Prediction of additive, epistatic, and dominance effects using models accounting for incomplete inbreeding in parental lines of hybrid rye and sugar beet.Frontiers in plant science · 2023Article
- Review: optimizing genomic selection for crossbred performance by model improvement and data collection.Journal of animal science · 2021Review
- Optimum mating designs for exploiting dominance in genomic selection schemes for aquaculture species.Genetics, selection, evolution : GSE · 2021Article
- Heterosis and Hybrid Crop Breeding: A Multidisciplinary Review.Frontiers in genetics · 2021Review
- Impact of inclusion rates of crossbred phenotypes and genotypes in nucleus selection programs.Journal of animal science · 2020Article
- Joint modeling of eQTLs and parent-of-origin effects using an orthogonal framework with RNA-seq data.Human genetics · 2020Article
- Estimation of additive and non-additive genetic variance component for growth traits in Adani goats.Tropical animal health and production · 2020Article
- Estimating dominance genetic variances for growth traits in American Angus males using genomic models.Journal of animal science · 2020Article
- Interdigital Hyperplasia in Holstein Cattle Is Associated With a Missense Mutation in the Signal Peptide Region of the Tyrosine-Protein Kinase Transmembrane Receptor Gene.Frontiers in genetics · 2019Article
- Non-additive Effects in Genomic Selection.Frontiers in genetics · 2018Review
Corrections and comments
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
In quantitative genetics, the average effect at a single locus can be estimated by an additive (A) model, or an additive plus dominance (AD) model. In the presence of dominance, the AD-model is expected to be more accurate, because the A-model falsely assumes that residuals are independent and identically distributed. Our objective was to investigate the accuracy of an estimated average effect ([Formula: see text]) in the presence of dominance, using either a single locus A-model or AD-model. Estimation was based on a finite sample from a large population in Hardy-Weinberg equilibrium (HWE), and the root mean squared error of [Formula: see text] was calculated for several broad-sense heritabilities, sample sizes, and sizes of the dominance effect. Results show that with the A-model, both sampling deviations of genotype frequencies from HWE frequencies and sampling deviations of allele frequencies contributed to the error. With the AD-model, only sampling deviations of allele frequencies contributed to the error, provided that all three genotype classes were sampled. In the presence of dominance, the root mean squared error of [Formula: see text] with the AD-model was always smaller than with the A-model, even when the heritability was less than one. Remarkably, in the absence of dominance, there was no disadvantage of fitting dominance. In conclusion, the AD-model yields more accurate estimates of average effects from a finite sample, because it is more robust against sampling deviations from HWE frequencies than the A-model. Genetic models that include dominance, therefore, yield higher accuracies of estimated average effects than purely additive models when dominance is present.
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