ArticleGenetics, selection, evolution : GSE2015
Non-additive genetic variation in growth, carcass and fertility traits of beef cattle.
Article in Genetics, selection, evolution : GSE, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 39 papers.
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Who cites it
39 citing papers in PubMed, 91 citations in OpenAlex.
- Genomic analysis of the inbreeding load for body weight, carcass and reproductive traits in the Rubia Gallega beef cattle population.Genetics, selection, evolution : GSE · 2026Article
- Genomic prediction of feed efficiency in boars by deep learning.G3 (Bethesda, Md.) · 2026Article
- Genomic Analysis of Reproductive Trait Divergence in Duroc and Yorkshire Pigs: A Comparison of Mixed Models and Selective Sweep Detection.Veterinary sciences · 2025Article
- The rumen microbiome and its metabolome together with the host metabolome regulate the growth performance of crossbred cattle.BMC genomics · 2025Article
- Evaluation of crossbreeding strategies for improved adaptation and productivity in African smallholder cattle farms.Genetics, selection, evolution : GSE · 2025Article
- Identifying candidate genetic variants for egg number by analyzing over 1,000 fully sequenced layers.GigaScience · 2025Article
- Breed-specific heterosis for growth and carcass traits in 18 U.S. cattle breeds.Journal of animal science · 2025Article
- Pleomorphic adenoma gene1 in reproduction and implication for embryonic survival in cattle: a review.Journal of animal science · 2024Review
- 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
- Impact of inclusion non-additive effects on genome-wide association and variance's components in Scottish black sheep.Animal biotechnology · 2023Article
- Genomic Analysis of Heterosis in an Angus × Hereford Cattle Population.Animals : an open access journal from MDPI · 2023Article
- Genome-Wide Association Study Reveals Additive and Non-Additive Effects on Growth Traits in Duroc Pigs.Genes · 2022Article
- Article
- Association of pleomorphic adenoma gene 1 with body weight and measurement of Bali cattle (Veterinary world · 2022Article
- Heritability and genetic correlation estimates of semen production traits with litter traits and pork production traits in purebred Duroc pigs.Journal of animal science · 2022Article
- Non-additive QTL mapping of lactation traits in 124,000 cattle reveals novel recessive loci.Genetics, selection, evolution : GSE · 2022Article
- Genomic Selection for Milk Production Traits in Xinjiang Brown Cattle.Animals : an open access journal from MDPI · 2022Article
- A Random Forest-Based Genome-Wide Scan Reveals Fertility-Related Candidate Genes and Potential Inter-Chromosomal Epistatic Regions Associated With Age at First Calving in Nellore Cattle.Frontiers in genetics · 2022Article
- Genomic prediction with non-additive effects in beef cattle: stability of variance component and genetic effect estimates against population size.BMC genomics · 2021Article
- Non-additive association analysis using proxy phenotypes identifies novel cattle syndromes.Nature genetics · 2021Article
Corrections and comments
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Authors and funding
7 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundA better understanding of non-additive variance could lead to increased knowledge on the genetic control and physiology of quantitative traits, and to improved prediction of the genetic value and phenotype of individuals. Genome-wide panels of single nucleotide polymorphisms (SNPs) have been mainly used to map additive effects for quantitative traits, but they can also be used to investigate non-additive effects. We estimated dominance and epistatic effects of SNPs on various traits in beef cattle and the variance explained by dominance, and quantified the increase in accuracy of phenotype prediction by including dominance deviations in its estimation.
methodsGenotype data (729 068 real or imputed SNPs) and phenotypes on up to 16 traits of 10 191 individuals from Bos taurus, Bos indicus and composite breeds were used. A genome-wide association study was performed by fitting the additive and dominance effects of single SNPs. The dominance variance was estimated by fitting a dominance relationship matrix constructed from the 729 068 SNPs. The accuracy of predicted phenotypic values was evaluated by best linear unbiased prediction using the additive and dominance relationship matrices. Epistatic interactions (additive × additive) were tested between each of the 28 SNPs that are known to have additive effects on multiple traits, and each of the other remaining 729 067 SNPs.
resultsThe number of significant dominance effects was greater than expected by chance and most of them were in the direction that is presumed to increase fitness and in the opposite direction to inbreeding depression. Estimates of dominance variance explained by SNPs varied widely between traits, but had large standard errors. The median dominance variance across the 16 traits was equal to 5% of the phenotypic variance. Including a dominance deviation in the prediction did not significantly increase its accuracy for any of the phenotypes. The number of additive × additive epistatic effects that were statistically significant was greater than expected by chance.
conclusionsSignificant dominance and epistatic effects occur for growth, carcass and fertility traits in beef cattle but they are difficult to estimate precisely and including them in phenotype prediction does not increase its accuracy.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.