ArticleBMC genomics2017
Dissection of additive, dominance, and imprinting effects for production and reproduction traits in Holstein cattle.
Article in BMC genomics, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 papers.
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Who cites it
28 citing papers in PubMed, 76 citations in OpenAlex.
- Benchmarking of feed-forward neural network models for genomic prediction of quantitative traits in pigs.Frontiers in genetics · 2025Article
- Genomic dissection of additive and non-additive genetic effects and genomic prediction in an open-pollinated family test of Japanese larch.BMC genomics · 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
- Simultaneous improvement of grain yield and grain protein concentration in durum wheat by using association tests and weighted GBLUP.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2023Article
- A Million-Cow Genome-Wide Association Study of Three Fertility Traits in U.S. Holstein Cows.International journal of molecular sciences · 2023Article
- Evaluation of Breeding Values and Variance Components of Birth and Weaning Weights in the Holstein Cows Herd Based on Genetic Information.Archives of Razi Institute · 2022Article
- Non-additive QTL mapping of lactation traits in 124,000 cattle reveals novel recessive loci.Genetics, selection, evolution : GSE · 2022Article
- Genomic Prediction Methods Accounting for Nonadditive Genetic Effects.Methods in molecular biology (Clifton, N.J.) · 2022Article
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- 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
- Improved genomic prediction of clonal performance in sugarcane by exploiting non-additive genetic effects.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2021Article
- Emerging issues in genomic selection.Journal of animal science · 2021Article
- Genomic Selection for Any Dairy Breeding Program via Optimized Investment in Phenotyping and Genotyping.Frontiers in genetics · 2021Article
- Inbreeding depression across the genome of Dutch Holstein Friesian dairy cattle.Genetics, selection, evolution : GSE · 2020Article
- Genome-wide identification of Diacylglycerol Acyltransferases (DGAT) family genes influencing Milk production in Buffalo.BMC genetics · 2020Article
- Favorable Conditions for Genomic Evaluation to Outperform Classical Pedigree Evaluation Highlighted by a Proof-of-Concept Study in Poplar.Frontiers in plant science · 2020Article
- Modification of Experimental Design and Statistical Method for Mapping Imprinted QTLs Based on Immortalized FFrontiers in genetics · 2020Article
- A Review of Genomic Models for the Analysis of Livestock Crossbred Data.Frontiers in genetics · 2020Review
- Article
Corrections and comments
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Authors and funding
6 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundAlthough genome-wide association and genomic selection studies have primarily focused on additive effects, dominance and imprinting effects play an important role in mammalian biology and development. The degree to which these non-additive genetic effects contribute to phenotypic variation and whether QTL acting in a non-additive manner can be detected in genetic association studies remain controversial.
resultsTo empirically answer these questions, we analyzed a large cattle dataset that consisted of 42,701 genotyped Holstein cows with genotyped parents and phenotypic records for eight production and reproduction traits. SNP genotypes were phased in pedigree to determine the parent-of-origin of alleles, and a three-component GREML was applied to obtain variance decomposition for additive, dominance, and imprinting effects. The results showed a significant non-zero contribution from dominance to production traits but not to reproduction traits. Imprinting effects significantly contributed to both production and reproduction traits. Interestingly, imprinting effects contributed more to reproduction traits than to production traits. Using GWAS and imputation-based fine-mapping analyses, we identified and validated a dominance association signal with milk yield near RUNX2, a candidate gene that has been associated with milk production in mice. When adding non-additive effects into the prediction models, however, we observed little or no increase in prediction accuracy for the eight traits analyzed.
conclusionsCollectively, our results suggested that non-additive effects contributed a non-negligible amount (more for reproduction traits) to the total genetic variance of complex traits in cattle, and detection of QTLs with non-additive effect is possible in GWAS using a large dataset.
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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.