ArticleBMC genetics2015
Validation of markers with non-additive effects on milk yield and fertility in Holstein and Jersey cows.
Article in BMC genetics, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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Who cites it
12 citing papers in PubMed.
- Integrative analysis of GWAS, Bayesian fine-mapping, Mendelian randomization and colocalization reveals genetic determinants underlying milk-related traits in dairy cattle.Genetics, selection, evolution : GSE · 2026Article
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- Genome-wide association and genomic prediction for a reproductive index summarizing fertility outcomes in U.S. Holsteins.G3 (Bethesda, Md.) · 2023Article
- Investigating the Effect of Imputed Structural Variants from Whole-Genome Sequence on Genome-Wide Association and Genomic Prediction in Dairy Cattle.Animals : an open access journal from MDPI · 2021Article
- Genomic Loci Affecting Milk Production in German Black Pied Cattle (DSN).Frontiers in genetics · 2021Article
- GWAS-Based Identification of New Loci for Milk Yield, Fat, and Protein in Holstein Cattle.Animals : an open access journal from MDPI · 2020Article
- Predicting Growth Traits with Genomic Selection Methods in Zhikong Scallop (Chlamys farreri).Marine biotechnology (New York, N.Y.) · 2018Article
- Technical note: an R package for fitting sparse neural networks with application in animal breeding.Journal of animal science · 2018Article
- Benefits of Dominance over Additive Models for the Estimation of Average Effects in the Presence of Dominance.G3 (Bethesda, Md.) · 2017Article
- Genome-wide association analysis of milk yield traits in Nordic Red Cattle using imputed whole genome sequence variants.BMC genetics · 2016Article
- The genetic regulatory network centered on Pto-Wuschela and its targets involved in wood formation revealed by association studies.Scientific reports · 2015Article
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5 authors.
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Abstract
backgroundIt has been suggested that traits with low heritability, such as fertility, may have proportionately more genetic variation arising from non-additive effects than traits with higher heritability, such as milk yield. Here, we performed a large genome scan with 408,255 single nucleotide polymorphism (SNP) markers to identify chromosomal regions associated with additive, dominance and epistatic (pairwise additive × additive) variability in milk yield and a measure of fertility, calving interval, using records from a population of 7,055 Holstein cows. The results were subsequently validated in an independent set of 3,795 Jerseys.
resultsWe identified genomic regions with validated additive effects on milk yield on Bos taurus autosomes (BTA) 5, 14 and 20, whereas SNPs with suggestive additive effects on fertility were observed on BTA 5, 9, 11, 18, 22, 27, 29 and the X chromosome. We also confirmed genome regions with suggestive dominance effects for milk yield (BTA 2, 3, 5, 26 and 27) and for fertility (BTA 1, 2, 3, 7, 23, 25 and 28). A number of significant epistatic effects for milk yield on BTA 14 were found across breeds. However on close inspection, these were likely to be associated with the mutation in the diacylglycerol O-acyltransferase 1 (DGAT1) gene, given that the associations were no longer significant when the additive effect of the DGAT1 mutation was included in the epistatic model.
conclusionsIn general, we observed a low statistical power (high false discovery rates and small number of significant SNPs) for non-additive genetic effects compared with additive effects for both traits which could be an artefact of higher dependence on linkage disequilibrium between markers and causative mutations or smaller size of non-additive effects relative to additive effects. The results of our study suggest that individual non-additive effects make a small contribution to the genetic variation of milk yield and fertility. Although we found no individual mutation with large dominance effect for both traits under investigation, a contribution to genetic variance is still possible from a large number of small dominance effects, so methods that simultaneously incorporate genotypes across all loci are suggested to test the variance explained by dominance gene actions.
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