ArticleGenetics, selection, evolution : GSE2016
Sequence variants selected from a multi-breed GWAS can improve the reliability of genomic predictions in dairy cattle.
Article in Genetics, selection, evolution : GSE, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 38 papers, 3 of them syntheses that pooled it.
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Who cites it
38 citing papers in PubMed, 3 syntheses or guidelines pooled it.
- GWAS and genomic prediction of milk urea nitrogen in Australian and New Zealand dairy cattle.Genetics, selection, evolution : GSE · 2022Pooled it
- Meta-analysis for milk fat and protein percentage using imputed sequence variant genotypes in 94,321 cattle from eight cattle breeds.Genetics, selection, evolution : GSE · 2020Pooled it
- Meta-analysis of sequence-based association studies across three cattle breeds reveals 25 QTL for fat and protein percentages in milk at nucleotide resolution.BMC genomics · 2017Pooled it
- Effects of the Temperature-Humidity Index on Milk Production Traits and Gene-Environment Interactions in Chinese Holstein Cows.Animals : an open access journal from MDPI · 2026Article
- Genomic Prediction Ability for Novel Profitability Traits Using Different Models in Nelore Cattle.Journal of animal breeding and genetics = Zeitschrift fur Tierzuchtung und Zuchtungsbiologie · 2026Article
- Genomic Selection for Economic Traits in Inner Mongolia Cashmere Goats by Integrating GWAS Prior Information.Veterinary sciences · 2025Article
- Incorporating information of causal variants in genomic prediction using GBLUP or machine learning models in a simulated livestock population.Journal of animal science and biotechnology · 2025Article
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- Improvement in genomic prediction of maize with prior gene ontology information depends on traits and environmental conditions.The plant genome · 2025Article
- Using expression data to fine map QTL associated with fertility in dairy cattle.Genetics, selection, evolution : GSE · 2024Article
- Article
- Using residual regressions to quantify and map signal leakage in genomic prediction.Genetics, selection, evolution : GSE · 2023Article
- Multi-line ssGBLUP evaluation using preselected markers from whole-genome sequence data in pigs.Frontiers in genetics · 2023Article
- Detection of potential functional variants based on systems-biology: the case of feed efficiency in beef cattle.BMC genomics · 2022Article
- Genomic prediction with whole-genome sequence data in intensely selected pig lines.Genetics, selection, evolution : GSE · 2022Article
- Sharing of either phenotypes or genetic variants can increase the accuracy of genomic prediction of feed efficiency.Genetics, selection, evolution : GSE · 2022Article
- Genetic variants associated with two major bovine milk fatty acids offer opportunities to breed for altered milk fat composition.Genetics, selection, evolution : GSE · 2022Article
- Using mid-infrared spectroscopy to increase GWAS power to detect QTL associated with blood urea nitrogen.Genetics, selection, evolution : GSE · 2022Article
- An evaluation of the predictive performance and mapping power of the BayesR model for genomic prediction.G3 (Bethesda, Md.) · 2021Article
- Dissection of the impact of prioritized QTL-linked and -unlinked SNP markers on the accuracy of genomic selectionBMC genomic data · 2021Article
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3 authors.
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No grant is acknowledged in the PubMed record.
Abstract
backgroundSequence data can potentially increase the reliability of genomic predictions, because such data include causative mutations instead of relying on linkage disequilibrium (LD) between causative mutations and prediction variants. However, the location of the causative mutations is not known, and the presence of many variants that are in low LD with the causative mutations may reduce prediction reliability. Our objective was to investigate whether the use of variants at quantitative trait loci (QTL) that are identified in a multi-breed genome-wide association study (GWAS) for milk, fat and protein yield would increase the reliability of within- and multi-breed genomic predictions in Holstein, Jersey and Danish Red cattle. A wide range of scenarios that test different strategies to select prediction markers, for both within-breed and multi-breed prediction, were compared.
resultsFor all breeds and traits, the use of variants selected from a multi-breed GWAS resulted in substantial increases in prediction reliabilities compared to within-breed prediction using a 50 K SNP array. Reliabilities depended highly on the choice of the prediction markers, and the scenario that led to the highest reliability varied between breeds and traits. While genomic correlations across breeds were low for genome-wide sequence variants, the effects of the QTL variants that yielded the highest reliabilities were highly correlated across breeds.
conclusionsOur results show that the use of sequence variants, which are located near peaks of QTL that are detected in a multi-breed GWAS, can increase reliability of genomic predictions.
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