ArticleBMC proceedings2012
Genomic breeding value prediction and QTL mapping of QTLMAS2011 data using Bayesian and GBLUP methods.
Article in BMC proceedings, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
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14 citing papers in PubMed.
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- Comparison of genome-wide association and genomic prediction methods for milk production traits in Korean Holstein cattle.Asian-Australasian journal of animal sciences · 2019Article
- Detection and validation of genomic regions associated with resistance to rust diseases in a worldwide hexaploid wheat landrace collection using BayesR and mixed linear model approaches.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2017Article
- Genome-wide association between single nucleotide polymorphisms with beef fatty acid profile in Nellore cattle using the single step procedure.BMC genomics · 2016Article
- Mixture models detect large effect QTL better than GBLUP and result in more accurate and persistent predictions.Journal of animal science and biotechnology · 2016Article
- Upweighting rare favourable alleles increases long-term genetic gain in genomic selection programs.Genetics, selection, evolution : GSE · 2015Article
- Prediction of genetic contributions to complex traits using whole genome sequencing data.BMC proceedings · 2014Article
- Genome-wide association mapping including phenotypes from relatives without genotypes in a single-step (ssGWAS) for 6-week body weight in broiler chickens.Frontiers in genetics · 2014Article
- Mixed model methods for genomic prediction and variance component estimation of additive and dominance effects using SNP markers.PloS one · 2014Article
- Comparison of the analyses of the XVth QTLMAS common dataset II: QTL analysis.BMC proceedings · 2012Article
- Comparison of analyses of the XVth QTLMAS common dataset III: Genomic Estimations of Breeding Values.BMC proceedings · 2012Article
- A two step Bayesian approach for genomic prediction of breeding values.BMC proceedings · 2012Article
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7 authors.
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Abstract
backgroundThe goal of this study was to apply Bayesian and GBLUP methods to predict genomic breeding values (GEBV), map QTL positions and explore the genetic architecture of the trait simulated for the 15th QTL-MAS workshop.
methodsThree methods with models considering dominance and epistasis inheritances were used to fit the data: (i) BayesB with a proportion π = 0.995 of SNPs assumed to have no effect, (ii) BayesCπ, where π is considered as unknown, and (iii) GBLUP, which directly fits animal genetic effects using a genomic relationship matrix.
resultsBayesB, BayesCπ and GBLUP with various fitted models detected 6, 5, and 4 out of 8 simulated QTL, respectively. All five additive QTL were detected by Bayesian methods. When two QTL were in either coupling or repulsion phase, GBLUP only detected one of them and missed the other. In addition, GBLUP yielded more false positives. One imprinted QTL was detected by BayesB and GBLUP despite that only additive gene action was assumed. This QTL was missed by BayesCπ. None of the methods found two simulated additive-by-additive epistatic QTL. Variance components estimation correctly detected no evidence for dominance gene-action. Bayesian methods predicted additive genetic merit more accurately than GBLUP, and similar accuracies were observed between BayesB and BayesCπ.
conclusionsBayesian methods and GBLUP mapped QTL to similar chromosome regions but Bayesian methods gave fewer false positives. Bayesian methods can be superior to GBLUP in GEBV prediction when genomic architecture is unknown.
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