ArticleGenetica2011
Marker-assisted prediction of non-additive genetic values.
Article in Genetica, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
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Who cites it
15 citing papers in PubMed.
- Genomic prediction for agronomic traits in a diverse Flax (Linum usitatissimum L.) germplasm collection.Scientific reports · 2024Article
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- Prediction of the importance of auxiliary traits using computational intelligence and machine learning: A simulation study.PloS one · 2021Article
- Genome-wide prediction for complex traits under the presence of dominance effects in simulated populations using GBLUP and machine learning methods.Journal of animal science · 2020Article
- A Multiple-Trait Bayesian Lasso for Genome-Enabled Analysis and Prediction of Complex Traits.Genetics · 2020Article
- Persistency of Prediction Accuracy and Genetic Gain in Synthetic Populations Under Recurrent Genomic Selection.G3 (Bethesda, Md.) · 2017Article
- Genomic prediction with epistasis models: on the marker-coding-dependent performance of the extended GBLUP and properties of the categorical epistasis model (CE).BMC bioinformatics · 2017Article
- Cross-Validation Without Doing Cross-Validation in Genome-Enabled Prediction.G3 (Bethesda, Md.) · 2016Article
- Accounting for genetic architecture improves sequence based genomic prediction for a Drosophila fitness trait.PloS one · 2015Article
- Genome-enabled prediction of quantitative traits in chickens using genomic annotation.BMC genomics · 2014Article
- Kernel-based variance component estimation and whole-genome prediction of pre-corrected phenotypes and progeny tests for dairy cow health traits.Frontiers in genetics · 2014Article
- Enhancing genome-enabled prediction by bagging genomic BLUP.PloS one · 2014Article
- Epistasis and quantitative traits: using model organisms to study gene-gene interactions.Nature reviews. Genetics · 2014Review
- Effect of regulatory architecture on broad versus narrow sense heritability.PLoS computational biology · 2013Article
- Genome-enabled prediction of genetic values using radial basis function neural networks.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2012Article
Corrections and comments
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
It has become increasingly clear from systems biology arguments that interaction and non-linearity play an important role in genetic regulation of phenotypic variation for complex traits. Marker-assisted prediction of genetic values assuming additive gene action has been widely investigated because of its relevance in artificial selection. On the other hand, it has been less well-studied when non-additive effects hold. Here, we explored a nonparametric model, radial basis function (RBF) regression, for predicting quantitative traits under different gene action modes (additivity, dominance and epistasis). Using simulation, it was found that RBF had better ability (higher predictive correlations and lower predictive mean square errors) of predicting merit of individuals in future generations in the presence of non-additive effects than a linear additive model, the Bayesian Lasso. This was true for populations undergoing either directional or random selection over several generations. Under additive gene action, RBF was slightly worse than the Bayesian Lasso. While prediction of genetic values under additive gene action is well handled by a variety of parametric models, nonparametric RBF regression is a useful counterpart for dealing with situations where non-additive gene action is suspected, and it is robust irrespective of mode of gene action.
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Registered trials
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.