ArticlePloS one2014
Improving the accuracy of whole genome prediction for complex traits using the results of genome wide association studies.
Article in PloS one, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 133 papers, 1 of them a synthesis that pooled it.
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Who cites it
133 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Optimizing Genomic-Enabled Prediction in Small-Scale Maize Hybrid Breeding Programs: A Roadmap Review.Frontiers in plant science · 2021Pooled it
- Functional genomic dissection and prediction of body size traits in pigs.Genetics, selection, evolution : GSE · 2026Article
- Improving genomic prediction accuracy of complex traits by integrating massive types of functional annotation information.Nature communications · 2026Article
- Leveraging weighted embedding and Transformer architecture to improve phenotype prediction of complex traits for crops.Nature communications · 2026Article
- GWKBR: a novel method integrating machine learning and Bayesian inference framework to improve genomic prediction accuracy.Briefings in bioinformatics · 2026Article
- Comparing wMAS, GWAS, and genomic prediction for selecting powdery mildew-resistant spring barley genotypes.BMC genomics · 2025Article
- Comparative evaluation of SNP-weighted, Bayesian, and machine learning models for genomic prediction in Holstein cattle.BMC genomics · 2025Article
- Genome Selection for Fleece Traits in Inner Mongolia Cashmere Goats Based on GWAS Prior Marker Information.Animals : an open access journal from MDPI · 2025Article
- Genomic predictions for growth and feed efficiency traits in a duck breeding population.BMC genomics · 2025Article
- Improving genomic prediction in pigs by integrating multi-population data and prior knowledge.BMC genomics · 2025Article
- Genomic Prediction of Adaptation in Common Bean (International journal of molecular sciences · 2025Article
- Genome Selection and Genome-Wide Association Analyses for Litter Size Traits in Large White Pigs.Animals : an open access journal from MDPI · 2025Article
- Genomic selection: Essence, applications, and prospects.The plant genome · 2025Review
- Impact of Selection Signature on Genomic Prediction and Heritability Estimation in Livestock.Animals : an open access journal from MDPI · 2025Article
- Enhancing Genomic Prediction Accuracy with a Single-Step Genomic Best Linear Unbiased Prediction Model Integrating Genome-Wide Association Study Results.Animals : an open access journal from MDPI · 2025Article
- ExAutoGP: Enhancing Genomic Prediction Stability and Interpretability with Automated Machine Learning and SHAP.Animals : an open access journal from MDPI · 2025Article
- Genetic Associations ofAnimals : an open access journal from MDPI · 2025Article
- Metabolic marker-assisted genomic prediction improves hybrid breeding.Plant communications · 2025Article
- Article
- Mutual information-based best linear unbiased prediction for enhanced genomic prediction accuracy.Journal of animal science · 2025Article
73 more citing papers are in PubMed but not listed here.
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8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Utilizing the whole genomic variation of complex traits to predict the yet-to-be observed phenotypes or unobserved genetic values via whole genome prediction (WGP) and to infer the underlying genetic architecture via genome wide association study (GWAS) is an interesting and fast developing area in the context of human disease studies as well as in animal and plant breeding. Though thousands of significant loci for several species were detected via GWAS in the past decade, they were not used directly to improve WGP due to lack of proper models. Here, we propose a generalized way of building trait-specific genomic relationship matrices which can exploit GWAS results in WGP via a best linear unbiased prediction (BLUP) model for which we suggest the name BLUP|GA. Results from two illustrative examples show that using already existing GWAS results from public databases in BLUP|GA improved the accuracy of WGP for two out of the three model traits in a dairy cattle data set, and for nine out of the 11 traits in a rice diversity data set, compared to the reference methods GBLUP and BayesB. While BLUP|GA outperforms BayesB, its required computing time is comparable to GBLUP. Further simulation results suggest that accounting for publicly available GWAS results is potentially more useful for WGP utilizing smaller data sets and/or traits of low heritability, depending on the genetic architecture of the trait under consideration. To our knowledge, this is the first study incorporating public GWAS results formally into the standard GBLUP model and we think that the BLUP|GA approach deserves further investigations in animal breeding, plant breeding as well as human genetics.
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