ArticleGenetics2016
Genomic Prediction for Quantitative Traits Is Improved by Mapping Variants to Gene Ontology Categories in Drosophila melanogaster.
Article in Genetics, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 77 papers, 1 of them a synthesis that pooled it.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
77 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Genome-wide association studies and meta-analysis uncovers new candidate genes for growth and carcass traits in pigs.PloS one · 2018Pooled it
- Prioritization of deleterious mutations informs genomic prediction and increases the rate of gain in common bean (Phaseolus vulgaris L.), a simulation study.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2026Article
- Enhancing genomic prediction accuracy in Huaxi cattle through integration of transcriptomic data and a self-attention-based SNP selection strategy.BMC bioinformatics · 2026Article
- FSBLUP: a novel strategy of fusion similarity matrix construction via optimally integrating intermediate omics data to enhance genomic prediction.Genome biology · 2026Article
- 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
- Mammary gland multi-omics data reveals new genetic insights into milk production traits in dairy cattle.PLoS genetics · 2025Article
- Evaluation of genomic selection models using whole genome sequence data and functional annotation in Belgian Blue cattle.Genetics, selection, evolution : GSE · 2025Article
- Improvement in genomic prediction of maize with prior gene ontology information depends on traits and environmental conditions.The plant genome · 2025Article
- Integrating Significant SNPs Identified by GWAS for Genomic Prediction of the Number of Ribs and Carcass Length in Suhuai Pigs.Animals : an open access journal from MDPI · 2025Article
- Comparing statistical learning methods for complex trait prediction from gene expression.PloS one · 2025Article
- Genomic Prediction of Semen Traits in Boars Incorporating Biological Interactions.International journal of molecular sciences · 2024Article
- Wide-ranging genetic variation in sensitivity to rapamycin in Drosophila melanogaster.Aging cell · 2024Article
- GWAS Enhances Genomic Prediction Accuracy of Caviar Yield, Caviar Color and Body Weight Traits in Sturgeons Using Whole-Genome Sequencing Data.International journal of molecular sciences · 2024Article
- Genomic Selection for Weaning Weight in Alpine Merino Sheep Based on GWAS Prior Marker Information.Animals : an open access journal from MDPI · 2024Article
- Comparing statistical learning methods for complex trait prediction from gene expression.bioRxiv : the preprint server for biology · 2024Article
- Residual networks without pooling layers improve the accuracy of genomic predictions.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2024Article
- Genomic prediction based on preselected single-nucleotide polymorphisms from genome-wide association study and imputed whole-genome sequence data annotation for growth traits in Duroc pigs.Evolutionary applications · 2024Article
- Increased Accuracy of Genomic Prediction Using Preselected SNPs from GWAS with Imputed Whole-Genome Sequence Data in Pigs.Animals : an open access journal from MDPI · 2023Article
17 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
Abstract
Predicting individual quantitative trait phenotypes from high-resolution genomic polymorphism data is important for personalized medicine in humans, plant and animal breeding, and adaptive evolution. However, this is difficult for populations of unrelated individuals when the number of causal variants is low relative to the total number of polymorphisms and causal variants individually have small effects on the traits. We hypothesized that mapping molecular polymorphisms to genomic features such as genes and their gene ontology categories could increase the accuracy of genomic prediction models. We developed a genomic feature best linear unbiased prediction (GFBLUP) model that implements this strategy and applied it to three quantitative traits (startle response, starvation resistance, and chill coma recovery) in the unrelated, sequenced inbred lines of the Drosophila melanogaster Genetic Reference Panel. Our results indicate that subsetting markers based on genomic features increases the predictive ability relative to the standard genomic best linear unbiased prediction (GBLUP) model. Both models use all markers, but GFBLUP allows differential weighting of the individual genetic marker relationships, whereas GBLUP weighs the genetic marker relationships equally. Simulation studies show that it is possible to further increase the accuracy of genomic prediction for complex traits using this model, provided the genomic features are enriched for causal variants. Our GFBLUP model using prior information on genomic features enriched for causal variants can increase the accuracy of genomic predictions in populations of unrelated individuals and provides a formal statistical framework for leveraging and evaluating information across multiple experimental studies to provide novel insights into the genetic architecture of complex traits.
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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.