ArticleHeredity2017
Enhancing genomic prediction with genome-wide association studies in multiparental maize populations.
Article in Heredity, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 50 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
50 citing papers in PubMed.
- Multienvironment multilocus association mapping reveals genomic regions for drought-related traits in tropical maize.G3 (Bethesda, Md.) · 2026Article
- Genetic determinants of aerial root morphology in Sierra Mixe-derived maize.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2026Article
- Highly Polygenic Control of Photosynthetic Responses to Nighttime Temperature Studied by Genomic Prediction.Plant, cell & environment · 2026Article
- Uncovering the genetic architecture of biomass yield and related traits in Southern US oat germplasm using genome-wide association study.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2026Article
- Integrating GWAS-guided markers preselection with genomic selection enhances prediction of pulpwood-related traits in slash pine (Pinus elliottii Englem.).BMC plant biology · 2026Article
- Improving genomic prediction accuracy of complex traits by integrating massive types of functional annotation information.Nature communications · 2026Article
- Optimizing genomic predictions in maize using a diversity panel and a multiparental population.The plant genome · 2026Article
- Predicted protein 3D structures provide essential insights into the genetic architecture underlying phenotypic diversity in maize.Genome research · 2026Article
- Longitudinal genomic prediction of cacao disease resilience identifies robust witches' broom disease targets.Frontiers in plant science · 2026Article
- Genome-wide association study identifies quantitative trait loci associated with resistance to Verticillium dahliae race 3 in tomato.The plant genome · 2025Article
- Genomic Prediction of Adaptation in Common Bean (International journal of molecular sciences · 2025Article
- Multifactor Analysis of a Genome-Wide Selection System inPlants (Basel, Switzerland) · 2025Article
- Optimization of sparse phenotyping strategy in multi-environmental trials in maize.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2025Article
- The whole-genome dissection of root system architecture provides new insights for the genetic improvement of alfalfa (Horticulture research · 2025Article
- GA-GBLUP: leveraging the genetic algorithm to improve the predictability of genomic selection.Briefings in bioinformatics · 2024Article
- Genomic prediction for agronomic traits in a diverse Flax (Linum usitatissimum L.) germplasm collection.Scientific reports · 2024Article
- Evaluation of penalized and machine learning methods for asthma disease prediction in the Korean Genome and Epidemiology Study (KoGES).BMC bioinformatics · 2024Article
- Preselection of QTL markers enhances accuracy of genomic selection in Norway spruce.BMC genomics · 2023Article
- Genome-wide family prediction unveils molecular mechanisms underlying the regulation of agronomic traits inFrontiers in plant science · 2023Article
- Outlook for Implementation of Genomics-Based Selection in Public Cotton Breeding Programs.Plants (Basel, Switzerland) · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Genome-wide association mapping using dense marker sets has identified some nucleotide variants affecting complex traits that have been validated with fine-mapping and functional analysis. However, many sequence variants associated with complex traits in maize have small effects and low repeatability. In contrast to genome-wide association study (GWAS), genomic prediction (GP) is typically based on models incorporating information from all available markers, rather than modeling effects of individual loci. We considered methods to integrate results of GWASs into GP models in the context of multiple interconnected families. We compared association tests based on a biallelic additive model constraining the effect of a single-nucleotide polymorphism (SNP) to be equal across all families in which it segregates to a model in which the effect of a SNP can vary across families. Association SNPs were then included as fixed effects into a GP model that also included the random effects of the whole genome background. Simulation studies revealed that the effectiveness of this joint approach depends on the extent of polygenicity of the traits. Congruent with this finding, cross-validation studies indicated that GP including the fixed effects of the most significantly associated SNPs along with the polygenic background was more accurate than the polygenic background model alone for moderately complex but not highly polygenic traits measured in the maize nested association mapping population. Individual SNPs with strong and robust association signals can effectively improve GP. Our approach provides a new integrative modeling approach for both reliable gene discovery and robust GP.
Indexed as
Identifiers
What OpenQuestion holds
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.