ArticleHeredity2016
The contribution of dominance to phenotype prediction in a pine breeding and simulated population.
Article in Heredity, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 38 papers.
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Who cites it
38 citing papers in PubMed.
- Genetic insights into bacterial wilt resistance using genomic prediction and association mapping in blueberry.The plant genome · 2026Article
- 2NPLGBM: a genomic model that merges the strengths of classical and machine learning methods in genomic prediction.Plant methods · 2026Article
- Predicting maize hybrid performance with machine learning and a locus-specific weighted degree of dominance transformation.Frontiers in plant science · 2026Article
- Quantifying genetic and genotypic gain gaps in Eucalyptus: the hidden cost of ignoring inbreeding and dominance.Heredity · 2025Article
- Evaluation of crossbreeding strategies for improved adaptation and productivity in African smallholder cattle farms.Genetics, selection, evolution : GSE · 2025Article
- Genomic Predicted cross performance: a tool for optimizing parental combinations in breeding programs.Database : the journal of biological databases and curation · 2025Article
- Genomic studies of the additive and dominant genetic control on production traits of Euterpe edulis fruits.Scientific reports · 2023Article
- Genomic selection for genotype performance and environmental stability in Coffea canephora.G3 (Bethesda, Md.) · 2023Article
- Increasing genomic prediction accuracy for unphenotyped full-sib families by modeling additive and dominance effects with large datasets in white spruce.Frontiers in plant science · 2023Article
- Genome-Wide SNP Markers Accelerate Perennial Forest Tree Breeding Rate for Disease Resistance through Marker-Assisted and Genome-Wide Selection.International journal of molecular sciences · 2022Review
- Genomic selection reveals hidden relatedness and increased breeding efficiency in western redcedar polycross breeding.Evolutionary applications · 2022Article
- Article
- Increasing cassava root yield: Additive-dominant genetic models for selection of parents and clones.Frontiers in plant science · 2022Article
- Article
- Genomic Prediction of Complex Traits in an Allogamous Annual Crop: The Case of Maize Single-Cross Hybrids.Methods in molecular biology (Clifton, N.J.) · 2022Article
- Genomic prediction in family bulks using different traits and cross-validations in pine.G3 (Bethesda, Md.) · 2021Article
- Nonlinear kernels, dominance, and envirotyping data increase the accuracy of genome-based prediction in multi-environment trials.Heredity · 2021Article
- Near-infrared spectroscopy outperforms genomics for predicting sugarcane feedstock quality traits.PloS one · 2021Article
- Genomic Predictions With Nonadditive Effects Improved Estimates of Additive Effects and Predictions of Total Genetic Values inFrontiers in plant science · 2021Article
- Genomic selection for resistance to spruce budworm in white spruce and relationships with growth and wood quality traits.Evolutionary applications · 2020Article
Corrections and comments
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Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Pedigrees and dense marker panels have been used to predict the genetic merit of individuals in plant and animal breeding, accounting primarily for the contribution of additive effects. However, nonadditive effects may also affect trait variation in many breeding systems, particularly when specific combining ability is explored. Here we used models with different priors, and including additive-only and additive plus dominance effects, to predict polygenic (height) and oligogenic (fusiform rust resistance) traits in a structured breeding population of loblolly pine (Pinus taeda L.). Models were largely similar in predictive ability, and the inclusion of dominance only improved modestly the predictions for tree height. Next, we simulated a genetically similar population to assess the ability of predicting polygenic and oligogenic traits controlled by different levels of dominance. The simulation showed an overall decrease in the accuracy of total genomic predictions as dominance increases, regardless of the method used for prediction. Thus, dominance effects may not be accounted for as effectively in prediction models compared with traits controlled by additive alleles only. When the ratio of dominance to total phenotypic variance reached 0.2, the additive-dominance prediction models were significantly better than the additive-only models. However, in the prediction of the subsequent progeny population, this accuracy increase was only observed for the oligogenic trait.
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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.