ArticleG3 (Bethesda, Md.)2016
Implementation of the Realized Genomic Relationship Matrix to Open-Pollinated White Spruce Family Testing for Disentangling Additive from Nonadditive Genetic Effects.
Article in G3 (Bethesda, Md.), 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 44 papers.
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44 citing papers in PubMed, 87 citations in OpenAlex.
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- Low-input breeding potential in stone pine, a multipurpose forest tree with low genome diversity.G3 (Bethesda, Md.) · 2025Article
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- Integrating environmental gradients into breeding: application of genomic reactions norms in a perennial species.Heredity · 2024Article
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- Genomic dissection of additive and non-additive genetic effects and genomic prediction in an open-pollinated family test of Japanese larch.BMC genomics · 2024Article
- Genomic evaluation for breeding and genetic management in Cordia africana, a multipurpose tropical tree species.BMC genomics · 2024Article
- Comparison of ddRADseq and EUChip60K SNP genotyping systems for population genetics and genomic selection inFrontiers in genetics · 2024Article
- Impact of inclusion non-additive effects on genome-wide association and variance's components in Scottish black sheep.Animal biotechnology · 2023Article
- Genomic studies of the additive and dominant genetic control on production traits of Euterpe edulis fruits.Scientific reports · 2023Article
- Preselection of QTL markers enhances accuracy of genomic selection in Norway spruce.BMC genomics · 2023Article
- Realized genomic selection across generations in a reciprocal recurrent selection breeding program ofFrontiers in plant science · 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
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- Genomic selection reveals hidden relatedness and increased breeding efficiency in western redcedar polycross breeding.Evolutionary applications · 2022Article
- Improving lodgepole pine genomic evaluation using spatial correlation structure and SNP selection with single-step GBLUP.Heredity · 2022Article
Corrections and comments
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Authors and funding
6 authors at 4 institutions in 4 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The open-pollinated (OP) family testing combines the simplest known progeny evaluation and quantitative genetics analyses as candidates' offspring are assumed to represent independent half-sib families. The accuracy of genetic parameter estimates is often questioned as the assumption of "half-sibling" in OP families may often be violated. We compared the pedigree- vs. marker-based genetic models by analysing 22-yr height and 30-yr wood density for 214 white spruce [Picea glauca (Moench) Voss] OP families represented by 1694 individuals growing on one site in Quebec, Canada. Assuming half-sibling, the pedigree-based model was limited to estimating the additive genetic variances which, in turn, were grossly overestimated as they were confounded by very minor dominance and major additive-by-additive epistatic genetic variances. In contrast, the implemented genomic pairwise realized relationship models allowed the disentanglement of additive from all nonadditive factors through genetic variance decomposition. The marker-based models produced more realistic narrow-sense heritability estimates and, for the first time, allowed estimating the dominance and epistatic genetic variances from OP testing. In addition, the genomic models showed better prediction accuracies compared to pedigree models and were able to predict individual breeding values for new individuals from untested families, which was not possible using the pedigree-based model. Clearly, the use of marker-based relationship approach is effective in estimating the quantitative genetic parameters of complex traits even under simple and shallow pedigree structure.
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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.