ArticleHeredity2019
Efficiency of genomic prediction across two Eucalyptus nitens seed orchards with different selection histories.
Article in Heredity, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 20 papers.
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Who cites it
20 citing papers in PubMed.
- Multivariate models improve accuracy of genomic prediction for spring frost tolerance in Norway spruce.The plant genome · 2025Article
- Increased genomic predictive ability in mango using GWAS-preselected variants and fixed-effect SNPs.Frontiers in plant science · 2025Article
- Comparison of ddRADseq and EUChip60K SNP genotyping systems for population genetics and genomic selection inFrontiers in genetics · 2024Article
- Metadata analysis indicates biased estimation of genetic parameters and gains using conventional pedigree information instead of genomic-based approaches in tree breeding.Scientific reports · 2022Article
- Genomic Prediction of Complex Traits in Perennial Plants: A Case for Forest Trees.Methods in molecular biology (Clifton, N.J.) · 2022Article
- Achievements and Challenges of Genomics-Assisted Breeding in Forest Trees: From Marker-Assisted Selection to Genome Editing.International journal of molecular sciences · 2021Review
- Genomic Predictions With Nonadditive Effects Improved Estimates of Additive Effects and Predictions of Total Genetic Values inFrontiers in plant science · 2021Article
- Factors Influencing Genomic Prediction Accuracies of Tropical Maize Resistance to Fall Armyworm and Weevils.Plants (Basel, Switzerland) · 2020Article
- Evaluation of the efficiency of genomic versus pedigree predictions for growth and wood quality traits in Scots pine.BMC genomics · 2020Article
- Genomic Studies Reveal Substantial Dominant Effects and Improved Genomic Predictions in an Open-Pollinated Breeding Population ofG3 (Bethesda, Md.) · 2020Article
- Preservation of Genetic Variation in a Breeding Population for Long-Term Genetic Gain.G3 (Bethesda, Md.) · 2020Article
- Effect of number of annual rings and tree ages on genomic predictive ability for solid wood properties of Norway spruce.BMC genomics · 2020Article
- Genomic Predictions Using Low-Density SNP Markers, Pedigree and GWAS Information: A Case Study with the Non-Model SpeciesPlants (Basel, Switzerland) · 2020Article
- Marker Selection in Multivariate Genomic Prediction Improves Accuracy of Low Heritability Traits.Frontiers in genetics · 2020Article
- Modern Strategies to Assess and Breed Forest Tree Adaptation to Changing Climate.Frontiers in plant science · 2020Review
- Predicting Thermal Adaptation by Looking Into Populations' Genomic Past.Frontiers in genetics · 2020Review
- SNP and Haplotype-Based Genomic Selection of Quantitative Traits inPlants (Basel, Switzerland) · 2019Article
- Effect of Hidden Relatedness on Single-Step Genetic Evaluation in an Advanced Open-Pollinated Breeding Program.The Journal of heredity · 2018Article
- Quantitative Genetics and Genomics Converge to Accelerate Forest Tree Breeding.Frontiers in plant science · 2018Review
- Article
Corrections and comments
- Erratum issued
Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Genomic selection is expected to enhance the genetic improvement of forest tree species by providing more accurate estimates of breeding values through marker-based relationship matrices compared with pedigree-based methodologies. When adequately robust genomic prediction models are available, an additional increase in genetic gains can be made possible with the shortening of the breeding cycle through elimination of the progeny testing phase and early selection of parental candidates. The potential of genomic selection was investigated in an advanced Eucalyptus nitens breeding population focused on improvement for solid wood production. A high-density SNP chip (EUChip60K) was used to genotype 691 individuals in the breeding population, which represented two seed orchards with different selection histories. Phenotypic records for growth and form traits at age six, and for wood quality traits at age seven were available to build genomic prediction models using GBLUP, which were compared to the traditional pedigree-based alternative using BLUP. GBLUP demonstrated that breeding value accuracy would be improved and substantial increases in genetic gains towards solid wood production would be achieved. Cross-validation within and across two different seed orchards indicated that genomic predictions would likely benefit in terms of higher predictive accuracy from increasing the size of the training data sets through higher relatedness and better utilization of LD.
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