Abstract:

We investigated the impact of combining the pedigree- and genomic-based relationship matrices in a multiple-trait individual-tree mixed model (a.k.a., multiple-trait combined approach) on the estimates of heritability and on the genomic correlations between growth and stem straightness in an open-pollinated Eucalyptus grandis population. Additionally, the added advantage of incorporating genomic information on the theoretical accuracies of parents and offspring breeding values was evaluated. Our results suggested that the use of the combined approach for estimating heritabilities and additive genetic correlations in multiple-trait evaluations is advantageous and including genomic information increases the expected accuracy of breeding values. Furthermore, the multiple-trait combined approach was proven to be superior to the single-trait combined approach in predicting breeding values, in particular for low-heritability traits. Finally, our results advocate the use of the combined approach in forest tree progeny testing trials, specifically when a multiple-trait individual-tree mixed model is considered.

Inst. de Recursos Biológicos

Author affiliation: Cappa, Eduardo Pablo. INTA. Instituto de Recursos Biológicos; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina

Author affiliation: El-Kassaby, Yousry A. University of British Columbia. Faculty of Forestry. Department of Forest and Conservation Sciences; Canada

Author affiliation: Muñoz, Facundo. Institut National de la Recherche Agronomique . Unité Amélioration, Génétique et Physiologie Forestières; Francia

Author affiliation: Garcia, Martin Nahuel. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. INTA. Instituto de Biotecnología; Argentina

Author affiliation: Villalba, Pamela Victoria. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. INTA. Instituto de Biotecnología; Argentina

Author affiliation: Klapste, Jaroslav. University of British Columbia. Faculty of Forestry. Department of Forest and Conservation Sciences; Canada. Czech University of Life Sciences. Faculty of Forestry and Wood Sciences. Department of Genetics and Physiology of Forest Trees; República Checa

Author affiliation: Marcucci Poltri, Susana Noemi. INTA. Instituto de Biotecnología; Argentina

Abstract:

Climate change and the increasing demand for sustainable energy resources require urgent strategies to increase the accuracy of selection in tree breeding (associated with higher gain). We investigated the combined pedigree and genomic-based relationship approach and its impact on the accuracy of predicted breeding values using data from 5-year-old Eucalyptus grandis progeny trial. The number of trees that can be genotyped in a tree breeding population is limited; therefore, the combined approach can be a feasible and efficient strategy to increase the genetic gain and provide more accurate predicted breeding values. We calculated the accuracy of predicted breeding values for two growth traits, diameter at breast height and total height, using two evaluation approaches: the combined approach and the classical pedigree-based approach. We also investigated the influence of two different trait heritabilities as well as the inclusion of competition genetic effects or environmental heterogeneity in an individual-tree mixed model on the estimated variance components and accuracy of breeding values. The genomic information of genotyped trees is automatically propagated to all trees with the combined approach, including the non-genotyped mothers. This increased the accuracy of overall breeding values, except for the non-genotyped trees from the competition model. The increase in the accuracy was higher for the total height, the trait with low heritability. The combined approach is a simple, fast, and accurate genomic selection method for genetic evaluation of growth traits in E. grandis and tree species in general. It is simple to implement in a traditional individual-tree mixed model and provides an easy extension to individual-tree mixed models with competition effects and/or environmental heterogeneity.

Inst. de Recursos Biológicos

Author affiliation: Cappa, Eduardo Pablo. INTA. Instituto de Recursos Biológicos; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina

Author affiliation: El-Kassaby, Yousry A. University of British Columbia. Faculty of Forestry. Department of Forest and Conservation Sciences; Canada

Author affiliation: Muñoz, Facundo. Institut National de la Recherche Agronomique . Unité Amélioration, Génétique et Physiologie Forestières; Francia

Author affiliation: Garcia, Martin Nahuel. INTA. Instituto de Biotecnología; Argentina

Author affiliation: Villalba, Pamela Victoria. INTA. Instituto de Biotecnología; Argentina

Author affiliation: Klapste, Jaroslav. University of British Columbia. Faculty of Forestry. Department of Forest and Conservation Sciences; Canada. Czech University of Life Sciences. Faculty of Forestry and Wood Sciences. Department of Genetics and Physiology of Forest Trees; República Checa

Author affiliation: Marcucci Poltri, Susana Noemi. INTA. Instituto de Biotecnología; Argentina

Abstract:

Climate change and the increasing demand for sustainable energy resources require urgent strategies to increase the accuracy of selection in tree breeding (associated with higher gain). We investigated the combined pedigree and genomic-based relationship approach and its impact on the accuracy of predicted breeding values using data from 5-year-old Eucalyptus grandis progeny trial. The number of trees that can be genotyped in a tree breeding population is limited; therefore, the combined approach can be a feasible and efficient strategy to increase the genetic gain and provide more accurate predicted breeding values. We calculated the accuracy of predicted breeding values for two growth traits, diameter at breast height and total height, using two evaluation approaches: the combined approach and the classical pedigree-based approach. We also investigated the influence of two different trait heritabilities as well as the inclusion of competition genetic effects or environmental heterogeneity in an individual-tree mixed model on the estimated variance components and accuracy of breeding values. The genomic information of genotyped trees is automatically propagated to all trees with the combined approach, including the non-genotyped mothers. This increased the accuracy of overall breeding values, except for the non-genotyped trees from the competition model. The increase in the accuracy was higher for the total height, the trait with low heritability. The combined approach is a simple, fast, and accurate genomic selection method for genetic evaluation of growth traits in E. grandis and tree species in general. It is simple to implement in a traditional individual-tree mixed model and provides an easy extension to individual-tree mixed models with competition effects and/or environmental heterogeneity.

Author affiliation: Cappa, Eduardo Pablo. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Instituto Nacional de Tecnología Agropecuaria. Centro de Investigación de Recursos Naturales. Instituto de Recursos Biológicos; Argentina

Author affiliation: El-Kassaby, Yousry A.. University of British Columbia; Canadá

Author affiliation: Muñoz, Facundo. Centre de Recherche de Nantes. Institut National de la Recherche Agronomique; Francia

Author affiliation: Garcia, Martín Nahuel. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Instituto Nacional de Tecnología Agropecuaria. Centro de Investigación en Ciencias Veterinarias y Agronómicas; Argentina

Author affiliation: Villalba, Pamela Victoria. Instituto Nacional de Tecnología Agropecuaria. Centro de Investigación en Ciencias Veterinarias y Agronómicas; Argentina

Author affiliation: Klápste, Jaroslav. University of British Columbia; Canadá. Czech University of Life Sciences Prague; República Checa

Author affiliation: Marcucci Poltri, Susana Noemí. Instituto Nacional de Tecnología Agropecuaria. Centro de Investigación en Ciencias Veterinarias y Agronómicas; Argentina

Abstract:

Simple sequence repeats (SSR) are the most widely used molecular markers for relatedness inference due to their multi-allelic nature and high informativeness. However, there is a growing trend toward using high-throughput and inter-specific transferable single-nucleotide polymorphisms (SNP) and Diversity Arrays Technology (DArT) in forest genetics owing to their wide genome coverage. We compared the efficiency of 15 SSRs, 181 SNPs and 2816 DArTs to estimate the relatedness coefficients, and their effects on genetic parameters’ precision, in a relatively small data set of an open-pollinated progeny trial of Eucalyptus grandis (Hill ex Maiden) with limited relationship from the pedigree. Both simulations and real data of Eucalyptus grandis were used to study the statistical performance of three relatedness estimators based on co-dominant markers. Relatedness estimates in pairs of individuals belonging to the same family (related) were higher for DArTs than for SNPs and SSRs. DArTs performed better compared to SSRs and SNPs in estimated relatedness coefficients in pairs of individuals belonging to different families (unrelated) and showed higher ability to discriminate unrelated from related individuals. The likelihood-based estimator exhibited the lowest root mean squared error (RMSE); however, the differences in RMSE among the three estimators studied were small. For the growth traits, heritability estimates based on SNPs yielded, on average, smaller standard errors compared to those based on SSRs and DArTs. Estimated relatedness in the realized relationship matrix and heritabilities can be accurately inferred from co-dominant or sufficiently dense dominant markers in a relatively small E. grandis data set with shallow pedigree.

Author affiliation: Cappa, Eduardo Pablo. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Instituto Nacional de Tecnología Agropecuaria. Centro Regional Buenos Aires; Argentina

Author affiliation: Klápště, Jaroslav. Czech University Of Life Sciences Prague; República Checa. University of British Columbia; Canadá. New Zealand Forest Research Institute Ltd.; Nueva Zelanda

Author affiliation: Garcia, Martín Nahuel. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Investigación En Ciencias Veterinarias y Agronómicas; Argentina

Author affiliation: Villalba, Pamela Victoria. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Investigación En Ciencias Veterinarias y Agronómicas; Argentina

Author affiliation: Marcucci Poltri, Susana Noemí. Investigación En Ciencias Veterinarias y Agronómicas; Argentina

Abstract:

Simple sequence repeats (SSR) are the most widely used molecular markers for relatedness inference due to their multi-allelic nature and high informativeness. However, there is a growing trend toward using high-throughput and inter-specific transferable single-nucleotide polymorphisms (SNP) and Diversity Arrays Technology (DArT) in forest genetics owing to their wide genome coverage. We compared the efficiency of 15 SSRs, 181 SNPs and 2816 DArTs to estimate the relatedness coefficients, and their effects on genetic parameters’ precision, in a relatively small data set of an open-pollinated progeny trial of Eucalyptus grandis (Hill ex Maiden) with limited relationship from the pedigree. Both simulations and real data of Eucalyptus grandis were used to study the statistical performance of three relatedness estimators based on co-dominant markers. Relatedness estimates in pairs of individuals belonging to the same family (related) were higher for DArTs than for SNPs and SSRs. DArTs performed better compared to SSRs and SNPs in estimated relatedness coefficients in pairs of individuals belonging to different families (unrelated) and showed higher ability to discriminate unrelated from related individuals. The likelihoodbased estimator exhibited the lowest root mean squared error (RMSE); however, the differences in RMSE among the three estimators studied were small. For the growth traits, heritability estimates based on SNPs yielded, on average, smaller standard errors compared to those based on SSRs and DArTs. Estimated relatedness in the realized relationship matrix and heritabilities can be accurately inferred from co-dominant or sufficiently dense dominant markers in a relatively small E. grandis data set with shallow pedigree.

Inst. de Biotecnología

Author affiliation: Cappa, Eduardo Pablo. INTA. Instituto de Recursos Biológicos; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina

Author affiliation: Klapste, Jaroslav. University of British Columbia. Department of Forest and Conservation Sciences; Canadá. Czech University of Life Sciences. Faculty of Forestry and Wood Sciences. Department of Genetics and Physiology of Forest Trees; República Checa

Author affiliation: Garcia, Martin Nahuel. INTA. Instituto de Biotecnología; Argentina

Author affiliation: Villalba, Pamela Victoria. INTA. Instituto de Biotecnología; Argentina

Author affiliation: Marcucci Poltri, Susana Noemi. INTA. Instituto de Biotecnología; Argentina

Abstract:

Maximization of genetic gain in forest tree breeding programs is contingent on the accuracy of the predicted breeding values and precision of the estimated genetic parameters. We investigated the effect of the combined use of contemporary pedigree information and genomic relatedness estimates on the accuracy of predicted breeding values and precision of estimated genetic parameters, as well as rankings of selection candidates, using single-step genomic evaluation (HBLUP). In this study, two traits with diverse heritabilities [tree height (HT) and wood density (WD)] were assessed at various levels of family genotyping efforts (0, 25, 50, 75, and 100%) from a population of white spruce (Picea glauca) consisting of 1694 trees from 214 open-pollinated families, representing 43 provenances in Québec, Canada. The results revealed that HBLUP bivariate analysis is effective in reducing the known bias in heritability estimates of open-pollinated populations, as it exposes hidden relatedness, potential pedigree errors, and inbreeding. The addition of genomic information in the analysis considerably improved the accuracy in breeding value estimates by accounting for both Mendelian sampling and historical coancestry that were not captured by the contemporary pedigree alone. Increasing family genotyping efforts were associated with continuous improvement in model fit, precision of genetic parameters, and breeding value accuracy. Yet, improvements were observed even at minimal genotyping effort, indicating that even modest genotyping effort is effective in improving genetic evaluation. The combined utilization of both pedigree and genomic information may be a cost-effective approach to increase the accuracy of breeding values in forest tree breeding programs where shallow pedigrees and large testing populations are the norm.

Inst. de Recursos Biológicos

Author affiliation: Rateliffe, Blaise. University of British Columbia, Faculty of Forestry. Department of Forest and Conservation Sciences; Canadá

Author affiliation: El-Dien, Omnia Gamal. University of British Columbia, Faculty of Forestry. Department of Forest and Conservation Sciences; Canadá. Alexandria University. Faculty of Pharmacy. Pharmacognosy Department; Egipto

Author affiliation: Cappa, Eduardo Pablo. INTA. Instituto de Recursos Biológicos; Argentina

Author affiliation: Porth, Ilga. Université Laval Québec. Faculté de Foresterie, de Géographie et Géomatique. Départment des Sciences du Bois et de la Forêt; Canadá

Author affiliation: Klapste, Jaroslav. Czech University of Life Sciences Prague. Faculty of Forestry and Wood Sciences. Department of Genetics and Physiology of Forest Trees; República Checa. Scion (New Zealand Forest Research Institute Ltd.); Nueva Zelanda

Author affiliation: El-Kassaby, Yousry A. University of British Columbia, Faculty of Forestry. Department of Forest and Conservation Sciences; Canadá

Author affiliation: Chen, Charles. Oklahoma State University. Department of Biochemistry and Molecular Biology; Estados Unidos