Single-step genomic prediction of Eucalyptus dunnii using different identity-by-descent and identity-by-state relationship matrices

Jurcic, Esteban Javier; Villalba, Pamela V.; Pathauer, P. S.; Palazzini, D. A.; Oberschelp, Gustavo Pedro Javier; Harrand, Leonel; García, Martín; Aguirre, Natalia Cristina; Acuña, Cintia V.; Martínez, Marcelino Álvarez; Rivas, Juan Gabriel; Cisneros, E. F.; López, Juan Adolfo; Poltri, Susana N. Marcucci; Munilla, S.; Cappa, Eduardo P.

doi:10.1038/s41437-021-00450-9

Cited by 12 publications

(21 citation statements)

References 69 publications

(104 reference statements)

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“…However, the dispersion of pair-wise relationship coefficients of ssGBLUP-IBD is lower than the ssGBLUP-IBS model ( Table 4 ). While the high heritability of ssGBLUP-IBS, low dispersion of relationship coefficients of ssGBLUP-IBD and high prediction accuracy of ssGBLUP-IBD model are similar to the results of Jurcic et al (2021) , there is however no difference between the two models in predictive ability with both GBLUP ( Figure 1 ) and ssGBLUP ( Figure 4 ). The discrepancy in the performance of the models with IBD in the current study and the previous study may be due to the type of population and the type of markers used in the two studies.…”

Section: Discussionsupporting

confidence: 70%

“…In a recent study, Jurcic et al (2021) have shown that implementation of a ssGBLUP with IBD relationship matrix resulted in better performance compared to a ssGBLUP model with IBS GRM in E. dunnii . Higher predictive ability was observed with IBD compared to the IBS matrix for DBH and stem straightness.…”

Section: Discussionmentioning

confidence: 99%

“…However, Forneris et al (2016) have observed higher accuracies of breeding value predictions with the IBD matrix in ssGBLUP. In a recent study in Eucalyptus dunnii ( E. dunnii ), higher breeding value accuracies with lower bias were observed for growth and stem form using the ssGBLUP model with IBD compared to the IBS matrix ( Jurcic et al 2021 ). The authors recommend using ssGBLUP with an IBD matrix in open-pollinated forest tree evaluations.…”

Section: Introductionmentioning

confidence: 99%

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Genomic studies with preselected markers reveal dominance effects influencing growth traits in Eucalyptus nitens

Thumma¹,

Joyce²,

Jacobs³

2021

G3 Genes|Genomes|Genetics

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Genomic selection (GS) is being increasingly adopted by the tree breeding community. Most of the GS studies in trees are focused on estimating additive genetic effects. Exploiting the dominance effects offers additional opportunities to improve genetic gain. To detect dominance effects, trait-relevant markers may be important compared to nonselected markers. Here, we used preselected markers to study the dominance effects in a Eucalyptus nitens (E. nitens) breeding population consisting of open-pollinated (OP) and controlled-pollinated (CP) families. We used 8221 trees from six progeny trials in this study. Of these, 868 progeny and 255 parents were genotyped with the E. nitens marker panel. Three traits; diameter at breast height (DBH), wood basic density (DEN), and kraft pulp yield (KPY) were analyzed. Two types of genomic relationship matrices based on identity-by-state (IBS) and identity-by-descent (IBD) were tested. Performance of the genomic best linear unbiased prediction (GBLUP) models with IBS and IBD matrices were compared with pedigree-based additive best linear unbiased prediction (ABLUP) models with and without the pedigree reconstruction. Similarly, the performance of the single-step GBLUP (ssGBLUP) with IBS and IBD matrices were compared with ABLUP models using all 8221 trees. Significant dominance effects were observed with the GBLUP-AD model for DBH. The predictive ability of DBH is higher with the GBLUP-AD model compared to other models. Similarly, the prediction accuracy of genotypic values is higher with GBLUP-AD compared to the GBLUP-A model. Among the two GBLUP models (IBS and IBD), no differences were observed in predictive abilities and prediction accuracies. While the estimates of predictive ability with additive effects were similar among all four models, prediction accuracies of ABLUP were lower than the GBLUP models. The prediction accuracy of ssGBLUP-IBD is higher than the other three models while the theoretical accuracy of ssGBLUP-IBS is consistently higher than the other three models across all three groups tested (parents, genotyped, and nongenotyped). Significant inbreeding depression was observed for DBH and KPY. While there is a linear relationship between inbreeding and DBH, the relationship between inbreeding and KPY is nonlinear and quadratic. These results indicate that the inbreeding depression of DBH is mainly due to directional dominance while in KPY it may be due to epistasis. Inbreeding depression may be the main source of the observed dominance effects in DBH. The significant dominance effect observed for DBH may be used to select complementary parents to improve the genetic merit of the progeny in E. nitens.

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Section: Discussionsupporting

confidence: 70%

Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Genomic studies with preselected markers reveal dominance effects influencing growth traits in Eucalyptus nitens

Thumma¹,

Joyce²,

Jacobs³

2021

G3 Genes|Genomes|Genetics

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“…However, that is not a major concern if SNP arrays are applied to screen populations that are genetically related to the resequencing panels. SNP arrays have proven particularly useful for genome-informed breeding applications, such as checking sample identity, pedigree and relationship assignment, trait mapping and genomic predictions [9][10][11][12][13][14]. Nonetheless, when applying SNP arrays to screen wild/natural populations, increased attention needs to be given to the possibility that genetic variation can be missed.…”

Section: Introductionmentioning

confidence: 99%

A multiplexed plant-animal SNP array for selective breeding and species conservation applications

Montanari

Deng

Koot

et al. 2022

Preprint

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Reliable and high-throughput genotyping platforms are of immense importance for identifying and dissecting genomic regions controlling important phenotypes, supporting selection processes in breeding programmes, and managing wild populations and germplasm collections. Amongst available genotyping tools, SNP arrays have been shown to be comparatively easy to use and generate highly accurate genotypic data. Single species arrays are the most commonly used type so far; however, some multi-species arrays have been developed for closely related species that share SNP markers, exploiting inter-species cross-amplification. In this study, the suitability of a multiplexed plant-animal SNP array, including both closely and distantly related species, was explored. The performance of the SNP array across species for diverse applications, ranging from intra-species diversity assessments to parentage analysis, was assessed. Moreover, the value of genotyping pooled DNA of distantly related species on the SNP array as a technique to further reduce costs was evaluated. SNP performance was generally high, and species-specific SNPs proved suitable for diverse applications. The multi-species SNP-array approach reported here could be transferred to other species to achieve cost savings resulting from the increased throughput when several projects use the same array, and the pooling technique adds another highly promising advancement to additionally decrease genotyping costs by half.

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“…Although there have been a number of studies applying this “HBLUP” approach to forest tree populations (e.g. Ratcliffe et al 2017 ; Klápště et al 2018 ; Thavamanikumar et al 2020 ; Ukrainetz and Mansfield 2020 ; Callister et al 2021 ; Jurcic et al 2021 ), none have yet considered multiple base populations such as provenances.…”

Section: Introductionmentioning

confidence: 99%

Accounting for population structure in genomic predictions of Eucalyptus globulus

Callister

Bermann

Elms³

et al. 2022

G3 Genes|Genomes|Genetics

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Genetic groups have been widely adopted in tree breeding to account for provenance effects within pedigree-derived relationship matrices. However, provenances or genetic groups have not yet been incorporated into single-step genomic BLUP (‘HBLUP’) analyses of tree populations. To quantify the impact of accounting for population structure in Eucalyptus globulus, we used HBLUP to compare breeding value predictions from models excluding base population effects and models including either fixed genetic groups or the marker-derived proxies, also known as metafounders (MF). Full-sib families from two separate breeding populations were evaluated across 13 sites in the ‘Green Triangle’ region of Australia. Gamma matrices (Γ) describing similarities among MF reflected the geographic distribution of populations and the origins of two land races were identified. Diagonal elements of Γ provided population diversity or allelic covariation estimates between 0.24 to 0.56. Genetic group solutions were strongly correlated with MF solutions across models and MF effects influenced the genetic solutions of base population parents. The accuracy, stability, dispersion, and bias of model solutions were compared using the linear regression method. Addition of genomic information increased accuracy from 0.41 to 0.47 and stability from 0.68 to 0.71, while increasing bias slightly. Dispersion was within 0.10 of the ideal value (1.0) for all models. Although inclusion of MF did not strongly affect accuracy or stability and had mixed effects on bias, we nevertheless recommend the incorporation of MF in prediction models to represent the hierarchical genetic population structure of recently domesticated populations.

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Single-step genomic prediction of Eucalyptus dunnii using different identity-by-descent and identity-by-state relationship matrices

Cited by 12 publications

References 69 publications

Genomic studies with preselected markers reveal dominance effects influencing growth traits in Eucalyptus nitens

Genomic studies with preselected markers reveal dominance effects influencing growth traits in Eucalyptus nitens

A multiplexed plant-animal SNP array for selective breeding and species conservation applications

Accounting for population structure in genomic predictions of Eucalyptus globulus

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