Genomic breeding values’ prediction including populational selfing rate in an open-pollinated Eucalyptus globulus breeding population

Quezada, Marianella; Aguilar, Ignácio; Balmelli, Gustavo

doi:10.1007/s11295-021-01534-7

Cited by 9 publications

(6 citation statements)

References 53 publications

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“…However, the inclusion of phenotype data of ungenotyped individuals in the HBLUP models resulted in a ~20% improvement of genomic predictions over standard GBLUP for E. urophylla. These results corroborate previous reports on the value of HBLUP over GBLUP in boosting genomic predictions in Eucalyptus ( Cappa et al., 2019 ; Callister et al., 2021 ; Quezada et al., 2022 ). However, for E. grandis , the predictive abilities with HBLUP were slightly worse than with GBLUP.…”

Section: Discussionsupporting

confidence: 92%

Realized genomic selection across generations in a reciprocal recurrent selection breeding program of Eucalyptus hybrids

Simiqueli,

Resende,

Takahashi

et al. 2023

Front. Plant Sci.

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IntroductionGenomic selection (GS) experiments in forest trees have largely reported estimates of predictive abilities from cross-validation among individuals in the same breeding generation. In such conditions, no effects of recombination, selection, drift, and environmental changes are accounted for. Here, we assessed the effectively realized predictive ability (RPA) for volume growth at harvest age by GS across generations in an operational reciprocal recurrent selection (RRS) program of hybrid Eucalyptus.MethodsGenomic best linear unbiased prediction with additive (GBLUP_G), additive plus dominance (GBLUP_G+D), and additive single-step (HBLUP) models were trained with different combinations of growth data of hybrids and pure species individuals (N = 17,462) of the G1 generation, 1,944 of which were genotyped with ~16,000 SNPs from SNP arrays. The hybrid G2 progeny trial (HPT267) was the GS target, with 1,400 selection candidates, 197 of which were genotyped still at the seedling stage, and genomically predicted for their breeding and genotypic values at the operational harvest age (6 years). Seedlings were then grown to harvest and measured, and their pedigree-based breeding and genotypic values were compared to their originally predicted genomic counterparts.ResultsGenomic RPAs ≥0.80 were obtained as the genetic relatedness between G1 and G2 increased, especially when the direct parents of selection candidates were used in training. GBLUP_G+D reached RPAs ≥0.70 only when hybrid or pure species data of G1 were included in training. HBLUP was only marginally better than GBLUP. Correlations ≥0.80 were obtained between pedigree and genomic individual ranks. Rank coincidence of the top 2.5% selections was the highest for GBLUP_G (45% to 60%) compared to GBLUP_G+D. To advance the pure species RRS populations, GS models were best when trained on pure species than hybrid data, and HBLUP yielded ~20% higher predictive abilities than GBLUP, but was not better than ABLUP for ungenotyped trees.DiscussionWe demonstrate that genomic data effectively enable accurate ranking of eucalypt hybrid seedlings for their yet-to-be observed volume growth at harvest age. Our results support a two-stage GS approach involving family selection by average genomic breeding value, followed by within-top-families individual GS, significantly increasing selection intensity, optimizing genotyping costs, and accelerating RRS breeding.

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Section: Discussionsupporting

confidence: 92%

Realized genomic selection across generations in a reciprocal recurrent selection breeding program of Eucalyptus hybrids

Simiqueli,

Resende,

Takahashi

et al. 2023

Front. Plant Sci.

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“…In our study, the ssGBLUP models showed a constant increase in additive variance estimates compared to the ABLUP models at all sites, except for the “without inbreeding” scenario at the ILRI site. This is in line with results reported for growth traits in other tree species, for example, Eucalyptus [ 47 , 48 ] , lodgepole pine [ 38 ], white spruce [ 49 ], and loblolly pine [ 50 ]. However, studies on other tree species have reported that models using genomic evaluation (GBLUP or ssGBLUP) show decreased or similar additive variance estimates compared to models using pedigree-based information only for growth and wood quality traits [ 51 – 53 ].…”

Section: Discussionsupporting

confidence: 90%

“…The BSOs in this study were established by taking the necessary precautions to avoid inbreeding, i.e., by selecting mother trees with a minimum of 100 m distance from each other and in areas with a larger number of trees when possible. However, since the selfing rate might vary among species, populations, and individuals, it should be estimated using DNA marker data from the population under study [ 48 ]. This is especially true for C. africana in Ethiopia, where the fragmentation makes diversity management tricky.…”

Section: Discussionmentioning

confidence: 99%

Genomic evaluation for breeding and genetic management in Cordia africana, a multipurpose tropical tree species

Ousmael,

Cappa,

Hansen

et al. 2024

BMC Genomics

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Background Planting tested forest reproductive material is crucial to ensure the increased resilience of intensively managed productive stands for timber and wood product markets under climate change scenarios. Single-step Genomic Best Linear Unbiased Prediction (ssGBLUP) analysis is a cost-effective option for using genomic tools to enhance the accuracy of predicted breeding values and genetic parameter estimation in forest tree species. Here, we tested the efficiency of ssGBLUP in a tropical multipurpose tree species, Cordia africana, by partial population genotyping. A total of 8070 trees from three breeding seedling orchards (BSOs) were phenotyped for height. We genotyped 6.1% of the phenotyped individuals with 4373 single nucleotide polymorphisms. The results of ssGBLUP were compared with pedigree-based best linear unbiased prediction (ABLUP) and genomic best linear unbiased prediction (GBLUP), based on genetic parameters, theoretical accuracy of breeding values, selection candidate ranking, genetic gain, and predictive accuracy and prediction bias. Results Genotyping a subset of the study population provided insights into the level of relatedness in BSOs, allowing better genetic management. Due to the inbreeding detected within the genotyped provenances, we estimated genetic parameters both with and without accounting for inbreeding. The ssGBLUP model showed improved performance in terms of additive genetic variance and theoretical breeding value accuracy. Similarly, ssGBLUP showed improved predictive accuracy and lower bias than the pedigree-based relationship matrix (ABLUP). Conclusions This study of C. africana, a species in decline due to deforestation and selective logging, revealed inbreeding depression. The provenance exhibiting the highest level of inbreeding had the poorest overall performance. The use of different relationship matrices and accounting for inbreeding did not substantially affect the ranking of candidate individuals. This is the first study of this approach in a tropical multipurpose tree species, and the analysed BSOs represent the primary effort to breed C. africana.

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“…Thus, the GBLUP methods were extended to include the information of non-genotyped individuals in prediction analysis, which is the so-called Single-step genomic best linear unbiased prediction (ssGBLUP) ( Aguilar et al., 2010 ). The ssGBLUP approach is widely adopted for genomic prediction in livestock ( Misztal et al., 2021 ) and recently applied in forest species ( Cappa et al., 2019 ; Quezada et al., 2022 ). The strength of this approach is the ability to jointly incorporate the information of all genotypes, observed phenotypes and pedigree information in one simple and single step model.…”

Section: Introductionmentioning

confidence: 99%

Single-step genome-wide association study for susceptibility to Teratosphaeria nubilosa and precocity of vegetative phase change in Eucalyptus globulus

et al. 2023

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IntroductionMycosphaerella leaf disease (MLD) is one of the most prevalent foliar diseases of Eucalyptus globulus plantations around the world. Since resistance management strategies have not been effective in commercial plantations, breeding to develop more resistant genotypes is the most promising strategy. Available genomic information can be used to detect genomic regions associated with resistance to MLD, which could significantly speed up the process of genetic improvement.MethodsWe investigated the genetic basis of MLD resistance in a breeding population of E. globulus which was genotyped with the EUChip60K SNP array. Resistance to MLD was evaluated through resistance of the juvenile foliage, as defoliation and leaf spot severity, and through precocity of change to resistant adult foliage. Genome-wide association studies (GWAS) were carried out applying four Single-SNP models, a Genomic Best Linear Unbiased Prediction (GBLUP-GWAS) approach, and a Single-step genome-wide association study (ssGWAS).ResultsThe Single-SNP (model K) and GBLUP-GWAS models detected 13 and 16 SNP-trait associations in chromosomes 2, 3 y 11; whereas the ssGWAS detected 66 SNP-trait associations in the same chromosomes, and additional significant SNP-trait associations in chromosomes 5 to 9 for the precocity of phase change (proportion of adult foliage). For this trait, the two main regions in chromosomes 3 and 11 were identified for the three approaches. The SNPs identified in these regions were positioned near the key miRNA genes, miR156.5 and miR157.4, which have a main role in the regulation of the timing of vegetative change, and also in the response to environmental stresses in plants.DiscussionOur results demonstrated that ssGWAS was more powerful in detecting regions that affect resistance than conventional GWAS approaches. Additionally, the results suggest a polygenic genetic architecture for the heteroblastic transition in E. globulus and identified useful SNP markers for the development of marker-assisted selection strategies for resistance to MLD.

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Genomic breeding values’ prediction including populational selfing rate in an open-pollinated Eucalyptus globulus breeding population

Cited by 9 publications

References 53 publications

Realized genomic selection across generations in a reciprocal recurrent selection breeding program of Eucalyptus hybrids

Realized genomic selection across generations in a reciprocal recurrent selection breeding program of Eucalyptus hybrids

Genomic evaluation for breeding and genetic management in Cordia africana, a multipurpose tropical tree species

Single-step genome-wide association study for susceptibility to Teratosphaeria nubilosa and precocity of vegetative phase change in Eucalyptus globulus

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