Abstract
Genomic selection (GS) is poised to revolutionize eucalypt tree improvement by shortening breeding cycles and increasing selection intensities. This could be particularly valuable for alternative, non-mainstream Eucalyptus species that are still in the initial stages of breeding. Eucalyptus benthamii is important for its adaptation to frost-prone subtropical regions. In this work, we compared seven genomic prediction models, six Bayesian and one frequentist GBLUP (Genomic Best Linear Unbiased Prediction) with the conventional pedigree-based ABLUP approach. Models were evaluated for their ability to estimate heritabilities and predict wood quality traits (wood density, extractives, lignin, and carbohydrates content) and volume growth in 77 open-pollinated families of Eucalyptus benthamii. We also evaluated predictive abilities and heritabilities using variable numbers of SNP in the models. Heritabilities ranged from 0.09 (extractives content) using Bayesian Lasso (BL) to 0.55 (wood density) using ABLUP. Predictive abilities (PA) ranged from 0.12 (for volume using ABLUP) to 0.44 (for wood density using three Bayesian models). All seven genomic models performed similarly well and better than the pedigree model for all traits, except extractives content. Subsets of 5000–7000 SNPs yielded heritabilities and PAs nearly as large as using all 15,293 SNPs. However, a low-density SNP panel might not be economically and technically advantageous compared to the current high-density multi-species Eucalyptus EUCHIP60k. Our results support a positive outlook to implement GS to accelerate Eucalyptus benthamii breeding for adaptation to frost-prone regions.
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Data Archiving Statement
Genotypic (10.6084/m9.figshare.14806449) and phenotypic (10.6084/m9.figshare.14807916) data used in this study are available in the Figshare Digital Repository.
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Acknowledgements
João Gabriel Zanon Paludeto received scholarships from the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES). Evandro V. Tambarussi and Dario Grattapaglia were supported by research productivity fellowships granted by CNPq (Brazilian National Council for Scientific and Technological Development).
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This work was partially supported by PRONEX-FAP-DF Grant 2009/00106-8 ‘NEXTREE’, CNPq (Brazilian Council for Scientific and Technological Development) Grant 400663/2012-0 and EMBRAPA Grant 03.11.01.007.00.00 to DG that allowed the development and validation of the multi-species EuCHIP60K used in this work.
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RAE Methodology, Formal analysis, Investigation, Resources, Data curation, Funding acquisition, Writing—Original Draft. JGZP Software, Formal analysis, Investigation, Data curation, Writing—Original Draft. BMSF Methodology, Formal analysis, Software, Investigation, Data curation, Writing—Original Draft. RAO Conceptualization, Methodology. CFA Formal analysis, Data curation, Writing—Review and Editing. MDVR Conceptualization, Methodology, EVT Visualization, Writing—Review and Editing. DG Conceptualization, Methodology, Investigation, Resources, Writing—Final Review and Editing, Supervision, Project administration.
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Estopa, R.A., Paludeto, J.G.Z., Müller, B.S.F. et al. Genomic prediction of growth and wood quality traits in Eucalyptus benthamii using different genomic models and variable SNP genotyping density. New Forests 54, 343–362 (2023). https://doi.org/10.1007/s11056-022-09924-y
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DOI: https://doi.org/10.1007/s11056-022-09924-y