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Genomic evaluation for breeding and genetic management in Cordia africana, a multipurpose tropical tree species.
Ousmael, Kedra M; Cappa, Eduardo P; Hansen, Jon K; Hendre, Prasad; Hansen, Ole K.
Afiliação
  • Ousmael KM; Department of Geosciences and Natural Resource Management, University of Copenhagen, Rolighedsvej 23, 1958, Frederiksberg C, Denmark. kou@ign.ku.dk.
  • Cappa EP; Instituto Nacional de Tecnología Agropecuaria (INTA), Instituto de Recursos Biológicos, Centro de Investigación en Recursos Naturales, De Los Reseros y Dr. Nicolás Repetto s/n, 1686, Hurlingham, Buenos Aires, Argentina.
  • Hansen JK; Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET), Buenos Aires, Argentina.
  • Hendre P; Department of Geosciences and Natural Resource Management, University of Copenhagen, Rolighedsvej 23, 1958, Frederiksberg C, Denmark.
  • Hansen OK; World Agroforestry Centre (ICRAF), United Nations Avenue, Nairobi, 00100, Kenya.
BMC Genomics ; 25(1): 9, 2024 Jan 02.
Article em En | MEDLINE | ID: mdl-38166623
ABSTRACT

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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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Árvores / Cordia Tipo de estudo: Prognostic_studies Limite: Humans Idioma: En Revista: BMC Genomics Assunto da revista: GENETICA Ano de publicação: 2024 Tipo de documento: Article País de afiliação: Dinamarca País de publicação: Reino Unido

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Árvores / Cordia Tipo de estudo: Prognostic_studies Limite: Humans Idioma: En Revista: BMC Genomics Assunto da revista: GENETICA Ano de publicação: 2024 Tipo de documento: Article País de afiliação: Dinamarca País de publicação: Reino Unido