Mostrar el registro sencillo del ítem
dc.contributor.author
Cappa, Eduardo Pablo
![Se ha confirmado la validez de este valor de autoridad por un usuario](/themes/CONICETDigital/images/authority_control/invisible.gif)
dc.contributor.author
de Lima, Bruno Marco
dc.contributor.author
Silva Junior, Orzenil B. da
![Se ha confirmado la validez de este valor de autoridad por un usuario](/themes/CONICETDigital/images/authority_control/invisible.gif)
dc.contributor.author
Garcia, Carla C.
dc.contributor.author
Mansfield, Shawn D.
dc.contributor.author
Grattapaglia, Dario
dc.date.available
2021-05-28T19:41:49Z
dc.date.issued
2019-07
dc.identifier.citation
Cappa, Eduardo Pablo; de Lima, Bruno Marco; Silva Junior, Orzenil B. da ; Garcia, Carla C.; Mansfield, Shawn D.; et al.; Improving genomic prediction of growth and wood traits in Eucalyptus using phenotypes from non-genotyped trees by single-step GBLUP; Elsevier Ireland; Plant Science; 284; 7-2019; 9-15
dc.identifier.issn
0168-9452
dc.identifier.uri
http://hdl.handle.net/11336/132791
dc.description.abstract
Genomic Best Linear Unbiased Prediction (GBLUP) in tree breeding typically only uses information from genotyped trees. However, information from phenotyped but non-genotyped trees can also be highly valuable. The single-step GBLUP approach (ssGBLUP) allows genomic prediction to take into account both genotyped and non-genotyped trees simultaneously in a single evaluation. In this study, we investigated the advantage, in terms of breeding value accuracy and bias, of including phenotypic observation from non-genotyped trees in a standard tree GBLUP evaluation. We compared the efficiency of the conventional pedigree-based (ABLUP), GBLUP and ssGBLUP approaches to evaluate eight growth and wood quality traits in a Eucalyptus hybrid population, genotyped with 33,398 single nucleotide polymorphisms (SNPs) using the EucHIP60k. Theoretical accuracies, predictive ability and bias were calculated by ten-fold cross validation on all traits. The use of additional phenotypic information from non-genotyped trees by means of ssGBLUP provided higher predictive ability (from 37% to 75%) and lower prediction bias (from 21% to 73%) for the genetic component of non-phenotyped but genotyped trees when compared to GBLUP. The increase (decrease) in the prediction accuracy (bias) became stronger as trait heritability decreased. We concluded that ssGBLUP is a promising breeding tool to improve accuracies and bias over classical GBLUP for genomic evaluation in Eucalyptus breeding practice.
dc.format
application/pdf
dc.language.iso
eng
dc.publisher
Elsevier Ireland
![Se ha confirmado la validez de este valor de autoridad por un usuario](/themes/CONICETDigital/images/authority_control/invisible.gif)
dc.rights
info:eu-repo/semantics/restrictedAccess
dc.rights.uri
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
dc.subject
ACCURACY
dc.subject
ADDITIONAL PHENOTYPIC INFORMATION
dc.subject
BIAS
dc.subject
EUCALYPTUS
dc.subject
SINGLE-STEP GENOMIC EVALUATION
dc.subject.classification
Otras Ciencias Agrícolas
![Se ha confirmado la validez de este valor de autoridad por un usuario](/themes/CONICETDigital/images/authority_control/invisible.gif)
dc.subject.classification
Otras Ciencias Agrícolas
![Se ha confirmado la validez de este valor de autoridad por un usuario](/themes/CONICETDigital/images/authority_control/invisible.gif)
dc.subject.classification
CIENCIAS AGRÍCOLAS
![Se ha confirmado la validez de este valor de autoridad por un usuario](/themes/CONICETDigital/images/authority_control/invisible.gif)
dc.title
Improving genomic prediction of growth and wood traits in Eucalyptus using phenotypes from non-genotyped trees by single-step GBLUP
dc.type
info:eu-repo/semantics/article
dc.type
info:ar-repo/semantics/artículo
dc.type
info:eu-repo/semantics/publishedVersion
dc.date.updated
2021-05-27T12:39:22Z
dc.journal.volume
284
dc.journal.pagination
9-15
dc.journal.pais
Irlanda
![Se ha confirmado la validez de este valor de autoridad por un usuario](/themes/CONICETDigital/images/authority_control/invisible.gif)
dc.description.fil
Fil: Cappa, Eduardo Pablo. Instituto Nacional de Tecnología Agropecuaria. Centro de Investigación de Recursos Naturales. Instituto de Recursos Biológicos; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
dc.description.fil
Fil: de Lima, Bruno Marco. Fibria S.A. Technology Center; Brasil
dc.description.fil
Fil: Silva Junior, Orzenil B. da. Ministerio da Agricultura Pecuaria e Abastecimento de Brasil. Empresa Brasileira de Pesquisa Agropecuaria; Brasil
dc.description.fil
Fil: Garcia, Carla C.. International Paper of Brazil; Brasil
dc.description.fil
Fil: Mansfield, Shawn D.. University of British Columbia; Canadá
dc.description.fil
Fil: Grattapaglia, Dario. Ministerio da Agricultura Pecuaria e Abastecimento de Brasil. Empresa Brasileira de Pesquisa Agropecuaria; Brasil. Universidade Católica de Brasília. Genomic Sciences Program; Brasil
dc.journal.title
Plant Science
![Se ha confirmado la validez de este valor de autoridad por un usuario](/themes/CONICETDigital/images/authority_control/invisible.gif)
dc.relation.alternativeid
info:eu-repo/semantics/altIdentifier/url/https://www.sciencedirect.com/science/article/pii/S0168945218314134
dc.relation.alternativeid
info:eu-repo/semantics/altIdentifier/doi/http://dx.doi.org/10.1016/j.plantsci.2019.03.017
Archivos asociados