Validation of an approximate approach to compute genetic correlations between longevity and linear traits
Tarrés, Joaquim (Universitat Autònoma de Barcelona. Grup de Recerca en Remugants (G2R))
Piedrafita, Jesús (Universitat Autònoma de Barcelona. Grup de Recerca en Remugants (G2R))
Ducrocq, Vincent (Institut National de la Recherche Agronomique (França))

Data:	2005
Resum:	The estimation of genetic correlations between a nonlinear trait such as longevity and linear traits is computationally difficult on large datasets. A two-step approach was proposed and was checked via simulation. First, univariate analyses were performed to get genetic variance estimates and to compute pseudo-records and their associated weights. These pseudo-records were virtual performances free of all environmental effects that can be used in a BLUP animal model, leading to the same breeding values as in the (possibly nonlinear) initial analyses. By combining these pseudo-records in a multiple trait model and fixing the genetic and residual variances to their values computed during the first step, we obtained correlation estimates by AI-REML and approximate MT-BLUP predicted breeding values that blend direct and indirect information on longevity. Mean genetic correlations and reliabilities obtained on simulated data confirmed the suitability of this approach in a wide range of situations. When nonzero residual correlations exist between traits, a sire model gave nearly unbiased estimates of genetic correlations, while the animal model estimates were biased upwards. Finally, when an incorrect genetic trend was simulated to lead to biased pseudo-records, a joint analysis including a time effect could adequately correct for this bias.
Drets:	Aquest document està subjecte a una llicència d'ús Creative Commons. Es permet la reproducció total o parcial, la distribució, la comunicació pública de l'obra i la creació d'obres derivades, fins i tot amb finalitats comercials, sempre i quan es reconegui l'autoria de l'obra original.
Llengua:	Anglès
Document:	Article ; recerca ; Versió publicada
Publicat a:	Genetics, selection, evolution, Vol. 38 (12 2005) , p. 65-83, ISSN 1297-9686

DOI: 10.1186/1297-9686-38-1-65
PMID: 16451792

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