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A bivariate quantitative genetic model for a threshold trait and a survival trait

Many of the functional traits considered in animal breeding can be analyzed as threshold traits or survival traits with examples including disease traits, conformation scores, calving difficulty and longevity. In this paper we derive and implement a bivariate quantitative genetic model for a thresho...

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Detalles Bibliográficos
Autores principales: Damgaard, Lars Holm, Korsgaard, Inge Riis
Formato: Texto
Lenguaje:English
Publicado: BioMed Central 2006
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2689264/
https://www.ncbi.nlm.nih.gov/pubmed/17129560
http://dx.doi.org/10.1186/1297-9686-38-6-565
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author Damgaard, Lars Holm
Korsgaard, Inge Riis
author_facet Damgaard, Lars Holm
Korsgaard, Inge Riis
author_sort Damgaard, Lars Holm
collection PubMed
description Many of the functional traits considered in animal breeding can be analyzed as threshold traits or survival traits with examples including disease traits, conformation scores, calving difficulty and longevity. In this paper we derive and implement a bivariate quantitative genetic model for a threshold character and a survival trait that are genetically and environmentally correlated. For the survival trait, we considered the Weibull log-normal animal frailty model. A Bayesian approach using Gibbs sampling was adopted in which model parameters were augmented with unobserved liabilities associated with the threshold trait. The fully conditional posterior distributions associated with parameters of the threshold trait reduced to well known distributions. For the survival trait the two baseline Weibull parameters were updated jointly by a Metropolis-Hastings step. The remaining model parameters with non-normalized fully conditional distributions were updated univariately using adaptive rejection sampling. The Gibbs sampler was tested in a simulation study and illustrated in a joint analysis of calving difficulty and longevity of dairy cattle. The simulation study showed that the estimated marginal posterior distributions covered well and placed high density to the true values used in the simulation of data. The data analysis of calving difficulty and longevity showed that genetic variation exists for both traits. The additive genetic correlation was moderately favorable with marginal posterior mean equal to 0.37 and 95% central posterior credibility interval ranging between 0.11 and 0.61. Therefore, this study suggests that selection for improving one of the two traits will be beneficial for the other trait as well.
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spelling pubmed-26892642009-06-02 A bivariate quantitative genetic model for a threshold trait and a survival trait Damgaard, Lars Holm Korsgaard, Inge Riis Genet Sel Evol Research Many of the functional traits considered in animal breeding can be analyzed as threshold traits or survival traits with examples including disease traits, conformation scores, calving difficulty and longevity. In this paper we derive and implement a bivariate quantitative genetic model for a threshold character and a survival trait that are genetically and environmentally correlated. For the survival trait, we considered the Weibull log-normal animal frailty model. A Bayesian approach using Gibbs sampling was adopted in which model parameters were augmented with unobserved liabilities associated with the threshold trait. The fully conditional posterior distributions associated with parameters of the threshold trait reduced to well known distributions. For the survival trait the two baseline Weibull parameters were updated jointly by a Metropolis-Hastings step. The remaining model parameters with non-normalized fully conditional distributions were updated univariately using adaptive rejection sampling. The Gibbs sampler was tested in a simulation study and illustrated in a joint analysis of calving difficulty and longevity of dairy cattle. The simulation study showed that the estimated marginal posterior distributions covered well and placed high density to the true values used in the simulation of data. The data analysis of calving difficulty and longevity showed that genetic variation exists for both traits. The additive genetic correlation was moderately favorable with marginal posterior mean equal to 0.37 and 95% central posterior credibility interval ranging between 0.11 and 0.61. Therefore, this study suggests that selection for improving one of the two traits will be beneficial for the other trait as well. BioMed Central 2006-11-28 /pmc/articles/PMC2689264/ /pubmed/17129560 http://dx.doi.org/10.1186/1297-9686-38-6-565 Text en Copyright © 2006 INRA, EDP Sciences
spellingShingle Research
Damgaard, Lars Holm
Korsgaard, Inge Riis
A bivariate quantitative genetic model for a threshold trait and a survival trait
title A bivariate quantitative genetic model for a threshold trait and a survival trait
title_full A bivariate quantitative genetic model for a threshold trait and a survival trait
title_fullStr A bivariate quantitative genetic model for a threshold trait and a survival trait
title_full_unstemmed A bivariate quantitative genetic model for a threshold trait and a survival trait
title_short A bivariate quantitative genetic model for a threshold trait and a survival trait
title_sort bivariate quantitative genetic model for a threshold trait and a survival trait
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2689264/
https://www.ncbi.nlm.nih.gov/pubmed/17129560
http://dx.doi.org/10.1186/1297-9686-38-6-565
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