Literature DB >> 17612477

An approximate multitrait model for genetic evaluation in dairy cattle with a robust estimation of genetic trends.

Jan Lassen1, Morten Kargo Sørensen, Per Madsen, Vincent Ducrocq.   

Abstract

In a stochastic simulation study of a dairy cattle population three multitrait models for estimation of genetic parameters and prediction of breeding values were compared. The first model was an approximate multitrait model using a two-step procedure. The first step was a single trait model for all traits. The solutions for fixed effects from these analyses were subtracted from the phenotypes. A multitrait model only containing an overall mean, an additive genetic and a residual term was applied on these preadjusted data. The second model was similar to the first model, but the multitrait model also contained a year effect. The third model was a full multitrait model. Genetic trends for total merit and for the individual traits in the breeding goal were compared for the three scenarios to rank the models. The full multitrait model gave the highest genetic response, but was not significantly better than the approximate multitrait model including a year effect. The inclusion of a year effect into the second step of the approximate multitrait model significantly improved the genetic trend for total merit. In this study, estimation of genetic parameters for breeding value estimation using models corresponding to the ones used for prediction of breeding values increased the accuracy on the breeding values and thereby the genetic progress.

Entities:  

Mesh:

Year:  2007        PMID: 17612477      PMCID: PMC2682816          DOI: 10.1186/1297-9686-39-4-353

Source DB:  PubMed          Journal:  Genet Sel Evol        ISSN: 0999-193X            Impact factor:   4.297


  2 in total

1.  A comparison of methods to calculate a total merit index using stochastic simulation.

Authors:  Christina Pfeiffer; Birgit Fuerst-Waltl; Hermann Schwarzenbacher; Franz Steininger; Christian Fuerst
Journal:  Genet Sel Evol       Date:  2015-05-02       Impact factor: 4.297

2.  Accuracies of univariate and multivariate genomic prediction models in African cassava.

Authors:  Uche Godfrey Okeke; Deniz Akdemir; Ismail Rabbi; Peter Kulakow; Jean-Luc Jannink
Journal:  Genet Sel Evol       Date:  2017-12-04       Impact factor: 4.297

  2 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.