Literature DB >> 16543556

Estimating maternal genetic effects in livestock.

P Bijma1.   

Abstract

This study investigates the estimation of direct and maternal genetic (co)variances, accounting for environmental covariances between direct and maternal effects. Estimated genetic correlations between direct and maternal effects presented in the literature have often been strongly negative, and their validity has been questioned. Explanations of extreme estimates have focused on the existence of environmental covariances between dam and offspring. As a solution, models including a regression on dam-phenotype have been proposed, but have yielded biased estimates. The performance of models that implement the variance structure arising from the classical model of Willham, however, has not been evaluated. This study investigated the covariance structure of the parts of the residual term that arise from Willham's model. Results show that a correlation between the residual of the record of an individual and that of its dam is a direct consequence of combining Willham's model with the usual assumption that phenotypic covariances between different traits are the sum of additive genetic and environmental covariances. Stochastic simulations show that fitting this structure yields unbiased estimates of the genetic (co)variances. When correlated residuals were ignored in the cases investigated, the bias in the estimated genetic correlations was approximately equal to the value of the environmental correlation. In contrast to models including a regression on dam-phenotype, there were no difficulties with interpretation of results, and the approach was consistent with standard quantitative genetic theory. The use of Willham's model while accounting for correlated residuals is conceptually appealing and yields unbiased results, with no need for regression on dam phenotype. Inclusion of the ability to fit the residual variance structure required for maternal effects into existing software packages would be helpful to animal breeders.

Mesh:

Year:  2006        PMID: 16543556     DOI: 10.2527/2006.844800x

Source DB:  PubMed          Journal:  J Anim Sci        ISSN: 0021-8812            Impact factor:   3.159


  12 in total

1.  Genetic variability of body weight in two goose strains under long-term selection.

Authors:  Tomasz Szwaczkowski; Stanislaw Wezyk; Elzbieta Stanisławska-Barczak; Jakub Badowski; Halina Bielińska; Anna Wolc
Journal:  J Appl Genet       Date:  2007       Impact factor: 3.240

2.  Direct and maternal (co)variance components and genetic parameters for growth and reproductive traits in the Boran cattle in Kenya.

Authors:  C B Wasike; D Indetie; J M K Ojango; A K Kahi
Journal:  Trop Anim Health Prod       Date:  2008-10-29       Impact factor: 1.559

3.  Genetic variances and covariances of live weight traits in Charolais cattle by multi-trait analysis.

Authors:  J B Herrera-Ojeda; G M Parra-Bracamonte; N Lopez-Villalobos; J C Martínez-González; J G Magaña-Monforte; S T Morris; L A López-Bustamante
Journal:  J Appl Genet       Date:  2019-08-12       Impact factor: 3.240

4.  Estimating variance components in population scale family trees.

Authors:  Tal Shor; Iris Kalka; Dan Geiger; Yaniv Erlich; Omer Weissbrod
Journal:  PLoS Genet       Date:  2019-05-09       Impact factor: 5.917

5.  Transcriptomic basis and evolution of the ant nurse-larval social interactome.

Authors:  Michael R Warner; Alexander S Mikheyev; Timothy A Linksvayer
Journal:  PLoS Genet       Date:  2019-05-20       Impact factor: 5.917

6.  Antagonistic maternal and direct effects of the leptin receptor gene on body weight in pigs.

Authors:  Emma Solé; Roger Ros-Freixedes; Marc Tor; Josep Reixach; Ramona N Pena; Joan Estany
Journal:  PLoS One       Date:  2021-01-28       Impact factor: 3.240

7.  Genome-wide discovery of maternal effect variants.

Authors:  Jack W Kent; Charles P Peterson; Thomas D Dyer; Laura Almasy; John Blangero
Journal:  BMC Proc       Date:  2009-12-15

8.  Accuracy of the unified approach in maternally influenced traits--illustrated by a simulation study in the honey bee (Apis mellifera).

Authors:  Pooja Gupta; Norbert Reinsch; Andreas Spötter; Tim Conrad; Kaspar Bienefeld
Journal:  BMC Genet       Date:  2013-05-06       Impact factor: 2.797

9.  Genetic analysis of growth traits in Polled Nellore cattle raised on pasture in tropical region using Bayesian approaches.

Authors:  Fernando Brito Lopes; Cláudio Ulhôa Magnabosco; Fernanda Paulini; Marcelo Corrêa da Silva; Eliane Sayuri Miyagi; Raysildo Barbosa Lôbo
Journal:  PLoS One       Date:  2013-09-10       Impact factor: 3.240

10.  Consequences of paternally inherited effects on the genetic evaluation of maternal effects.

Authors:  Luis Varona; Sebastián Munilla; Joaquim Casellas; Carlos Moreno; Juan Altarriba
Journal:  Genet Sel Evol       Date:  2015-08-13       Impact factor: 4.297

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