Open Access

Simulation analysis to test the influence of model adequacy and data structure on the estimation of genetic parameters for traits with direct and maternal effects

  • Virginie Clément1Email author,
  • Bernard Bibé1,
  • Étienne Verrier2, 3,
  • Jean-Michel Elsen1,
  • Eduardo Manfredi1,
  • Jacques Bouix1 and
  • Éric Hanocq1
Genetics Selection Evolution200133:369

https://doi.org/10.1186/1297-9686-33-4-369

Received: 3 May 2000

Accepted: 5 May 2001

Published: 15 July 2001

Abstract

Simulations were used to study the influence of model adequacy and data structure on the estimation of genetic parameters for traits governed by direct and maternal effects. To test model adequacy, several data sets were simulated according to different underlying genetic assumptions and analysed by comparing the correct and incorrect models. Results showed that omission of one of the random effects leads to an incorrect decomposition of the other components. If maternal genetic effects exist but are neglected, direct heritability is overestimated, and sometimes more than double. The bias depends on the value of the genetic correlation between direct and maternal effects. To study the influence of data structure on the estimation of genetic parameters, several populations were simulated, with different degrees of known paternity and different levels of genetic connectedness between flocks. Results showed that the lack of connectedness affects estimates when flocks have different genetic means because no distinction can be made between genetic and environmental differences between flocks. In this case, direct and maternal heritabilities are under-estimated, whereas maternal environmental effects are overestimated. The insufficiency of pedigree leads to biased estimates of genetic parameters.

Keywords

genetic parameters animal model maternal effects simulations connectedness

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Authors’ Affiliations

(1)
Station d'amélioration génétique des animaux, Institut national de la recherche agronomique
(2)
Station de génétique quantitative et appliquée, Institut national de la recherche agronomique
(3)
Département des sciences animales, Institut national agronomique Paris-Grignon

Copyright

© INRA, EDP Sciences 2001

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