Literature DB >> 27625008

Estimation of genetic (co)variances of Gompertz growth function parameters in pigs.

J M Coyne1,2,3, K Matilainen2, D P Berry1, M-L Sevon-Aimonen2, E A Mäntysaari2, J Juga3, T Serenius4, N McHugh1.   

Abstract

The objective of this study was to estimate genetic (co)variances for the Gompertz growth function parameters, asymptotic mature weight (A), the ratio of mature weight to birthweight (B) and rate of maturation (k), using alternative modelling approaches. The data set consisted of 51 893 live weight records from 10 201 growing pigs. The growth of each pig was modelled using the Gompertz model employing either a two-step fixed effect or mixed model approach or a one-step mixed model approach using restricted maximum likelihood for the estimation of genetic (co)variance. Heritability estimates for the Gompertz growth function parameters, A (0.40), B (0.69) and k (0.45), were greatest for the one-step approach, compared with the two-step fixed effects approach, A (0.10), B (0.33) and k (0.13), and the two-step mixed model approach, A (0.17), B (0.32) and k (0.18). Inferred genetic correlations (i.e. correlations of estimated breeding values) between growth function parameters within models ranged from -0.78 to 0.76, and across models ranged from 0.28 to 0.73 for parameter A, 0.75 to 0.88 for parameter B and 0.09 to 0.37 for parameter k. Correlations between predicted daily sire live weights based on the Gompertz growth curve parameters' estimated breeding values from 60 to 200 days of age between all three modelled approaches were moderately to strongly correlated (0.75 to 0.95). Results from this study provide heritability estimates for biologically interpretable parameters of pig growth through the quantification of genetic (co)variances, thereby facilitating the estimation of breeding values for inclusion in breeding objectives to aid in breeding and selection decisions.
© 2016 Blackwell Verlag GmbH.

Entities:  

Keywords:  Genetic (co)variances; Gompertz; heritability; pigs

Mesh:

Year:  2016        PMID: 27625008     DOI: 10.1111/jbg.12237

Source DB:  PubMed          Journal:  J Anim Breed Genet        ISSN: 0931-2668            Impact factor:   2.380


  2 in total

1.  Evaluation of feed efficiency traits for genetic improvement in Japanese Black cattle.

Authors:  Masayuki Takeda; Yoshinobu Uemoto; Keiichi Inoue; Atsushi Ogino; Takayoshi Nozaki; Kazuhito Kurogi; Takanori Yasumori; Masahiro Satoh
Journal:  J Anim Sci       Date:  2018-04-03       Impact factor: 3.159

2.  Bayesian, Likelihood-Free Modelling of Phenotypic Plasticity and Variability in Individuals and Populations.

Authors:  Joao A N Filipe; Ilias Kyriazakis
Journal:  Front Genet       Date:  2019-09-20       Impact factor: 4.599

  2 in total

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