Literature DB >> 11811452

Estimation of additive and nonadditive genetic variances in Hereford, Gelbvieh, and Charolais by Method R.

M Duangjinda1, J K Bertrand, I Misztal, T Druet.   

Abstract

Parameters for direct and maternal dominance were estimated in models that included non-additive genetic effects. The analyses used weaning weight records adjusted for age of dam from populations of Canadian Hereford (n = 467,814), American Gelbvieh (n = 501,552), and American Charolais (n = 314,552). Method R estimates of direct additive genetic, maternal additive genetic, permanent maternal environment, direct dominance, and maternal dominance variances as a proportion of the total variance were 23, 12, 13, 19, and 14% in Hereford; 27, 7, 10, 18, and 2% in Gelbvieh; and 34, 15, 15, 23, and 2% in Charolais. The correlations between direct and maternal additive genetic effects were -0.30, -0.23, and -0.47 in Hereford, Gelbvieh, and Charolais, respectively. The correlations between direct and maternal dominance were -0.38, -0.02, and -0.04 in Hereford, Gelbvieh, and Charolais, respectively. Estimates of inbreeding depression were -0.20, -0.18, and -0.13 kg per 1% of inbreeding for Hereford, Gelbvieh, and Charolais, respectively. Estimates of the maternal inbreeding depression were -0.01, -0.02, and -0.02 kg, respectively. The high ratio of direct dominance to additive genetic variances provided some evidence that direct dominance effects should be considered in beef cattle evaluation. However, maternal dominance effects seemed to be important only for Hereford cattle.

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Year:  2001        PMID: 11811452     DOI: 10.2527/2001.79122997x

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


  3 in total

1.  Genetic and phenotypic parameters and annual trends for growth and fertility traits of Charolais and Hereford beef cattle breeds in Kenya.

Authors:  J S K Orenge; E D Ilatsia; I S Kosgey; A K Kahi
Journal:  Trop Anim Health Prod       Date:  2008-10-31       Impact factor: 1.559

2.  Estimating additive and non-additive genetic variances and predicting genetic merits using genome-wide dense single nucleotide polymorphism markers.

Authors:  Guosheng Su; Ole F Christensen; Tage Ostersen; Mark Henryon; Mogens S Lund
Journal:  PLoS One       Date:  2012-09-13       Impact factor: 3.240

3.  Improvement of prediction ability for genomic selection of dairy cattle by including dominance effects.

Authors:  Chuanyu Sun; Paul M VanRaden; John B Cole; Jeffrey R O'Connell
Journal:  PLoS One       Date:  2014-08-01       Impact factor: 3.240

  3 in total

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