Staff Publications

Staff Publications

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    'Staff publications' is the digital repository of Wageningen University & Research

    'Staff publications' contains references to publications authored by Wageningen University staff from 1976 onward.

    Publications authored by the staff of the Research Institutes are available from 1995 onwards.

    Full text documents are added when available. The database is updated daily and currently holds about 240,000 items, of which 72,000 in open access.

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Record number 342232
Title Comparison of different strategies to analyze growth and carcass traits in a crossbred pig population: Finite and infinitesimal polygenic models
Author(s) Moraes Gonçalves, T. de; Nunes de Oliveira, H.; Bovenhuis, H.; Bink, M.C.A.M.; Arendonk, J.A.M. van
Source Revista Brasileira de Zootecnia 34 (2005)5. - ISSN 1516-3598 - p. 1531 - 1539.
Department(s) Animal Breeding and Genetics
PRI Biometris
Publication type Refereed Article in a scientific journal
Publication year 2005
Keyword(s) meat quality traits - pedigree-analysis - loci - inheritance - components - fertility - holsteins - variance
Abstract A Bayesian marker-free segregation analysis was applied for the estimation of variance components and to search for evidence of segregation genes affecting two carcass traits: intramuscular fat (IMF), %, and backfat thickness (BF), mm ; and one growth trait: body weight gain (LG) from 25 to 90 kg, approximately, g/day. In this study, 1,257 animals from the F2 design produced by breeding among pigs Meishan (male) and Dutch Large White and Landrace lines (female) were used. In animal breeding, finite polygenic models (FPM) may be an alternative to the infinitesimal polygenic model (IPM) for genetic evaluation of populations with multiple-generations pedigree for quantitative traits. FPM, IPM and FPM combined with IPM were empirically tested for estimation of variance components and number of genes in FPM. Estimation of marginal posteriori means of variance components and parameters were performed by using Markov Chain Monte Carlo techniques with the Gibbs sampler and the reversible Jump sampler (Metropolis-Hastings). The results showed evidence for four Major Genes (MG), i.e., two for IMF and two BF. For BF, the MG explained almost all of genetic variance, while for IMF, MG reduced the polygenic variance significantly. The LG was not likely influenced by MG. The polygenic heritability estimates for IMF, BF and LG were 0.37, 0.24 and 0.37, respectively. Further molecular genetic research, based on the same experimental data, aiming to map the major genes estimated for IMF and BF has a high probability of success.
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