Alternative models for detection of quantitative trait loci (QTL) for growth and carcass traits in pigs chromosomes 4, 5 and 7

T. de Moraes Gonçalves, H. Nunes de Oliveira, H. Bovenhuis, M.C.A.M. Bink, J.A.M. van Arendonk

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4 Citations (Scopus)

Abstract

Genome scans can be used to identify chromosomal regions and eventually genes that control quantitative traits (QTL) of economic importance. In an experimental cross between Meishan (male) and Dutch Large White and Landrace lines (female), 298 F1 and 831 F2 animals were evaluated for intramuscular fat (GIM), % and growth trait: body weight gain (GP) from approximately 25 to 90 kg, g/day and 324 F1 and 805 F2 for backfat thickness, mm (ET). The animals of generations F1 and F2 were typed for 29 microsatellite markers. Linkage was studied among chromosomes 4, 6, 7 and GIM, ETand GP. QTL analyses using Bayesian methodology was applied under three genetic models: infinitesimal polygenic model (MPI); finite polygenic model (MPF) with three loci and MPF combined with MPI. The number of QTL, their map positions in the three chromosomes, and phenotypic effects were all estimated simultaneously within the same framework. The summaries of the estimated parameters were based on the marginal posterior distributions, that were obtained through Markov chain Monte Carlo (MCMC) methods. The results showed two QTLs for GIM on chromosomes 4 and 6 and two for ET on chromosomes 4 and 7. QTLs on chromosome 4 for ET and GIM were detected only under the PMI. Failure of theses approaches to detect weight gain QTL was possibly due to insufficient power from marker data or due to absence of segregating QTL on the chromosomes 4, 6 and 7 for this population. This study shows the benefit of analyzing experimental data under different genetic models and these analyses clearly illustrate the utility and wide applicability of Bayesian methodology.
Original languageEnglish
Pages (from-to)1540-1552
JournalRevista Brasileira de Zootecnia
Volume34
Issue number5
Publication statusPublished - 2005

Keywords

  • chain-monte-carlo
  • meat quality traits
  • intramuscular fat
  • backfat thickness
  • bayesian-analysis
  • pedigree-analysis
  • fatness
  • populations
  • genes
  • cross

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