Use of microsatellite markers to detect quantitative trait loci in yorkshire pigs

To identify genetic markers associated with economic traits in pigs, 157 microsatellite markers were examined in Yorkshire pigs. Thirty eight female Yorkshire pigs were initially examined and six of them were selected as progenitors; half were more than 1.5 standard deviations (SD) above the mean fo...

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Veröffentlicht in:Journal of Reproduction and Development 2006, Vol.52(2), pp.229-237
Hauptverfasser: Kim, C.W.(Jinju National Univ. (Korea R.)), Hong, Y.H, Yun, S.I, Lee, S.R, Kim, Y.H, Kim, M.S, Chung, K.H, Jung, W.Y, Kwon, E.J, Hwang, S.S, Park, D.H, Cho, K. K, Lee, J.G, Kim, B.W, Kim, J.W, Kang, Y.S, Yeo, J.S, Chang, K.T
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Sprache:eng
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Zusammenfassung:To identify genetic markers associated with economic traits in pigs, 157 microsatellite markers were examined in Yorkshire pigs. Thirty eight female Yorkshire pigs were initially examined and six of them were selected as progenitors; half were more than 1.5 standard deviations (SD) above the mean for average daily gain (ADG) and backfat thickness (BFT), and the remaining half were more than 1.5 SD below the mean. These pigs were then mated to male Duroc pigs, and 200 F2 pig offspring were examined for the association of specific alleles with ADG and BFT. To confirm the specific markers identified in the initial analysis, associations of significant markers with economic traits were further examined in 228 additional performance-tested purebred pigs. Twenty-five microsatellite markers were significantly associated with either ADG or BFT, and among these, 17 were associated with both traits. The markers with the highest association to ADG were also associated with BFT. Our study reveals that specific markers could be used to predict economic significance, and confirms several quantitative trait loci (QTL) identified in previous studies. However, further analysis with more closely-spaced microsatellite markers is required to refine predictive values for economic traits and positions of QTL that are reliable for actual phenotypic prediction.
ISSN:0916-8818
1348-4400
DOI:10.1262/jrd.17046