Int J Biol Sci 2009; 5(6):528-542. doi:10.7150/ijbs.5.528 This issue

Research Paper

Discovery of novel genetic networks associated with 19 economically important traits in beef cattle

Zhihua Jiang1, ✉, Jennifer J. Michal1, Jie Chen1, Tyler F. Daniels1, Tanja Kunej1, Matthew D. Garcia2, Charles T. Gaskins1, Jan R. Busboom1, Leeson J. Alexander3, Raymond W. Wright Jr. 1, Michael D. MacNeil3

1. Department of Animal Sciences, Washington State University, Pullman, WA 99164-6351, USA;
2. School of Animal Sciences, Louisiana State University, Baton Rouge, LA 70803, USA;
3. USDA-ARS, Fort Keogh Livestock and Range Research Laboratory, Miles City, MT 59301, USA

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Jiang Z, Michal JJ, Chen J, Daniels TF, Kunej T, Garcia MD, Gaskins CT, Busboom JR, Alexander LJ, Wright Jr. RW, MacNeil MD. Discovery of novel genetic networks associated with 19 economically important traits in beef cattle. Int J Biol Sci 2009; 5(6):528-542. doi:10.7150/ijbs.5.528. Available from

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Quantitative or complex traits are determined by the combined effects of many loci, and are affected by genetic networks or molecular pathways. In the present study, we genotyped a total of 138 mutations, mainly single nucleotide polymorphisms derived from 71 functional genes on a Wagyu x Limousin reference population. Two hundred forty six F2 animals were measured for 5 carcass, 6 eating quality and 8 fatty acid composition traits. A total of 2,280 single marker-trait association runs with 120 tagged mutations selected based on the HAPLOVIEW analysis revealed 144 significant associations (P < 0.05), but 50 of them were removed from the analysis due to the small number of animals (≤ 9) in one genotype group or absence of one genotype among three genotypes. The remaining 94 single-trait associations were then placed into three groups of quantitative trait modes (QTMs) with additive, dominant and overdominant effects. All significant markers and their QTMs associated with each of these 19 traits were involved in a linear regression model analysis, which confirmed single-gene associations for 4 traits, but revealed two-gene networks for 8 traits and three-gene networks for 5 traits. Such genetic networks involving both genotypes and QTMs resulted in high correlations between predicted and actual values of performance, thus providing evidence that the classical Mendelian principles of inheritance can be applied in understanding genetic complexity of complex phenotypes. Our present study also indicated that carcass, eating quality and fatty acid composition traits rarely share genetic networks. Therefore, marker-assisted selection for improvement of one category of these traits would not interfere with improvement of another.

Keywords: Quantitative traits, quantitative trait modes, genetic networks, beef cattle.