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

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          Abstract

          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 F 2 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.

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          Most cited references34

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          Complete structure of the 11-subunit bovine mitochondrial cytochrome bc1 complex.

          Mitochondrial cytochrome bc1 complex performs two functions: It is a respiratory multienzyme complex and it recognizes a mitochondrial targeting presequence. Refined crystal structures of the 11-subunit bc1 complex from bovine heart reveal full views of this bifunctional enzyme. The "Rieske" iron-sulfur protein subunit shows significant conformational changes in different crystal forms, suggesting a new electron transport mechanism of the enzyme. The mitochondrial targeting presequence of the "Rieske" protein (subunit 9) is lodged between the two "core" subunits at the matrix side of the complex. These "core" subunits are related to the matrix processing peptidase, and the structure unveils how mitochondrial targeting presequences are recognized.
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            Replication and transcription of vertebrate mitochondrial DNA.

            D Clayton (1990)
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              Finding the molecular basis of quantitative traits: successes and pitfalls.

              Understanding the molecular basis of quantitative genetic variation is a principal goal for biomedicine. Although the complex genetic architecture of quantitative traits has so far largely frustrated attempts to identify genes in humans by standard linkage methodologies, quantitative trait loci (QTL) have been mapped in plants, insects and rodents. However, identifying the molecular bases of QTL remains a challenge. Here, we discuss why this is and how new experimental strategies and analytical techniques, combined with the fruits of the genome projects, are beginning to identify candidate genes for QTL studies in several model organisms.
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                Author and article information

                Journal
                Int J Biol Sci
                ijbs
                International Journal of Biological Sciences
                Ivyspring International Publisher (Sydney )
                1449-2288
                2009
                29 July 2009
                : 5
                : 6
                : 528-542
                Affiliations
                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
                Author notes
                ✉ Correspondence to: Dr. Zhihua Jiang, Department of Animal Sciences, Washington State University, Pullman, WA 99164 - 6351. Tel: +509 335 8761; Fax: +509 335 4246; E-mail: jiangz@ 123456wsu.edu

                Conflict of interests: The authors have declared that no conflict of interest exists.

                Article
                ijbsv05p0528
                10.7150/ijbs.5.528
                2726579
                19727437
                8bebbfb8-5bf6-43cb-8af6-00dfa45bea53
                © Ivyspring International Publisher. This is an open-access article distributed under the terms of the Creative Commons License (http://creativecommons.org/licenses/by-nc-nd/3.0/). Reproduction is permitted for personal, noncommercial use, provided that the article is in whole, unmodified, and properly cited.
                History
                : 5 June 2009
                : 16 July 2009
                Categories
                Research Paper

                Life sciences
                beef cattle.,genetic networks,quantitative trait modes,quantitative traits
                Life sciences
                beef cattle., genetic networks, quantitative trait modes, quantitative traits

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