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      Genome-wide QTL analysis of meat quality-related traits in a large F 2 intercross between Landrace and Korean native pigs

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          Abstract

          Background

          We conducted a genome-wide linkage analysis to identify quantitative trait loci (QTL) that influence meat quality-related traits in a large F 2 intercross between Landrace and Korean native pigs. Thirteen meat quality-related traits of the m. longissimus lumborum et thoracis were measured in more than 830 F 2 progeny. All these animals were genotyped with 173 microsatellite markers located throughout the pig genome, and the GridQTL program based on the least squares regression model was used to perform the QTL analysis.

          Results

          We identified 23 genome-wide significant QTL in eight chromosome regions (SSC1, 2, 6, 7, 9, 12, 13, and 16) (SSC for Sus Scrofa) and detected 51 suggestive QTL in the 17 chromosome regions. QTL that affect 10 meat quality traits were detected on SSC12 and were highly significant at the genome-wide level. In particular, the QTL with the largest effect affected crude fat percentage and explained 22.5% of the phenotypic variance ( F-ratio = 278.0 under the additive model, nominal P = 5.5 × 10 −55). Interestingly, the QTL on SSC12 that influenced meat quality traits showed an obvious trend for co-localization.

          Conclusions

          Our results confirm several previously reported QTL. In addition, we identified novel QTL for meat quality traits, which together with the associated positional candidate genes improve the knowledge on the genetic structure that underlies genetic variation for meat quality traits in pigs.

          Electronic supplementary material

          The online version of this article (doi:10.1186/s12711-014-0080-6) contains supplementary material, which is available to authorized users.

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          Most cited references26

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          Identification of a mutation in porcine ryanodine receptor associated with malignant hyperthermia.

          Malignant hyperthermia (MH) causes neurological, liver, and kidney damage and death in humans and major economic losses in the swine industry. A single point mutation in the porcine gene for the skeletal muscle ryanodine receptor (ryr1) was found to be correlated with MH in five major breeds of lean, heavily muscled swine. Haplotyping suggests that the mutation in all five breeds has a common origin. Assuming that this is the causal mutation for MH, the development of a noninvasive diagnostic test will provide the basis for elimination of the MH gene or its controlled inclusion in swine breeding programs.
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            A mutation in PRKAG3 associated with excess glycogen content in pig skeletal muscle.

            A high proportion of purebred Hampshire pigs carries the dominant RN- mutation, which causes high glycogen content in skeletal muscle. The mutation has beneficial effects on meat content but detrimental effects on processing yield. Here, it is shown that the mutation is a nonconservative substitution (R200Q) in the PRKAG3 gene, which encodes a muscle-specific isoform of the regulatory gamma subunit of adenosine monophosphate-activated protein kinase (AMPK). Loss-of-function mutations in the homologous gene in yeast (SNF4) cause defects in glucose metabolism, including glycogen storage. Further analysis of the PRKAG3 signaling pathway may provide insights into muscle physiology as well as the pathogenesis of noninsulin-dependent diabetes mellitus in humans, a metabolic disorder associated with impaired glycogen synthesis.
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              Confidence intervals in QTL mapping by bootstrapping.

              The determination of empirical confidence intervals for the location of quantitative trait loci (QTLs) was investigated using simulation. Empirical confidence intervals were calculated using a bootstrap resampling method for a backcross population derived from inbred lines. Sample sizes were either 200 or 500 individuals, and the QTL explained 1, 5, or 10% of the phenotypic variance. The method worked well in that the proportion of empirical confidence intervals that contained the simulated QTL was close to expectation. In general, the confidence intervals were slightly conservatively biased. Correlations between the test statistic and the width of the confidence interval were strongly negative, so that the stronger the evidence for a QTL segregating, the smaller the empirical confidence interval for its location. The size of the average confidence interval depended heavily on the population size and the effect of the QTL. Marker spacing had only a small effect on the average empirical confidence interval. The LOD drop-off method to calculate empirical support intervals gave confidence intervals that generally were too small, in particular if confidence intervals were calculated only for samples above a certain significance threshold. The bootstrap method is easy to implement and is useful in the analysis of experimental data.
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                Author and article information

                Contributors
                choic4753@korea.kr
                yck1985@gnu.ac.kr
                bilf@gnu.ac.kr
                ejjung@gnu.ac.kr
                hansh04@naver.com
                lee6470@korea.kr
                koms21c@korea.kr
                s_htim@gnu.ac.kr
                heebok.park@cnu.ac.kr
                Journal
                Genet Sel Evol
                Genet. Sel. Evol
                Genetics, Selection, Evolution : GSE
                BioMed Central (London )
                0999-193X
                1297-9686
                22 February 2015
                22 February 2015
                2015
                : 47
                : 1
                : 7
                Affiliations
                [ ]Subtropical Animal Experiment Station, National Institute of Animal Science, Rural Development Administration, Jeju, 690-150 Korea
                [ ]Department of Animal Science, College of Agriculture and Life Sciences, Gyeongsang National University, Jinju, 660-701 Korea
                [ ]Institute of Agriculture and Life Science, Gyeongsang National University, Jinju, 660-701 Korea
                [ ]Department of Animal Science and Biotechnology (BK21 plus program), College of Agriculture and Life Sciences, Chungnam National University, Daejeon, 305-764 Korea
                Article
                80
                10.1186/s12711-014-0080-6
                4336478
                25888076
                f2d3491d-bedb-4406-9eac-708d9c33ae1c
                © Cho et al.; licensee BioMed Central. 2015

                This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

                History
                : 23 October 2013
                : 20 November 2014
                Categories
                Research
                Custom metadata
                © The Author(s) 2015

                Genetics
                Genetics

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