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      Differences in Muscle Transcriptome among Pigs Phenotypically Extreme for Fatty Acid Composition

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          Abstract

          Background

          Besides having an impact on human health, the porcine muscle fatty acid profile determines meat quality and taste. The RNA-Seq technologies allowed us to explore the pig muscle transcriptome with an unprecedented detail. The aim of this study was to identify differentially-expressed genes between two groups of 6 sows belonging to an Iberian × Landrace backcross with extreme phenotypes according to FA profile.

          Results

          We sequenced the muscle transcriptome acquiring 787.5 M of 75 bp paired-end reads. About 85.1% of reads were mapped to the reference genome. Of the total reads, 79.1% were located in exons, 6.0% in introns and 14.9% in intergenic regions, indicating expressed regions not annotated in the reference genome. We identified a 34.5% of the intergenic regions as interspersed repetitive regions. We predicted a total of 2,372 putative proteins. Pathway analysis with 131 differentially-expressed genes revealed that the most statistically-significant metabolic pathways were related with lipid metabolism. Moreover, 18 of the differentially-expressed genes were located in genomic regions associated with IMF composition in an independent GWAS study in the same genetic background. Thus, our results indicate that the lipid metabolism of FAs is differently modulated when the FA composition in muscle differs. For instance, a high content of PUFA may reduce FA and glucose uptake resulting in an inhibition of the lipogenesis. These results are consistent with previous studies of our group analysing the liver and the adipose tissue transcriptomes providing a view of each of the main organs involved in lipid metabolism.

          Conclusions

          The results obtained in the muscle transcriptome analysis increase the knowledge of the gene regulation of IMF deposition, FA profile and meat quality, in terms of taste and nutritional value. Besides, our results may be important in terms of human health.

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          Most cited references38

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          Identification of a lipokine, a lipid hormone linking adipose tissue to systemic metabolism.

          Dysregulation of lipid metabolism in individual tissues leads to systemic disruption of insulin action and glucose metabolism. Utilizing quantitative lipidomic analyses and mice deficient in adipose tissue lipid chaperones aP2 and mal1, we explored how metabolic alterations in adipose tissue are linked to whole-body metabolism through lipid signals. A robust increase in de novo lipogenesis rendered the adipose tissue of these mice resistant to the deleterious effects of dietary lipid exposure. Systemic lipid profiling also led to identification of C16:1n7-palmitoleate as an adipose tissue-derived lipid hormone that strongly stimulates muscle insulin action and suppresses hepatosteatosis. Our data reveal a lipid-mediated endocrine network and demonstrate that adipose tissue uses lipokines such as C16:1n7-palmitoleate to communicate with distant organs and regulate systemic metabolic homeostasis.
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            A novel ChREBP isoform in adipose tissue regulates systemic glucose metabolism

            Summary The prevalence of obesity and type 2-diabetes is increasing worldwide and threatens to shorten lifespan. Impaired insulin action in peripheral tissues is a major pathogenic factor. Insulin stimulates glucose uptake in adipose tissue through the Glut4-glucose transporter and alterations in adipose-Glut4 expression or function regulate systemic insulin sensitivity. Downregulation of adipose tissue-Glut4 occurs early in diabetes development. Here we report that adipose tissue-Glut4 regulates the expression of carbohydrate responsive-element binding protein (ChREBP), a transcriptional regulator of lipogenic and glycolytic genes. Furthermore, adipose-ChREBP is a major determinant of adipose tissue fatty acid synthesis and systemic insulin sensitivity. We discovered a new mechanism for glucose-regulation of ChREBP: Glucose-mediated activation of the canonical ChREBP isoform (ChREBPα) induces expression of a novel, potent isoform (ChREBPβ) that is transcribed from an alternative promoter. ChREBPβ expression in human adipose tissue predicts insulin sensitivity indicating that it may be an effective target for treating diabetes.
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              The lipogenic transcription factor ChREBP dissociates hepatic steatosis from insulin resistance in mice and humans.

              Nonalcoholic fatty liver disease (NAFLD) is associated with all features of the metabolic syndrome. Although deposition of excess triglycerides within liver cells, a hallmark of NAFLD, is associated with a loss of insulin sensitivity, it is not clear which cellular abnormality arises first. We have explored this in mice overexpressing carbohydrate responsive element-binding protein (ChREBP). On a standard diet, mice overexpressing ChREBP remained insulin sensitive, despite increased expression of genes involved in lipogenesis/fatty acid esterification and resultant hepatic steatosis (simple fatty liver). Lipidomic analysis revealed that the steatosis was associated with increased accumulation of monounsaturated fatty acids (MUFAs). In primary cultures of mouse hepatocytes, ChREBP overexpression induced expression of stearoyl-CoA desaturase 1 (Scd1), the enzyme responsible for the conversion of saturated fatty acids (SFAs) into MUFAs. SFA impairment of insulin-responsive Akt phosphorylation was therefore rescued by the elevation of Scd1 levels upon ChREBP overexpression, whereas pharmacological or shRNA-mediated reduction of Scd1 activity decreased the beneficial effect of ChREBP on Akt phosphorylation. Importantly, ChREBP-overexpressing mice fed a high-fat diet showed normal insulin levels and improved insulin signaling and glucose tolerance compared with controls, despite having greater hepatic steatosis. Finally, ChREBP expression in liver biopsies from patients with nonalcoholic steatohepatitis was increased when steatosis was greater than 50% and decreased in the presence of severe insulin resistance. Together, these results demonstrate that increased ChREBP can dissociate hepatic steatosis from insulin resistance, with beneficial effects on both glucose and lipid metabolism.
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                Author and article information

                Contributors
                Role: Editor
                Journal
                PLoS One
                PLoS ONE
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, USA )
                1932-6203
                2014
                13 June 2014
                : 9
                : 6
                : e99720
                Affiliations
                [1 ]Departament de Genètica Animal, Centre de Recerca en Agrigenòmica (CRAG), Bellaterra, Spain
                [2 ]Departament de Ciència Animal i dels Aliments, Universitat Autònoma de Barcelona (UAB), Bellaterra, Spain
                [3 ]Génétique Animale et Biologie Intégrative UMR1313 (GABI), Institut National de la Recherche Agronomique (INRA), Jouy-en-Josas, France
                [4 ]Génétique Animale et Biologie Intégrative UMR1313 (GABI), AgroParisTech, Jouy-en-Josas, France
                [5 ]Laboratoire de Radiobiologie et Etude du Génome (LREG), Commissariat à l'énergie atomique et aux énergies alternatives (CEA), Jouy-en-Josas, France
                [6 ]Departamento de Genética Animal, Instituto Nacional de Investigación y Tecnología Agraria y Alimentaria (INIA), Madrid, Spain
                [7 ]Computational and Systems Biology, Commonwealth Scientific and Industrial Research Organisation (CSIRO) Animal, Food and Health SciencesQLD, Brisbane, Australia
                [8 ]Departament de Genètica i Millora Animal, Institut de Recerca i Tecnologies Agroalimentàries (IRTA), Lleida, Spain
                INRA, France
                Author notes

                Competing Interests: The authors have declared that no competing interests exist.

                Conceived and designed the experiments: JMF MB. Performed the experiments: APO JMF MB. Analyzed the data: APO YRC MB JE. Contributed reagents/materials/analysis tools: JMF J. Corominas J. Casellas DPM JE YRC. Wrote the paper: APO JMF MB NH.

                Article
                PONE-D-13-54388
                10.1371/journal.pone.0099720
                4057286
                24926690
                8d8915be-f8ec-4832-a1d0-b835a39f0a7f
                Copyright @ 2014

                This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 23 December 2013
                : 19 May 2014
                Page count
                Pages: 11
                Funding
                This work has been funded by MICINN project AGL2011-29821-C02 (Ministerio de Economía y Competitividad) and by the Innovation Consolider-Ingenio 2010 Program (CSD2007-00036). A. Puig-Oliveras was funded by a Personal Investigador en Formación (PIF) PhD grant from the Universitat Autònoma de Barcelona (458-01-1/2011). J. Corominas was funded by a Formación de Personal Investigador (FPI) PhD grant from Spanish Ministerio de Educación (BES-2009-018223), Y. Ramayo by a Formación del Profesorado Universitario (FPU) PhD grant (AP2008-01450). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Research Article
                Biology and Life Sciences
                Computational Biology
                Genome Analysis
                Transcriptome Analysis
                Genome Expression Analysis
                Gene Prediction
                Genetics
                Animal Genetics
                Gene Expression
                Genomics
                Research and Analysis Methods
                Model Organisms
                Animal Models

                Uncategorized
                Uncategorized

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