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Liver transcriptome profile in pigs with extreme phenotypes of intramuscular fatty acid composition
Ramayo-Caldas, Yuliaxis (Centre de Recerca en Agrigenòmica)
Mach Casellas, Núria (Institut national de la recherche agronomique (França))
Esteve Codina, Anna (Centre de Recerca en Agrigenòmica)
Corominas Galbany, Jordi (Centre de Recerca en Agrigenòmica)
Castelló Farré, Anna (Centre de Recerca en Agrigenòmica)
Ballester Devis, Maria (Centre de Recerca en Agrigenòmica)
Estellé Fabrellas, Jordi (Institut national de la recherche agronomique (França))
Ibáñez Escriche, Noelia (Institut de Recerca i Tecnologia Agroalimentàries)
Fernández, Ana I. (Instituto Nacional de Investigaciones Agrarias (Espanya). Departamento de Mejora Genética Animal)
Perez-Enciso, Miguel (Universitat Autònoma de Barcelona. Departament de Ciència Animal i dels Aliments)
Folch Albareda, Josep Maria (Universitat Autònoma de Barcelona. Departament de Ciència Animal i dels Aliments)

Fecha: 2012
Resumen: Background: New advances in high-throughput technologies have allowed for the massive analysis of genomic data, providing new opportunities for the characterization of the transcriptome architectures. Recent studies in pigs have employed RNA-Seq to explore the transcriptome of different tissues in a reduced number of animals. The main goal of this study was the identification of differentially-expressed genes in the liver of Iberian x Landrace crossbred pigs showing extreme phenotypes for intramuscular fatty acid composition using RNA-Seq. Results: The liver transcriptomes of two female groups (H and L) with phenotypically extreme intramuscular fatty acid composition were sequenced using RNA-Seq. A total of 146 and 180 unannotated protein-coding genes were identified in intergenic regions for the L and H groups, respectively. In addition, a range of 5. 8 to 7. 3% of repetitive elements was found, with SINEs being the most abundant elements. The expression in liver of 186 (L) and 270 (H) lncRNAs was also detected. The higher reproducibility of the RNA-Seq data was validated by RT-qPCR and porcine expression microarrays, therefore showing a strong correlation between RT-qPCR and RNA-Seq data (ranking from 0. 79 to 0. 96), as well as between microarrays and RNA-Seq (r=0. 72). A differential expression analysis between H and L animals identified 55 genes differentially-expressed between groups. Pathways analysis revealed that these genes belong to biological functions, canonical pathways and three gene networks related to lipid and fatty acid metabolism. In concordance with the phenotypic classification, the pathways analysis inferred that linolenic and arachidonic acids metabolism was altered between extreme individuals. In addition, a connection was observed among the top three networks, hence suggesting that these genes are interconnected and play an important role in lipid and fatty acid metabolism. Conclusions: In the present study RNA-Seq was used as a tool to explore the liver transcriptome of pigs with extreme phenotypes for intramuscular fatty acid composition. The differential gene expression analysis showed potential gene networks which affect lipid and fatty acid metabolism. These results may help in the design of selection strategies to improve the sensorial and nutritional quality of pork meat.
Nota: Número d'acord de subvenció EC/FP7/222664
Nota: Número d'acord de subvenció MICINN/AGL2011-29821-C02-01
Nota: Número d'acord de subvenció MICINN/AGL2008-04818-C03/GAN
Nota: Número d'acord de subvenció MICINN/CSD2007-00036
Nota: Número d'acord de subvenció MEC/BES-2009-018223
Nota: Número d'acord de subvenció MEC/BES-2008-005772
Nota: Número d'acord de subvenció MEC/AP2008-01450
Derechos: Aquest document està subjecte a una llicència d'ús Creative Commons. Es permet la reproducció total o parcial, la distribució, la comunicació pública de l'obra i la creació d'obres derivades, fins i tot amb finalitats comercials, sempre i quan es reconegui l'autoria de l'obra original. Creative Commons
Lengua: Anglès
Documento: article ; publishedVersion
Publicado en: BMC genomics, Vol. 13, N. 547 (October 2012) , p. 1-18, ISSN 1471-2164

DOI: 10.1186/1471-2164-13-547
PMID: 23051667

18 p, 1.6 MB

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