Longissimus and semimembranosus muscles transcriptome comparison in pig displays marked differences
Herault , Frédéric (INRA , Saint Gilles (France). UMR 1348 Physiologie, Environnement et Génétique pour l'Animal et les Systèmes d'Elevage ) | Vincent , Annie (INRA , Saint Gilles (France). UMR 1348 Physiologie, Environnement et Génétique pour l'Animal et les Systèmes d'Elevage ) | Dameron , Olivier (Institut National de la Santé et de la Recherche Médicale, Rennes(France). UMR936) | Le Roy , Pascale (INRA , Saint Gilles (France). UMR 1348 Physiologie, Environnement et Génétique pour l'Animal et les Systèmes d'Elevage ) | Cherel , Pierre (Hendrix Genetics, Saint Jean de Braye) | Damon , Marie (INRA , Saint Gilles (France). UMR 1348 Physiologie, Environnement et Génétique pour l'Animal et les Systèmes d'Elevage )
Longissimus lumborum (LM) and semimembranosus (SM) are used for different meat consumption. Both are classified as glycolytic muscles but have different myofiber composition and metabolic properties. Compare LM and SM transcriptome profiles may clarify the biological events which could explain their phenotypic differences. The 90 pigs used in this study were produced as an inter-cross between 2 commercial sire lines. Muscle samples were collected 20 minutes post-mortem, snap frozen and used for total RNA isolation. Transcriptome analysis was undertaken using a pig muscle microarray: the 15K Genmascqchip. Analyses were performed using R software. Raw data were submitted to quality filtration and normalization. Probes with the smallest expression variability were filtered out. Normalized data were analyzed using a linear model of variance taking into account fixed effects of slaughter date, sex, sire and muscle. Carcass weight was used as a covariate. Genes wh ich were differentially expressed between muscles were clustered according to their semantic similarities. Semantic similarities were computed according to Wang’s method using Gene Ontology (GO) Biological Process (BP) terms. Thus, functional characterizations of genes clusters were performed with WebGestalt using GO BP terms. A total of 3,867 genes were differentially expressed between the 2 muscles, out of which 1,729 and 2,138 were over-represented respectively in LM and in SM. A set of 1,047 differentially expressed genes with a muscle fold change ratio above 1.5 was used for functional characterization. Five clusters related to energy metabolism, cell cycle, gene expression, anatomical structure development and signal transduction/immune response were identified. These results shed light on differential transcriptome profiles between LM and SM. This variability could affect muscle development and hence meat quality.
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