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Recherche de biomarqueurs plasmatiques pour prédire la qualité de la viande bovine

Abstract : A challenge for the ruminant sector is to predict and manage the phenotypic traits related to meat production and quality especially tenderness, a priority of the beef industry. Meat quality is a complex phenotype that can be evaluated only after slaughtering and meat ageing. Previous research efforts have investigated the potential of muscle-derived markers to assess meat quality from biopsy or on carcass samples. However, recent studies have reported relationship sometimes inverse between protein abundance and tenderness depending on the muscle type or animal considered. Thus, the identification of “generic” and low-invasive biomarkers is an issue for the beef sector. In this context, the objective of my PhD thesis was to discover plasma candidate biomarkers to predict and manage beef tenderness. To meet this objective, my research included two complementary approaches: (i) a molecular data aggregation from publicly available data combined with bioinformatics (in silico approach) to reconstruct the secretome associated withtenderness; (ii) a proteomic analysis (Shotgun LC-MS/MS) to identify plasma and muscle candidates (Longissimus et Rectus abdominis muscles) from contrasted tenderness groups of PGI Fleur d’Aubrac heifers. Extreme groups of tenderness were established based on three evaluation methods: Warner Bratzler Shear Force, sensory analysis, and according to a synthetic index which combines the previous two evaluation systems. Thanks to the combination of the two approaches, I can propose for the first time an atlas of 107 plasma candidate proteins to assess the tenderness in cattle, of which 32 are included in tenderness QTL. I could also complete the list of muscle candidates reported in the scientific literature. While published data report mainly data on male bovines (steers, bull calves), my PhD work allows to propose for the first time a list of plasma and novel muscle candidates for heifer tenderness. My results also contribute to improve knowledge on tenderness determinism, notably through the involvement of extracellular vesicles (micro-vesicular (EVs), macro-vesicular (exosomes)), and the primary cilia. This knowledge will help to design phenotypic tools for “tenderness potential” prediction, in living animal and to add value to high-quality beef sector.
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Sabrina Boudon. Recherche de biomarqueurs plasmatiques pour prédire la qualité de la viande bovine. Agronomie. Université Clermont Auvergne, 2020. Français. ⟨NNT : 2020CLFAC004⟩. ⟨tel-02901653⟩

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