Research of biomarkers of beef qualities, tenderness and intramuscular fat content (IMF), follows the workflow of human disease biomarkers studies aimed to be clinically used for diagnosis (Rifai et al., 2006). The first step was the discovery of candidate biomarkers by comparing extreme groups of tenderness and IMF. Two-dimensional electrophoresis associated with mass spectrometry was first used (Picard and Gagaoua 2018), and further combined with a "label-free" quantitative shotgun (Bazile et al., 2019). Samples of semimembranosus muscle (SM) were collected on 89 cows of the French Maine Anjou Protected Denomination of Origin. Shotgun analysis revealed 875 proteins with a unique ID identified by at least 2 peptides among the 89 SM muscles. Comparative analysis of groups of high versus low tenderness and high versus low IMF (n=5 cows for each group), revealed respectively 53 and 77 proteins differentially abundant between groups. A second step consisted in predicting the tenderness and IMF on the whole population of the 89 cows. A logistic regression allowed to perfectly distinguish (100% well classified) the SM samples of high, medium or low tenderness with 7 proteins, and of high or low IMF with 5 proteins. Bioinformatic analysis with the ProteINSIDE tool (Kaspric et al., 2015) allows highlighting the corresponding biological functions. The next step is to select the method to be used in diagnostic tools to accurately qualify and quantify these biomarkers. Several MS-based methods allowing absolute quantification were compared including selected reaction monitoring (SRM), parallel reaction monitoring (PRM) and sequential windowed acquisition of all theoretical spectral SWATH-MS methods (Bons et al., 2018). PRM has qualified 6 proteins over 10 candidate biomarkers as differentially abundant between groups of muscles divergent by the tenderness or IMF values. A semi-quantitative immunological assay (Reverse Phase Protein Array) is currently developed to accurately and quickly assay these muscular proteins.