When performed at the whole genome sequence level, the meta-analysis (MA) of within-population GWAS results can be powerful and accurate to identify causal variants for complex traits. An objective of the H2020 BovReg project is to perform MA at the sequence level for various dairy and beef cattle traits. For beef production, five partners from France, Switzerland, Germany, and Canada contributed with 54,782 animals from 15 purebred populations Charolais, Montbéliarde, Normande, Limousine, Blonde d’Aquitaine, Brown Swiss, Original Braunvieh or crossbred Charolais x Holstein, and Angus, Charolais and beef composite. Each partner conducted sequence-based within-population GWAS for 4 growth, 9 morphology, and/or 15 carcass traits. We combined these GWAS results to conduct 16 MA with both fixed effects and z-score methods. This study demonstrates the value of MA, in complement to within-population GWAS, in identifying a larger number of QTL, a lower number of variants in QTL and candidate variants located more frequently in genes. By applying here the most commonly MA methods used for GWAS, we confirm that the fixed effects method appears more powerful in detecting QTL, although MA combine substantially different traits in the present study. In several regions, MA directly pointed out variants in genes, including MSTN, LCORL, ARRDC3, and PLAG1, previously associated with morphology and carcass traits in various studies. For example, the Q204X mutation, ranked 1st in the QTL peaks at the proximal end of BTA2 and causing a premature stop codon in the gene encoding myostatin (MSTN), was reported as one of the polymorphisms responsible for the double-muscled phenotype in several cattle breeds. We also identified dozens of other variants located in genes having a function that may be related to meat production traits (e.g. COL3A1 collagen type III alpha 1 chain). By better identifying genes and candidate causative variants associated with beef production traits in cattle, MA appear to be of great interest to decipher the biological mechanisms underlying these traits. The BovReg project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 815668.