The yeast Saccharomyces cerevisiae is an attractive industrial host for the production of a wide range of bulk and fine chemicals, such as biofuels, flavors and fragrances or pharmaceutical products. The intermediates of yeast central carbon metabolism (CCM) are the building blocks of these biosynthetic pathways. Their production kinetics and intracellular availability depend on the balance of numerous single intracellular reactions, which together form intracellular fluxes. Therefore, efficient product biosynthesis is influenced by the distribution of these fluxes. We recently demonstrated great variations in the metabolic fluxes of CCM between yeast strains of different origins. However, due to the complexity of flux regulatory mechanisms, we have a limited understanding of how fluxes are modulated and even less knowledge about the genetic basis of variations in flux distributions. In this study, we investigated the potential of quantitative trait locus (QTL) mapping to elucidate the genetic variations responsible for differences in metabolic flux distributions (fQTL) using a population of 130 F2-segregants from a cross of two wine yeast strains. Intracellular metabolic fluxes were estimated by constraint-based modeling and used as quantitative phenotypes, and differences in fluxes were linked to genomic variations in the progeny population. Using this approach, we detected four fQTLs that influence metabolic pathways. The molecular dissection of these QTLs revealed the contribution of two allelic gene variants, PDB1 and VID30, which have an influence on glycolysis, glycerol synthesis, ethanol synthesis, tricarboxylic acid cycle fluxes and transport and excretion of main metabolites. The elucidation of genetic determinants influencing metabolic fluxes, as reported here for the first time, creates new opportunities for the development of strains with optimized metabolite profiles for various applications using metabolic engineering or breeding strategies.