System-wide "omics" approaches have been widely applied to study a limited number of laboratory strains of Saccharomyces cerevisiae. More recently, industrial S. cerevisiae strains have become the target of such analyses, mainly to improve our understanding of biotechnologically relevant phenotypes that cannot be adequately studied in laboratory strains. Most of these studies have investigated single strains in a single medium. This experimental layout cannot differentiate between generally relevant molecular responses and strain- or media-specific features. Here we analyzed the transcriptomes of two phenotypically diverging wine yeast strains in two different fermentation media at three stages of wine fermentation. The data show that the intersection of transcriptome datasets from fermentations using either synthetic MS300 (simulated wine must) or real grape must (Colombard) can help to delineate relevant from "noisy" changes in gene expression in response to experimental factors such as fermentation stage and strain identity. The differences in the expression profiles of strains in the different environments also provide relevant insights into the transcriptional responses toward specific compositional features of the media. The data also suggest that MS300 is a representative environment for conducting research on wine fermentation and industrially relevant properties of wine yeast strains.