Correlation between transcriptome and interactome mapping data from Saccharomyces cerevisiae

Genomic and proteomic approaches can provide hypotheses concerning function for the large number of genes predicted from genome sequences(1-5). Becaus e of the artificial nature of the assays, however, the information from the se high-throughput approaches should be considered with caution. Although i t is possible that more meaningful hypotheses could be formulated by integr ating the data from various functional genomic and proteomic projects(6), i t has yet to be seen to what extent the data can be correlated and how such integration can be achieved. We developed a 'transcriptome-interactome cor relation mapping' strategy to compare the interactions between proteins enc oded by genes that belong to common expression-profiling clusters with thos e between proteins encoded by genes that belong to different clusters. Usin g this strategy with currently available data sets for Saccharomyces cerevi siae, we provide the first global evidence that genes with similar expressi on profiles are more likely to encode interacting proteins. We show how thi s correlation between transcriptome and interactome data can be used to imp rove the quality of hypotheses based on the information from both approache s. The strategy described here may help to integrate other functional genom ic and proteomic data, both in yeast and in higher organisms.