Correlation between the gene expression profiles and the protein-protein interactions within and across different genomes

Nitin Bhardwaj, Hui Lu

Department of Bioengineering, University of Illinois at Chicago, IL, USA

Function annotation of an unclassified protein on the basis of its interaction partners is well documented in literature. Reliable predictions of interactions from other data sources such as gene expression measurements would provide a useful route to function annotation. We investigate the global relationship of protein-protein interactions with gene expression. This relationship is studied in four evolutionarily diverse species, for which substantial information regarding their interactions and expression is available: human, mouse, yeast and E. coli. In E. Coli the expression of interacting pairs is highly correlated in comparison to random pairs, while in the other three species the correlation of expression of interacting pairs is only slightly stronger than that of random pairs. To strengthen the correlation, we developed a protocol to integrate ortholog information into the interaction and expression datasets. In all four genomes, the likelihood of predicting protein interactions from highly correlated expression data is increased using our protocol. In yeast, for example, the likelihood of predicting a true interaction, when the correlation is higher than 0.9, increases from 1.4 to 9.4. The improvement demonstrates that protein interactions are reflected in gene expression and the correlation between the two is strengthened by evolution information. The results establish that co-expression of interacting protein pairs is more conserved than that of random ones.

Supplementary data:

Protein-protein interaction list for the four species (as of Sept 2003)

Expression data for the four species

Complete list of the metagenes across the species