On the Consistency between Gene Expression and the Gene Regulatory Network of .

Transcriptional regulation of gene expression is crucial for the adaptation and survival of bacteria. Regulatory interactions are commonly modeled as Gene Regulatory Networks (GRNs) derived from experiments such as RNA-seq, microarray and ChIP-seq. While the reconstruction of GRNs is fundamental to decipher cellular function, even GRNs of economically important bacteria such as are incomplete. Here, we analyzed the predictive power of GRNs if used as in silico models for gene expression and investigated the consistency of the GRN with gene expression data from the GEO database. We assessed the consistency of the GRN using real, as well as simulated, expression data and showed that GRNs alone cannot explain the expression profiles well. Our results suggest that more sophisticated mechanisms such as a combination of transcriptional, post-transcriptional regulation and signaling should be taken into consideration when analyzing and constructing GRNs.