Decoding dendritic cell function through module and network analysis

Systems biology approaches that utilize large genomic data sets hold great potential for deciphering complex immunological process. In this paper, we propose such an approach to derive informative modules and networks from large gene expression data sets. Our approach starts with the clustering of such data sets to derive groups of tightly co-expressed genes, also known as co-expression modules. These modules are then converted into co-expression networks, and combined with transcriptional regulatory and protein interaction data to generate integrated networks that can help decipher the regulatory structure of these modules. We use this approach to derive the first set of modules and networks focused on dendritic cells (DCs). These cells are responsible for sampling the local environment to inform the adaptive immune system about peripheral stimuli, thus leading to the induction of an immune response. Using the ImmGen gene expression data set, we derive co-expression modules and integrated networks for the pDC, cDC and CD8. + DC subsets. In addition to recapitulating genes known to regulate the functions of these subsets, these networks reveal several novel genes and interactions that might have important roles in DC biology.