Genetic network identification by high density, multiplexed reversed transcriptional (HD-MRT) analysis in steroidogenic axis model cell lines

Transcriptional network analysis in steroidogenic axis cell lines requires an understanding of cellular network composition and complexity. Previous studies have shown that absence of transcriptional network components in a cell line compromises that cell line's functional capacity for transcriptional regulation. Our goal was to analyze qualitatively steroidogenic axis-derived cell lines' expression of a putative transcriptional network involved in human and mouse development. To pursue this analysis we used Northern blots and a high density-multiplexed reverse transcription-polymerase chain reaction (HD-MRT-PCR) approach. Our results revealed that, while some members of this putative network were universally expressed, only a minority of the non-constitutive targeted transcripts were present in any single line. Based on our data and previously published results for contextual expression of these transcription factors, a model was constructed possessing the topology suggestive of a scale-free network: certain network members were highly connected nodes and would represent critical sites of vulnerability. The importance of these highly connected nodes for network function is supported by the severe phenotypes exhibited by human patients and animal models when these genes are mutated. We conclude that knowledge of network composition in specific cell lines is essential for their use as models to investigate functional interactions within selected subnetworks.