RT Journal Article
SR Electronic
T1 The transcription factor basal regulatory network of Homo sapiens and Saccharomyces cerevisiae: uncovering the relationship between topology and phenotype
JF bioRxiv
FD Cold Spring Harbor Laboratory
SP 669697
DO 10.1101/669697
A1 JL Hernández-Domínguez
A1 A. Brass
A1 EM Navarro-López
YR 2019
UL http://biorxiv.org/content/early/2019/06/12/669697.abstract
AB Transcription factors play a key role in controlling which proteins are made by a cell. As transcription factors are themselves proteins, they are part of a complex interconnected and self-regulated network. We define the transcription factor basal regulatory network (TFBRN) as the network formed by the interactions between transcription factors (TFs) as proteins acting on target genes which are themselves TFs. The question then becomes as to whether topological features of this network are important in determining phenotypes caused by perturbations in TFs. To explore this, we developed two simple TFBRN models; one based on data from human TFs, and the other on the budding yeast. Even from this basic model we did find some very clear correlations between local topological measures and phenotypes seen in cancer and rare genetic diseases. This strongly suggests that the local network architecture of the TFBRN provides important information around the roles of transcription factors and the impacts to an organisation of their perturbation.Author Summary The human body is controlled by proteins whose production is coordinated by proteins known as transcription factors. These transcription factors can control multiple proteins, including other transcription factors. Does this network itself play any role in determining the properties of the transcription factors and their roles in cancer and disease? In this paper we find that there is a relationship between the local structures in the network and processes such as cancer and rare genetic diseases. We also found a similar relationship between local network characteristics and budding yeast phenotypes. This work therefore shows that simple properties of the network of interactions between transcription factors and their targets can be useful in determining the effects caused by changes in transcription factors (whether through deletion or allelic variation).