An integrated regulatory network reveals pervasive cross-regulation among transcription and splicing factors
Traditionally the gene expression pathway has been regarded as being comprised of independent steps, from RNA transcription to protein translation. To date there is increasing evidence of coupling between the different processes of the pathway, specifically between transcription and splicing. Given the extensive cross-talk between these processes, we derived a transcription-splicing integrated network. The nodes of the network included experimentally verified human proteins belonging to three groups of regulators: transcription factors, splicing factors and kinases. The nodes were wired by instances of predicted transcriptional and alternative splicing regulation. Analysis of the network indicated a pervasive cross-regulation among the nodes; specifically, splicing factors are significantly more connected by alternative splicing regulatory edges relative to the two other subgroups, while transcription factors are more extensively controlled by transcriptional regulation. Furthermore, we found that splicing factors are the most regulated of the three regulatory groups and are subject to extensive combinatorial control by alternative splicing and transcriptional regulation. Consistent with the network results, our bioinformatics analyses showed that the subgroup of kinases have the highest density of predicted phosphorylation sites. Overall, our systematic study reveals that an organizing principle in the logic of integrated networks favor the regulation of regulatory proteins by the specific regulation they conduct. Based on these results, we propose a new regulatory paradigm postulating that gene expression regulation of the master regulators in the cell is predominantly achieved by cross-regulation.
Density of transcription and splicing regulation inedges. (A) Distribution of transcription regulation inedges for the three subgroups of network targets: SFs (red), TFs (blue) and kinases (yellow) (network reconstructed based on Dataset A). (B) Distribution of splicing regulation inedges for the three subgroups: SFs (red), TFs (blue) and kinases (yellow). (C) A diagram summarizing the transcription and AS predicted interactions among the three subgroups in the network; the arrows represent interactions across and between subgroups (blue and red arrows for transcriptional and splicing regulation, respectively). The average density of inedges per group is shown in numbers within the arrow and is represented by the color intensity of the arrow. As demonstrated, cross-regulation is far more prevalent than cross-talk for both transcriptional and AS regulation.