Evolutionarily conserved multisubunit RBL2/p130 and E2F4 protein complex represses human cell cycle-dependent genes in quiescence

The mammalian Retinoblastoma (RB) family including pRB, p107, and p130 represses E2F target genes through mechanisms that are not fully understood. In D. melanogaster, RB-dependent repression is mediated in part by the multisubunit protein complex Drosophila RBF, E2F, and Myb (dREAM) that contains homologs of the C. elegans synthetic multivulva class B (synMuvB) gene products. Using an integrated approach combining proteomics, genomics, and bioinformatic analyses, we identified a p130 complex termed DP, RB-like, E2F, and MuvB (DREAM) that contains mammalian homologs of synMuvB proteins LIN-9, LIN-37, LIN-52, LIN-54, and LIN-53/RBBP4. DREAM bound to more than 800 human promoters in G0 and was required for repression of E2F target genes. In S phase, MuvB proteins dissociated from p130 and formed a distinct submodule that bound MYB. This work reveals an evolutionarily conserved multisubunit protein complex that contains p130 and E2F4, but not pRB, and mediates the repression of cell cycle-dependent genes in quiescence.     

RB1CC1 protein positively regulates transforming growth factor-beta signaling through the modulation of Arkadia E3 ubiquitin ligase activity

Transforming growth factor-β (TGF-β) signaling is controlled by a variety of regulators, of which Smad7, c-Ski, and SnoN play a pivotal role in its negative regulation. Arkadia is a RING-type E3 ubiquitin ligase that targets these negative regulators for degradation to enhance TGF-β signaling. In the present study we identified a candidate human tumor suppressor gene product RB1CC1/FIP200 as a novel positive regulator of TGF-β signaling that functions as a substrate-selective cofactor of Arkadia. Overexpression of RB1CC1 enhanced TGF-β signaling, and knockdown of endogenous RB1CC1 attenuated TGF-β-induced expression of target genes as well as TGF-β-induced cytostasis. RB1CC1 down-regulated the protein levels of c-Ski but not SnoN by enhancing the activity of Arkadia E3 ligase toward c-Ski. Substrate selectivity is primarily attributable to the physical interaction of RB1CC1 with substrates, suggesting its role as a scaffold protein. RB1CC1 thus appears to play a unique role as a modulator of TGF-β signaling by restricting substrate specificity of Arkadia.     

Conditional mutual inclusive information enables accurate quantification of associations in gene regulatory networks

Mutual information (MI), a quantity describing the nonlinear dependence between two random variables, has been widely used to construct gene regulatory networks (GRNs). Despite its good performance, MI cannot separate the direct regulations from indirect ones among genes. Although the conditional mutual information (CMI) is able to identify the direct regulations, it generally underestimates the regulation strength, i.e. it may result in false negatives when inferring gene regulations. In this work, to overcome the problems, we propose a novel concept, namely conditional mutual inclusive information (CMI2), to describe the regulations between genes. Furthermore, with CMI2, we develop a new approach, namely CMI2NI (CMI2-based network inference), for reverse-engineering GRNs. In CMI2NI, CMI2 is used to quantify the mutual information between two genes given a third one through calculating the Kullback–Leibler divergence between the postulated distributions of including and excluding the edge between the two genes. The benchmark results on the GRNs from DREAM challenge as well as the SOS DNA repair network in Escherichia coli demonstrate the superior performance of CMI2NI. Specifically, even for gene expression data with small sample size, CMI2NI can not only infer the correct topology of the regulation networks but also accurately quantify the regulation strength between genes. As a case study, CMI2NI was also used to reconstruct cancer-specific GRNs using gene expression data from The Cancer Genome Atlas (TCGA). CMI2NI is freely accessible at http://www.comp-sysbio.org/cmi2ni.