No abstract

Protein sumoylation is an important reversible post-translational modification on proteins, and orchestrates a variety of cellular processes. Recently, computational prediction of sumoylation sites has attracted much attention for its cost-efficiency and power in genomic data mining. In this work, we developed SUMOsp 2.0, an accurate computing program with an improved group-based phosphorylation scoring algorithm. Our analysis demonstrated that SUMOsp 2.0 has greater prediction accuracy than SUMOsp 1.0 and other existing tools, with a sensitivity of 88.17% and a specificity of 92.69% under the medium threshold. Previously, several large-scale experiments have identified a list of potential sumoylated substrates in Saccharomyces cerevisiae and Homo sapiens; however, the exact sumoylation sites in most of these proteins remain elusive. We have predicted potential sumoylation sites in these proteins using SUMOsp 2.0, which provides a great resource for researchers and an outline for further mechanistic studies of sumoylation in cellular plasticity and dynamics. The online service and local packages of SUMOsp 2.0 are freely available at: http://sumosp.biocuckoo.org/.

We combine the labeling of newly transcribed RNAs with 5-ethynyluridine with the characterization of bound proteins. This approach, named capture of the newly transcribed RNA interactome using click chemistry (RICK), systematically captures proteins bound to a wide range of RNAs, including nascent RNAs and traditionally neglected nonpolyadenylated RNAs. RICK has identified mitotic regulators amongst other novel RNA-binding proteins with preferential affinity for nonpolyadenylated RNAs, revealed a link between metabolic enzymes/factors and nascent RNAs, and expanded the known RNA-bound proteome of mouse embryonic stem cells. RICK will facilitate an in-depth interrogation of the total RNA-bound proteome in different cells and systems.