RNF20 and USP44 regulate stem cell differentiation by modulating H2B monoubiquitylation.

Embryonic stem cells (ESCs) maintain high genomic plasticity, which is essential for their capacity to enter diverse differentiation pathways. Posttranscriptional modifications of chromatin histones play a pivotal role in maintaining this plasticity. We now report that one such modification, monoubiquitylation of histone H2B on lysine 120 (H2Bub1), catalyzed by the E3 ligase RNF20, increases during ESC differentiation and is required for efficient execution of this process. This increase is particularly important for the transcriptional induction of relatively long genes during ESC differentiation. Furthermore, we identify the deubiquitinase USP44 as a negative regulator of H2B ubiquitylation, whose downregulation during ESC differentiation contributes to the increase in H2Bub1. Our findings suggest that optimal ESC differentiation requires dynamic changes in H2B ubiquitylation patterns, which must occur in a timely and well-coordinated manner.

Molecular dissection of the genetic mechanisms that underlie expression conservation in orthologous yeast ribosomal promoters.

Recent studies have shown a surprising phenomenon, whereby orthologous regulatory regions from different species drive similar expression levels despite being highly diverged in sequence. Here, we investigated this phenomenon by genomically integrating hundreds of ribosomal protein (RP) promoters from nine different yeast species into S. cerevisiae and accurately measuring their activity. We found that orthologous RP promoters have extreme expression conservation even across evolutionarily distinct yeast species. Notably, our measurements reveal two distinct mechanisms that underlie this conservation and which act in different regions of the promoter. In the core promoter region, we found compensatory changes, whereby effects of sequence variations in one part of the core promoter were reversed by variations in another part. In contrast, we observed robustness in Rap1 transcription factor binding sites, whereby significant sequence variations had little effect on promoter activity. Finally, cases in which orthologous promoter activities were not conserved could largely be explained by the sequence variation within the core promoter. Together, our results provide novel insights into the mechanisms by which expression is conserved throughout evolution across diverged promoter sequences.

SPIKE--a database, visualization and analysis tool of cellular signaling pathways.

BACKGROUND: Biological signaling pathways that govern cellular physiology form an intricate web of tightly regulated interlocking processes. Data on these regulatory networks are accumulating at an unprecedented pace. The assimilation, visualization and interpretation of these data have become a major challenge in biological research, and once met, will greatly boost our ability to understand cell functioning on a systems level. RESULTS: To cope with this challenge, we are developing the SPIKE knowledge-base of signaling pathways. SPIKE contains three main software components: 1) A database (DB) of biological signaling pathways. Carefully curated information from the literature and data from large public sources constitute distinct tiers of the DB. 2) A visualization package that allows interactive graphic representations of regulatory interactions stored in the DB and superposition of functional genomic and proteomic data on the maps. 3) An algorithmic inference engine that analyzes the networks for novel functional interplays between network components.SPIKE is designed and implemented as a community tool and therefore provides a user-friendly interface that allows registered users to upload data to SPIKE DB. Our vision is that the DB will be populated by a distributed and highly collaborative effort undertaken by multiple groups in the research community, where each group contributes data in its field of expertise. CONCLUSION: The integrated capabilities of SPIKE make it a powerful platform for the analysis of signaling networks and the integration of knowledge on such networks with omics data.