Combs Miles (italysock70)

Based on the largest single-molecule R-loop dataset to date, we show that individual R-loops form non-randomly, defining discrete sets of overlapping molecular clusters that pile-up through larger R-loop zones. R-loops most often map to intronic regions and their individual start and stop positions do not match with intron-exon boundaries, reinforcing the model that they form co-transcriptionally from unspliced transcripts. SMRF-seq further established that R-loop distribution patterns are not simply driven by intrinsic DNA sequence features but most likely also reflect DNA topological constraints. Overall, DRIP-based and SMRF-based approaches independently provide a complementary and congruent view of R-loop distribution, consolidating our understanding of the principles underlying R-loop formation. The baseline level of transcription, variable and difficult to quantify, seriously complicates the normalization of comparative transcriptomic data, but its biological importance remains unappreciated. We show that this currently neglected ingredient is essential for controlling gene network multistability and therefore cellular differentiation. Basal expression is correlated to the degree of chromatin loosening measured by DNA accessibility, and systematically leads to cellular dedifferentiation as assessed by transcriptomic signatures, irrespective of the molecular and cellular tools used. Modeling gene network motifs formally involved in developmental bifurcations, reveals that the epigenetic landscapes of Waddington are restructured by the level of non-specific expression, such that the attractors of progenitor and differentiated cells can be mutually exclusive. This mechanism is universal and holds beyond the particular nature of the genes involved, provided the multistable circuits are correctly described with autonomous basal expression. These results explain the relationships long established between gene expression noise, chromatin decondensation and cellular dedifferentiation, and highlight how heterochromatin maintenance is essential for preventing pathological cellular reprogramming, age-related diseases and cancer. Recently generated proteomic data provides unprecedented insight into stress granule composition and stands as fruitful ground for further analysis. Stress granules are stress-induced biological assemblies that are of keen interest due to being linked to both long-term cell viability and a variety of protein aggregation-based diseases. Herein we compile recently published stress granule composition data, formed specifically through heat and oxidative stress, for both mammalian (Homo sapiens) and yeast (Saccharomyces cerevisiae) cells. Interrogation of the data reveals that stress granule proteins are enriched in features that favor protein liquid-liquid phase separation; being highly disordered, soluble, and abundant while maintaining a high level of protein-protein interactions under basal conditions. Furthermore, these "stress granuleomes" are shown to be enriched for multidomained, RNA-binding proteins with increased potential for post-translational modifications. Findings are consistent with the notion that stress granule formation is driven by protein liquid-liquid phase separation. Furthermore, stress granule proteins appear poised near solubility limits while possessing the ability to dynamically alter their phase behavior in response to external threat. Interestingly, several features, such as protein disorder, are more prominent among stress granule proteins which share homologs between yeast and mammalian systems also found within stress induced foci. We culminate results from our stress granule analysis into novel predictors for granule incorporation and validate the mammalian predictor's performance against multiple types of membraneless condensates and with colocalization microscopy. Non-coding RNAs (ncRNAs), such as lncRNAs, circRNAs and pri-miRNAs, play important roles in physiological and