The DNA damage response acts as a safeguardagainst harmful DNA–RNA hybrids ofdifferent origins

Despite playing physiological roles in specific situations, DNA–RNA hybrids threat genome integrity. To investigate how cells do counteract spontaneous DNA–RNA hybrids, here we screen an siRNA library covering 240 human DNA damage response (DDR) genes and select siRNAs causing DNA–RNA hybrid accumulation and a significant increase in hybrid‐dependent DNA breakage. We identify post‐replicative repair and DNA damage checkpoint factors, including those of the ATM/CHK2 and ATR/CHK1 pathways. Thus, spontaneous DNA–RNA hybrids are likely a major source of replication stress, but they can also accumulate and menace genome integrity as a consequence of unrepaired DSBs and post‐replicative ssDNA gaps in normal cells. We show that DNA–RNA hybrid accumulation correlates with increased DNA damage and chromatin compaction marks. Our results suggest that different mechanisms can lead to DNA–RNA hybrids with distinct consequences for replication and DNA dynamics at each cell cycle stage and support the conclusion that DNA–RNA hybrids are a common source of spontaneous DNA damage that remains unsolved under a deficient DDR.European Research Council (ERC2014AdG669898TARLOOP)Worldwide Cancer Research (WCR15-00098

A Bayesian measurement error model for two-channel cell-based RNAi data with replicates

RNA interference (RNAi) is an endogenous cellular process in which small double-stranded RNAs lead to the destruction of mRNAs with complementary nucleoside sequence. With the production of RNAi libraries, large-scale RNAi screening in human cells can be conducted to identify unknown genes involved in a biological pathway. One challenge researchers face is how to deal with the multiple testing issue and the related false positive rate (FDR) and false negative rate (FNR). This paper proposes a Bayesian hierarchical measurement error model for the analysis of data from a two-channel RNAi high-throughput experiment with replicates, in which both the activity of a particular biological pathway and cell viability are monitored and the goal is to identify short hair-pin RNAs (shRNAs) that affect the pathway activity without affecting cell activity. Simulation studies demonstrate the flexibility and robustness of the Bayesian method and the benefits of having replicates in the experiment. This method is illustrated through analyzing the data from a RNAi high-throughput screening that searches for cellular factors affecting HCV replication without affecting cell viability; comparisons of the results from this HCV study and some of those reported in the literature are included.Comment: Published in at http://dx.doi.org/10.1214/11-AOAS496 the Annals of Applied Statistics (http://www.imstat.org/aoas/) by the Institute of Mathematical Statistics (http://www.imstat.org

Telomeres in ICF syndrome cells are vulnerable to DNA damage due to elevated DNA:RNA hybrids.

DNA:RNA hybrids, nucleic acid structures with diverse physiological functions, can disrupt genome integrity when dysregulated. Human telomeres were shown to form hybrids with the lncRNA TERRA, yet the formation and distribution of these hybrids among telomeres, their regulation and their cellular effects remain elusive. Here we predict and confirm in several human cell types that DNA:RNA hybrids form at many subtelomeric and telomeric regions. We demonstrate that ICF syndrome cells, which exhibit short telomeres and elevated TERRA levels, are enriched for hybrids at telomeric regions throughout the cell cycle. Telomeric hybrids are associated with high levels of DNA damage at chromosome ends in ICF cells, which are significantly reduced with overexpression of RNase H1. Our findings suggest that abnormally high TERRA levels in ICF syndrome lead to accumulation of telomeric hybrids that, in turn, can result in telomeric dysfunction

Computational Investigations on Polymerase Actions in Gene Transcription and Replication Combining Physical Modeling and Atomistic Simulations

Polymerases are protein enzymes that move along nucleic acid chains and catalyze template-based polymerization reactions during gene transcription and replication. The polymerases also substantially improve transcription or replication fidelity through the non-equilibrium enzymatic cycles. We briefly review computational efforts that have been made toward understanding mechano-chemical coupling and fidelity control mechanisms of the polymerase elongation. The polymerases are regarded as molecular information motors during the elongation process. It requires a full spectrum of computational approaches from multiple time and length scales to understand the full polymerase functional cycle. We keep away from quantum mechanics based approaches to the polymerase catalysis due to abundant former surveys, while address only statistical physics modeling approach and all-atom molecular dynamics simulation approach. We organize this review around our own modeling and simulation practices on a single-subunit T7 RNA polymerase, and summarize commensurate studies on structurally similar DNA polymerases. For multi-subunit RNA polymerases that have been intensively studied in recent years, we leave detailed discussions on the simulation achievements to other computational chemical surveys, while only introduce very recently published representative studies, including our own preliminary work on structure-based modeling on yeast RNA polymerase II. In the end, we quickly go through kinetic modeling on elongation pauses and backtracking activities. We emphasize the fluctuation and control mechanisms of the polymerase actions, highlight the non-equilibrium physical nature of the system, and try to bring some perspectives toward understanding replication and transcription regulation from single molecular details to a genome-wide scale

Simulation support for performance assessment of building components

The determination of performance metrics for novel building components requires that the tests are conducted in the outdoor environment. It is usually difficult to do this when the components are located in a full-scale building because of the difficulty in controlling the experiments. Test cells allow the components to be tested in realistic, but controlled, conditions. High-quality outdoor experiments and identification analysis methods can be used to determine key parameters that quantify performance. This is important for achieving standardised metrics that characterise the building component of interest, whether it is a passive solar component such as a ventilated window, or an active component such as a hybrid photovoltaic module. However, such testing and analysis does not determine how the building component will perform when placed in a real building in a particular location and climate. For this, it is necessary to model the whole building with and without the building component of interest. A procedure has been developed, and applied within several major European projects, that consists of calibrating a simulation model with high-quality data from the outdoor tests and then applying scaling and replication to one or more buildings and locations to determine performance in practice of building components. This paper sets out the methodology that has been developed and applied in these European projects. A case study is included demonstrating its application to the performance evaluation of hybrid photovoltaic modules