12 research outputs found
Dust in Supernovae and Supernova Remnants II: Processing and survival
Observations have recently shown that supernovae are efficient dust factories, as predicted for a long time by theoretical models. The rapid evolution of their stellar progenitors combined with their efficiency in precipitating refractory elements from the gas phase into dust grains make supernovae the major potential suppliers of dust in the early Universe, where more conventional sources like Asymptotic Giant Branch (AGB) stars did not have time to evolve. However, dust yields inferred from observations of young supernovae or derived from models do not reflect the net amount of supernova-condensed dust able to be expelled from the remnants and reach the interstellar medium. The cavity where the dust is formed and initially resides is crossed by the high velocity reverse shock which is generated by the pressure of the circumstellar material shocked by the expanding supernova blast wave. Depending on grain composition and initial size, processing by the reverse shock may lead to substantial dust erosion and even complete destruction. The goal of this review is to present the state of the art about processing and survival of dust inside supernova remnants, in terms of theoretical modelling and comparison to observations
Robustness of differential gene expression analysis of RNA-seq
RNA-sequencing (RNA-seq) is a relatively new technology that lacks standardisation. RNA-seq can be used for Differential Gene Expression (DGE) analysis, however, no consensus exists as to which methodology ensures robust and reproducible results. Indeed, it is broadly acknowledged that DGE methods provide disparate results. Despite obstacles, RNA-seq assays are in advanced development for clinical use but further optimisation will be needed. Herein, five DGE models (DESeq2, voom + limma, edgeR, EBSeq, NOISeq) for gene-level detection were investigated for robustness to sequencing alterations using a controlled analysis of fixed count matrices. Two breast cancer datasets were analysed with full and reduced sample sizes. DGE model robustness was compared between filtering regimes and for different expression levels (high, low) using unbiased metrics. Test sensitivity estimated as relative False Discovery Rate (FDR), concordance between model outputs and comparisons of a âpopulationâ of slopes of relative FDRs across different library sizes, generated using linear regressions, were examined. Patterns of relative DGE model robustness proved dataset-agnostic and reliable for drawing conclusions when sample sizes were sufficiently large. Overall, the non-parametric method NOISeq was the most robust followed by edgeR, voom, EBSeq and DESeq2. Our rigorous appraisal provides information for method selection for molecular diagnostics. Metrics may prove useful towards improving the standardisation of RNA-seq for precision medicine
The nuclear oncogene SET controls DNA repair by KAP1 and HP1 retention to chromatin
Cells experience damage from exogenous and endogenous sources that endanger genome stability. Several cellular pathways have evolved to detect DNA damage and mediate its repair. Although many proteins have been implicated in these processes, only recent studies have revealed how they operate in the context of high-ordered chromatin structure. Here, we identify the nuclear oncogene SET (I2PP2A) as a modulator of DNA damage response (DDR) and repair in chromatin surrounding double-strand breaks (DSBs). We demonstrate that depletion of SET increases DDR and survival in the presence of radiomimetic drugs, while overexpression of SET impairs DDR and homologous recombination (HR)-mediated DNA repair. SET interacts with the Kruppel-associated box (KRAB)-associated co-repressor KAP1, and its overexpression results inthe sustained retention of KAP1 and Heterochromatin protein 1 (HP1) on chromatin. Our results are consistent with a model in which SET-mediated chromatin compaction triggers an inhibition of DNA end resection and HR. © 2015 The Authors
Global urban environmental change drives adaptation in white clover
Urbanization transforms environments in ways that alter biological evolution. We examined whether urban environmental change drives parallel evolution by sampling 110,019 white clover plants from 6169 populations in 160 cities globally. Plants were assayed for a Mendelian antiherbivore defense that also affects tolerance to abiotic stressors. Urban-rural gradients were associated with the evolution of clines in defense in 47% of cities throughout the world. Variation in the strength of clines was explained by environmental changes in drought stress and vegetation cover that varied among cities. Sequencing 2074 genomes from 26 cities revealed that the evolution of urban-rural clines was best explained by adaptive evolution, but the degree of parallel adaptation varied among cities. Our results demonstrate that urbanization leads to adaptation at a global scale