13 research outputs found

    Pan-cancer analysis of whole genomes

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    Cancer is driven by genetic change, and the advent of massively parallel sequencing has enabled systematic documentation of this variation at the whole-genome scale(1-3). Here we report the integrative analysis of 2,658 whole-cancer genomes and their matching normal tissues across 38 tumour types from the Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium of the International Cancer Genome Consortium (ICGC) and The Cancer Genome Atlas (TCGA). We describe the generation of the PCAWG resource, facilitated by international data sharing using compute clouds. On average, cancer genomes contained 4-5 driver mutations when combining coding and non-coding genomic elements; however, in around 5% of cases no drivers were identified, suggesting that cancer driver discovery is not yet complete. Chromothripsis, in which many clustered structural variants arise in a single catastrophic event, is frequently an early event in tumour evolution; in acral melanoma, for example, these events precede most somatic point mutations and affect several cancer-associated genes simultaneously. Cancers with abnormal telomere maintenance often originate from tissues with low replicative activity and show several mechanisms of preventing telomere attrition to critical levels. Common and rare germline variants affect patterns of somatic mutation, including point mutations, structural variants and somatic retrotransposition. A collection of papers from the PCAWG Consortium describes non-coding mutations that drive cancer beyond those in the TERT promoter(4); identifies new signatures of mutational processes that cause base substitutions, small insertions and deletions and structural variation(5,6); analyses timings and patterns of tumour evolution(7); describes the diverse transcriptional consequences of somatic mutation on splicing, expression levels, fusion genes and promoter activity(8,9); and evaluates a range of more-specialized features of cancer genomes(8,10-18).Peer reviewe

    Framework for strategic wind farm site prioritisation based on modelled wolf reproduction habitat in Croatia

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    In order to meet carbon reduction targets, many nations are greatly expanding their wind power capacity. However, wind farm infrastructure potentially harms wildlife, and we must therefore find ways to balance clean energy demands with the need to protect wildlife. Wide-ranging carnivores live at low density and are particularly susceptible to disturbance from infrastructure development, so are a particular concern in this respect. We focused on Croatia, which holds an important population of wolves and is currently planning to construct many new wind farms. Specifically, we sought to identify an optimal subset of planned wind farms that would meet energy targets while minimising potential impact on wolves. A suitability model for wolf breeding habitat was carried out using Maxent, based on six environmental variables and 31 reproduction site locations collected between 1997 and 2015. Wind farms were prioritised using Marxan to find the optimal trade-off between energy capacity and overlap with critical wolf reproduction habitat. The habitat suitability model predictions were consistent with the current knowledge: probability of wolf breeding site presence increased with distance to settlements, distance to farmland and distance to roads and decreased with distance to forest. Spatial optimisation showed that it would be possible to meet current energy targets with only 31% of currently proposed wind farms, selected in a way that reduces the potential ecological cost (overall predicted wolf breeding site presence within wind farm sites) by 91%. This is a highly efficient outcome, demonstrating the value of this approach for prioritising infrastructure development based on its potential impact on wide-ranging wildlife species

    Septal glucagon-like peptide 1 receptor expression determines suppression of cocaine-induced behavior

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    © 2015 American College of Neuropsychopharmacology. Glucagon-like peptide 1 (GLP-1) and its receptor GLP-1R are a key component of the satiety signaling system, and long-acting GLP-1 analogs have been approved for the treatment of type-2 diabetes mellitus. Previous reports demonstrate that GLP-1 regulates glucose homeostasis alongside the rewarding effects of food. Both palatable food and illicit drugs activate brain reward circuitries, and pharmacological studies suggest that central nervous system GLP-1 signaling holds potential for the treatment of addiction. However, the role of endogenous GLP-1 in the attenuation of reward-oriented behavior, and the essential domains of the mesolimbic system mediating these beneficial effects, are largely unknown. We hypothesized that the central regions of highest Glp-1r gene activity are essential in mediating responses to drugs of abuse. Here, we show that Glp-1r-deficient (Glp-1r -/-) mice have greatly augmented cocaine-induced locomotor responses and enhanced conditional place preference compared with wild-type (Glp-1r +/+) controls. Employing mRNA in situ hybridization we located peak Glp-1r mRNA expression in GABAergic neurons of the dorsal lateral septum, an anatomical site with a crucial function in reward perception. Whole-cell patch-clamp recordings of dorsal lateral septum neurons revealed that genetic Glp-1r ablation leads to increased excitability of these cells. Viral vector-mediated Glp-1r gene delivery to the dorsal lateral septum of Glp-1r -/- animals reduced cocaine-induced locomotion and conditional place preference to wild-type levels. This site-specific genetic complementation did not affect the anxiogenic phenotype observed in Glp-1r -/- controls. These data reveal a novel role of GLP-1R in dorsal lateral septum function driving behavioral responses to cocaine
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