544 research outputs found

    Mapping the genetic architecture of gene expression in human liver

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    Genetic variants that are associated with common human diseases do not lead directly to disease, but instead act on intermediate, molecular phenotypes that in turn induce changes in higher-order disease traits. Therefore, identifying the molecular phenotypes that vary in response to changes in DNA and that also associate with changes in disease traits has the potential to provide the functional information required to not only identify and validate the susceptibility genes that are directly affected by changes in DNA, but also to understand the molecular networks in which such genes operate and how changes in these networks lead to changes in disease traits. Toward that end, we profiled more than 39,000 transcripts and we genotyped 782,476 unique single nucleotide polymorphisms (SNPs) in more than 400 human liver samples to characterize the genetic architecture of gene expression in the human liver, a metabolically active tissue that is important in a number of common human diseases, including obesity, diabetes, and atherosclerosis. This genome-wide association study of gene expression resulted in the detection of more than 6,000 associations between SNP genotypes and liver gene expression traits, where many of the corresponding genes identified have already been implicated in a number of human diseases. The utility of these data for elucidating the causes of common human diseases is demonstrated by integrating them with genotypic and expression data from other human and mouse populations. This provides much-needed functional support for the candidate susceptibility genes being identified at a growing number of genetic loci that have been identified as key drivers of disease from genome-wide association studies of disease. By using an integrative genomics approach, we highlight how the gene RPS26 and not ERBB3 is supported by our data as the most likely susceptibility gene for a novel type 1 diabetes locus recently identified in a large-scale, genome-wide association study. We also identify SORT1 and CELSR2 as candidate susceptibility genes for a locus recently associated with coronary artery disease and plasma low-density lipoprotein cholesterol levels in the process. © 2008 Schadt et al

    Regulating Clothing Outwork: A Sceptic's View

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    By applying the strategies of international anti-sweatshop campaigns to the Australian context, recent regulations governing home-based clothing production hold retailers responsible for policing the wages and employment conditions of clothing outworkers who manufacture clothing on their behalf. This paper argues that the new approach oversimplifies the regulatory challenge by assuming (1) that Australian clothing production is organised in a hierarchical ‘buyer-led’ linear structure in which core retail firms have the capacity to control their suppliers’ behaviour; (2) that firms act as unitary moral agents; and (3) that interventions imported from other times and places are applicable to the contemporary Australian context. After considering some alternative regulatory approaches, the paper concludes that the new regulatory strategy effectively privatises responsibility for labour market conditions – a development that cries out for further debate

    Self-Organization, Layered Structure, and Aggregation Enhance Persistence of a Synthetic Biofilm Consortium

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    Microbial consortia constitute a majority of the earth’s biomass, but little is known about how these cooperating communities persist despite competition among community members. Theory suggests that non-random spatial structures contribute to the persistence of mixed communities; when particular structures form, they may provide associated community members with a growth advantage over unassociated members. If true, this has implications for the rise and persistence of multi-cellular organisms. However, this theory is difficult to study because we rarely observe initial instances of non-random physical structure in natural populations. Using two engineered strains of Escherichia coli that constitute a synthetic symbiotic microbial consortium, we fortuitously observed such spatial self-organization. This consortium forms a biofilm and, after several days, adopts a defined layered structure that is associated with two unexpected, measurable growth advantages. First, the consortium cannot successfully colonize a new, downstream environment until it selforganizes in the initial environment; in other words, the structure enhances the ability of the consortium to survive environmental disruptions. Second, when the layered structure forms in downstream environments the consortium accumulates significantly more biomass than it did in the initial environment; in other words, the structure enhances the global productivity of the consortium. We also observed that the layered structure only assembles in downstream environments that are colonized by aggregates from a previous, structured community. These results demonstrate roles for self-organization and aggregation in persistence of multi-cellular communities, and also illustrate a role for the techniques of synthetic biology in elucidating fundamental biological principles

    Immunogenic cell death pathway polymorphisms for predicting oxaliplatin efficacy in metastatic colorectal cancer

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    Background Immunogenic cell death (ICD) is a tumor cell death involving both innate and adaptive immune responses. Given published findings that oxaliplatin, but not irinotecan, drives ICD, we investigated whether single nucleotide polymorphisms (SNPs) in the ICD pathway are associated with the efficacy of oxaliplatin-based chemotherapy in metastatic colorectal cancer (mCRC). Methods Two randomized clinical trials data were analyzed: discovery cohort, FOLFOX/bevacizumab arm (MAVERICC); validation cohort, FOLFOXIRI/bevacizumab arm (TRIBE); and two control cohorts, FOLFIRI/bevacizumab arms (both trials). Genomic DNA extracted from blood samples was genotyped. Ten SNPs in the ICD pathway were tested for associations with clinical outcomes. Results In total, 648 patients were included. In the discovery cohort, three SNPs were significantly associated with clinical outcomes in univariate analysis: CALR rs1010222 with progression-free survival (G/G vs any A, HR=0.61, 95% CI 0.43-0.88), ANXA1 rs1050305 with overall survival (OS) (A/A vs any G, HR=1.87, 95% CI 1.04-3.35), and LRP1 rs1799986 with OS (C/C vs any T, HR=1.69, 95% CI 1.07-2.70). Multivariate analysis confirmed the trend, but statistical significance was not reached. In the validation cohort, ANXA1 rs1050305, and LRP1 rs1799986 were validated to have the significant associations with clinical outcome. No significant associations of these SNPs were observed in the two control cohorts. Treatment-by-SNP interaction test confirmed the predictive values. Conclusions The predictive utility of ICD-related SNPs for the efficacy of oxaliplatin-based chemotherapy was demonstrated, warranting further validation studies to be translated into personalized treatment strategies using conventional cytotoxic agents in mCRC

    Drift as a Force of Evolution: A Manipulationist Account

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    Can evolutionary theory be properly characterised as a “theory of forces”, like Newtonian mechanics? One common criticism to this claim concerns the possibility to conceive genetic drift as a causal process endowed by a specific magnitude and direction. In this article, we aim to offer an original response to this criticism by pointing out a connection between the notion of force and the notion of explanatory depth, as depicted in Hitchcock and Woodward’s manipulationist account of causal explanation. In a nutshell, our argument is that, since force-explanations can be consistently reframed as deep explanations and vice versa, and the notion of drift can be characterised in manipulationist terms as constitutively intervening in evolutionary deep explanations, then drift-explanations can be consistently reframed as force-explanations, and drift can be properly considered as a force of evolution. Insofar as similar considerations may be extended also to other evolutionary factors – chiefly selection –, our analysis offers an important support to the claim that evolutionary theory is a theory of forces.info:eu-repo/semantics/publishedVersio

    Dr. Android and Mr. Hide: Fine-grained security policies on unmodified Android

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    Google’s Android platform includes a permission model that protects access to sensitive capabilities, such as Internet access, GPS use, and telephony. We have found that Android’s current permissions are often overly broad, providing apps with more access than they truly require. This deviation from least privilege increases the threat from vulnerabilities and malware. To address this issue, we present a novel system that can replace existing platform permissions with finer-grained ones. A key property of our approach is that it runs today, on stock Android devices, requiring no platform modifications. Our solution is composed of two parts: Mr. Hide, which runs in a separate process on a device and provides access to sensitive data as a service; and Dr. Android (Dalvik Rewriter for Android), a tool that transforms existing Android apps to access sensitive resources via Mr. Hide rather than directly through the system. Together, Dr. Android and Mr. Hide can completely remove several of an app’s existing permissions and replace them with finer-grained ones, leveraging the platform to provide complete mediation for protected resources. We evaluated our ideas on several popular, free Android apps. We found that we can replace many commonly used "dangerous" permissions with finer-grained permissions. Moreover, apps transformed to use these finer-grained permissions run largely as expected, with reasonable performance overhead

    Detection of regulator genes and eQTLs in gene networks

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    Genetic differences between individuals associated to quantitative phenotypic traits, including disease states, are usually found in non-coding genomic regions. These genetic variants are often also associated to differences in expression levels of nearby genes (they are "expression quantitative trait loci" or eQTLs for short) and presumably play a gene regulatory role, affecting the status of molecular networks of interacting genes, proteins and metabolites. Computational systems biology approaches to reconstruct causal gene networks from large-scale omics data have therefore become essential to understand the structure of networks controlled by eQTLs together with other regulatory genes, and to generate detailed hypotheses about the molecular mechanisms that lead from genotype to phenotype. Here we review the main analytical methods and softwares to identify eQTLs and their associated genes, to reconstruct co-expression networks and modules, to reconstruct causal Bayesian gene and module networks, and to validate predicted networks in silico.Comment: minor revision with typos corrected; review article; 24 pages, 2 figure
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