87 research outputs found

    MAGE-A cancer/testis antigens inhibit MDM2 ubiquitylation function and promote increased levels of MDM4

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    Melanoma antigen A (MAGE-A) proteins comprise a structurally and biochemically similar sub-family of Cancer/Testis antigens that are expressed in many cancer types and are thought to contribute actively to malignancy. MAGE-A proteins are established regulators of certain cancer-associated transcription factors, including p53, and are activators of several RING finger-dependent ubiquitin E3 ligases. Here, we show that MAGE-A2 associates with MDM2, a ubiquitin E3 ligase that mediates ubiquitylation of more than 20 substrates including mainly p53, MDM2 itself, and MDM4, a potent p53 inhibitor and MDM2 partner that is structurally related to MDM2. We find that MAGE-A2 interacts with MDM2 via the N-terminal p53-binding pocket and the RING finger domain of MDM2 that is required for homo/hetero-dimerization and for E2 ligase interaction. Consistent with these data, we show that MAGE-A2 is a potent inhibitor of the E3 ubiquitin ligase activity of MDM2, yet it does not have any significant effect on p53 turnover mediated by MDM2. Strikingly, however, increased MAGE-A2 expression leads to reduced ubiquitylation and increased levels of MDM4. Similarly, silencing of endogenous MAGE-A expression diminishes MDM4 levels in a manner that can be rescued by the proteasomal inhibitor, bortezomid, and permits increased MDM2/MDM4 association. These data suggest that MAGE-A proteins can: (i) uncouple the ubiquitin ligase and degradation functions of MDM2; (ii) act as potent inhibitors of E3 ligase function; and (iii) regulate the turnover of MDM4. We also find an association between the presence of MAGE-A and increased MDM4 levels in primary breast cancer, suggesting that MAGE-A-dependent control of MDM4 levels has relevance to cancer clinically

    Genetic determinants of co-accessible chromatin regions in activated T cells across humans.

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    Over 90% of genetic variants associated with complex human traits map to non-coding regions, but little is understood about how they modulate gene regulation in health and disease. One possible mechanism is that genetic variants affect the activity of one or more cis-regulatory elements leading to gene expression variation in specific cell types. To identify such cases, we analyzed ATAC-seq and RNA-seq profiles from stimulated primary CD4+ T cells in up to 105 healthy donors. We found that regions of accessible chromatin (ATAC-peaks) are co-accessible at kilobase and megabase resolution, consistent with the three-dimensional chromatin organization measured by in situ Hi-C in T cells. Fifteen percent of genetic variants located within ATAC-peaks affected the accessibility of the corresponding peak (local-ATAC-QTLs). Local-ATAC-QTLs have the largest effects on co-accessible peaks, are associated with gene expression and are enriched for autoimmune disease variants. Our results provide insights into how natural genetic variants modulate cis-regulatory elements, in isolation or in concert, to influence gene expression

    A survey and classification of storage deduplication systems

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    The automatic elimination of duplicate data in a storage system commonly known as deduplication is increasingly accepted as an effective technique to reduce storage costs. Thus, it has been applied to different storage types, including archives and backups, primary storage, within solid state disks, and even to random access memory. Although the general approach to deduplication is shared by all storage types, each poses specific challenges and leads to different trade-offs and solutions. This diversity is often misunderstood, thus underestimating the relevance of new research and development. The first contribution of this paper is a classification of deduplication systems according to six criteria that correspond to key design decisions: granularity, locality, timing, indexing, technique, and scope. This classification identifies and describes the different approaches used for each of them. As a second contribution, we describe which combinations of these design decisions have been proposed and found more useful for challenges in each storage type. Finally, outstanding research challenges and unexplored design points are identified and discussed.This work is funded by the European Regional Development Fund (EDRF) through the COMPETE Programme (operational programme for competitiveness) and by National Funds through the Fundacao para a Ciencia e a Tecnologia (FCT; Portuguese Foundation for Science and Technology) within project RED FCOMP-01-0124-FEDER-010156 and the FCT by PhD scholarship SFRH-BD-71372-2010

    <em>CYP2D6 </em>genotype and adjuvant tamoxifen:meta-analysis of heterogeneous study populations

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    Whipworm genome and dual-species transcriptome analyses provide molecular insights into an intimate host-parasite interaction.

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    Whipworms are common soil-transmitted helminths that cause debilitating chronic infections in man. These nematodes are only distantly related to Caenorhabditis elegans and have evolved to occupy an unusual niche, tunneling through epithelial cells of the large intestine. We report here the whole-genome sequences of the human-infective Trichuris trichiura and the mouse laboratory model Trichuris muris. On the basis of whole-transcriptome analyses, we identify many genes that are expressed in a sex- or life stage-specific manner and characterize the transcriptional landscape of a morphological region with unique biological adaptations, namely, bacillary band and stichosome, found only in whipworms and related parasites. Using RNA sequencing data from whipworm-infected mice, we describe the regulated T helper 1 (TH1)-like immune response of the chronically infected cecum in unprecedented detail. In silico screening identified numerous new potential drug targets against trichuriasis. Together, these genomes and associated functional data elucidate key aspects of the molecular host-parasite interactions that define chronic whipworm infection

    A Population Genetic Approach to Mapping Neurological Disorder Genes Using Deep Resequencing

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    Deep resequencing of functional regions in human genomes is key to identifying potentially causal rare variants for complex disorders. Here, we present the results from a large-sample resequencing (n = 285 patients) study of candidate genes coupled with population genetics and statistical methods to identify rare variants associated with Autism Spectrum Disorder and Schizophrenia. Three genes, MAP1A, GRIN2B, and CACNA1F, were consistently identified by different methods as having significant excess of rare missense mutations in either one or both disease cohorts. In a broader context, we also found that the overall site frequency spectrum of variation in these cases is best explained by population models of both selection and complex demography rather than neutral models or models accounting for complex demography alone. Mutations in the three disease-associated genes explained much of the difference in the overall site frequency spectrum among the cases versus controls. This study demonstrates that genes associated with complex disorders can be mapped using resequencing and analytical methods with sample sizes far smaller than those required by genome-wide association studies. Additionally, our findings support the hypothesis that rare mutations account for a proportion of the phenotypic variance of these complex disorders
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