117 research outputs found

    Multiple Epistasis Interactions Within MHC Are Associated With Ulcerative Colitis

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    Successful searching for epistasis is much challenging, which generally requires very large sample sizes and/or very dense marker information. We exploited the largest Crohn's disease (CD) dataset (18,000 cases + 34,000 controls) and ulcerative colitis (UC) dataset (14,000 cases + 34,000 controls) to date. Leveraging its dense marker information and the large sample size of this IBD dataset, we employed a two-step approach to exhaustively search for epistasis. We detected abundant genome-wide significant (p < 1 × 10−13) epistatic signals, all within the MHC region. These signals were reduced substantially when conditional on the additive background, but still nine pairs remained significant at the Immunochip-wide level (P < 1.1 × 10−8) in conditional tests for UC. All these nine epistatic interactions come from the MHC region, and each explains on average 0.15% of the phenotypic variance. Eight of them were replicated in a replication cohort. There are multiple but relatively weak interactions independent of the additive effects within the MHC region for UC. Our promising results warrant the search for epistasis in large data sets with dense markers, exploiting dependencies between markers

    Geographical limits to species-range shifts are suggested by climate velocity

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    The reorganization of patterns of species diversity driven by anthropogenic climate change, and the consequences for humans, are not yet fully understood or appreciated. Nevertheless, changes in climate conditions are useful for predicting shifts in species distributions at global and local scales. Here we use the velocity of climate change to derive spatial trajectories for climatic niches from 1960 to 2009 (ref. 7) and from 2006 to 2100, and use the properties of these trajectories to infer changes in species distributions. Coastlines act as barriers and locally cooler areas act as attractors for trajectories, creating source and sink areas for local climatic conditions. Climate source areas indicate where locally novel conditions are not connected to areas where similar climates previously occurred, and are thereby inaccessible to climate migrants tracking isotherms: 16% of global surface area for 1960 to 2009, and 34% of ocean for the \u27business as usual\u27 climate scenario (representative concentration pathway (RCP) 8.5)8 representing continued use of fossil fuels without mitigation. Climate sink areas are where climate conditions locally disappear, potentially blocking the movement of climate migrants. Sink areas comprise 1.0% of ocean area and 3.6% of land and are prevalent on coasts and high ground. Using this approach to infer shifts in species distributions gives global and regional maps of the expected direction and rate of shifts of climate migrants, and suggests areas of potential loss of species richness

    Genomic, Pathway Network, and Immunologic Features Distinguishing Squamous Carcinomas

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    This integrated, multiplatform PanCancer Atlas study co-mapped and identified distinguishing molecular features of squamous cell carcinomas (SCCs) from five sites associated with smokin

    Pan-Cancer Analysis of lncRNA Regulation Supports Their Targeting of Cancer Genes in Each Tumor Context

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    Long noncoding RNAs (lncRNAs) are commonly dys-regulated in tumors, but only a handful are known toplay pathophysiological roles in cancer. We inferredlncRNAs that dysregulate cancer pathways, onco-genes, and tumor suppressors (cancer genes) bymodeling their effects on the activity of transcriptionfactors, RNA-binding proteins, and microRNAs in5,185 TCGA tumors and 1,019 ENCODE assays.Our predictions included hundreds of candidateonco- and tumor-suppressor lncRNAs (cancerlncRNAs) whose somatic alterations account for thedysregulation of dozens of cancer genes and path-ways in each of 14 tumor contexts. To demonstrateproof of concept, we showed that perturbations tar-geting OIP5-AS1 (an inferred tumor suppressor) andTUG1 and WT1-AS (inferred onco-lncRNAs) dysre-gulated cancer genes and altered proliferation ofbreast and gynecologic cancer cells. Our analysis in-dicates that, although most lncRNAs are dysregu-lated in a tumor-specific manner, some, includingOIP5-AS1, TUG1, NEAT1, MEG3, and TSIX, synergis-tically dysregulate cancer pathways in multiple tumorcontexts

    Pan-cancer Alterations of the MYC Oncogene and Its Proximal Network across the Cancer Genome Atlas

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    Although theMYConcogene has been implicated incancer, a systematic assessment of alterations ofMYC, related transcription factors, and co-regulatoryproteins, forming the proximal MYC network (PMN),across human cancers is lacking. Using computa-tional approaches, we define genomic and proteo-mic features associated with MYC and the PMNacross the 33 cancers of The Cancer Genome Atlas.Pan-cancer, 28% of all samples had at least one ofthe MYC paralogs amplified. In contrast, the MYCantagonists MGA and MNT were the most frequentlymutated or deleted members, proposing a roleas tumor suppressors.MYCalterations were mutu-ally exclusive withPIK3CA,PTEN,APC,orBRAFalterations, suggesting that MYC is a distinct onco-genic driver. Expression analysis revealed MYC-associated pathways in tumor subtypes, such asimmune response and growth factor signaling; chro-matin, translation, and DNA replication/repair wereconserved pan-cancer. This analysis reveals insightsinto MYC biology and is a reference for biomarkersand therapeutics for cancers with alterations ofMYC or the PMN

    Spatial Organization and Molecular Correlation of Tumor-Infiltrating Lymphocytes Using Deep Learning on Pathology Images

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    Beyond sample curation and basic pathologic characterization, the digitized H&E-stained images of TCGA samples remain underutilized. To highlight this resource, we present mappings of tumorinfiltrating lymphocytes (TILs) based on H&E images from 13 TCGA tumor types. These TIL maps are derived through computational staining using a convolutional neural network trained to classify patches of images. Affinity propagation revealed local spatial structure in TIL patterns and correlation with overall survival. TIL map structural patterns were grouped using standard histopathological parameters. These patterns are enriched in particular T cell subpopulations derived from molecular measures. TIL densities and spatial structure were differentially enriched among tumor types, immune subtypes, and tumor molecular subtypes, implying that spatial infiltrate state could reflect particular tumor cell aberration states. Obtaining spatial lymphocytic patterns linked to the rich genomic characterization of TCGA samples demonstrates one use for the TCGA image archives with insights into the tumor-immune microenvironment

    Proteomic Analysis of Neisseria gonorrhoeae Biofilms Shows Shift to Anaerobic Respiration and Changes in Nutrient Transport and Outermembrane Proteins

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    Neisseria gonorrhoeae, the causative agent of gonorrhea, can form biofilms in vitro and in vivo. In biofilms, the organism is more resistant to antibiotic treatment and can serve as a reservoir for chronic infection. We have used stable isotope labeling by amino acids in cell culture (SILAC) to compare protein expression in biofilm and planktonic organisms. Two parallel populations of N. gonorrhoeae strain 1291, which is an arginine auxotroph, were grown for 48 h in continuous-flow chambers over glass, one supplemented with 13C6-arginine for planktonic organisms and the other with unlabeled arginine for biofilm growth. The biofilm and planktonic cells were harvested and lysed separately, and fractionated into three sequential protein extracts. Corresponding heavy (H) planktonic and light (L) biofilm protein extracts were mixed and separated by 1D SDS-PAGE gels, and samples were extensively analyzed by liquid chromatography-mass spectrometry. Overall, 757 proteins were identified, and 152 unique proteins met a 1.5-fold cutoff threshold for differential expression with p-values <0.05. Comparing biofilm to planktonic organisms, this set included 73 upregulated and 54 downregulated proteins. Nearly a third of the upregulated proteins were involved in energy metabolism, with cell envelope proteins making up the next largest group. Of the downregulated proteins, the largest groups were involved in protein synthesis and energy metabolism. These proteomics results were compared with our previously reported results from transcriptional profiling of gonococcal biofilms using microarrays. Nitrite reductase and cytochrome c peroxidase, key enzymes required for anaerobic growth, were detected as highly upregulated in both the proteomic and transcriptomic datasets. These and other protein expression changes observed in the present study were consistent with a shift to anaerobic respiration in gonococcal biofilms, although changes in membrane proteins not explicitly related to this shift may have other functions

    Principles of genetic circuit design

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    Cells navigate environments, communicate and build complex patterns by initiating gene expression in response to specific signals. Engineers seek to harness this capability to program cells to perform tasks or create chemicals and materials that match the complexity seen in nature. This Review describes new tools that aid the construction of genetic circuits. Circuit dynamics can be influenced by the choice of regulators and changed with expression 'tuning knobs'. We collate the failure modes encountered when assembling circuits, quantify their impact on performance and review mitigation efforts. Finally, we discuss the constraints that arise from circuits having to operate within a living cell. Collectively, better tools, well-characterized parts and a comprehensive understanding of how to compose circuits are leading to a breakthrough in the ability to program living cells for advanced applications, from living therapeutics to the atomic manufacturing of functional materials.National Institute of General Medical Sciences (U.S.) (Grant P50 GM098792)National Institute of General Medical Sciences (U.S.) (Grant R01 GM095765)National Science Foundation (U.S.). Synthetic Biology Engineering Research Center (EEC0540879)Life Technologies, Inc. (A114510)National Science Foundation (U.S.). Graduate Research FellowshipUnited States. Office of Naval Research. Multidisciplinary University Research Initiative (Grant 4500000552
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