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  • 1
    Publication Date: 2014-08-01
    Description: The translational control of oncoprotein expression is implicated in many cancers. Here we report an eIF4A RNA helicase-dependent mechanism of translational control that contributes to oncogenesis and underlies the anticancer effects of silvestrol and related compounds. For example, eIF4A promotes T-cell acute lymphoblastic leukaemia development in vivo and is required for leukaemia maintenance. Accordingly, inhibition of eIF4A with silvestrol has powerful therapeutic effects against murine and human leukaemic cells in vitro and in vivo. We use transcriptome-scale ribosome footprinting to identify the hallmarks of eIF4A-dependent transcripts. These include 5' untranslated region (UTR) sequences such as the 12-nucleotide guanine quartet (CGG)4 motif that can form RNA G-quadruplex structures. Notably, among the most eIF4A-dependent and silvestrol-sensitive transcripts are a number of oncogenes, superenhancer-associated transcription factors, and epigenetic regulators. Hence, the 5' UTRs of select cancer genes harbour a targetable requirement for the eIF4A RNA helicase.〈br /〉〈br /〉〈a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4492470/" target="_blank"〉〈img src="https://static.pubmed.gov/portal/portal3rc.fcgi/4089621/img/3977009" border="0"〉〈/a〉   〈a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4492470/" target="_blank"〉This paper as free author manuscript - peer-reviewed and accepted for publication〈/a〉〈br /〉〈br /〉〈span class="detail_caption"〉Notes: 〈/span〉Wolfe, Andrew L -- Singh, Kamini -- Zhong, Yi -- Drewe, Philipp -- Rajasekhar, Vinagolu K -- Sanghvi, Viraj R -- Mavrakis, Konstantinos J -- Jiang, Man -- Roderick, Justine E -- Van der Meulen, Joni -- Schatz, Jonathan H -- Rodrigo, Christina M -- Zhao, Chunying -- Rondou, Pieter -- de Stanchina, Elisa -- Teruya-Feldstein, Julie -- Kelliher, Michelle A -- Speleman, Frank -- Porco, John A Jr -- Pelletier, Jerry -- Ratsch, Gunnar -- Wendel, Hans-Guido -- GM-067041/GM/NIGMS NIH HHS/ -- GM-073855/GM/NIGMS NIH HHS/ -- MOP-10653/Canadian Institutes of Health Research/Canada -- P30 CA008748/CA/NCI NIH HHS/ -- R01 CA142798/CA/NCI NIH HHS/ -- R01-CA142798-01/CA/NCI NIH HHS/ -- England -- Nature. 2014 Sep 4;513(7516):65-70. doi: 10.1038/nature13485. Epub 2014 Jul 27.〈br /〉〈span class="detail_caption"〉Author address: 〈/span〉1] Cancer Biology and Genetics, Memorial Sloan-Kettering Cancer Center, New York, New York 10065, USA [2] Weill Cornell Graduate School of Medical Sciences, New York, New York 10065, USA [3]. ; 1] Cancer Biology and Genetics, Memorial Sloan-Kettering Cancer Center, New York, New York 10065, USA [2]. ; Computational Biology Department, Memorial Sloan-Kettering Cancer Center, New York, New York 10065, USA. ; Stem Cell Center and Developmental Biology Program, Memorial Sloan-Kettering Cancer Center, New York, New York 10065, USA. ; Cancer Biology and Genetics, Memorial Sloan-Kettering Cancer Center, New York, New York 10065, USA. ; 1] Cancer Biology and Genetics, Memorial Sloan-Kettering Cancer Center, New York, New York 10065, USA [2] Novartis, Cambridge, Massachusetts 02139, USA (K.J.M.); The University of Arizona Cancer Center, Tucson, Arizona 85719, USA (J.H.S.). ; Department of Cancer Biology, University of Massachusetts Medical School, Worcester, Massachusetts 01605 USA. ; 1] Cancer Biology and Genetics, Memorial Sloan-Kettering Cancer Center, New York, New York 10065, USA [2] Center for Medical Genetics, Ghent University Hospital, De Pintelaan 185, B-9000 Ghent, Belgium. ; 1] Cancer Biology and Genetics, Memorial Sloan-Kettering Cancer Center, New York, New York 10065, USA [2] Department of Medicine, Memorial Sloan-Kettering Cancer Center, New York, New York 10065, USA [3] Novartis, Cambridge, Massachusetts 02139, USA (K.J.M.); The University of Arizona Cancer Center, Tucson, Arizona 85719, USA (J.H.S.). ; Department of Chemistry, Center for Chemical Methodology and Library Development, Boston University, Boston, Massachusetts 02215, USA. ; Center for Medical Genetics, Ghent University Hospital, De Pintelaan 185, B-9000 Ghent, Belgium. ; Molecular Pharmacology Program, Memorial Sloan-Kettering Cancer Center, New York, New York 10065, USA. ; Department of Pathology, Memorial Sloan-Kettering Cancer Center, New York, New York 10065, USA. ; 1] Department of Biochemistry, McGill University, Montreal, Quebec H3G 1Y6, Canada [2] Department of Oncology, McGill University, Montreal, Quebec H3G 1Y6, Canada [3] The Rosalind and Morris Goodman Cancer Research Center, McGill University, Montreal, Quebec H3G 1Y6, Canada.〈br /〉〈span class="detail_caption"〉Record origin:〈/span〉 〈a href="http://www.ncbi.nlm.nih.gov/pubmed/25079319" target="_blank"〉PubMed〈/a〉
    Keywords: 5' Untranslated Regions/*genetics ; Animals ; Antineoplastic Agents, Phytogenic/pharmacology/therapeutic use ; Base Sequence ; Cell Line, Tumor ; Epigenesis, Genetic ; Eukaryotic Initiation Factor-4A/*metabolism ; Female ; *G-Quadruplexes ; Humans ; Mice ; Mice, Inbred C57BL ; Nucleotide Motifs ; Oncogene Proteins/*biosynthesis/*genetics ; Precursor T-Cell Lymphoblastic Leukemia-Lymphoma/drug ; therapy/genetics/*metabolism ; *Protein Biosynthesis/drug effects ; Ribosomes/metabolism ; Transcription Factors/metabolism ; Transcription, Genetic/drug effects/genetics ; Triterpenes/pharmacology
    Print ISSN: 0028-0836
    Electronic ISSN: 1476-4687
    Topics: Biology , Chemistry and Pharmacology , Medicine , Natural Sciences in General , Physics
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  • 2
    Publication Date: 2011-08-30
    Description: Genetic differences between Arabidopsis thaliana accessions underlie the plant's extensive phenotypic variation, and until now these have been interpreted largely in the context of the annotated reference accession Col-0. Here we report the sequencing, assembly and annotation of the genomes of 18 natural A. thaliana accessions, and their transcriptomes. When assessed on the basis of the reference annotation, one-third of protein-coding genes are predicted to be disrupted in at least one accession. However, re-annotation of each genome revealed that alternative gene models often restore coding potential. Gene expression in seedlings differed for nearly half of expressed genes and was frequently associated with cis variants within 5 kilobases, as were intron retention alternative splicing events. Sequence and expression variation is most pronounced in genes that respond to the biotic environment. Our data further promote evolutionary and functional studies in A. thaliana, especially the MAGIC genetic reference population descended from these accessions.〈br /〉〈span class="detail_caption"〉Notes: 〈/span〉Gan, Xiangchao -- Stegle, Oliver -- Behr, Jonas -- Steffen, Joshua G -- Drewe, Philipp -- Hildebrand, Katie L -- Lyngsoe, Rune -- Schultheiss, Sebastian J -- Osborne, Edward J -- Sreedharan, Vipin T -- Kahles, Andre -- Bohnert, Regina -- Jean, Geraldine -- Derwent, Paul -- Kersey, Paul -- Belfield, Eric J -- Harberd, Nicholas P -- Kemen, Eric -- Toomajian, Christopher -- Kover, Paula X -- Clark, Richard M -- Ratsch, Gunnar -- Mott, Richard -- 090532/Wellcome Trust/United Kingdom -- 090532/Z/09/Z/Wellcome Trust/United Kingdom -- BB/D016029/2/Biotechnology and Biological Sciences Research Council/United Kingdom -- BB/F019793/1/Biotechnology and Biological Sciences Research Council/United Kingdom -- BB/F020759/1/Biotechnology and Biological Sciences Research Council/United Kingdom -- BB/F022697/1/Biotechnology and Biological Sciences Research Council/United Kingdom -- England -- Nature. 2011 Aug 28;477(7365):419-23. doi: 10.1038/nature10414.〈br /〉〈span class="detail_caption"〉Author address: 〈/span〉Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford OX3 7BN, UK.〈br /〉〈span class="detail_caption"〉Record origin:〈/span〉 〈a href="http://www.ncbi.nlm.nih.gov/pubmed/21874022" target="_blank"〉PubMed〈/a〉
    Keywords: Arabidopsis/classification/*genetics ; Arabidopsis Proteins/genetics ; Base Sequence ; *Gene Expression Profiling ; Gene Expression Regulation, Plant/*genetics ; Genes, Plant/genetics ; Genome, Plant/*genetics ; Genomics ; Haplotypes/genetics ; INDEL Mutation/genetics ; Molecular Sequence Annotation ; Phylogeny ; Polymorphism, Single Nucleotide/genetics ; Proteome/genetics ; Seedlings/genetics ; Sequence Analysis, DNA ; Transcription, Genetic/*genetics
    Print ISSN: 0028-0836
    Electronic ISSN: 1476-4687
    Topics: Biology , Chemistry and Pharmacology , Medicine , Natural Sciences in General , Physics
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  • 3
    Electronic Resource
    Electronic Resource
    Amsterdam : Elsevier
    Regional and Urban Economics 3 (1973), S. 315-325 
    ISSN: 0034-3331
    Source: Elsevier Journal Backfiles on ScienceDirect 1907 - 2002
    Topics: Architecture, Civil Engineering, Surveying , Economics
    Type of Medium: Electronic Resource
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  • 4
    Electronic Resource
    Electronic Resource
    Amsterdam : Elsevier
    Regional and Urban Economics 1 (1971), S. 227-246 
    ISSN: 0034-3331
    Source: Elsevier Journal Backfiles on ScienceDirect 1907 - 2002
    Topics: Architecture, Civil Engineering, Surveying , Economics
    Type of Medium: Electronic Resource
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  • 5
    Electronic Resource
    Electronic Resource
    Amsterdam : Elsevier
    Cities 3 (1986), S. 333-349 
    ISSN: 0264-2751
    Source: Elsevier Journal Backfiles on ScienceDirect 1907 - 2002
    Topics: Architecture, Civil Engineering, Surveying , Geography
    Type of Medium: Electronic Resource
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  • 6
    Electronic Resource
    Electronic Resource
    Amsterdam : Elsevier
    Regional Science and Urban Economics 3 (1973), S. 315-325 
    ISSN: 0166-0462
    Source: Elsevier Journal Backfiles on ScienceDirect 1907 - 2002
    Topics: Architecture, Civil Engineering, Surveying , Geography , Sociology , Economics
    Type of Medium: Electronic Resource
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  • 7
    Publication Date: 2013-10-04
    Description: Motivation: High-throughput sequencing of mRNA (RNA-Seq) has led to tremendous improvements in the detection of expressed genes and reconstruction of RNA transcripts. However, the extensive dynamic range of gene expression, technical limitations and biases, as well as the observed complexity of the transcriptional landscape, pose profound computational challenges for transcriptome reconstruction. Results: We present the novel framework MITIE (Mixed Integer Transcript IdEntification) for simultaneous transcript reconstruction and quantification. We define a likelihood function based on the negative binomial distribution, use a regularization approach to select a few transcripts collectively explaining the observed read data and show how to find the optimal solution using Mixed Integer Programming. MITIE can (i) take advantage of known transcripts, (ii) reconstruct and quantify transcripts simultaneously in multiple samples, and (iii) resolve the location of multi-mapping reads. It is designed for genome- and assembly-based transcriptome reconstruction. We present an extensive study based on realistic simulated RNA-Seq data. When compared with state-of-the-art approaches, MITIE proves to be significantly more sensitive and overall more accurate. Moreover, MITIE yields substantial performance gains when used with multiple samples. We applied our system to 38 Drosophila melanogaster modENCODE RNA-Seq libraries and estimated the sensitivity of reconstructing omitted transcript annotations and the specificity with respect to annotated transcripts. Our results corroborate that a well-motivated objective paired with appropriate optimization techniques lead to significant improvements over the state-of-the-art in transcriptome reconstruction. Availability: MITIE is implemented in C++ and is available from http://bioweb.me/mitie under the GPL license. Contact: Jonas_Behr@web.de and raetsch@cbio.mskcc.org Supplementary information: Supplementary data are available at Bioinformatics online.
    Print ISSN: 1367-4803
    Electronic ISSN: 1460-2059
    Topics: Biology , Computer Science , Medicine
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  • 8
    Publication Date: 2014-04-25
    Description: We present Oqtans , an open-source workbench for quantitative transcriptome analysis, that is integrated in Galaxy . Its distinguishing features include customizable computational workflows and a modular pipeline architecture that facilitates comparative assessment of tool and data quality. Oqtans integrates an assortment of machine learning-powered tools into Galaxy , which show superior or equal performance to state-of-the-art tools. Implemented tools comprise a complete transcriptome analysis workflow: short-read alignment, transcript identification/quantification and differential expression analysis. Oqtans and Galaxy facilitate persistent storage, data exchange and documentation of intermediate results and analysis workflows. We illustrate how Oqtans aids the interpretation of data from different experiments in easy to understand use cases. Users can easily create their own workflows and extend Oqtans by integrating specific tools. Oqtans is available as (i) a cloud machine image with a demo instance at cloud.oqtans.org, (ii) a public Galaxy instance at galaxy.cbio.mskcc.org, (iii) a git repository containing all installed software (oqtans.org/git); most of which is also available from (iv) the Galaxy Toolshed and (v) a share string to use along with Galaxy CloudMan . Contact: vipin@cbio.mskcc.org , ratschg@mskcc.org Supplementary information: Supplementary data are available at Bioinformatics online.
    Print ISSN: 1367-4803
    Electronic ISSN: 1460-2059
    Topics: Biology , Computer Science , Medicine
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  • 9
    Publication Date: 2013-05-29
    Description: Deep transcriptome sequencing (RNA-Seq) has become a vital tool for studying the state of cells in the context of varying environments, genotypes and other factors. RNA-Seq profiling data enable identification of novel isoforms, quantification of known isoforms and detection of changes in transcriptional or RNA-processing activity. Existing approaches to detect differential isoform abundance between samples either require a complete isoform annotation or fall short in providing statistically robust and calibrated significance estimates. Here, we propose a suite of statistical tests to address these open needs: a parametric test that uses known isoform annotations to detect changes in relative isoform abundance and a non-parametric test that detects differential read coverages and can be applied when isoform annotations are not available. Both methods account for the discrete nature of read counts and the inherent biological variability. We demonstrate that these tests compare favorably to previous methods, both in terms of accuracy and statistical calibrations. We use these techniques to analyze RNA-Seq libraries from Arabidopsis thaliana and Drosophila melanogaster. The identified differential RNA processing events were consistent with RT–qPCR measurements and previous studies. The proposed toolkit is available from http://bioweb.me/rdiff and enables in-depth analyses of transcriptomes, with or without available isoform annotation.
    Keywords: Computational Methods, Massively Parallel (Deep) Sequencing, Genomics
    Print ISSN: 0305-1048
    Electronic ISSN: 1362-4962
    Topics: Biology
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  • 10
    Publication Date: 2016-12-30
    Description: Motivation: Deep sequencing based ribosome footprint profiling can provide novel insights into the regulatory mechanisms of protein translation. However, the observed ribosome profile is fundamentally confounded by transcriptional activity. In order to decipher principles of translation regulation, tools that can reliably detect changes in translation efficiency in case–control studies are needed. Results: We present a statistical framework and an analysis tool, RiboDiff, to detect genes with changes in translation efficiency across experimental treatments. RiboDiff uses generalized linear models to estimate the over-dispersion of RNA-Seq and ribosome profiling measurements separately, and performs a statistical test for differential translation efficiency using both mRNA abundance and ribosome occupancy. Availability and Implementation: RiboDiff webpage http://bioweb.me/ribodiff . Source code including scripts for preprocessing the FASTQ data are available at http://github.com/ratschlab/ribodiff . Contacts: zhongy@cbio.mskcc.org or raetsch@inf.ethz.ch Supplementary information: Supplementary data are available at Bioinformatics online.
    Print ISSN: 1367-4803
    Electronic ISSN: 1460-2059
    Topics: Biology , Computer Science , Medicine
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