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Detection of Interacting Transcription Factors in Human Tissues Using
Myšičková and Vingron BMC Genomics 2012, 13(Suppl 1):S2 http://www.biomedcentral.com/1471-2164/13/S1/S2 PROCEEDINGS Open Access Detection of interacting transcription factors in human tissues using predicted DNA binding affinity Alena Myšičková*, Martin Vingron From The Tenth Asia Pacific Bioinformatics Conference (APBC 2012) Melbourne, Australia. 17-19 January 2012 Abstract Background: Tissue-specific gene expression is generally regulated by combinatorial interactions among transcription factors (TFs) which bind to the DNA. Despite this known fact, previous discoveries of the mechanism that controls gene expression usually consider only a single TF. Results: We provide a prediction of interacting TFs in 22 human tissues based on their DNA-binding affinity in promoter regions. We analyze all possible pairs of 130 vertebrate TFs from the JASPAR database. First, all human promoter regions are scanned for single TF-DNA binding affinities with TRAP and for each TF a ranked list of all promoters ordered by the binding affinity is created. We then study the similarity of the ranked lists and detect candidates for TF-TF interaction by applying a partial independence test for multiway contingency tables. Our candidates are validated by both known protein-protein interactions (PPIs) and known gene regulation mechanisms in the selected tissue. We find that the known PPIs are significantly enriched in the groups of our predicted TF-TF interactions (2 and 7 times more common than expected by chance). In addition, the predicted interacting TFs for studied tissues (liver, muscle, hematopoietic stem cell) are supported in literature to be active regulators or to be expressed in the corresponding tissue. -
Identifying and Mapping Cell-Type-Specific Chromatin PNAS PLUS Programming of Gene Expression
Identifying and mapping cell-type-specific chromatin PNAS PLUS programming of gene expression Troels T. Marstranda and John D. Storeya,b,1 aLewis-Sigler Institute for Integrative Genomics, and bDepartment of Molecular Biology, Princeton University, Princeton, NJ 08544 Edited by Wing Hung Wong, Stanford University, Stanford, CA, and approved January 2, 2014 (received for review July 2, 2013) A problem of substantial interest is to systematically map variation Relating DHS to gene-expression levels across multiple cell in chromatin structure to gene-expression regulation across con- types is challenging because the DHS represents a continuous ditions, environments, or differentiated cell types. We developed variable along the genome not bound to any specific region, and and applied a quantitative framework for determining the exis- the relationship between DHS and gene expression is largely tence, strength, and type of relationship between high-resolution uncharacterized. To exploit variation across cell types and test chromatin structure in terms of DNaseI hypersensitivity and genome- for cell-type-specific relationships between DHS and gene expres- wide gene-expression levels in 20 diverse human cell types. We sion, the measurement units must be placed on a common scale, show that ∼25% of genes show cell-type-specific expression ex- the continuous DHS measure associated to each gene in a well- plained by alterations in chromatin structure. We find that distal defined manner, and all measurements considered simultaneously. regions of chromatin structure (e.g., ±200 kb) capture more genes Moreover, the chromatin and gene-expression relationship may with this relationship than local regions (e.g., ±2.5 kb), yet the local only manifest in a single cell type, making standard measures of regions show a more pronounced effect. -
REST Mediates Androgen Receptor Actions on Gene Repression And
Published online 24 October 2013 Nucleic Acids Research, 2014, Vol. 42, No. 2 999–1015 doi:10.1093/nar/gkt921 REST mediates androgen receptor actions on gene repression and predicts early recurrence of prostate cancer Charlotte Svensson1, Jens Ceder2, Diego Iglesias-Gato1, Yin-Choy Chuan1, See Tong Pang3, Anders Bjartell2, Roxana Merino Martinez4, Laura Bott5, Leszek Helczynski6, David Ulmert2,7, Yuzhuo Wang8, Yuanjie Niu9, Colin Collins8 and Amilcar Flores-Morales1,* 1Novo Nordisk Foundation Center for Protein Research, Faculty of Health Sciences, University of Copenhagen, Downloaded from DK-2200 Copenhagen, Denmark, 2Division of Urological Cancers, Department of Clinical Sciences, Ska˚ ne University Hospital, Lund University, 20502 Malmo¨ , Sweden, 3Department of Urology, Chang Gung Memorial Hospital, Tao-Yuan 33305, Taiwan, R.O.C., 4Department of Epidemiology, Karolinska Institutet, 171 77 Stockholm, Sweden, 5Department of Cell and Molecular Biology, Karolinska Institute, 171 77 Stockholm, Sweden, 6Regional Laboratories Region Ska˚ ne, Clinical Pathology, 205 80 Malmo¨ , Sweden, 7Department of Surgery (Urology), Memorial Sloan-Kettering Cancer Center, New York, NY 100 65, USA, 8Vancouver Prostate http://nar.oxfordjournals.org/ Centre and The Department of Urologic Sciences, University of British Columbia, Vancouver, BC Canada V6H 3Z6 and 9Tianjin Institute of Urology, Tianjin Medical University, Tianjin 300 211, China Received December 19, 2012; Accepted September 20, 2013 ABSTRACT that has previously been implicated in the growth at University of British Columbia on August 12, 2014 The androgen receptor (AR) is a key regulator of NE-like castration-resistant tumors. The of prostate tumorgenesis through actions that are analysis of prostate cancer tissue microarrays not fully understood. We identified the repressor revealed that tumors with reduced expression of element (RE)-1 silencing transcription factor REST have higher probability of early recurrence, (REST) as a mediator of AR actions on gene repres- independently of their Gleason score. -
Further Delineation of Chromosomal Consensus Regions in Primary
Leukemia (2007) 21, 2463–2469 & 2007 Nature Publishing Group All rights reserved 0887-6924/07 $30.00 www.nature.com/leu ORIGINAL ARTICLE Further delineation of chromosomal consensus regions in primary mediastinal B-cell lymphomas: an analysis of 37 tumor samples using high-resolution genomic profiling (array-CGH) S Wessendorf1,6, TFE Barth2,6, A Viardot1, A Mueller3, HA Kestler3, H Kohlhammer1, P Lichter4, M Bentz5,HDo¨hner1,PMo¨ller2 and C Schwaenen1 1Klinik fu¨r Innere Medizin III, Zentrum fu¨r Innere Medizin der Universita¨t Ulm, Ulm, Germany; 2Institut fu¨r Pathologie, Universita¨t Ulm, Ulm, Germany; 3Forschungsdozentur Bioinformatik, Universita¨t Ulm, Ulm, Germany; 4Abt. Molekulare Genetik, Deutsches Krebsforschungszentrum, Heidelberg, Germany and 5Sta¨dtisches Klinikum Karlsruhe, Karlsruhe, Germany Primary mediastinal B-cell lymphoma (PMBL) is an aggressive the expression of BSAP, BOB1, OCT2, PAX5 and PU1 was extranodal B-cell non-Hodgkin’s lymphoma with specific clin- added to the spectrum typical of PMBL features.9 ical, histopathological and genomic features. To characterize Genetically, a pattern of highly recurrent karyotype alterations further the genotype of PMBL, we analyzed 37 tumor samples and PMBL cell lines Med-B1 and Karpas1106P using array- with the hallmark of chromosomal gains of the subtelomeric based comparative genomic hybridization (matrix- or array- region of chromosome 9 supported the concept of a unique CGH) to a 2.8k genomic microarray. Due to a higher genomic disease entity that distinguishes PMBL from other B-cell non- resolution, we identified altered chromosomal regions in much Hodgkin’s lymphomas.10,11 Together with less specific gains on higher frequencies compared with standard CGH: for example, 2p15 and frequent mutations of the SOCS1 gene, a notable þ 9p24 (68%), þ 2p15 (51%), þ 7q22 (32%), þ 9q34 (32%), genomic similarity to classical Hodgkin’s lymphoma was þ 11q23 (18%), þ 12q (30%) and þ 18q21 (24%). -
A Computational Approach for Defining a Signature of Β-Cell Golgi Stress in Diabetes Mellitus
Page 1 of 781 Diabetes A Computational Approach for Defining a Signature of β-Cell Golgi Stress in Diabetes Mellitus Robert N. Bone1,6,7, Olufunmilola Oyebamiji2, Sayali Talware2, Sharmila Selvaraj2, Preethi Krishnan3,6, Farooq Syed1,6,7, Huanmei Wu2, Carmella Evans-Molina 1,3,4,5,6,7,8* Departments of 1Pediatrics, 3Medicine, 4Anatomy, Cell Biology & Physiology, 5Biochemistry & Molecular Biology, the 6Center for Diabetes & Metabolic Diseases, and the 7Herman B. Wells Center for Pediatric Research, Indiana University School of Medicine, Indianapolis, IN 46202; 2Department of BioHealth Informatics, Indiana University-Purdue University Indianapolis, Indianapolis, IN, 46202; 8Roudebush VA Medical Center, Indianapolis, IN 46202. *Corresponding Author(s): Carmella Evans-Molina, MD, PhD ([email protected]) Indiana University School of Medicine, 635 Barnhill Drive, MS 2031A, Indianapolis, IN 46202, Telephone: (317) 274-4145, Fax (317) 274-4107 Running Title: Golgi Stress Response in Diabetes Word Count: 4358 Number of Figures: 6 Keywords: Golgi apparatus stress, Islets, β cell, Type 1 diabetes, Type 2 diabetes 1 Diabetes Publish Ahead of Print, published online August 20, 2020 Diabetes Page 2 of 781 ABSTRACT The Golgi apparatus (GA) is an important site of insulin processing and granule maturation, but whether GA organelle dysfunction and GA stress are present in the diabetic β-cell has not been tested. We utilized an informatics-based approach to develop a transcriptional signature of β-cell GA stress using existing RNA sequencing and microarray datasets generated using human islets from donors with diabetes and islets where type 1(T1D) and type 2 diabetes (T2D) had been modeled ex vivo. To narrow our results to GA-specific genes, we applied a filter set of 1,030 genes accepted as GA associated. -
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Produktinformation Diagnostik & molekulare Diagnostik Laborgeräte & Service Zellkultur & Verbrauchsmaterial Forschungsprodukte & Biochemikalien Weitere Information auf den folgenden Seiten! See the following pages for more information! Lieferung & Zahlungsart Lieferung: frei Haus Bestellung auf Rechnung SZABO-SCANDIC Lieferung: € 10,- HandelsgmbH & Co KG Erstbestellung Vorauskassa Quellenstraße 110, A-1100 Wien T. +43(0)1 489 3961-0 Zuschläge F. +43(0)1 489 3961-7 [email protected] • Mindermengenzuschlag www.szabo-scandic.com • Trockeneiszuschlag • Gefahrgutzuschlag linkedin.com/company/szaboscandic • Expressversand facebook.com/szaboscandic Tel:240-252-7368(USA) Fax:240-252-7376(USA) www.elabscience.com ® E-mail:[email protected] Elabscience Elabscience Biotechnology Inc. RIC8A Polyclonal Antibody Catalog No. E-AB-52943 Reactivity H,M,R Storage Store at -20℃. Avoid freeze / thaw cycles. Host Rabbit Applications IHC,ELISA Isotype IgG Note: Centrifuge before opening to ensure complete recovery of vial contents. Images Immunogen Information Immunogen Fusion protein of human RIC8A Gene Accession BC011821 Swissprot Q9NPQ8 Synonyms MGC104517,MGC131931,MGC148073,MGC14807 4,RIC8,RIC8A,RIC8A,Synembryn-A Immunohistochemistry of paraffin- Product Information embedded Human tonsil tissue using Buffer PBS with 0.05% NaN3 and 40% Glycerol,pH7.4 RIC8A Polyclonal Antibody at Purify Antigen affinity purification dilution of 1:80(×200) Dilution IHC 1:50-1:300, ELISA 1:5000-1:10000 Background Guanine nucleotide exchange factor (GEF), which can activate some, but not all, G-alpha proteins. Able to activate GNAI1, GNAO1 and GNAQ, Immunohistochemistry of paraffin- but not GNAS by exchanging bound GDP for free GTP. Involved in embedded Human liver cancer tissue regulation of microtubule pulling forces during mitotic movement of using RIC8A Polyclonal Antibody at chromosomes by stimulating G(i)-alpha protein, possibly leading to dilution of 1:80(×200) release G(i)-alpha-GTP and NuMA proteins from the NuMA- GPSM2-G(i)-alpha-GDP complex (By similarity). -
Prox1regulates the Subtype-Specific Development of Caudal Ganglionic
The Journal of Neuroscience, September 16, 2015 • 35(37):12869–12889 • 12869 Development/Plasticity/Repair Prox1 Regulates the Subtype-Specific Development of Caudal Ganglionic Eminence-Derived GABAergic Cortical Interneurons X Goichi Miyoshi,1 Allison Young,1 Timothy Petros,1 Theofanis Karayannis,1 Melissa McKenzie Chang,1 Alfonso Lavado,2 Tomohiko Iwano,3 Miho Nakajima,4 Hiroki Taniguchi,5 Z. Josh Huang,5 XNathaniel Heintz,4 Guillermo Oliver,2 Fumio Matsuzaki,3 Robert P. Machold,1 and Gord Fishell1 1Department of Neuroscience and Physiology, NYU Neuroscience Institute, Smilow Research Center, New York University School of Medicine, New York, New York 10016, 2Department of Genetics & Tumor Cell Biology, St. Jude Children’s Research Hospital, Memphis, Tennessee 38105, 3Laboratory for Cell Asymmetry, RIKEN Center for Developmental Biology, Kobe 650-0047, Japan, 4Laboratory of Molecular Biology, Howard Hughes Medical Institute, GENSAT Project, The Rockefeller University, New York, New York 10065, and 5Cold Spring Harbor Laboratory, Cold Spring Harbor, New York 11724 Neurogliaform (RELNϩ) and bipolar (VIPϩ) GABAergic interneurons of the mammalian cerebral cortex provide critical inhibition locally within the superficial layers. While these subtypes are known to originate from the embryonic caudal ganglionic eminence (CGE), the specific genetic programs that direct their positioning, maturation, and integration into the cortical network have not been eluci- dated. Here, we report that in mice expression of the transcription factor Prox1 is selectively maintained in postmitotic CGE-derived cortical interneuron precursors and that loss of Prox1 impairs the integration of these cells into superficial layers. Moreover, Prox1 differentially regulates the postnatal maturation of each specific subtype originating from the CGE (RELN, Calb2/VIP, and VIP). -
Exome-Wide Meta-Analysis Identifies Rare 3'-UTR Variant In
View metadata, citation and similar papers at core.ac.uk brought to you by CORE provided by Erasmus University Digital Repository ORIGINAL RESEARCH published: 18 October 2017 doi: 10.3389/fgene.2017.00151 Exome-Wide Meta-Analysis Identifies Rare 3′-UTR Variant in ERCC1/CD3EAP Associated with Symptoms of Sleep Apnea Ashley van der Spek 1, Annemarie I. Luik 2, Desana Kocevska 3, Chunyu Liu 4, 5, 6, Rutger W. W. Brouwer 7, Jeroen G. J. van Rooij 8, 9, 10, Mirjam C. G. N. van den Hout 7, Robert Kraaij 1, 8, 9, Albert Hofman 1, 11, André G. Uitterlinden 1, 8, 9, Wilfred F. J. van IJcken 7, Daniel J. Gottlieb 12, 13, 14, Henning Tiemeier 1, 15, Cornelia M. van Duijn 1 and Najaf Amin 1* 1 Department of Epidemiology, Erasmus Medical Center, Rotterdam, Netherlands, 2 Sleep and Circadian Neuroscience Institute, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom, 3 Department of Child and Adolescent Psychiatry, Erasmus Medical Center, Rotterdam, Netherlands, 4 Framingham Heart Study, National Heart, Lung, and Blood Institute, Framingham, MA, United States, 5 Population Sciences Branch, National Heart, Lung, and Blood Institute, Bethesda, MD, United States, 6 Department of Biostatistics, School of Public Health, Boston University, Boston, MA, United States, 7 Center for Biomics, Erasmus Medical Center, Rotterdam, Netherlands, 8 Department of Internal Medicine, Erasmus Medical Center, Rotterdam, Netherlands, 9 Netherlands Consortium for Healthy Ageing, Rotterdam, Netherlands, 10 Department of Neurology, Erasmus -
Clinical Utility of Recently Identified Diagnostic, Prognostic, And
Modern Pathology (2017) 30, 1338–1366 1338 © 2017 USCAP, Inc All rights reserved 0893-3952/17 $32.00 Clinical utility of recently identified diagnostic, prognostic, and predictive molecular biomarkers in mature B-cell neoplasms Arantza Onaindia1, L Jeffrey Medeiros2 and Keyur P Patel2 1Instituto de Investigacion Marques de Valdecilla (IDIVAL)/Hospital Universitario Marques de Valdecilla, Santander, Spain and 2Department of Hematopathology, MD Anderson Cancer Center, Houston, TX, USA Genomic profiling studies have provided new insights into the pathogenesis of mature B-cell neoplasms and have identified markers with prognostic impact. Recurrent mutations in tumor-suppressor genes (TP53, BIRC3, ATM), and common signaling pathways, such as the B-cell receptor (CD79A, CD79B, CARD11, TCF3, ID3), Toll- like receptor (MYD88), NOTCH (NOTCH1/2), nuclear factor-κB, and mitogen activated kinase signaling, have been identified in B-cell neoplasms. Chronic lymphocytic leukemia/small lymphocytic lymphoma, diffuse large B-cell lymphoma, follicular lymphoma, mantle cell lymphoma, Burkitt lymphoma, Waldenström macroglobulinemia, hairy cell leukemia, and marginal zone lymphomas of splenic, nodal, and extranodal types represent examples of B-cell neoplasms in which novel molecular biomarkers have been discovered in recent years. In addition, ongoing retrospective correlative and prospective outcome studies have resulted in an enhanced understanding of the clinical utility of novel biomarkers. This progress is reflected in the 2016 update of the World Health Organization classification of lymphoid neoplasms, which lists as many as 41 mature B-cell neoplasms (including provisional categories). Consequently, molecular genetic studies are increasingly being applied for the clinical workup of many of these neoplasms. In this review, we focus on the diagnostic, prognostic, and/or therapeutic utility of molecular biomarkers in mature B-cell neoplasms. -
Targeted Resequencing Identifies Genes with Recurrent Variation In
www.nature.com/npjgenmed ARTICLE OPEN Targeted resequencing identifies genes with recurrent variation in cerebral palsy C. L. van Eyk 1,2, M. A. Corbett 1,2, M. S. B. Frank 1,2, D. L. Webber1,2, M. Newman3, J. G. Berry 1,2, K. Harper1,2, B. P. Haines1,2, G. McMichael1,2, J. A. Woenig1,2, A. H. MacLennan1,2 and J. Gecz 1,2,4* A growing body of evidence points to a considerable and heterogeneous genetic aetiology of cerebral palsy (CP). To identify recurrently variant CP genes, we designed a custom gene panel of 112 candidate genes. We tested 366 clinically unselected singleton cases with CP, including 271 cases not previously examined using next-generation sequencing technologies. Overall, 5.2% of the naïve cases (14/271) harboured a genetic variant of clinical significance in a known disease gene, with a further 4.8% of individuals (13/271) having a variant in a candidate gene classified as intolerant to variation. In the aggregate cohort of individuals from this study and our previous genomic investigations, six recurrently hit genes contributed at least 4% of disease burden to CP: COL4A1, TUBA1A, AGAP1, L1CAM, MAOB and KIF1A. Significance of Rare VAriants (SORVA) burden analysis identified four genes with a genome-wide significant burden of variants, AGAP1, ERLIN1, ZDHHC9 and PROC, of which we functionally assessed AGAP1 using a zebrafish model. Our investigations reinforce that CP is a heterogeneous neurodevelopmental disorder with known as well as novel genetic determinants. npj Genomic Medicine (2019) ; https://doi.org/10.1038/s41525-019-0101-z4:27 1234567890():,; INTRODUCTION is likely also due in part to the stringent criteria used to select Cerebral palsy (CP) is the most common motor disability of causative variants. -
Genome-Wide DNA Methylation Analysis of KRAS Mutant Cell Lines Ben Yi Tew1,5, Joel K
www.nature.com/scientificreports OPEN Genome-wide DNA methylation analysis of KRAS mutant cell lines Ben Yi Tew1,5, Joel K. Durand2,5, Kirsten L. Bryant2, Tikvah K. Hayes2, Sen Peng3, Nhan L. Tran4, Gerald C. Gooden1, David N. Buckley1, Channing J. Der2, Albert S. Baldwin2 ✉ & Bodour Salhia1 ✉ Oncogenic RAS mutations are associated with DNA methylation changes that alter gene expression to drive cancer. Recent studies suggest that DNA methylation changes may be stochastic in nature, while other groups propose distinct signaling pathways responsible for aberrant methylation. Better understanding of DNA methylation events associated with oncogenic KRAS expression could enhance therapeutic approaches. Here we analyzed the basal CpG methylation of 11 KRAS-mutant and dependent pancreatic cancer cell lines and observed strikingly similar methylation patterns. KRAS knockdown resulted in unique methylation changes with limited overlap between each cell line. In KRAS-mutant Pa16C pancreatic cancer cells, while KRAS knockdown resulted in over 8,000 diferentially methylated (DM) CpGs, treatment with the ERK1/2-selective inhibitor SCH772984 showed less than 40 DM CpGs, suggesting that ERK is not a broadly active driver of KRAS-associated DNA methylation. KRAS G12V overexpression in an isogenic lung model reveals >50,600 DM CpGs compared to non-transformed controls. In lung and pancreatic cells, gene ontology analyses of DM promoters show an enrichment for genes involved in diferentiation and development. Taken all together, KRAS-mediated DNA methylation are stochastic and independent of canonical downstream efector signaling. These epigenetically altered genes associated with KRAS expression could represent potential therapeutic targets in KRAS-driven cancer. Activating KRAS mutations can be found in nearly 25 percent of all cancers1. -
Gene Standard Deviation MTOR 0.12553731 PRPF38A
BMJ Publishing Group Limited (BMJ) disclaims all liability and responsibility arising from any reliance Supplemental material placed on this supplemental material which has been supplied by the author(s) Gut Gene Standard Deviation MTOR 0.12553731 PRPF38A 0.141472605 EIF2B4 0.154700091 DDX50 0.156333027 SMC3 0.161420017 NFAT5 0.166316903 MAP2K1 0.166585267 KDM1A 0.16904912 RPS6KB1 0.170330192 FCF1 0.170391706 MAP3K7 0.170660513 EIF4E2 0.171572093 TCEB1 0.175363093 CNOT10 0.178975095 SMAD1 0.179164705 NAA15 0.179904998 SETD2 0.180182498 HDAC3 0.183971158 AMMECR1L 0.184195031 CHD4 0.186678211 SF3A3 0.186697697 CNOT4 0.189434633 MTMR14 0.189734199 SMAD4 0.192451524 TLK2 0.192702667 DLG1 0.19336621 COG7 0.193422331 SP1 0.194364189 PPP3R1 0.196430217 ERBB2IP 0.201473001 RAF1 0.206887192 CUL1 0.207514271 VEZF1 0.207579584 SMAD3 0.208159809 TFDP1 0.208834504 VAV2 0.210269344 ADAM17 0.210687138 SMURF2 0.211437666 MRPS5 0.212428684 TMUB2 0.212560675 SRPK2 0.216217428 MAP2K4 0.216345366 VHL 0.219735582 SMURF1 0.221242495 PLCG1 0.221688351 EP300 0.221792349 Sundar R, et al. Gut 2020;0:1–10. doi: 10.1136/gutjnl-2020-320805 BMJ Publishing Group Limited (BMJ) disclaims all liability and responsibility arising from any reliance Supplemental material placed on this supplemental material which has been supplied by the author(s) Gut MGAT5 0.222050228 CDC42 0.2230598 DICER1 0.225358787 RBX1 0.228272533 ZFYVE16 0.22831803 PTEN 0.228595789 PDCD10 0.228799406 NF2 0.23091035 TP53 0.232683696 RB1 0.232729172 TCF20 0.2346075 PPP2CB 0.235117302 AGK 0.235416298