DDX17 Specifically, and Independently of DDX5, Controls Use of the HIV A4/5 Splice Acceptor Cluster and Is Essential for Efficient Replication of HIV
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Katalog 2015 Cover Paul Lin *Hinweis Förderung.Indd
Product List 2015 WE LIVE SERVICE Certificates quartett owns two productions sites that are certified according to EN ISO 9001:2008 Quality management systems - Requirements EN ISO 13485:2012 + AC:2012 Medical devices - Quality management systems - Requirements for regulatory purposes GMP Conformity Our quality management guarantees products of highest quality! 2 Foreword to the quartett product list 2015 quartett Immunodiagnostika, Biotechnologie + Kosmetik Vertriebs GmbH welcomes you as one of our new business partners as well as all of our previous loyal clients. You are now member of quartett´s worldwide customers. First of all we would like to introduce ourselves to you. Founded as a family-run company in 1986, quartett ensures for more than a quarter of a century consistent quality of products. Service and support of our valued customers are our daily businesses. And we will continue! In the end 80´s quartett offered radioimmunoassay and enzyme immunoassay kits from different manufacturers in the USA. In the beginning 90´s the company changed its strategy from offering products for routine diagnostic to the increasing field of research and development. Setting up a production plant in 1997 and a second one in 2011 supported this decision. The company specialized its product profile in the field of manufacturing synthetic peptides for antibody production, peptides such as protease inhibitors, biochemical reagents and products for histology, cytology and immunohistology. All products are exclusively manufactured in Germany without outsourcing any production step. Nowadays, we expand into all other diagnostic and research fields and supply our customers in universities, government institutes, pharmaceutical and biotechnological companies, hospitals, and private doctor offices. -
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. -
DDX5 Targets Tissue-Specific Rnas to Promote Intestine Tumorigenesis
bioRxiv preprint doi: https://doi.org/10.1101/2020.03.25.006668; this version posted March 26, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. DDX5 targets tissue-specific RNAs to promote intestine tumorigenesis Nazia Abbasi1,4, Tianyun Long1,4, Yuxin Li1, Evelyn Ma1, Brian A. Yee1, Parth R. Patel1, Ibrahim M SayeD2, Nissi Varki2, Soumita Das2, PraDipta Ghosh1, 3, Gene W. Yeo1, WenDy J.M. Huang1,5 1 Department of Cellular anD Molecular MeDicine, University of California San Diego, La Jolla, CA 2 Department of Pathology, University of California San Diego, La Jolla, CA 3 Department of MeDicine, University of California San Diego, La Jolla, CA 4 These authors contributeD equally 5 CorresponDing author email: [email protected] Abstract Tumorigenesis in Different segments of the intestinal tract involves tissue-specific oncogenic Drivers. In the colon, complement component 3 (C3) activation is a major contributor to inflammation anD malignancies. By contrast, tumorigenesis in the small intestine involves fatty aciD-binding protein 1 (FABP1). However, little is known of the upstream mechanisms Driving their expressions in Different segments of the intestinal tract. Here, we report that an RNA binDing protein DDX5 augments C3 and FABP1 expressions post-transcriptionally to promote tumorigenesis in the colon anD small intestine, respectively. Mice with epithelial-specific knockout of DDX5 are protecteD from intestine tumorigenesis. The iDentification of DDX5 as the common upstream regulator of tissue-specific oncogenic molecules proviDes a new therapeutic target for intestine cancers. -
Supplementary Table S4. FGA Co-Expressed Gene List in LUAD
Supplementary Table S4. FGA co-expressed gene list in LUAD tumors Symbol R Locus Description FGG 0.919 4q28 fibrinogen gamma chain FGL1 0.635 8p22 fibrinogen-like 1 SLC7A2 0.536 8p22 solute carrier family 7 (cationic amino acid transporter, y+ system), member 2 DUSP4 0.521 8p12-p11 dual specificity phosphatase 4 HAL 0.51 12q22-q24.1histidine ammonia-lyase PDE4D 0.499 5q12 phosphodiesterase 4D, cAMP-specific FURIN 0.497 15q26.1 furin (paired basic amino acid cleaving enzyme) CPS1 0.49 2q35 carbamoyl-phosphate synthase 1, mitochondrial TESC 0.478 12q24.22 tescalcin INHA 0.465 2q35 inhibin, alpha S100P 0.461 4p16 S100 calcium binding protein P VPS37A 0.447 8p22 vacuolar protein sorting 37 homolog A (S. cerevisiae) SLC16A14 0.447 2q36.3 solute carrier family 16, member 14 PPARGC1A 0.443 4p15.1 peroxisome proliferator-activated receptor gamma, coactivator 1 alpha SIK1 0.435 21q22.3 salt-inducible kinase 1 IRS2 0.434 13q34 insulin receptor substrate 2 RND1 0.433 12q12 Rho family GTPase 1 HGD 0.433 3q13.33 homogentisate 1,2-dioxygenase PTP4A1 0.432 6q12 protein tyrosine phosphatase type IVA, member 1 C8orf4 0.428 8p11.2 chromosome 8 open reading frame 4 DDC 0.427 7p12.2 dopa decarboxylase (aromatic L-amino acid decarboxylase) TACC2 0.427 10q26 transforming, acidic coiled-coil containing protein 2 MUC13 0.422 3q21.2 mucin 13, cell surface associated C5 0.412 9q33-q34 complement component 5 NR4A2 0.412 2q22-q23 nuclear receptor subfamily 4, group A, member 2 EYS 0.411 6q12 eyes shut homolog (Drosophila) GPX2 0.406 14q24.1 glutathione peroxidase -
1714 Gene Comprehensive Cancer Panel Enriched for Clinically Actionable Genes with Additional Biologically Relevant Genes 400-500X Average Coverage on Tumor
xO GENE PANEL 1714 gene comprehensive cancer panel enriched for clinically actionable genes with additional biologically relevant genes 400-500x average coverage on tumor Genes A-C Genes D-F Genes G-I Genes J-L AATK ATAD2B BTG1 CDH7 CREM DACH1 EPHA1 FES G6PC3 HGF IL18RAP JADE1 LMO1 ABCA1 ATF1 BTG2 CDK1 CRHR1 DACH2 EPHA2 FEV G6PD HIF1A IL1R1 JAK1 LMO2 ABCB1 ATM BTG3 CDK10 CRK DAXX EPHA3 FGF1 GAB1 HIF1AN IL1R2 JAK2 LMO7 ABCB11 ATR BTK CDK11A CRKL DBH EPHA4 FGF10 GAB2 HIST1H1E IL1RAP JAK3 LMTK2 ABCB4 ATRX BTRC CDK11B CRLF2 DCC EPHA5 FGF11 GABPA HIST1H3B IL20RA JARID2 LMTK3 ABCC1 AURKA BUB1 CDK12 CRTC1 DCUN1D1 EPHA6 FGF12 GALNT12 HIST1H4E IL20RB JAZF1 LPHN2 ABCC2 AURKB BUB1B CDK13 CRTC2 DCUN1D2 EPHA7 FGF13 GATA1 HLA-A IL21R JMJD1C LPHN3 ABCG1 AURKC BUB3 CDK14 CRTC3 DDB2 EPHA8 FGF14 GATA2 HLA-B IL22RA1 JMJD4 LPP ABCG2 AXIN1 C11orf30 CDK15 CSF1 DDIT3 EPHB1 FGF16 GATA3 HLF IL22RA2 JMJD6 LRP1B ABI1 AXIN2 CACNA1C CDK16 CSF1R DDR1 EPHB2 FGF17 GATA5 HLTF IL23R JMJD7 LRP5 ABL1 AXL CACNA1S CDK17 CSF2RA DDR2 EPHB3 FGF18 GATA6 HMGA1 IL2RA JMJD8 LRP6 ABL2 B2M CACNB2 CDK18 CSF2RB DDX3X EPHB4 FGF19 GDNF HMGA2 IL2RB JUN LRRK2 ACE BABAM1 CADM2 CDK19 CSF3R DDX5 EPHB6 FGF2 GFI1 HMGCR IL2RG JUNB LSM1 ACSL6 BACH1 CALR CDK2 CSK DDX6 EPOR FGF20 GFI1B HNF1A IL3 JUND LTK ACTA2 BACH2 CAMTA1 CDK20 CSNK1D DEK ERBB2 FGF21 GFRA4 HNF1B IL3RA JUP LYL1 ACTC1 BAG4 CAPRIN2 CDK3 CSNK1E DHFR ERBB3 FGF22 GGCX HNRNPA3 IL4R KAT2A LYN ACVR1 BAI3 CARD10 CDK4 CTCF DHH ERBB4 FGF23 GHR HOXA10 IL5RA KAT2B LZTR1 ACVR1B BAP1 CARD11 CDK5 CTCFL DIAPH1 ERCC1 FGF3 GID4 HOXA11 IL6R KAT5 ACVR2A -
Transcriptomic and Proteomic Profiling Provides Insight Into
BASIC RESEARCH www.jasn.org Transcriptomic and Proteomic Profiling Provides Insight into Mesangial Cell Function in IgA Nephropathy † † ‡ Peidi Liu,* Emelie Lassén,* Viji Nair, Celine C. Berthier, Miyuki Suguro, Carina Sihlbom,§ † | † Matthias Kretzler, Christer Betsholtz, ¶ Börje Haraldsson,* Wenjun Ju, Kerstin Ebefors,* and Jenny Nyström* *Department of Physiology, Institute of Neuroscience and Physiology, §Proteomics Core Facility at University of Gothenburg, University of Gothenburg, Gothenburg, Sweden; †Division of Nephrology, Department of Internal Medicine and Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, Michigan; ‡Division of Molecular Medicine, Aichi Cancer Center Research Institute, Nagoya, Japan; |Department of Immunology, Genetics and Pathology, Uppsala University, Uppsala, Sweden; and ¶Integrated Cardio Metabolic Centre, Karolinska Institutet Novum, Huddinge, Sweden ABSTRACT IgA nephropathy (IgAN), the most common GN worldwide, is characterized by circulating galactose-deficient IgA (gd-IgA) that forms immune complexes. The immune complexes are deposited in the glomerular mesangium, leading to inflammation and loss of renal function, but the complete pathophysiology of the disease is not understood. Using an integrated global transcriptomic and proteomic profiling approach, we investigated the role of the mesangium in the onset and progression of IgAN. Global gene expression was investigated by microarray analysis of the glomerular compartment of renal biopsy specimens from patients with IgAN (n=19) and controls (n=22). Using curated glomerular cell type–specific genes from the published literature, we found differential expression of a much higher percentage of mesangial cell–positive standard genes than podocyte-positive standard genes in IgAN. Principal coordinate analysis of expression data revealed clear separation of patient and control samples on the basis of mesangial but not podocyte cell–positive standard genes. -
Regulates Target Gene Transcription Via Single-Stranded DNA Response Elements
TLS/FUS (translocated in liposarcoma/fused in sarcoma) regulates target gene transcription via single-stranded DNA response elements Adelene Y. Tan1, Todd R. Riley, Tristan Coady, Harmen J. Bussemaker, and James L. Manley2 Department of Biological Sciences, Columbia University, New York, NY 10027 Contributed by James L. Manley, February 29, 2012 (sent for review December 9, 2011) TLS/FUS (TLS) is a multifunctional protein implicated in a wide range TLS has also been linked to splicing. It contains an RNP-type of cellular processes, including transcription and mRNA processing, RNA-binding domain and associates directly with SR protein as well as in both cancer and neurological disease. However, little is splicing factors (11). TET proteins have been detected in spliceo- currently known about TLS target genes and how they are recog- somes (12), and TLS was found associated with RNAP II and nized. Here, we used ChIP and promoter microarrays to identify snRNPs in a transcription and splicing complex in vitro (13). It is genes potentially regulated by TLS. Among these genes, we detected unclear whether and how TLS recruits splicing factors to sites of a number that correlate with previously known functions of TLS, active transcription, but one possibility is through its interaction and confirmed TLS occupancy at several of them by ChIP. We also with TBP and the TFIID complex. detected changes in mRNA levels of these target genes in cells where Here we provide insight into TLS regulation of RNAP II-tran- scribed genes. We used ChIP followed by promoter microarray TLS levels were altered, indicative of both activation and repression. -
Supp Table 6.Pdf
Supplementary Table 6. Processes associated to the 2037 SCL candidate target genes ID Symbol Entrez Gene Name Process NM_178114 AMIGO2 adhesion molecule with Ig-like domain 2 adhesion NM_033474 ARVCF armadillo repeat gene deletes in velocardiofacial syndrome adhesion NM_027060 BTBD9 BTB (POZ) domain containing 9 adhesion NM_001039149 CD226 CD226 molecule adhesion NM_010581 CD47 CD47 molecule adhesion NM_023370 CDH23 cadherin-like 23 adhesion NM_207298 CERCAM cerebral endothelial cell adhesion molecule adhesion NM_021719 CLDN15 claudin 15 adhesion NM_009902 CLDN3 claudin 3 adhesion NM_008779 CNTN3 contactin 3 (plasmacytoma associated) adhesion NM_015734 COL5A1 collagen, type V, alpha 1 adhesion NM_007803 CTTN cortactin adhesion NM_009142 CX3CL1 chemokine (C-X3-C motif) ligand 1 adhesion NM_031174 DSCAM Down syndrome cell adhesion molecule adhesion NM_145158 EMILIN2 elastin microfibril interfacer 2 adhesion NM_001081286 FAT1 FAT tumor suppressor homolog 1 (Drosophila) adhesion NM_001080814 FAT3 FAT tumor suppressor homolog 3 (Drosophila) adhesion NM_153795 FERMT3 fermitin family homolog 3 (Drosophila) adhesion NM_010494 ICAM2 intercellular adhesion molecule 2 adhesion NM_023892 ICAM4 (includes EG:3386) intercellular adhesion molecule 4 (Landsteiner-Wiener blood group)adhesion NM_001001979 MEGF10 multiple EGF-like-domains 10 adhesion NM_172522 MEGF11 multiple EGF-like-domains 11 adhesion NM_010739 MUC13 mucin 13, cell surface associated adhesion NM_013610 NINJ1 ninjurin 1 adhesion NM_016718 NINJ2 ninjurin 2 adhesion NM_172932 NLGN3 neuroligin -
UTR Shortening Is a Molecular Signature of Mtorc1 Activation
ARTICLE Received 22 Sep 2014 | Accepted 18 Apr 2015 | Published 15 Jun 2015 DOI: 10.1038/ncomms8218 mRNA 30-UTR shortening is a molecular signature of mTORC1 activation Jae-Woong Chang1,*, Wei Zhang2,*, Hsin-Sung Yeh1, Ebbing P. de Jong1, Semo Jun1, Kwan-Hyun Kim1, Sun S. Bae3, Kenneth Beckman4, Tae Hyun Hwang5, Kye-Seong Kim6, Do-Hyung Kim1, Timothy J. Griffin1, Rui Kuang2 & Jeongsik Yong1 Mammalian target of rapamycin (mTOR) enhances translation from a subset of messenger RNAs containing distinct 50-untranslated region (UTR) sequence features. Here we identify 30-UTR shortening of mRNAs as an additional molecular signature of mTOR activation and show that 30-UTR shortening enhances the translation of specific mRNAs. Using genetic or chemical modulations of mTOR activity in cells or mouse tissues, we show that cellular mTOR activity is crucial for 30-UTR shortening. Although long 30-UTR-containing transcripts minimally contribute to translation, 3-0UTR-shortened transcripts efficiently form polysomes in the mTOR-activated cells, leading to increased protein production. Strikingly, selected E2 and E3 components of ubiquitin ligase complexes are enriched by this mechanism, resulting in elevated levels of protein ubiquitination on mTOR activation. Together, these findings identify a previously uncharacterized role for mTOR in the selective regulation of protein synthesis by modulating 30-UTR length of mRNAs. 1 Department of Biochemistry, Molecular Biology and Biophysics, University of Minnesota Twin Cities, 321 Church Street, SE 6-155 Jackson Hall, Minneapolis, Minnesota 55455, USA. 2 Department of Computer Science and Engineering, University of Minnesota, Minneapolis, Minnesota 55455, USA. 3 Department of Pharmacology, Pusan National University School of Medicine, Yangsan 626-870, Republic of Korea. -
Estrogen Regulation and Physiopathologic Significance of Alternative Promoters in Breast Cancer
Published OnlineFirst April 20, 2010; DOI: 10.1158/0008-5472.CAN-09-3988 Published OnlineFirst on April 20, 2010 as 10.1158/0008-5472.CAN-09-3988 Tumor and Stem Cell Biology Cancer Research Estrogen Regulation and Physiopathologic Significance of Alternative Promoters in Breast Cancer Martin Dutertre1, Lise Gratadou1, Etienne Dardenne1, Sophie Germann1, Samaan Samaan1, Rosette Lidereau2, Keltouma Driouch2, Pierre de la Grange3, and Didier Auboeuf1 Abstract Alternative promoters (AP) occur in >30% protein-coding genes and contribute to proteome diversity. How- ever, large-scale analyses of AP regulation are lacking, and little is known about their potential physiopatho- logic significance. To better understand the transcriptomic effect of estrogens, which play a major role in breast cancer, we analyzed gene and AP regulation by estradiol in MCF7 cells using pan-genomic exon arrays. We thereby identified novel estrogen-regulated genes (ERG) and determined the regulation of AP-encoded transcripts in 150 regulated genes. In <30% cases, APs were regulated in a similar manner by estradiol, whereas in >70% cases, they were regulated differentially. The patterns of AP regulation correlated with the patterns of estrogen receptor α (ERα) and CCCTC-binding factor (CTCF) binding sites at regulated gene loci. Interest- ingly, among genes with differentially regulated (DR) APs, we identified cases where estradiol regulated APs in an opposite manner, sometimes without affecting global gene expression levels. This promoter switch was mediated by the DDX5/DDX17 family of ERα coregulators. Finally, genes with DR promoters were preferen- tially involved in specific processes (e.g., cell structure and motility, and cell cycle). We show, in particular, that isoforms encoded by the NET1 gene APs, which are inversely regulated by estradiol, play distinct roles in cell adhesion and cell cycle regulation and that their expression is differentially associated with prognosis in ER+ breast cancer. -
Identification of Protein Features Encoded by Alternative Exons Using Exon Ontology
Downloaded from genome.cshlp.org on October 2, 2021 - Published by Cold Spring Harbor Laboratory Press Resource Identification of protein features encoded by alternative exons using Exon Ontology Léon-Charles Tranchevent,1 Fabien Aubé,1 Louis Dulaurier,1 Clara Benoit-Pilven,1 Amandine Rey,1 Arnaud Poret,1 Emilie Chautard,2 Hussein Mortada,1 François-Olivier Desmet,1 Fatima Zahra Chakrama,1 Maira Alejandra Moreno-Garcia,1 Evelyne Goillot,3 Stéphane Janczarski,1 Franck Mortreux,1 Cyril F. Bourgeois,1,4 and Didier Auboeuf1,4 1Université Lyon 1, ENS de Lyon, CNRS UMR 5239, INSERM U1210, Laboratory of Biology and Modelling of the Cell, F-69007, Lyon, France; 2Laboratoire de Biométrie et Biologie Évolutive, Université Lyon 1, UMR CNRS 5558, INRIA Erable, Villeurbanne, F-69622, France; 3Institut NeuroMyoGène, CNRS UMR 5310, INSERM U1217, Université Lyon 1, Lyon, F-69007 France Transcriptomic genome-wide analyses demonstrate massive variation of alternative splicing in many physiological and pathological situations. One major challenge is now to establish the biological contribution of alternative splicing var- iation in physiological- or pathological-associated cellular phenotypes. Toward this end, we developed a computational approach, named Exon Ontology, based on terms corresponding to well-characterized protein features organized in an ontology tree. Exon Ontology is conceptually similar to Gene Ontology-based approaches but focuses on exon-encod- ed protein features instead of gene level functional annotations. Exon Ontology describes the protein features encoded by a selected list of exons and looks for potential Exon Ontology term enrichment. By applying this strategy to exons that are differentially spliced between epithelial and mesenchymal cells and after extensive experimental validation, we demonstrate that Exon Ontology provides support to discover specific protein features regulated by alternative splic- ing. -
Integrative Genomic Analysis of Hnrnp L Splicing Regulation
University of Pennsylvania ScholarlyCommons Publicly Accessible Penn Dissertations 2015 Terrae Incognitae: Integrative Genomic Analysis of Hnrnp L Splicing Regulation Brian Sebastian Cole University of Pennsylvania, [email protected] Follow this and additional works at: https://repository.upenn.edu/edissertations Part of the Allergy and Immunology Commons, Biochemistry Commons, Bioinformatics Commons, Immunology and Infectious Disease Commons, and the Medical Immunology Commons Recommended Citation Cole, Brian Sebastian, "Terrae Incognitae: Integrative Genomic Analysis of Hnrnp L Splicing Regulation" (2015). Publicly Accessible Penn Dissertations. 1664. https://repository.upenn.edu/edissertations/1664 This paper is posted at ScholarlyCommons. https://repository.upenn.edu/edissertations/1664 For more information, please contact [email protected]. Terrae Incognitae: Integrative Genomic Analysis of Hnrnp L Splicing Regulation Abstract Alternative splicing is a critical component of human gene control that generates functional diversity from a limited genome. Defects in alternative splicing are associated with disease in humans. Alternative splicing is regulated developmentally and physiologically by the combinatorial actions of cis- and trans- acting factors, including RNA binding proteins that regulate splicing through sequence-specific interactions with pre-mRNAs. In T cells, the splicing regulator hnRNP L is an essential factor that regulates alternative splicing of physiologically important mRNAs, however the broader physical and functional impact of hnRNP L remains unknown. In this dissertation, I present analysis of hnRNP L-RNA interactions with CLIP-seq, which identifies transcriptome-wide binding sites and uncovers novel functional targets. I then use functional genomics studies to define pre-mRNA processing alterations induced by hnRNP L depletion, chief among which is cassette-type alternative splicing.