DDX5 Potentiates HIV-1 Transcription As a Co-Factor Of
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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. - 
												
												Functional Control of HIV-1 Post-Transcriptional Gene Expression by Host Cell Factors
Functional control of HIV-1 post-transcriptional gene expression by host cell factors DISSERTATION Presented in Partial Fulfillment of the Requirements for the Degree Doctor of Philosophy in the Graduate School of The Ohio State University By Amit Sharma, B.Tech. Graduate Program in Molecular Genetics The Ohio State University 2012 Dissertation Committee Dr. Kathleen Boris-Lawrie, Advisor Dr. Anita Hopper Dr. Karin Musier-Forsyth Dr. Stephen Osmani Copyright by Amit Sharma 2012 Abstract Retroviruses are etiological agents of several human and animal immunosuppressive disorders. They are associated with certain types of cancer and are useful tools for gene transfer applications. All retroviruses encode a single primary transcript that encodes a complex proteome. The RNA genome is reverse transcribed into DNA, integrated into the host genome, and uses host cell factors to transcribe, process and traffic transcripts that encode viral proteins and act as virion precursor RNA, which is packaged into the progeny virions. The functionality of retroviral RNA is governed by ribonucleoprotein (RNP) complexes formed by host RNA helicases and other RNA- binding proteins. The 5’ leader of retroviral RNA undergoes alternative inter- and intra- molecular RNA-RNA and RNA-protein interactions to complete multiple steps of the viral life cycle. Retroviruses do not encode any RNA helicases and are dependent on host enzymes and RNA chaperones. Several members of the host RNA helicase superfamily are necessary for progressive steps during the retroviral replication. RNA helicase A (RHA) interacts with the redundant structural elements in the 5’ untranslated region (UTR) of retroviral and selected cellular mRNAs and this interaction is necessary to facilitate polyribosome formation and productive protein synthesis. - 
												
												The RNA Helicase a in Malignant Transformation
www.impactjournals.com/oncotarget/ Oncotarget, Vol. 7, No. 19 The RNA helicase A in malignant transformation Marco Fidaleo1,2, Elisa De Paola1,2 and Maria Paola Paronetto1,2 1 Department of Movement, Human and Health Sciences, University of Rome “Foro Italico”, Rome, Italy 2 Laboratory of Cellular and Molecular Neurobiology, CERC, Fondazione Santa Lucia, Rome, Italy Correspondence to: Maria Paola Paronetto, email: [email protected] Keywords: RHA helicase, genomic stability, cancer Received: October 02, 2015 Accepted: January 29, 2016 Published: February 14, 2016 ABSTRACT The RNA helicase A (RHA) is involved in several steps of RNA metabolism, such as RNA processing, cellular transit of viral molecules, ribosome assembly, regulation of transcription and translation of specific mRNAs. RHA is a multifunctional protein whose roles depend on the specific interaction with different molecular partners, which have been extensively characterized in physiological situations. More recently, the functional implication of RHA in human cancer has emerged. Interestingly, RHA was shown to cooperate with both tumor suppressors and oncoproteins in different tumours, indicating that its specific role in cancer is strongly influenced by the cellular context. For instance, silencing of RHA and/or disruption of its interaction with the oncoprotein EWS-FLI1 rendered Ewing sarcoma cells more sensitive to genotoxic stresses and affected tumor growth and maintenance, suggesting possible therapeutic implications. Herein, we review the recent advances in the cellular functions of RHA and discuss its implication in oncogenesis, providing a perspective for future studies and potential translational opportunities in human cancer. INTRODUCTION females, which contain two X chromosomes [8]. The C. elegans RHA-1 displays about 60% of similarity with both RNA helicase A (RHA) is a DNA/RNA helicase human RHA and Drosophila MLE and is involved in gene involved in all the essential steps of RNA metabolism, silencing. - 
												
												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 - 
												
												Integrating Many Co-Splicing Networks to Reconstruct Splicing Regulatory Modules
Dai et al. BMC Systems Biology 2012, 6(Suppl 1):S17 http://www.biomedcentral.com/1752-0509/6/S1/S17 RESEARCH Open Access Integrating many co-splicing networks to reconstruct splicing regulatory modules Chao Dai1,2†, Wenyuan Li2†, Juan Liu1, Xianghong Jasmine Zhou2* From The 5th IEEE International Conference on Computational Systems Biology (ISB 2011) Zhuhai, China. 02-04 September 2011 Abstract Background: Alternative splicing is a ubiquitous gene regulatory mechanism that dramatically increases the complexity of the proteome. However, the mechanism for regulating alternative splicing is poorly understood, and study of coordinated splicing regulation has been limited to individual cases. To study genome-wide splicing regulation, we integrate many human RNA-seq datasets to identify splicing module, which we define as a set of cassette exons co-regulated by the same splicing factors. Results: We have designed a tensor-based approach to identify co-splicing clusters that appear frequently across multiple conditions, thus very likely to represent splicing modules - a unit in the splicing regulatory network. In particular, we model each RNA-seq dataset as a co-splicing network, where the nodes represent exons and the edges are weighted by the correlations between exon inclusion rate profiles. We apply our tensor-based method to the 38 co-splicing networks derived from human RNA-seq datasets and indentify an atlas of frequent co-splicing clusters. We demonstrate that these identified clusters represent potential splicing modules by validating against four biological knowledge databases. The likelihood that a frequent co-splicing cluster is biologically meaningful increases with its recurrence across multiple datasets, highlighting the importance of the integrative approach. - 
												
												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.