RNA Dynamics in Alzheimer's Disease
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DNA Damage Activates a Spatially Distinct Late Cytoplasmic Cell-Cycle Checkpoint Network Controlled by MK2-Mediated RNA Stabilization
DNA Damage Activates a Spatially Distinct Late Cytoplasmic Cell-Cycle Checkpoint Network Controlled by MK2-Mediated RNA Stabilization The MIT Faculty has made this article openly available. Please share how this access benefits you. Your story matters. Citation Reinhardt, H. Christian, Pia Hasskamp, Ingolf Schmedding, Sandra Morandell, Marcel A.T.M. van Vugt, XiaoZhe Wang, Rune Linding, et al. “DNA Damage Activates a Spatially Distinct Late Cytoplasmic Cell-Cycle Checkpoint Network Controlled by MK2-Mediated RNA Stabilization.” Molecular Cell 40, no. 1 (October 2010): 34–49.© 2010 Elsevier Inc. As Published http://dx.doi.org/10.1016/j.molcel.2010.09.018 Publisher Elsevier B.V. Version Final published version Citable link http://hdl.handle.net/1721.1/85107 Terms of Use Article is made available in accordance with the publisher's policy and may be subject to US copyright law. Please refer to the publisher's site for terms of use. Molecular Cell Article DNA Damage Activates a Spatially Distinct Late Cytoplasmic Cell-Cycle Checkpoint Network Controlled by MK2-Mediated RNA Stabilization H. Christian Reinhardt,1,6,7,8 Pia Hasskamp,1,10,11 Ingolf Schmedding,1,10,11 Sandra Morandell,1 Marcel A.T.M. van Vugt,5 XiaoZhe Wang,9 Rune Linding,4 Shao-En Ong,2 David Weaver,9 Steven A. Carr,2 and Michael B. Yaffe1,2,3,* 1David H. Koch Institute for Integrative Cancer Research, Department of Biology, Massachusetts Institute of Technology, Cambridge, MA 02132, USA 2Broad Institute of MIT and Harvard, Cambridge, MA 02132, USA 3Center for Cell Decision Processes, -
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. -
Supplementary Materials
Supplementary Materials COMPARATIVE ANALYSIS OF THE TRANSCRIPTOME, PROTEOME AND miRNA PROFILE OF KUPFFER CELLS AND MONOCYTES Andrey Elchaninov1,3*, Anastasiya Lokhonina1,3, Maria Nikitina2, Polina Vishnyakova1,3, Andrey Makarov1, Irina Arutyunyan1, Anastasiya Poltavets1, Evgeniya Kananykhina2, Sergey Kovalchuk4, Evgeny Karpulevich5,6, Galina Bolshakova2, Gennady Sukhikh1, Timur Fatkhudinov2,3 1 Laboratory of Regenerative Medicine, National Medical Research Center for Obstetrics, Gynecology and Perinatology Named after Academician V.I. Kulakov of Ministry of Healthcare of Russian Federation, Moscow, Russia 2 Laboratory of Growth and Development, Scientific Research Institute of Human Morphology, Moscow, Russia 3 Histology Department, Medical Institute, Peoples' Friendship University of Russia, Moscow, Russia 4 Laboratory of Bioinformatic methods for Combinatorial Chemistry and Biology, Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry of the Russian Academy of Sciences, Moscow, Russia 5 Information Systems Department, Ivannikov Institute for System Programming of the Russian Academy of Sciences, Moscow, Russia 6 Genome Engineering Laboratory, Moscow Institute of Physics and Technology, Dolgoprudny, Moscow Region, Russia Figure S1. Flow cytometry analysis of unsorted blood sample. Representative forward, side scattering and histogram are shown. The proportions of negative cells were determined in relation to the isotype controls. The percentages of positive cells are indicated. The blue curve corresponds to the isotype control. Figure S2. Flow cytometry analysis of unsorted liver stromal cells. Representative forward, side scattering and histogram are shown. The proportions of negative cells were determined in relation to the isotype controls. The percentages of positive cells are indicated. The blue curve corresponds to the isotype control. Figure S3. MiRNAs expression analysis in monocytes and Kupffer cells. Full-length of heatmaps are presented. -
Bioinformatics-Based Screening of Key Genes for Transformation of Liver
Jiang et al. J Transl Med (2020) 18:40 https://doi.org/10.1186/s12967-020-02229-8 Journal of Translational Medicine RESEARCH Open Access Bioinformatics-based screening of key genes for transformation of liver cirrhosis to hepatocellular carcinoma Chen Hao Jiang1,2, Xin Yuan1,2, Jiang Fen Li1,2, Yu Fang Xie1,2, An Zhi Zhang1,2, Xue Li Wang1,2, Lan Yang1,2, Chun Xia Liu1,2, Wei Hua Liang1,2, Li Juan Pang1,2, Hong Zou1,2, Xiao Bin Cui1,2, Xi Hua Shen1,2, Yan Qi1,2, Jin Fang Jiang1,2, Wen Yi Gu4, Feng Li1,2,3 and Jian Ming Hu1,2* Abstract Background: Hepatocellular carcinoma (HCC) is the most common type of liver tumour, and is closely related to liver cirrhosis. Previous studies have focussed on the pathogenesis of liver cirrhosis developing into HCC, but the molecular mechanism remains unclear. The aims of the present study were to identify key genes related to the transformation of cirrhosis into HCC, and explore the associated molecular mechanisms. Methods: GSE89377, GSE17548, GSE63898 and GSE54236 mRNA microarray datasets from Gene Expression Omni- bus (GEO) were analysed to obtain diferentially expressed genes (DEGs) between HCC and liver cirrhosis tissues, and network analysis of protein–protein interactions (PPIs) was carried out. String and Cytoscape were used to analyse modules and identify hub genes, Kaplan–Meier Plotter and Oncomine databases were used to explore relationships between hub genes and disease occurrence, development and prognosis of HCC, and the molecular mechanism of the main hub gene was probed using Kyoto Encyclopedia of Genes and Genomes(KEGG) pathway analysis. -
Aneuploidy: Using Genetic Instability to Preserve a Haploid Genome?
Health Science Campus FINAL APPROVAL OF DISSERTATION Doctor of Philosophy in Biomedical Science (Cancer Biology) Aneuploidy: Using genetic instability to preserve a haploid genome? Submitted by: Ramona Ramdath In partial fulfillment of the requirements for the degree of Doctor of Philosophy in Biomedical Science Examination Committee Signature/Date Major Advisor: David Allison, M.D., Ph.D. Academic James Trempe, Ph.D. Advisory Committee: David Giovanucci, Ph.D. Randall Ruch, Ph.D. Ronald Mellgren, Ph.D. Senior Associate Dean College of Graduate Studies Michael S. Bisesi, Ph.D. Date of Defense: April 10, 2009 Aneuploidy: Using genetic instability to preserve a haploid genome? Ramona Ramdath University of Toledo, Health Science Campus 2009 Dedication I dedicate this dissertation to my grandfather who died of lung cancer two years ago, but who always instilled in us the value and importance of education. And to my mom and sister, both of whom have been pillars of support and stimulating conversations. To my sister, Rehanna, especially- I hope this inspires you to achieve all that you want to in life, academically and otherwise. ii Acknowledgements As we go through these academic journeys, there are so many along the way that make an impact not only on our work, but on our lives as well, and I would like to say a heartfelt thank you to all of those people: My Committee members- Dr. James Trempe, Dr. David Giovanucchi, Dr. Ronald Mellgren and Dr. Randall Ruch for their guidance, suggestions, support and confidence in me. My major advisor- Dr. David Allison, for his constructive criticism and positive reinforcement. -
Binding Specificities of Human RNA Binding Proteins Towards Structured
bioRxiv preprint doi: https://doi.org/10.1101/317909; this version posted March 1, 2019. 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. 1 Binding specificities of human RNA binding proteins towards structured and linear 2 RNA sequences 3 4 Arttu Jolma1,#, Jilin Zhang1,#, Estefania Mondragón4,#, Teemu Kivioja2, Yimeng Yin1, 5 Fangjie Zhu1, Quaid Morris5,6,7,8, Timothy R. Hughes5,6, Louis James Maher III4 and Jussi 6 Taipale1,2,3,* 7 8 9 AUTHOR AFFILIATIONS 10 11 1Department of Medical Biochemistry and Biophysics, Karolinska Institutet, Solna, Sweden 12 2Genome-Scale Biology Program, University of Helsinki, Helsinki, Finland 13 3Department of Biochemistry, University of Cambridge, Cambridge, United Kingdom 14 4Department of Biochemistry and Molecular Biology and Mayo Clinic Graduate School of 15 Biomedical Sciences, Mayo Clinic College of Medicine and Science, Rochester, USA 16 5Department of Molecular Genetics, University of Toronto, Toronto, Canada 17 6Donnelly Centre, University of Toronto, Toronto, Canada 18 7Edward S Rogers Sr Department of Electrical and Computer Engineering, University of 19 Toronto, Toronto, Canada 20 8Department of Computer Science, University of Toronto, Toronto, Canada 21 #Authors contributed equally 22 *Correspondence: [email protected] 23 24 25 SUMMARY 26 27 Sequence specific RNA-binding proteins (RBPs) control many important 28 processes affecting gene expression. They regulate RNA metabolism at multiple 29 levels, by affecting splicing of nascent transcripts, RNA folding, base modification, 30 transport, localization, translation and stability. Despite their central role in most 31 aspects of RNA metabolism and function, most RBP binding specificities remain 32 unknown or incompletely defined. -
Figure S1. Androgen Signaling Upregulates an Intronic
Figure S1. Androgen signaling upregulates an intronic polyadenylated EWSR1 isoform A) Gene expression correlation of EWSR1 and AR in 550 prostate cancer patients from the PRAD data set. B) EWSR1 polyadenylation site (PAS) information from PolyA_db v3.2. There are seven PAS for this gene and they are numbered starting from the 5’ end of the gene. C) Diagram of PAS locations at EWSR1 numbered according to table in A. D) Normalized read count for PAS #2, the PAS for ntEWS, from 3’ sequencing data across various cell types. E) RNA levels of PSA in VCaP, LNCaP, and LNCaP-AR cells treated with DMSO or 10nM R1881 for 24 hours. Expression is normalized to 18S and relative to the DMSO condition. The mean ± SEM for three replicates is shown. F) Immuno blot of ntEWS in PC3 cells overexpressing HA-ntEWS. G) Immunoblot of ntEWS in VCaP cells overexpressing vector alone or shRNAs targeting the 3’ UTR of ntEWS. Tubulin is used as a loading control for immunoblots. Figure S2. AR binding to Intron 5 of EWSR1 directly regulates ntEWS expression A) Gene tracks for AR binding in patient tumor and matched adjacent normal tissue at known AR enhancers. Order of tracks is consistent with Figure 2a. Figure S3. ntEWS promotes phenotypes related to oncogenesis A) Immunoblot of 3xHA tagged EWS isoforms expressed in PC3 cells. Tubulin is used as a loading control. B) MTT proliferation assay of PC3 isoform-expressing lines. Figure S4. The ntEWS alternative last exon encodes an alpha helical domain important for function A) IUPRED prediction of disorder of ntEWS (bottom) and EWS(1-355aa) (top). -
HNRNPA0 Mouse Monoclonal Antibody [Clone ID: OTI8H8] Product Data
OriGene Technologies, Inc. 9620 Medical Center Drive, Ste 200 Rockville, MD 20850, US Phone: +1-888-267-4436 [email protected] EU: [email protected] CN: [email protected] Product datasheet for CF809308 HNRNPA0 Mouse Monoclonal Antibody [Clone ID: OTI8H8] Product data: Product Type: Primary Antibodies Clone Name: OTI8H8 Applications: IHC, WB Recommended Dilution: WB 1:2000, IHC 1:150 Reactivity: Human, Mouse, Rat Host: Mouse Isotype: IgG1 Clonality: Monoclonal Immunogen: Human recombinant protein fragment corresponding to amino acids 139-183 of human HNRNPA0 (NP_006796) produced in E.coli. Formulation: Lyophilized powder (original buffer 1X PBS, pH 7.3, 8% trehalose) Reconstitution Method: For reconstitution, we recommend adding 100uL distilled water to a final antibody concentration of about 1 mg/mL. To use this carrier-free antibody for conjugation experiment, we strongly recommend performing another round of desalting process. (OriGene recommends Zeba Spin Desalting Columns, 7KMWCO from Thermo Scientific) Purification: Purified from mouse ascites fluids or tissue culture supernatant by affinity chromatography (protein A/G) Conjugation: Unconjugated Storage: Store at -20°C as received. Stability: Stable for 12 months from date of receipt. Predicted Protein Size: 30.7 kDa Gene Name: Homo sapiens heterogeneous nuclear ribonucleoprotein A0 (HNRNPA0), mRNA. Database Link: NP_006796 Entrez Gene 10949 Human Q13151 This product is to be used for laboratory only. Not for diagnostic or therapeutic use. View online » ©2021 OriGene Technologies, Inc., 9620 Medical Center Drive, Ste 200, Rockville, MD 20850, US 1 / 5 HNRNPA0 Mouse Monoclonal Antibody [Clone ID: OTI8H8] – CF809308 Background: This gene belongs to the A/B subfamily of ubiquitously expressed heterogeneous nuclear ribonucleoproteins (hnRNPs). -
Chromosomal Microarray Analysis in Turkish Patients with Unexplained Developmental Delay and Intellectual Developmental Disorders
177 Arch Neuropsychitry 2020;57:177−191 RESEARCH ARTICLE https://doi.org/10.29399/npa.24890 Chromosomal Microarray Analysis in Turkish Patients with Unexplained Developmental Delay and Intellectual Developmental Disorders Hakan GÜRKAN1 , Emine İkbal ATLI1 , Engin ATLI1 , Leyla BOZATLI2 , Mengühan ARAZ ALTAY2 , Sinem YALÇINTEPE1 , Yasemin ÖZEN1 , Damla EKER1 , Çisem AKURUT1 , Selma DEMİR1 , Işık GÖRKER2 1Faculty of Medicine, Department of Medical Genetics, Edirne, Trakya University, Edirne, Turkey 2Faculty of Medicine, Department of Child and Adolescent Psychiatry, Trakya University, Edirne, Turkey ABSTRACT Introduction: Aneuploids, copy number variations (CNVs), and single in 39 (39/123=31.7%) patients. Twelve CNV variant of unknown nucleotide variants in specific genes are the main genetic causes of significance (VUS) (9.75%) patients and 7 CNV benign (5.69%) patients developmental delay (DD) and intellectual disability disorder (IDD). were reported. In 6 patients, one or more pathogenic CNVs were These genetic changes can be detected using chromosome analysis, determined. Therefore, the diagnostic efficiency of CMA was found to chromosomal microarray (CMA), and next-generation DNA sequencing be 31.7% (39/123). techniques. Therefore; In this study, we aimed to investigate the Conclusion: Today, genetic analysis is still not part of the routine in the importance of CMA in determining the genomic etiology of unexplained evaluation of IDD patients who present to psychiatry clinics. A genetic DD and IDD in 123 patients. diagnosis from CMA can eliminate genetic question marks and thus Method: For 123 patients, chromosome analysis, DNA fragment analysis alter the clinical management of patients. Approximately one-third and microarray were performed. Conventional G-band karyotype of the positive CMA findings are clinically intervenable. -
Electronic Supplementary Material (ESI) for Chemcomm. This Journal Is © the Royal Society of Chemistry 2015
Electronic Supplementary Material (ESI) for ChemComm. This journal is © The Royal Society of Chemistry 2015 tel26 Nuclear proteins identification ‐ Summary Accession Score Mass Matches tel26 Exp 1 Matches tel26 Exp 2 Protein(s) name* scr26 Exp1** scr26 Exp2** XRCC5_HUMAN 450 83222 39 49 X‐ray repair cross‐complementing protein 5 OS=Homo sapiens GN=XRCC5 PE=1 SV=3 yes yes XRCC6_HUMAN 444 70084 35 53 X‐ray repair cross‐complementing protein 6 OS=Homo sapiens GN=XRCC6 PE=1 SV=2 no no HMGB1_HUMAN 88 25049 9 25 High mobility group protein B1 OS=Homo sapiens GN=HMGB1 PE=1 SV=3 no no HMGB2_HUMAN 69 24190 4 17 High mobility group protein B2 OS=Homo sapiens GN=HMGB2 PE=1 SV=2 yes yes FUBP2_HUMAN 126 73355 9 9 Far upstream element‐binding protein 2 OS=Homo sapiens GN=KHSRP PE=1 SV=4 no no RFA1_HUMAN 67 68723 7 10 Replication protein A 70 kDa DNA‐binding subunit OS=Homo sapiens GN=RPA1 PE=1 SV=2 no no PPIA_HUMAN 95 18229 11 3 Peptidyl‐prolyl cis‐trans isomerase A OS=Homo sapiens GN=PPIA PE=1 SV=2 yes yes LMNB1_HUMAN 64 66653 6 8 Lamin‐B1 OS=Homo sapiens GN=LMNB1 PE=1 SV=2 no no ROAA_HUMAN 52 36316 3 10 Heterogeneous nuclear ribonucleoprotein A/B OS=Homo sapiens GN=HNRNPAB PE=1 SV=2 no no EHD4_HUMAN 70 61365 6 7 EH domain‐containing protein 4 OS=Homo sapiens GN=EHD4 PE=1 SV=1 no no FUBP1_HUMAN 49 67690 5 8 Far upstream element‐binding protein 1 OS=Homo sapiens GN=FUBP1 PE=1 SV=3 no yes MCM7_HUMAN 53 81884 5 7 DNA replication licensing factor MCM7 OS=Homo sapiens GN=MCM7 PE=1 SV=4 no no SEPT9_HUMAN 41 65646 3 9 Septin‐9 OS=Homo sapiens GN=SEPT9 PE=1 -
Inactivation of the Tumor Suppressor P53 by Long Noncoding RNA RMRP
Inactivation of the tumor suppressor p53 by long noncoding RNA RMRP Yajie Chena,b,c,d,1, Qian Haoa,b,c,1,2, Shanshan Wanga,b,c,1, Mingming Caoa,b,c, Yingdan Huanga,b,c, Xiaoling Wenga,b,c, Jieqiong Wange,f, Zhen Zhangc,d, Xianghuo Hea,b,c,g,h, Hua Lue,f, and Xiang Zhoua,b,c,g,h,2 aFudan University Shanghai Cancer Center, Fudan University, Shanghai 200032, China; bInstitutes of Biomedical Sciences, Fudan University, Shanghai 200032, China; cDepartment of Oncology, Shanghai Medical College, Fudan University, Shanghai 200032, China; dDepartment of Radiation Oncology, Fudan University Shanghai Cancer Center, Fudan University, Shanghai 200032, China; eDepartment of Biochemistry & Molecular Biology, Tulane University School of Medicine, New Orleans, LA 70112; fTulane Cancer Center, Tulane University School of Medicine, New Orleans, LA 70112; gKey Laboratory of Breast Cancer in Shanghai, Fudan University Shanghai Cancer Center, Fudan University, Shanghai 200032, China; and hShanghai Key Laboratory of Medical Epigenetics, International Co-laboratory of Medical Epigenetics and Metabolism, Ministry of Science and Technology, Institutes of Biomedical Sciences, Fudan University, Shanghai 200032, China Edited by Carol Prives, Columbia University, New York, NY, and approved May 24, 2021 (received for review December 31, 2020) p53 inactivation is highly associated with tumorigenesis and drug role of MDM2 in the control of p53 activity (12, 13). Cancer cells resistance. Here, we identify a long noncoding RNA, the RNA also utilize diverse oncogenic molecules to modulate the MDM2– component of mitochondrial RNA-processing endoribonuclease p53 axis. For instance, NGFR and PHLDB3 that are highly (RMRP), as an inhibitor of p53. -
HNRNPA0 Rabbit Pab
Leader in Biomolecular Solutions for Life Science HNRNPA0 Rabbit pAb Catalog No.: A6029 Basic Information Background Catalog No. This gene belongs to the A/B subfamily of ubiquitously expressed heterogeneous A6029 nuclear ribonucleoproteins (hnRNPs). The hnRNPs are RNA binding proteins and they complex with heterogeneous nuclear RNA (hnRNA). These proteins are associated with Observed MW pre-mRNAs in the nucleus and appear to influence pre-mRNA processing and other 37kDa aspects of mRNA metabolism and transport. While all of the hnRNPs are present in the nucleus, some seem to shuttle between the nucleus and the cytoplasm. The hnRNP Calculated MW proteins have distinct nucleic acid binding properties. The protein encoded by this gene 30kDa has two repeats of quasi-RRM domains that bind RNAs, followed by a glycine-rich C- terminus. Category Primary antibody Applications WB, IHC, IF, IP Cross-Reactivity Human, Mouse, Rat Recommended Dilutions Immunogen Information WB 1:500 - 1:1000 Gene ID Swiss Prot 10949 Q13151 IHC 1:50 - 1:100 Immunogen 1:50 - 1:100 IF Recombinant fusion protein containing a sequence corresponding to amino acids 1-180 of human HNRNPA0 (NP_006796.1). IP 1:50 - 1:100 Synonyms HNRNPA0;HNRPA0 Contact Product Information www.abclonal.com Source Isotype Purification Rabbit IgG Affinity purification Storage Store at -20℃. Avoid freeze / thaw cycles. Buffer: PBS with 0.02% sodium azide,50% glycerol,pH7.3. Validation Data Western blot analysis of extracts of various cell lines, using HNRNPA0 antibody (A6029) at 1:3000 dilution. Secondary antibody: HRP Goat Anti-Rabbit IgG (H+L) (AS014) at 1:10000 dilution.