Nuclear PTEN Safeguards Pre-Mrna Splicing to Link Golgi Apparatus for Its Tumor Suppressive Role
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Supplemental Note Hominoid Fission of Chromosome 14/15 and Role Of
Supplemental Note Supplemental Note Hominoid fission of chromosome 14/15 and role of segmental duplications Giuliana Giannuzzi, Michele Pazienza, John Huddleston, Francesca Antonacci, Maika Malig, Laura Vives, Evan E. Eichler and Mario Ventura 1. Analysis of the macaque contig spanning the hominoid 14/15 fission site We grouped contig clones based on their FISH pattern on human and macaque chromosomes (Groups F1, F2, F3, G1, G2, G3, and G4). Group F2 clones (Hsa15b- and Hsa15c-positive) showed a single signal on macaque 7q and three signal clusters on human chromosome 15: at the orthologous 15q26, as expected, as well as at 15q11–14 and 15q24–25, which correspond to the actual and ancestral pericentromeric regions, respectively (Ventura et al. 2003). Indeed, this locus contains an LCR15 copy (Pujana et al. 2001) in both the macaque and human genomes. Most BAC clones were one-end anchored in the human genome (chr15:100,028–100,071 kb). In macaque this region experienced a 64 kb duplicative insertion from chromosome 17 (orthologous to human chromosome 13) (Figure 2), with the human configuration (absence of insertion) likely being the ancestral state because it is identical in orangutan and marmoset. Four Hsa15b- positive clones mapped on macaque and human chromosome 19, but neither human nor macaque assemblies report the STS Hsa15b duplicated at this locus. The presence of assembly gaps in macaque may explain why the STS is not annotated in this region. We aligned the sequence of macaque CH250-70H12 (AC187495.2) versus its human orthologous sequence (hg18 chr15:100,039k-100,170k) and found a 12 kb human expansion through tandem duplication of a ~100 bp unit corresponding to a portion of exon 20 of DNM1 (Figure S3). -
Topological Scoring of Protein Interaction Networks
bioRxiv preprint doi: https://doi.org/10.1101/438408; this version posted October 8, 2018. The copyright holder for this preprint (which was not certified by peer review) is the author/funder.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. Topological Scoring of Protein Interaction Networks Mihaela E. Sardiu1, Joshua M. Gilmore1,2, Brad D. Groppe1,3, Arnob Dutta1,4, Laurence Florens1, and Michael P. Washburn1,5‡ 1Stowers Institute for Medical Research, Kansas City, MO 64110 U.S.A. 2Current Address: Boehringer Ingelheim Vetmedica, St. Joseph, MO 64506 U.S.A. 3Current Address: Thermo Fisher Scientific, Waltham, MA 02451, U.S.A. 4Current Address: Department of Cell and Molecular Biology, University of Rhode Island, 287 CBLS, 120 Flagg Road, Kingston, RI 02881. 5 Department of Pathology and Laboratory Medicine, The University of Kansas Medical Center, 3901 Rainbow Boulevard, Kansas City, Kansas 66160, USA ‡To whom correspondence should be addressed: Michael Washburn, Ph.D. Stowers Institute for Medical Research 1000 E. 50th St. Kansas City, MO 64110 Phone: 816-926-4457 E-mail: [email protected] 1 bioRxiv preprint doi: https://doi.org/10.1101/438408; this version posted October 8, 2018. 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. Abstract It remains a significant challenge to define individual protein associations within networks where an individual protein can directly interact with other proteins and/or be part of large complexes, which contain functional modules. Here we demonstrate the topological scoring (TopS) algorithm for the analysis of quantitative proteomic analyses of affinity purifications. -
Supplemental Material Table of Contents
Supplemental material Table of Contents Detailed Materials and Methods ......................................................................................................... 2 Perioperative period ........................................................................................................................... 2 Ethical aspects ................................................................................................................................... 4 Evaluation of heart failure ................................................................................................................. 4 Sample preparation for ANP mRNA expression .................................................................................. 5 Sample preparation for validative qRT-PCR (Postn, Myh7, Gpx3, Tgm2) ............................................ 6 Tissue fibrosis .................................................................................................................................... 7 Ventricular remodeling and histological tissue preservation ................................................................ 8 Evaluation of the histological preservation of cardiac tissue ................................................................ 9 Sample preparation and quantitative label-free proteomics analyses .................................................. 10 Statistical methods ........................................................................................................................... 12 References ........................................................................................................................................ -
ANP32A and ANP32B Are Key Factors in the Rev Dependent CRM1 Pathway
bioRxiv preprint doi: https://doi.org/10.1101/559096; this version posted February 24, 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 ANP32A and ANP32B are key factors in the Rev dependent CRM1 pathway 2 for nuclear export of HIV-1 unspliced mRNA 3 Yujie Wang1, Haili Zhang1, Lei Na 1, Cheng Du1, Zhenyu Zhang1, Yong-Hui Zheng1,2, Xiaojun Wang1* 4 1State Key Laboratory of Veterinary Biotechnology, Harbin Veterinary Research Institute, the Chinese 5 Academy of Agricultural Sciences, Harbin 150069, China 6 2Department of Microbiology and Molecular Genetics, Michigan State University, East Lansing, Michigan, 7 USA. 8 * Address correspondence to Xiaojun Wang, [email protected]. 9 10 11 12 13 14 15 16 17 18 19 20 21 1 bioRxiv preprint doi: https://doi.org/10.1101/559096; this version posted February 24, 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. 22 Abstract 23 The nuclear export receptor CRM1 is an important regulator involved in the shuttling of various cellular 24 and viral RNAs between the nucleus and the cytoplasm. HIV-1 Rev interacts with CRM1 in the late phase of 25 HIV-1 replication to promote nuclear export of unspliced and single spliced HIV-1 transcripts. However, the 26 knowledge of cellular factors that are involved in the CRM1-dependent viral RNA nuclear export remains 27 inadequate. Here, we identified that ANP32A and ANP32B mediate the export of unspliced or partially spliced 28 viral mRNA via interacting with Rev and CRM1. -
Protein Interaction Network of Alternatively Spliced Isoforms from Brain Links Genetic Risk Factors for Autism
ARTICLE Received 24 Aug 2013 | Accepted 14 Mar 2014 | Published 11 Apr 2014 DOI: 10.1038/ncomms4650 OPEN Protein interaction network of alternatively spliced isoforms from brain links genetic risk factors for autism Roser Corominas1,*, Xinping Yang2,3,*, Guan Ning Lin1,*, Shuli Kang1,*, Yun Shen2,3, Lila Ghamsari2,3,w, Martin Broly2,3, Maria Rodriguez2,3, Stanley Tam2,3, Shelly A. Trigg2,3,w, Changyu Fan2,3, Song Yi2,3, Murat Tasan4, Irma Lemmens5, Xingyan Kuang6, Nan Zhao6, Dheeraj Malhotra7, Jacob J. Michaelson7,w, Vladimir Vacic8, Michael A. Calderwood2,3, Frederick P. Roth2,3,4, Jan Tavernier5, Steve Horvath9, Kourosh Salehi-Ashtiani2,3,w, Dmitry Korkin6, Jonathan Sebat7, David E. Hill2,3, Tong Hao2,3, Marc Vidal2,3 & Lilia M. Iakoucheva1 Increased risk for autism spectrum disorders (ASD) is attributed to hundreds of genetic loci. The convergence of ASD variants have been investigated using various approaches, including protein interactions extracted from the published literature. However, these datasets are frequently incomplete, carry biases and are limited to interactions of a single splicing isoform, which may not be expressed in the disease-relevant tissue. Here we introduce a new interactome mapping approach by experimentally identifying interactions between brain-expressed alternatively spliced variants of ASD risk factors. The Autism Spliceform Interaction Network reveals that almost half of the detected interactions and about 30% of the newly identified interacting partners represent contribution from splicing variants, emphasizing the importance of isoform networks. Isoform interactions greatly contribute to establishing direct physical connections between proteins from the de novo autism CNVs. Our findings demonstrate the critical role of spliceform networks for translating genetic knowledge into a better understanding of human diseases. -
The Utility of Genetic Risk Scores in Predicting the Onset of Stroke March 2021 6
DOT/FAA/AM-21/24 Office of Aerospace Medicine Washington, DC 20591 The Utility of Genetic Risk Scores in Predicting the Onset of Stroke Diana Judith Monroy Rios, M.D1 and Scott J. Nicholson, Ph.D.2 1. KR 30 # 45-03 University Campus, Building 471, 5th Floor, Office 510 Bogotá D.C. Colombia 2. FAA Civil Aerospace Medical Institute, 6500 S. MacArthur Blvd Rm. 354, Oklahoma City, OK 73125 March 2021 NOTICE This document is disseminated under the sponsorship of the U.S. Department of Transportation in the interest of information exchange. The United States Government assumes no liability for the contents thereof. _________________ This publication and all Office of Aerospace Medicine technical reports are available in full-text from the Civil Aerospace Medical Institute’s publications Web site: (www.faa.gov/go/oamtechreports) Technical Report Documentation Page 1. Report No. 2. Government Accession No. 3. Recipient's Catalog No. DOT/FAA/AM-21/24 4. Title and Subtitle 5. Report Date March 2021 The Utility of Genetic Risk Scores in Predicting the Onset of Stroke 6. Performing Organization Code 7. Author(s) 8. Performing Organization Report No. Diana Judith Monroy Rios M.D1, and Scott J. Nicholson, Ph.D.2 9. Performing Organization Name and Address 10. Work Unit No. (TRAIS) 1 KR 30 # 45-03 University Campus, Building 471, 5th Floor, Office 510, Bogotá D.C. Colombia 11. Contract or Grant No. 2 FAA Civil Aerospace Medical Institute, 6500 S. MacArthur Blvd Rm. 354, Oklahoma City, OK 73125 12. Sponsoring Agency name and Address 13. Type of Report and Period Covered Office of Aerospace Medicine Federal Aviation Administration 800 Independence Ave., S.W. -
Genome-Wide Association Study of Copy Number Variations (Cnvs) with Opioid Dependence
Neuropsychopharmacology (2015) 40, 1016–1026 & 2015 American College of Neuropsychopharmacology. All rights reserved 0893-133X/15 www.neuropsychopharmacology.org Genome-Wide Association Study of Copy Number Variations (CNVs) with Opioid Dependence Dawei Li*,1,2,3,4, Hongyu Zhao5,6, Henry R Kranzler7, Ming D Li8, Kevin P Jensen1, Tetyana Zayats1, Lindsay A Farrer9 and Joel Gelernter1,6,10 1 2 Department of Psychiatry, School of Medicine, Yale University, New Haven, CT, USA; Department of Microbiology and Molecular Genetics, University of Vermont, Burlington, VT, USA; 3Department of Computer Science, University of Vermont, Burlington, VT, USA; 4Neuroscience, Behavior, and Health Initiative, University of Vermont, Burlington, VT, USA; 5Department of Biostatistics, Yale School of Public Health, New Haven, 6 7 CT, USA; Department of Genetics, School of Medicine, Yale University, New Haven, CT, USA; Department of Psychiatry, University of 8 Pennsylvania School of Medicine and VISN 4 MIRECC, Philadelphia VAMC, Philadelphia, PA, USA; Department of Psychiatry and 9 Neurobehavioral Sciences, University of Virginia, Charlottesville, VA, USA; Departments of Medicine (Biomedical Genetics), Neurology, Ophthalmology, Genetics and Genomics, Biostatistics, and Epidemiology, Boston University Schools of Medicine and Public Health, Boston, MA, USA; 10VA Connecticut Healthcare Center, Department of Neurobiology, Yale University School of Medicine, New Haven, CT, USA Single-nucleotide polymorphisms that have been associated with opioid dependence (OD) altogether account for only a small proportion of the known heritability. Most of the genetic risk factors are unknown. Some of the ‘missing heritability’ might be explained by copy number variations (CNVs) in the human genome. We used Illumina HumanOmni1 arrays to genotype 5152 African-American and European-American OD cases and screened controls and implemented combined CNV calling methods. -
Datasheet: VPA00331KT Product Details
Datasheet: VPA00331KT Description: PRPF19 ANTIBODY WITH CONTROL LYSATE Specificity: PRPF19 Format: Purified Product Type: PrecisionAb™ Polyclonal Isotype: Polyclonal IgG Quantity: 2 Westerns Product Details Applications This product has been reported to work in the following applications. This information is derived from testing within our laboratories, peer-reviewed publications or personal communications from the originators. Please refer to references indicated for further information. For general protocol recommendations, please visit www.bio-rad-antibodies.com/protocols. Yes No Not Determined Suggested Dilution Western Blotting 1/1000 PrecisionAb antibodies have been extensively validated for the western blot application. The antibody has been validated at the suggested dilution. Where this product has not been tested for use in a particular technique this does not necessarily exclude its use in such procedures. Further optimization may be required dependant on sample type. Target Species Human Species Cross Reacts with: Mouse, Rat Reactivity N.B. Antibody reactivity and working conditions may vary between species. Product Form Purified IgG - liquid Preparation 20μl Rabbit polyclonal antibody purified by affinity chromatography Buffer Solution Phosphate buffered saline Preservative 0.09% Sodium Azide (NaN ) Stabilisers 3 Immunogen KLH-conjugated synthetic peptide corresponding to aa 4-33 of human PRPF19 External Database Links UniProt: Q9UMS4 Related reagents Entrez Gene: 27339 PRPF19 Related reagents Synonyms NMP200, PRP19, SNEV Page 1 of 3 Specificity Rabbit anti Human PRPF19 antibody recognizes PRPF19, also known as PRP19/PSO4 homolog, PRP19/PSO4 pre-mRNA processing factor 19 homolog, nuclear matrix protein 200, nuclear matrix protein NMP200 related to splicing factor PRP19, psoralen 4 and senescence evasion factor. The PRPF19 gene is the human homolog of yeast Pso4, a gene essential for cell survival and DNA repair (Beck et al. -
Miasdb: a Database of Molecular Interactions Associated with Alternative Splicing of Human Pre-Mrnas
RESEARCH ARTICLE MiasDB: A Database of Molecular Interactions Associated with Alternative Splicing of Human Pre-mRNAs Yongqiang Xing1, Xiujuan Zhao1, Tao Yu2, Dong Liang1, Jun Li1, Guanyun Wei1, Guoqing Liu1, Xiangjun Cui1, Hongyu Zhao1, Lu Cai1* 1 School of Life Science and Technology, Inner Mongolia University of Science and Technology, Baotou, 014010, China, 2 School of Science, Inner Mongolia University of Science and Technology, Baotou, 014010, China a11111 * [email protected] Abstract Alternative splicing (AS) is pervasive in human multi-exon genes and is a major contributor to expansion of the transcriptome and proteome diversity. The accurate recognition of alter- OPEN ACCESS native splice sites is regulated by information contained in networks of protein-protein and Citation: Xing Y, Zhao X, Yu T, Liang D, Li J, Wei G, protein-RNA interactions. However, the mechanisms leading to splice site selection are not et al. (2016) MiasDB: A Database of Molecular fully understood. Although numerous databases have been built to describe AS, molecular Interactions Associated with Alternative Splicing of Human Pre-mRNAs. PLoS ONE 11(5): e0155443. interaction databases associated with AS have only recently emerged. In this study, we doi:10.1371/journal.pone.0155443 present a new database, MiasDB, that provides a description of molecular interactions Editor: Ruben Artero, University of Valencia, SPAIN associated with human AS events. This database covers 938 interactions between human splicing factors, RNA elements, transcription factors, kinases and modified histones for 173 Received: November 19, 2015 human AS events. Every entry includes the interaction partners, interaction type, experi- Accepted: April 28, 2016 mental methods, AS type, tissue specificity or disease-relevant information, a simple Published: May 11, 2016 description of the functionally tested interaction in the AS event and references. -
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. -
GOLGA2/GM130 Is a Novel Target for Neuroprotection Therapy in Intracerebral Hemorrhage
GOLGA2/GM130 is a Novel Target for Neuroprotection Therapy in Intracerebral Hemorrhage Shuwen Deng Second Xiangya Hospital Qing Hu Second Xiangya Hospital Qiang He Second Xiangya Hospital Xiqian Chen Second Xiangya Hospital Wei Lu ( [email protected] ) Second Xiangya Hospital, central south university https://orcid.org/0000-0002-3760-1550 Research Article Keywords: Golgi apparatus, therapy, intracerebral hemorrhage, autophagy, blood–brain barrier Posted Date: June 1st, 2021 DOI: https://doi.org/10.21203/rs.3.rs-547422/v1 License: This work is licensed under a Creative Commons Attribution 4.0 International License. Read Full License Page 1/25 Abstract Blood–brain barrier (BBB) impairment after intracerebral hemorrhage (ICH) can lead to secondary brain injury and aggravate neurological decits. Currently, there are no effective methods for its prevention or treatment partly because of to our lack of understanding of the mechanism of ICH injury to the BBB. Here, we explored the role of Golgi apparatus protein GM130 in the BBB and neurological function after ICH. The levels of the tight junction-associated proteins ZO-1 and occludin decreased, whereas those of LC3-II, an autophagosome marker, increased in hemin-treated Bend.3 cells (p < 0.05). Additionally, GM130 overexpression increased ZO-1 and occludin levels, while decreasing LC3-II levels (p < 0.05). GM130 silencing reversed these effects and mimicked the effect of hemin treatment (p < 0.05). Moreover, tight junctions were disrupted after hemin treatment or GM130 silencing and repaired by GM130 overexpression. GM130 silencing in Bend.3 cells increased autophagic ux, whereas GM130 overexpression downregulated this activity. Furthermore, GM130 silencing-induced tight junction disruption was partially restored by 3-methyladenine (an autophagy inhibitor) administration. -
Molecular Signatures in IASLC/ATS/ERS Classified Growth Patterns of Lung Adenocarcinoma
RESEARCH ARTICLE Molecular signatures in IASLC/ATS/ERS classified growth patterns of lung adenocarcinoma 1 1 1,2 1¤a Heike ZabeckID *, Hendrik Dienemann , Hans Hoffmann , Joachim Pfannschmidt , Arne Warth2,3, Philipp A. Schnabel3¤b, Thomas Muley2,4, Michael Meister2,4, Holger SuÈ ltmann2,5, Holger FroÈ hlich6, Ruprecht Kuner2,5¤c, Felix Lasitschka3 1 Department of Thoracic Surgery, Thoraxklinik, University Hospital Heidelberg, Heidelberg, Germany, 2 Translational Lung Research Centre Heidelberg (TLRC-H), German Centre for Lung Research (DZL), a1111111111 Heidelberg, Germany, 3 Institute of Pathology, University Hospital Heidelberg, Heidelberg, Germany, a1111111111 4 Translational Research Unit (STF), Thoraxklinik, University of Heidelberg, Heidelberg, Germany, 5 Cancer a1111111111 Genome Research (B063), German Cancer Research Center (DKFZ) and German Cancer Consortium a1111111111 (DKTK), Heidelberg, Germany, 6 Institute for Computer Science, c/o Bonn-Aachen International Center for a1111111111 IT, Algorithmic Bioinformatics, University of Bonn, Bonn, Germany ¤a Current address: Department of Thoracic Surgery, Lung Clinic Heckeshorn at HELIOS Hospital Emil von Behring, Berlin, Germany ¤b Current address: Institute of Pathology, Saarland University, Homburg/Saar, Germany ¤c Current address: TRONÐTranslational Oncology at the University Medical Center of Johannes OPEN ACCESS Gutenberg University, Mainz, Germany * [email protected] Citation: Zabeck H, Dienemann H, Hoffmann H, Pfannschmidt J, Warth A, Schnabel PA, et al. (2018) Molecular signatures in IASLC/ATS/ERS classified growth patterns of lung adenocarcinoma. Abstract PLoS ONE 13(10): e0206132. https://doi.org/ 10.1371/journal.pone.0206132 Editor: Stefania Crispi, Institute for Bioscience and Background Biotechnology Research, ITALY The current classification of human lung adenocarcinoma defines five different histological Received: April 4, 2018 growth patterns within the group of conventional invasive adenocarcinomas.