Searchable Database of Spliceosome Proteins
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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 The copyright holder for this preprint (which was not certified by peer review) is the author/funder.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 The copyright holder for this preprint (which was not certified by peer review) is the author/funder.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 ........................................................................................................................................ -
Premature Termination Codons in PRPF31 Cause Retinitis Pigmentosa Via Haploinsufficiency Due to Nonsense-Mediated Mrna Decay
Premature termination codons in PRPF31 cause retinitis pigmentosa via haploinsufficiency due to nonsense-mediated mRNA decay Thomas Rio Frio, … , Jacques S. Beckmann, Carlo Rivolta J Clin Invest. 2008;118(4):1519-1531. https://doi.org/10.1172/JCI34211. Research Article Genetics Dominant mutations in the gene encoding the mRNA splicing factor PRPF31 cause retinitis pigmentosa, a hereditary form of retinal degeneration. Most of these mutations are characterized by DNA changes that lead to premature termination codons. We investigated 6 different PRPF31 mutations, represented by single-base substitutions or microdeletions, in cell lines derived from 9 patients with dominant retinitis pigmentosa. Five of these mutations lead to premature termination codons, and 1 leads to the skipping of exon 2. Allele-specific measurement of PRPF31 transcripts revealed a strong reduction in the expression of mutant alleles. As a consequence, total PRPF31 protein abundance was decreased, and no truncated proteins were detected. Subnuclear localization of the full-length PRPF31 that was present remained unaffected. Blocking nonsense-mediated mRNA decay significantly restored the amount of mutant PRPF31 mRNA but did not restore the synthesis of mutant proteins, even in conjunction with inhibitors of protein degradation pathways. Our results indicate that most PRPF31 mutations ultimately result in null alleles through the activation of surveillance mechanisms that inactivate mutant mRNA and, possibly, proteins. Furthermore, these data provide compelling evidence that the pathogenic effect of PRPF31 mutations is likely due to haploinsufficiency rather than to gain of function. Find the latest version: https://jci.me/34211/pdf Research article Premature termination codons in PRPF31 cause retinitis pigmentosa via haploinsufficiency due to nonsense-mediated mRNA decay Thomas Rio Frio,1 Nicholas M. -
Molecular and Physiological Basis for Hair Loss in Near Naked Hairless and Oak Ridge Rhino-Like Mouse Models: Tracking the Role of the Hairless Gene
University of Tennessee, Knoxville TRACE: Tennessee Research and Creative Exchange Doctoral Dissertations Graduate School 5-2006 Molecular and Physiological Basis for Hair Loss in Near Naked Hairless and Oak Ridge Rhino-like Mouse Models: Tracking the Role of the Hairless Gene Yutao Liu University of Tennessee - Knoxville Follow this and additional works at: https://trace.tennessee.edu/utk_graddiss Part of the Life Sciences Commons Recommended Citation Liu, Yutao, "Molecular and Physiological Basis for Hair Loss in Near Naked Hairless and Oak Ridge Rhino- like Mouse Models: Tracking the Role of the Hairless Gene. " PhD diss., University of Tennessee, 2006. https://trace.tennessee.edu/utk_graddiss/1824 This Dissertation is brought to you for free and open access by the Graduate School at TRACE: Tennessee Research and Creative Exchange. It has been accepted for inclusion in Doctoral Dissertations by an authorized administrator of TRACE: Tennessee Research and Creative Exchange. For more information, please contact [email protected]. To the Graduate Council: I am submitting herewith a dissertation written by Yutao Liu entitled "Molecular and Physiological Basis for Hair Loss in Near Naked Hairless and Oak Ridge Rhino-like Mouse Models: Tracking the Role of the Hairless Gene." I have examined the final electronic copy of this dissertation for form and content and recommend that it be accepted in partial fulfillment of the requirements for the degree of Doctor of Philosophy, with a major in Life Sciences. Brynn H. Voy, Major Professor We have read this dissertation and recommend its acceptance: Naima Moustaid-Moussa, Yisong Wang, Rogert Hettich Accepted for the Council: Carolyn R. -
Molecular Basis for the Distinct Cellular Functions of the Lsm1-7 and Lsm2-8 Complexes
bioRxiv preprint doi: https://doi.org/10.1101/2020.04.22.055376; this version posted April 23, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license. Molecular basis for the distinct cellular functions of the Lsm1-7 and Lsm2-8 complexes Eric J. Montemayor1,2, Johanna M. Virta1, Samuel M. Hayes1, Yuichiro Nomura1, David A. Brow2, Samuel E. Butcher1 1Department of Biochemistry, University of Wisconsin-Madison, Madison, WI, USA. 2Department of Biomolecular Chemistry, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA. Correspondence should be addressed to E.J.M. ([email protected]) and S.E.B. ([email protected]). Abstract Eukaryotes possess eight highly conserved Lsm (like Sm) proteins that assemble into circular, heteroheptameric complexes, bind RNA, and direct a diverse range of biological processes. Among the many essential functions of Lsm proteins, the cytoplasmic Lsm1-7 complex initiates mRNA decay, while the nuclear Lsm2-8 complex acts as a chaperone for U6 spliceosomal RNA. It has been unclear how these complexes perform their distinct functions while differing by only one out of seven subunits. Here, we elucidate the molecular basis for Lsm-RNA recognition and present four high-resolution structures of Lsm complexes bound to RNAs. The structures of Lsm2-8 bound to RNA identify the unique 2′,3′ cyclic phosphate end of U6 as a prime determinant of specificity. In contrast, the Lsm1-7 complex strongly discriminates against cyclic phosphates and tightly binds to oligouridylate tracts with terminal purines. -
Supplementary Table S1. Upregulated Genes Differentially
Supplementary Table S1. Upregulated genes differentially expressed in athletes (p < 0.05 and 1.3-fold change) Gene Symbol p Value Fold Change 221051_s_at NMRK2 0.01 2.38 236518_at CCDC183 0.00 2.05 218804_at ANO1 0.00 2.05 234675_x_at 0.01 2.02 207076_s_at ASS1 0.00 1.85 209135_at ASPH 0.02 1.81 228434_at BTNL9 0.03 1.81 229985_at BTNL9 0.01 1.79 215795_at MYH7B 0.01 1.78 217979_at TSPAN13 0.01 1.77 230992_at BTNL9 0.01 1.75 226884_at LRRN1 0.03 1.74 220039_s_at CDKAL1 0.01 1.73 236520_at 0.02 1.72 219895_at TMEM255A 0.04 1.72 201030_x_at LDHB 0.00 1.69 233824_at 0.00 1.69 232257_s_at 0.05 1.67 236359_at SCN4B 0.04 1.64 242868_at 0.00 1.63 1557286_at 0.01 1.63 202780_at OXCT1 0.01 1.63 1556542_a_at 0.04 1.63 209992_at PFKFB2 0.04 1.63 205247_at NOTCH4 0.01 1.62 1554182_at TRIM73///TRIM74 0.00 1.61 232892_at MIR1-1HG 0.02 1.61 204726_at CDH13 0.01 1.6 1561167_at 0.01 1.6 1565821_at 0.01 1.6 210169_at SEC14L5 0.01 1.6 236963_at 0.02 1.6 1552880_at SEC16B 0.02 1.6 235228_at CCDC85A 0.02 1.6 1568623_a_at SLC35E4 0.00 1.59 204844_at ENPEP 0.00 1.59 1552256_a_at SCARB1 0.02 1.59 1557283_a_at ZNF519 0.02 1.59 1557293_at LINC00969 0.03 1.59 231644_at 0.01 1.58 228115_at GAREM1 0.01 1.58 223687_s_at LY6K 0.02 1.58 231779_at IRAK2 0.03 1.58 243332_at LOC105379610 0.04 1.58 232118_at 0.01 1.57 203423_at RBP1 0.02 1.57 AMY1A///AMY1B///AMY1C///AMY2A///AMY2B// 208498_s_at 0.03 1.57 /AMYP1 237154_at LOC101930114 0.00 1.56 1559691_at 0.01 1.56 243481_at RHOJ 0.03 1.56 238834_at MYLK3 0.01 1.55 213438_at NFASC 0.02 1.55 242290_at TACC1 0.04 1.55 ANKRD20A1///ANKRD20A12P///ANKRD20A2/// -
HNRNPR Regulates the Expression of Classical and Nonclassical MHC Class I Proteins
HNRNPR Regulates the Expression of Classical and Nonclassical MHC Class I Proteins This information is current as Adi Reches, Daphna Nachmani, Orit Berhani, Alexandra of September 29, 2021. Duev-Cohen, Dorin Shreibman, Yael Ophir, Barbara Seliger and Ofer Mandelboim J Immunol 2016; 196:4967-4976; Prepublished online 18 May 2016; doi: 10.4049/jimmunol.1501550 Downloaded from http://www.jimmunol.org/content/196/12/4967 References This article cites 34 articles, 6 of which you can access for free at: http://www.jimmunol.org/content/196/12/4967.full#ref-list-1 http://www.jimmunol.org/ Why The JI? Submit online. • Rapid Reviews! 30 days* from submission to initial decision • No Triage! Every submission reviewed by practicing scientists by guest on September 29, 2021 • Fast Publication! 4 weeks from acceptance to publication *average Subscription Information about subscribing to The Journal of Immunology is online at: http://jimmunol.org/subscription Permissions Submit copyright permission requests at: http://www.aai.org/About/Publications/JI/copyright.html Email Alerts Receive free email-alerts when new articles cite this article. Sign up at: http://jimmunol.org/alerts The Journal of Immunology is published twice each month by The American Association of Immunologists, Inc., 1451 Rockville Pike, Suite 650, Rockville, MD 20852 Copyright © 2016 by The American Association of Immunologists, Inc. All rights reserved. Print ISSN: 0022-1767 Online ISSN: 1550-6606. The Journal of Immunology HNRNPR Regulates the Expression of Classical and Nonclassical MHC Class I Proteins Adi Reches,* Daphna Nachmani,* Orit Berhani,* Alexandra Duev-Cohen,* Dorin Shreibman,* Yael Ophir,* Barbara Seliger,† and Ofer Mandelboim* MHC class I molecules, in addition to their role in specific activation of the CTL of adaptive immune system, function also as the main ligands for NK cell inhibitory receptors, which prevent NK cells from killing normal, healthy cells. -
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. -
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. -
Genetic and Genomic Analysis of Hyperlipidemia, Obesity and Diabetes Using (C57BL/6J × TALLYHO/Jngj) F2 Mice
University of Tennessee, Knoxville TRACE: Tennessee Research and Creative Exchange Nutrition Publications and Other Works Nutrition 12-19-2010 Genetic and genomic analysis of hyperlipidemia, obesity and diabetes using (C57BL/6J × TALLYHO/JngJ) F2 mice Taryn P. Stewart Marshall University Hyoung Y. Kim University of Tennessee - Knoxville, [email protected] Arnold M. Saxton University of Tennessee - Knoxville, [email protected] Jung H. Kim Marshall University Follow this and additional works at: https://trace.tennessee.edu/utk_nutrpubs Part of the Animal Sciences Commons, and the Nutrition Commons Recommended Citation BMC Genomics 2010, 11:713 doi:10.1186/1471-2164-11-713 This Article is brought to you for free and open access by the Nutrition at TRACE: Tennessee Research and Creative Exchange. It has been accepted for inclusion in Nutrition Publications and Other Works by an authorized administrator of TRACE: Tennessee Research and Creative Exchange. For more information, please contact [email protected]. Stewart et al. BMC Genomics 2010, 11:713 http://www.biomedcentral.com/1471-2164/11/713 RESEARCH ARTICLE Open Access Genetic and genomic analysis of hyperlipidemia, obesity and diabetes using (C57BL/6J × TALLYHO/JngJ) F2 mice Taryn P Stewart1, Hyoung Yon Kim2, Arnold M Saxton3, Jung Han Kim1* Abstract Background: Type 2 diabetes (T2D) is the most common form of diabetes in humans and is closely associated with dyslipidemia and obesity that magnifies the mortality and morbidity related to T2D. The genetic contribution to human T2D and related metabolic disorders is evident, and mostly follows polygenic inheritance. The TALLYHO/ JngJ (TH) mice are a polygenic model for T2D characterized by obesity, hyperinsulinemia, impaired glucose uptake and tolerance, hyperlipidemia, and hyperglycemia. -
Transcriptome Sequencing and Genome-Wide Association Analyses Reveal Lysosomal Function and Actin Cytoskeleton Remodeling in Schizophrenia and Bipolar Disorder
Molecular Psychiatry (2015) 20, 563–572 © 2015 Macmillan Publishers Limited All rights reserved 1359-4184/15 www.nature.com/mp ORIGINAL ARTICLE Transcriptome sequencing and genome-wide association analyses reveal lysosomal function and actin cytoskeleton remodeling in schizophrenia and bipolar disorder Z Zhao1,6,JXu2,6, J Chen3,6, S Kim4, M Reimers3, S-A Bacanu3,HYu1, C Liu5, J Sun1, Q Wang1, P Jia1,FXu2, Y Zhang2, KS Kendler3, Z Peng2 and X Chen3 Schizophrenia (SCZ) and bipolar disorder (BPD) are severe mental disorders with high heritability. Clinicians have long noticed the similarities of clinic symptoms between these disorders. In recent years, accumulating evidence indicates some shared genetic liabilities. However, what is shared remains elusive. In this study, we conducted whole transcriptome analysis of post-mortem brain tissues (cingulate cortex) from SCZ, BPD and control subjects, and identified differentially expressed genes in these disorders. We found 105 and 153 genes differentially expressed in SCZ and BPD, respectively. By comparing the t-test scores, we found that many of the genes differentially expressed in SCZ and BPD are concordant in their expression level (q ⩽ 0.01, 53 genes; q ⩽ 0.05, 213 genes; q ⩽ 0.1, 885 genes). Using genome-wide association data from the Psychiatric Genomics Consortium, we found that these differentially and concordantly expressed genes were enriched in association signals for both SCZ (Po10 − 7) and BPD (P = 0.029). To our knowledge, this is the first time that a substantially large number of genes show concordant expression and association for both SCZ and BPD. Pathway analyses of these genes indicated that they are involved in the lysosome, Fc gamma receptor-mediated phagocytosis, regulation of actin cytoskeleton pathways, along with several cancer pathways. -
DEAD-Box RNA Helicases in Cell Cycle Control and Clinical Therapy
cells Review DEAD-Box RNA Helicases in Cell Cycle Control and Clinical Therapy Lu Zhang 1,2 and Xiaogang Li 2,3,* 1 Department of Nephrology, Renmin Hospital of Wuhan University, Wuhan 430060, China; [email protected] 2 Department of Internal Medicine, Mayo Clinic, 200 1st Street, SW, Rochester, MN 55905, USA 3 Department of Biochemistry and Molecular Biology, Mayo Clinic, 200 1st Street, SW, Rochester, MN 55905, USA * Correspondence: [email protected]; Tel.: +1-507-266-0110 Abstract: Cell cycle is regulated through numerous signaling pathways that determine whether cells will proliferate, remain quiescent, arrest, or undergo apoptosis. Abnormal cell cycle regula- tion has been linked to many diseases. Thus, there is an urgent need to understand the diverse molecular mechanisms of how the cell cycle is controlled. RNA helicases constitute a large family of proteins with functions in all aspects of RNA metabolism, including unwinding or annealing of RNA molecules to regulate pre-mRNA, rRNA and miRNA processing, clamping protein complexes on RNA, or remodeling ribonucleoprotein complexes, to regulate gene expression. RNA helicases also regulate the activity of specific proteins through direct interaction. Abnormal expression of RNA helicases has been associated with different diseases, including cancer, neurological disorders, aging, and autosomal dominant polycystic kidney disease (ADPKD) via regulation of a diverse range of cellular processes such as cell proliferation, cell cycle arrest, and apoptosis. Recent studies showed that RNA helicases participate in the regulation of the cell cycle progression at each cell cycle phase, including G1-S transition, S phase, G2-M transition, mitosis, and cytokinesis.