A Deep Proteomics Perspective on CRM1-Mediated Nuclear Export and Nucleocytoplasmic Partitioning
Total Page:16
File Type:pdf, Size:1020Kb
Load more
Recommended publications
-
KO Kidney.Xlsx
Supplemental Table 18: Dietary Impact on the CGL KO Kidney Sulfhydrome DR/AL Accession Molecular Cysteine Spectral Protein Name Number Alternate ID Weight Residues Count Ratio P‐value Ig gamma‐2A chain C region, A allele P01863 (+1) Ighg 36 kDa 10 C 5.952 0.03767 Heterogeneous nuclear ribonucleoprotein M Q9D0E1 (+1) Hnrnpm 78 kDa 6 C 5.000 0.00595 Phospholipase D3 O35405 Pld3 54 kDa 8 C 4.167 0.04761 Ig kappa chain V‐V region L7 (Fragment) P01642 Gm10881 13 kDa 2 C 2.857 0.01232 UPF0160 protein MYG1, mitochondrial Q9JK81 Myg1 43 kDa 7 C 2.333 0.01613 Copper homeostasis protein cutC homolog Q9D8X1 Cutc 29 kDa 7 C 10.333 0.16419 Corticosteroid‐binding globulin Q06770 Serpina6 45 kDa 3 C 10.333 0.16419 28S ribosomal protein S22, mitochondrial Q9CXW2 Mrps22 41 kDa 2 C 7.333 0.3739 Isoform 3 of Agrin A2ASQ1‐3 Agrn 198 kDa 2 C 7.333 0.3739 3‐oxoacyl‐[acyl‐carrier‐protein] synthase, mitochondrial Q9D404 Oxsm 49 kDa 11 C 7.333 0.3739 Cordon‐bleu protein‐like 1 Q3UMF0 (+3)Cobll1 137 kDa 10 C 5.833 0.10658 ADP‐sugar pyrophosphatase Q9JKX6 Nudt5 24 kDa 5 C 4.167 0.15819 Complement C4‐B P01029 C4b 193 kDa 29 C 3.381 0.23959 Protein‐glutamine gamma‐glutamyltransferase 2 P21981 Tgm2 77 kDa 20 C 3.381 0.23959 Isochorismatase domain‐containing protein 1 Q91V64 Isoc1 32 kDa 5 C 3.333 0.10588 Serpin B8 O08800 Serpinb8 42 kDa 11 C 2.903 0.06902 Heterogeneous nuclear ribonucleoprotein A0 Q9CX86 Hnrnpa0 31 kDa 3 C 2.667 0.5461 Proteasome subunit beta type‐8 P28063 Psmb8 30 kDa 5 C 2.583 0.36848 Ig kappa chain V‐V region MOPC 149 P01636 12 kDa 2 C 2.583 0.36848 -
Entrez Symbols Name Termid Termdesc 117553 Uba3,Ube1c
Entrez Symbols Name TermID TermDesc 117553 Uba3,Ube1c ubiquitin-like modifier activating enzyme 3 GO:0016881 acid-amino acid ligase activity 299002 G2e3,RGD1310263 G2/M-phase specific E3 ubiquitin ligase GO:0016881 acid-amino acid ligase activity 303614 RGD1310067,Smurf2 SMAD specific E3 ubiquitin protein ligase 2 GO:0016881 acid-amino acid ligase activity 308669 Herc2 hect domain and RLD 2 GO:0016881 acid-amino acid ligase activity 309331 Uhrf2 ubiquitin-like with PHD and ring finger domains 2 GO:0016881 acid-amino acid ligase activity 316395 Hecw2 HECT, C2 and WW domain containing E3 ubiquitin protein ligase 2 GO:0016881 acid-amino acid ligase activity 361866 Hace1 HECT domain and ankyrin repeat containing, E3 ubiquitin protein ligase 1 GO:0016881 acid-amino acid ligase activity 117029 Ccr5,Ckr5,Cmkbr5 chemokine (C-C motif) receptor 5 GO:0003779 actin binding 117538 Waspip,Wip,Wipf1 WAS/WASL interacting protein family, member 1 GO:0003779 actin binding 117557 TM30nm,Tpm3,Tpm5 tropomyosin 3, gamma GO:0003779 actin binding 24779 MGC93554,Slc4a1 solute carrier family 4 (anion exchanger), member 1 GO:0003779 actin binding 24851 Alpha-tm,Tma2,Tmsa,Tpm1 tropomyosin 1, alpha GO:0003779 actin binding 25132 Myo5b,Myr6 myosin Vb GO:0003779 actin binding 25152 Map1a,Mtap1a microtubule-associated protein 1A GO:0003779 actin binding 25230 Add3 adducin 3 (gamma) GO:0003779 actin binding 25386 AQP-2,Aqp2,MGC156502,aquaporin-2aquaporin 2 (collecting duct) GO:0003779 actin binding 25484 MYR5,Myo1e,Myr3 myosin IE GO:0003779 actin binding 25576 14-3-3e1,MGC93547,Ywhah -
Autism Multiplex Family with 16P11.2P12.2 Microduplication Syndrome in Monozygotic Twins and Distal 16P11.2 Deletion in Their Brother
European Journal of Human Genetics (2012) 20, 540–546 & 2012 Macmillan Publishers Limited All rights reserved 1018-4813/12 www.nature.com/ejhg ARTICLE Autism multiplex family with 16p11.2p12.2 microduplication syndrome in monozygotic twins and distal 16p11.2 deletion in their brother Anne-Claude Tabet1,2,3,4, Marion Pilorge2,3,4, Richard Delorme5,6,Fre´de´rique Amsellem5,6, Jean-Marc Pinard7, Marion Leboyer6,8,9, Alain Verloes10, Brigitte Benzacken1,11,12 and Catalina Betancur*,2,3,4 The pericentromeric region of chromosome 16p is rich in segmental duplications that predispose to rearrangements through non-allelic homologous recombination. Several recurrent copy number variations have been described recently in chromosome 16p. 16p11.2 rearrangements (29.5–30.1 Mb) are associated with autism, intellectual disability (ID) and other neurodevelopmental disorders. Another recognizable but less common microdeletion syndrome in 16p11.2p12.2 (21.4 to 28.5–30.1 Mb) has been described in six individuals with ID, whereas apparently reciprocal duplications, studied by standard cytogenetic and fluorescence in situ hybridization techniques, have been reported in three patients with autism spectrum disorders. Here, we report a multiplex family with three boys affected with autism, including two monozygotic twins carrying a de novo 16p11.2p12.2 duplication of 8.95 Mb (21.28–30.23 Mb) characterized by single-nucleotide polymorphism array, encompassing both the 16p11.2 and 16p11.2p12.2 regions. The twins exhibited autism, severe ID, and dysmorphic features, including a triangular face, deep-set eyes, large and prominent nasal bridge, and tall, slender build. The eldest brother presented with autism, mild ID, early-onset obesity and normal craniofacial features, and carried a smaller, overlapping 16p11.2 microdeletion of 847 kb (28.40–29.25 Mb), inherited from his apparently healthy father. -
Supp Material.Pdf
Simon et al. Supplementary information: Table of contents p.1 Supplementary material and methods p.2-4 • PoIy(I)-poly(C) Treatment • Flow Cytometry and Immunohistochemistry • Western Blotting • Quantitative RT-PCR • Fluorescence In Situ Hybridization • RNA-Seq • Exome capture • Sequencing Supplementary Figures and Tables Suppl. items Description pages Figure 1 Inactivation of Ezh2 affects normal thymocyte development 5 Figure 2 Ezh2 mouse leukemias express cell surface T cell receptor 6 Figure 3 Expression of EZH2 and Hox genes in T-ALL 7 Figure 4 Additional mutation et deletion of chromatin modifiers in T-ALL 8 Figure 5 PRC2 expression and activity in human lymphoproliferative disease 9 Figure 6 PRC2 regulatory network (String analysis) 10 Table 1 Primers and probes for detection of PRC2 genes 11 Table 2 Patient and T-ALL characteristics 12 Table 3 Statistics of RNA and DNA sequencing 13 Table 4 Mutations found in human T-ALLs (see Fig. 3D and Suppl. Fig. 4) 14 Table 5 SNP populations in analyzed human T-ALL samples 15 Table 6 List of altered genes in T-ALL for DAVID analysis 20 Table 7 List of David functional clusters 31 Table 8 List of acquired SNP tested in normal non leukemic DNA 32 1 Simon et al. Supplementary Material and Methods PoIy(I)-poly(C) Treatment. pIpC (GE Healthcare Lifesciences) was dissolved in endotoxin-free D-PBS (Gibco) at a concentration of 2 mg/ml. Mice received four consecutive injections of 150 μg pIpC every other day. The day of the last pIpC injection was designated as day 0 of experiment. -
Literature Mining Sustains and Enhances Knowledge Discovery from Omic Studies
LITERATURE MINING SUSTAINS AND ENHANCES KNOWLEDGE DISCOVERY FROM OMIC STUDIES by Rick Matthew Jordan B.S. Biology, University of Pittsburgh, 1996 M.S. Molecular Biology/Biotechnology, East Carolina University, 2001 M.S. Biomedical Informatics, University of Pittsburgh, 2005 Submitted to the Graduate Faculty of School of Medicine in partial fulfillment of the requirements for the degree of Doctor of Philosophy University of Pittsburgh 2016 UNIVERSITY OF PITTSBURGH SCHOOL OF MEDICINE This dissertation was presented by Rick Matthew Jordan It was defended on December 2, 2015 and approved by Shyam Visweswaran, M.D., Ph.D., Associate Professor Rebecca Jacobson, M.D., M.S., Professor Songjian Lu, Ph.D., Assistant Professor Dissertation Advisor: Vanathi Gopalakrishnan, Ph.D., Associate Professor ii Copyright © by Rick Matthew Jordan 2016 iii LITERATURE MINING SUSTAINS AND ENHANCES KNOWLEDGE DISCOVERY FROM OMIC STUDIES Rick Matthew Jordan, M.S. University of Pittsburgh, 2016 Genomic, proteomic and other experimentally generated data from studies of biological systems aiming to discover disease biomarkers are currently analyzed without sufficient supporting evidence from the literature due to complexities associated with automated processing. Extracting prior knowledge about markers associated with biological sample types and disease states from the literature is tedious, and little research has been performed to understand how to use this knowledge to inform the generation of classification models from ‘omic’ data. Using pathway analysis methods to better understand the underlying biology of complex diseases such as breast and lung cancers is state-of-the-art. However, the problem of how to combine literature- mining evidence with pathway analysis evidence is an open problem in biomedical informatics research. -
Plasma Cells in Vitro Generation of Long-Lived Human
Downloaded from http://www.jimmunol.org/ by guest on September 24, 2021 is online at: average * The Journal of Immunology , 32 of which you can access for free at: 2012; 189:5773-5785; Prepublished online 16 from submission to initial decision 4 weeks from acceptance to publication November 2012; doi: 10.4049/jimmunol.1103720 http://www.jimmunol.org/content/189/12/5773 In Vitro Generation of Long-lived Human Plasma Cells Mario Cocco, Sophie Stephenson, Matthew A. Care, Darren Newton, Nicholas A. Barnes, Adam Davison, Andy Rawstron, David R. Westhead, Gina M. Doody and Reuben M. Tooze J Immunol cites 65 articles Submit online. Every submission reviewed by practicing scientists ? is published twice each month by Submit copyright permission requests at: http://www.aai.org/About/Publications/JI/copyright.html Receive free email-alerts when new articles cite this article. Sign up at: http://jimmunol.org/alerts http://jimmunol.org/subscription http://www.jimmunol.org/content/suppl/2012/11/16/jimmunol.110372 0.DC1 This article http://www.jimmunol.org/content/189/12/5773.full#ref-list-1 Information about subscribing to The JI No Triage! Fast Publication! Rapid Reviews! 30 days* Why • • • Material References Permissions Email Alerts Subscription Supplementary The Journal of Immunology The American Association of Immunologists, Inc., 1451 Rockville Pike, Suite 650, Rockville, MD 20852 Copyright © 2012 by The American Association of Immunologists, Inc. All rights reserved. Print ISSN: 0022-1767 Online ISSN: 1550-6606. This information is current as of September 24, 2021. The Journal of Immunology In Vitro Generation of Long-lived Human Plasma Cells Mario Cocco,*,1 Sophie Stephenson,*,1 Matthew A. -
Transcriptome-Wide Map of M6a Circrnas Identified in a Rat Model Of
Su et al. BMC Genomics (2020) 21:39 https://doi.org/10.1186/s12864-020-6462-y RESEARCH ARTICLE Open Access Transcriptome-wide map of m6A circRNAs identified in a rat model of hypoxia mediated pulmonary hypertension Hua Su, Guowen Wang, Lingfang Wu, Xiuqing Ma, Kejing Ying and Ruifeng Zhang* Abstract Background: Hypoxia mediated pulmonary hypertension (HPH) is a lethal disease and lacks effective therapy. CircRNAs play significant roles in physiological process. Recently, circRNAs are found to be m6A-modified. The abundance of circRNAs was influenced by m6A. Furthermore, the significance of m6A circRNAs has not been elucidated in HPH yet. Here we aim to investigate the transcriptome-wide map of m6A circRNAs in HPH. Results: Differentially expressed m6A abundance was detected in lungs of HPH rats. M6A abundance in circRNAs was significantly reduced in hypoxia in vitro. M6A circRNAs were mainly from protein-coding genes spanned single exons in control and HPH groups. Moreover, m6A influenced the circRNA–miRNA–mRNA co-expression network in hypoxia. M6A circXpo6 and m6A circTmtc3 were firstly identified to be downregulated in HPH. Conclusion: Our study firstly identified the transcriptome-wide map of m6AcircRNAsinHPH. M6A can influence circRNA–miRNA–mRNA network. Furthermore, we firstly identified two HPH-associated m6AcircRNAs: circXpo6 and circTmtc3. However, the clinical significance of m6A circRNAs for HPH should be further validated. Keywords: m6A circRNAs, Hypoxia mediated pulmonary hypertension, m6A circXpo6, m6A circTmtc3 Background Circular RNAs (circRNAs) were firstly found abundant Pulmonary hypertension (PH) is a lethal disease and defined in eukaryotes using RNA-seq approach [5–7]. Pre-mRNA as an increase in the mean pulmonary arterial pressure ≥ 25 is spliced with the 5′ and 3′ ends, forming a ‘head-to-tail’ mmHg at rest, as measured by right heart catheterization [1]. -
Investigation of Differentially Expressed Genes in Nasopharyngeal Carcinoma by Integrated Bioinformatics Analysis
916 ONCOLOGY LETTERS 18: 916-926, 2019 Investigation of differentially expressed genes in nasopharyngeal carcinoma by integrated bioinformatics analysis ZhENNING ZOU1*, SIYUAN GAN1*, ShUGUANG LIU2, RUjIA LI1 and jIAN hUANG1 1Department of Pathology, Guangdong Medical University, Zhanjiang, Guangdong 524023; 2Department of Pathology, The Eighth Affiliated hospital of Sun Yat‑sen University, Shenzhen, Guangdong 518033, P.R. China Received October 9, 2018; Accepted April 10, 2019 DOI: 10.3892/ol.2019.10382 Abstract. Nasopharyngeal carcinoma (NPC) is a common topoisomerase 2α and TPX2 microtubule nucleation factor), malignancy of the head and neck. The aim of the present study 8 modules, and 14 TFs were identified. Modules analysis was to conduct an integrated bioinformatics analysis of differ- revealed that cyclin-dependent kinase 1 and exportin 1 were entially expressed genes (DEGs) and to explore the molecular involved in the pathway of Epstein‑Barr virus infection. In mechanisms of NPC. Two profiling datasets, GSE12452 and summary, the hub genes, key modules and TFs identified in GSE34573, were downloaded from the Gene Expression this study may promote our understanding of the pathogenesis Omnibus database and included 44 NPC specimens and of NPC and require further in-depth investigation. 13 normal nasopharyngeal tissues. R software was used to identify the DEGs between NPC and normal nasopharyngeal Introduction tissues. Distributions of DEGs in chromosomes were explored based on the annotation file and the CYTOBAND database Nasopharyngeal carcinoma (NPC) is a common malignancy of DAVID. Gene ontology (GO) and Kyoto Encyclopedia of occurring in the head and neck. It is prevalent in the eastern Genes and Genomes (KEGG) pathway enrichment analysis and southeastern parts of Asia, especially in southern China, were applied. -
Open Data for Differential Network Analysis in Glioma
International Journal of Molecular Sciences Article Open Data for Differential Network Analysis in Glioma , Claire Jean-Quartier * y , Fleur Jeanquartier y and Andreas Holzinger Holzinger Group HCI-KDD, Institute for Medical Informatics, Statistics and Documentation, Medical University Graz, Auenbruggerplatz 2/V, 8036 Graz, Austria; [email protected] (F.J.); [email protected] (A.H.) * Correspondence: [email protected] These authors contributed equally to this work. y Received: 27 October 2019; Accepted: 3 January 2020; Published: 15 January 2020 Abstract: The complexity of cancer diseases demands bioinformatic techniques and translational research based on big data and personalized medicine. Open data enables researchers to accelerate cancer studies, save resources and foster collaboration. Several tools and programming approaches are available for analyzing data, including annotation, clustering, comparison and extrapolation, merging, enrichment, functional association and statistics. We exploit openly available data via cancer gene expression analysis, we apply refinement as well as enrichment analysis via gene ontology and conclude with graph-based visualization of involved protein interaction networks as a basis for signaling. The different databases allowed for the construction of huge networks or specified ones consisting of high-confidence interactions only. Several genes associated to glioma were isolated via a network analysis from top hub nodes as well as from an outlier analysis. The latter approach highlights a mitogen-activated protein kinase next to a member of histondeacetylases and a protein phosphatase as genes uncommonly associated with glioma. Cluster analysis from top hub nodes lists several identified glioma-associated gene products to function within protein complexes, including epidermal growth factors as well as cell cycle proteins or RAS proto-oncogenes. -
Intrinsic Disorder of the BAF Complex: Roles in Chromatin Remodeling and Disease Development
International Journal of Molecular Sciences Article Intrinsic Disorder of the BAF Complex: Roles in Chromatin Remodeling and Disease Development Nashwa El Hadidy 1 and Vladimir N. Uversky 1,2,* 1 Department of Molecular Medicine, Morsani College of Medicine, University of South Florida, 12901 Bruce B. Downs Blvd. MDC07, Tampa, FL 33612, USA; [email protected] 2 Laboratory of New Methods in Biology, Institute for Biological Instrumentation of the Russian Academy of Sciences, Federal Research Center “Pushchino Scientific Center for Biological Research of the Russian Academy of Sciences”, Pushchino, 142290 Moscow Region, Russia * Correspondence: [email protected]; Tel.: +1-813-974-5816; Fax: +1-813-974-7357 Received: 20 September 2019; Accepted: 21 October 2019; Published: 23 October 2019 Abstract: The two-meter-long DNA is compressed into chromatin in the nucleus of every cell, which serves as a significant barrier to transcription. Therefore, for processes such as replication and transcription to occur, the highly compacted chromatin must be relaxed, and the processes required for chromatin reorganization for the aim of replication or transcription are controlled by ATP-dependent nucleosome remodelers. One of the most highly studied remodelers of this kind is the BRG1- or BRM-associated factor complex (BAF complex, also known as SWItch/sucrose non-fermentable (SWI/SNF) complex), which is crucial for the regulation of gene expression and differentiation in eukaryotes. Chromatin remodeling complex BAF is characterized by a highly polymorphic structure, containing from four to 17 subunits encoded by 29 genes. The aim of this paper is to provide an overview of the role of BAF complex in chromatin remodeling and also to use literature mining and a set of computational and bioinformatics tools to analyze structural properties, intrinsic disorder predisposition, and functionalities of its subunits, along with the description of the relations of different BAF complex subunits to the pathogenesis of various human diseases. -
Mouse Haus1 Conditional Knockout Project (CRISPR/Cas9)
https://www.alphaknockout.com Mouse Haus1 Conditional Knockout Project (CRISPR/Cas9) Objective: To create a Haus1 conditional knockout Mouse model (C57BL/6J) by CRISPR/Cas-mediated genome engineering. Strategy summary: The Haus1 gene (NCBI Reference Sequence: NM_146089 ; Ensembl: ENSMUSG00000041840 ) is located on Mouse chromosome 18. 9 exons are identified, with the ATG start codon in exon 1 and the TGA stop codon in exon 9 (Transcript: ENSMUST00000048192). Exon 3~4 will be selected as conditional knockout region (cKO region). Deletion of this region should result in the loss of function of the Mouse Haus1 gene. To engineer the targeting vector, homologous arms and cKO region will be generated by PCR using BAC clone RP23-196O5 as template. Cas9, gRNA and targeting vector will be co-injected into fertilized eggs for cKO Mouse production. The pups will be genotyped by PCR followed by sequencing analysis. Note: Exon 3 starts from about 24.7% of the coding region. The knockout of Exon 3~4 will result in frameshift of the gene. The size of intron 2 for 5'-loxP site insertion: 2655 bp, and the size of intron 4 for 3'-loxP site insertion: 951 bp. The size of effective cKO region: ~2727 bp. The cKO region does not have any other known gene. Page 1 of 7 https://www.alphaknockout.com Overview of the Targeting Strategy Wildtype allele 5' gRNA region gRNA region 3' 1 3 4 5 6 9 Targeting vector Targeted allele Constitutive KO allele (After Cre recombination) Legends Exon of mouse Haus1 Homology arm cKO region loxP site Page 2 of 7 https://www.alphaknockout.com Overview of the Dot Plot Window size: 10 bp Forward Reverse Complement Sequence 12 Note: The sequence of homologous arms and cKO region is aligned with itself to determine if there are tandem repeats. -
Identification of Differential Expression of P53 Associated Rnas at 3 Different Treatment Timepoints, and Association with Chip- Seq Identified P53 Genes
Rochester Institute of Technology RIT Scholar Works Theses 5-19-2017 Identification of Differential Expression of p53 associated RNAs at 3 Different Treatment Timepoints, and Association with ChIP- seq Identified p53 Genes. Julia Freewoman [email protected] Follow this and additional works at: https://scholarworks.rit.edu/theses Recommended Citation Freewoman, Julia, "Identification of Differential Expression of p53 associated RNAs at 3 Different Treatment Timepoints, and Association with ChIP-seq Identified p53 Genes." (2017). Thesis. Rochester Institute of Technology. Accessed from This Thesis is brought to you for free and open access by RIT Scholar Works. It has been accepted for inclusion in Theses by an authorized administrator of RIT Scholar Works. For more information, please contact [email protected]. R.I.T. Identification of Differential Expression of p53 associated RNAs at 3 Different Treatment Timepoints, and Association with ChIP-seq Identified p53 Genes. by Julia Freewoman A Thesis Submitted in Partial Fulfillment of the Requirements for the Degree of Master of Science in Bioinformatics. School of Thomas H. Gosnell School of Life Sciences Bioinformatics Program College of Science Rochester Institute of Technology Rochester, NY May 19, 2017 Thesis Committee Members: Feng Cui, Ph.D., thesis advisor Andre Hudson, Ph.D. Gary R. Skuse, Ph.D. ii Table of Contents Abstract ........................................................................................................................................... 1 I. Introduction