Gene Section Review
Total Page:16
File Type:pdf, Size:1020Kb
Load more
Recommended publications
-
In Silico Prediction of High-Resolution Hi-C Interaction Matrices
ARTICLE https://doi.org/10.1038/s41467-019-13423-8 OPEN In silico prediction of high-resolution Hi-C interaction matrices Shilu Zhang1, Deborah Chasman 1, Sara Knaack1 & Sushmita Roy1,2* The three-dimensional (3D) organization of the genome plays an important role in gene regulation bringing distal sequence elements in 3D proximity to genes hundreds of kilobases away. Hi-C is a powerful genome-wide technique to study 3D genome organization. Owing to 1234567890():,; experimental costs, high resolution Hi-C datasets are limited to a few cell lines. Computa- tional prediction of Hi-C counts can offer a scalable and inexpensive approach to examine 3D genome organization across multiple cellular contexts. Here we present HiC-Reg, an approach to predict contact counts from one-dimensional regulatory signals. HiC-Reg pre- dictions identify topologically associating domains and significant interactions that are enri- ched for CCCTC-binding factor (CTCF) bidirectional motifs and interactions identified from complementary sources. CTCF and chromatin marks, especially repressive and elongation marks, are most important for HiC-Reg’s predictive performance. Taken together, HiC-Reg provides a powerful framework to generate high-resolution profiles of contact counts that can be used to study individual locus level interactions and higher-order organizational units of the genome. 1 Wisconsin Institute for Discovery, 330 North Orchard Street, Madison, WI 53715, USA. 2 Department of Biostatistics and Medical Informatics, University of Wisconsin-Madison, Madison, WI 53715, USA. *email: [email protected] NATURE COMMUNICATIONS | (2019) 10:5449 | https://doi.org/10.1038/s41467-019-13423-8 | www.nature.com/naturecommunications 1 ARTICLE NATURE COMMUNICATIONS | https://doi.org/10.1038/s41467-019-13423-8 he three-dimensional (3D) organization of the genome has Results Temerged as an important component of the gene regulation HiC-Reg for predicting contact count using Random Forests. -
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. -
Systems Analysis Implicates WAVE2&Nbsp
JACC: BASIC TO TRANSLATIONAL SCIENCE VOL.5,NO.4,2020 ª 2020 THE AUTHORS. PUBLISHED BY ELSEVIER ON BEHALF OF THE AMERICAN COLLEGE OF CARDIOLOGY FOUNDATION. THIS IS AN OPEN ACCESS ARTICLE UNDER THE CC BY-NC-ND LICENSE (http://creativecommons.org/licenses/by-nc-nd/4.0/). PRECLINICAL RESEARCH Systems Analysis Implicates WAVE2 Complex in the Pathogenesis of Developmental Left-Sided Obstructive Heart Defects a b b b Jonathan J. Edwards, MD, Andrew D. Rouillard, PHD, Nicolas F. Fernandez, PHD, Zichen Wang, PHD, b c d d Alexander Lachmann, PHD, Sunita S. Shankaran, PHD, Brent W. Bisgrove, PHD, Bradley Demarest, MS, e f g h Nahid Turan, PHD, Deepak Srivastava, MD, Daniel Bernstein, MD, John Deanfield, MD, h i j k Alessandro Giardini, MD, PHD, George Porter, MD, PHD, Richard Kim, MD, Amy E. Roberts, MD, k l m m,n Jane W. Newburger, MD, MPH, Elizabeth Goldmuntz, MD, Martina Brueckner, MD, Richard P. Lifton, MD, PHD, o,p,q r,s t d Christine E. Seidman, MD, Wendy K. Chung, MD, PHD, Martin Tristani-Firouzi, MD, H. Joseph Yost, PHD, b u,v Avi Ma’ayan, PHD, Bruce D. Gelb, MD VISUAL ABSTRACT Edwards, J.J. et al. J Am Coll Cardiol Basic Trans Science. 2020;5(4):376–86. ISSN 2452-302X https://doi.org/10.1016/j.jacbts.2020.01.012 JACC: BASIC TO TRANSLATIONALSCIENCEVOL.5,NO.4,2020 Edwards et al. 377 APRIL 2020:376– 86 WAVE2 Complex in LVOTO HIGHLIGHTS ABBREVIATIONS AND ACRONYMS Combining CHD phenotype–driven gene set enrichment and CRISPR knockdown screening in zebrafish is an effective approach to identifying novel CHD genes. -
Molecular Profiling of Peripheral Blood Is Associated with Circulating Tumor Cells Content and Poor Survival in Metastatic Castration-Resistant Prostate Cancer
www.impactjournals.com/oncotarget/ Oncotarget, Vol. 6, No. 12 Molecular profiling of peripheral blood is associated with circulating tumor cells content and poor survival in metastatic castration-resistant prostate cancer Mercedes Marín-Aguilera1, Òscar Reig1,2, Juan José Lozano3, Natalia Jiménez1, Susana García-Recio1,4, Nadina Erill5, Lydia Gaba2, Andrea Tagliapietra2, Vanesa Ortega2, Gemma Carrera6, Anna Colomer5, Pedro Gascón4 and Begoña Mellado1,2 1 Translational Genomics Group and Targeted Therapeutics in Solid Tumors Group, Institut d’Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain 2 Medical Oncology Department, Hospital Clínic, Barcelona, Spain 3 Bioinformatics Platform Department, Centro de Investigación Biomédica en Red en el Área temática de Enfermedades Hepáticas y Digestivas (CIBEREHD), Hospital Clínic, Barcelona, Spain 4 Laboratory of Translational Oncology, Fundació Clínic per a la Recerca Biomèdica, Barcelona, Spain 5 Althia, Barcelona, Spain 6 Medical Oncology Department, Hospital Plató, Barcelona, Spain Correspondence to: Begoña Mellado, email: [email protected] Keywords: circulating tumor cells, peripheral blood, microarrays, cell search system Received: January 22, 2015 Accepted: February 14, 2015 Published: March 12, 2015 This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. ABSTRACT The enumeration of circulating -
IL21R Expressing CD14+CD16+ Monocytes Expand in Multiple
Plasma Cell Disorders SUPPLEMENTARY APPENDIX IL21R expressing CD14 +CD16 + monocytes expand in multiple myeloma patients leading to increased osteoclasts Marina Bolzoni, 1 Domenica Ronchetti, 2,3 Paola Storti, 1,4 Gaetano Donofrio, 5 Valentina Marchica, 1,4 Federica Costa, 1 Luca Agnelli, 2,3 Denise Toscani, 1 Rosanna Vescovini, 1 Katia Todoerti, 6 Sabrina Bonomini, 7 Gabriella Sammarelli, 1,7 Andrea Vecchi, 8 Daniela Guasco, 1 Fabrizio Accardi, 1,7 Benedetta Dalla Palma, 1,7 Barbara Gamberi, 9 Carlo Ferrari, 8 Antonino Neri, 2,3 Franco Aversa 1,4,7 and Nicola Giuliani 1,4,7 1Myeloma Unit, Dept. of Medicine and Surgery, University of Parma; 2Dept. of Oncology and Hemato-Oncology, University of Milan; 3Hematology Unit, “Fondazione IRCCS Ca’ Granda”, Ospedale Maggiore Policlinico, Milan; 4CoreLab, University Hospital of Parma; 5Dept. of Medical-Veterinary Science, University of Parma; 6Laboratory of Pre-clinical and Translational Research, IRCCS-CROB, Referral Cancer Center of Basilicata, Rionero in Vulture; 7Hematology and BMT Center, University Hospital of Parma; 8Infectious Disease Unit, University Hospital of Parma and 9“Dip. Oncologico e Tecnologie Avanzate”, IRCCS Arcispedale Santa Maria Nuova, Reggio Emilia, Italy ©2017 Ferrata Storti Foundation. This is an open-access paper. doi:10.3324/haematol. 2016.153841 Received: August 5, 2016. Accepted: December 23, 2016. Pre-published: January 5, 2017. Correspondence: [email protected] SUPPLEMENTAL METHODS Immunophenotype of BM CD14+ in patients with monoclonal gammopathies. Briefly, 100 μl of total BM aspirate was incubated in the dark with anti-human HLA-DR-PE (clone L243; BD), anti-human CD14-PerCP-Cy 5.5, anti-human CD16-PE-Cy7 (clone B73.1; BD) and anti-human CD45-APC-H 7 (clone 2D1; BD) for 20 min. -
Cellular and Molecular Signatures in the Disease Tissue of Early
Cellular and Molecular Signatures in the Disease Tissue of Early Rheumatoid Arthritis Stratify Clinical Response to csDMARD-Therapy and Predict Radiographic Progression Frances Humby1,* Myles Lewis1,* Nandhini Ramamoorthi2, Jason Hackney3, Michael Barnes1, Michele Bombardieri1, Francesca Setiadi2, Stephen Kelly1, Fabiola Bene1, Maria di Cicco1, Sudeh Riahi1, Vidalba Rocher-Ros1, Nora Ng1, Ilias Lazorou1, Rebecca E. Hands1, Desiree van der Heijde4, Robert Landewé5, Annette van der Helm-van Mil4, Alberto Cauli6, Iain B. McInnes7, Christopher D. Buckley8, Ernest Choy9, Peter Taylor10, Michael J. Townsend2 & Costantino Pitzalis1 1Centre for Experimental Medicine and Rheumatology, William Harvey Research Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, Charterhouse Square, London EC1M 6BQ, UK. Departments of 2Biomarker Discovery OMNI, 3Bioinformatics and Computational Biology, Genentech Research and Early Development, South San Francisco, California 94080 USA 4Department of Rheumatology, Leiden University Medical Center, The Netherlands 5Department of Clinical Immunology & Rheumatology, Amsterdam Rheumatology & Immunology Center, Amsterdam, The Netherlands 6Rheumatology Unit, Department of Medical Sciences, Policlinico of the University of Cagliari, Cagliari, Italy 7Institute of Infection, Immunity and Inflammation, University of Glasgow, Glasgow G12 8TA, UK 8Rheumatology Research Group, Institute of Inflammation and Ageing (IIA), University of Birmingham, Birmingham B15 2WB, UK 9Institute of -
Supplemental Information
Supplemental information Dissection of the genomic structure of the miR-183/96/182 gene. Previously, we showed that the miR-183/96/182 cluster is an intergenic miRNA cluster, located in a ~60-kb interval between the genes encoding nuclear respiratory factor-1 (Nrf1) and ubiquitin-conjugating enzyme E2H (Ube2h) on mouse chr6qA3.3 (1). To start to uncover the genomic structure of the miR- 183/96/182 gene, we first studied genomic features around miR-183/96/182 in the UCSC genome browser (http://genome.UCSC.edu/), and identified two CpG islands 3.4-6.5 kb 5’ of pre-miR-183, the most 5’ miRNA of the cluster (Fig. 1A; Fig. S1 and Seq. S1). A cDNA clone, AK044220, located at 3.2-4.6 kb 5’ to pre-miR-183, encompasses the second CpG island (Fig. 1A; Fig. S1). We hypothesized that this cDNA clone was derived from 5’ exon(s) of the primary transcript of the miR-183/96/182 gene, as CpG islands are often associated with promoters (2). Supporting this hypothesis, multiple expressed sequences detected by gene-trap clones, including clone D016D06 (3, 4), were co-localized with the cDNA clone AK044220 (Fig. 1A; Fig. S1). Clone D016D06, deposited by the German GeneTrap Consortium (GGTC) (http://tikus.gsf.de) (3, 4), was derived from insertion of a retroviral construct, rFlpROSAβgeo in 129S2 ES cells (Fig. 1A and C). The rFlpROSAβgeo construct carries a promoterless reporter gene, the β−geo cassette - an in-frame fusion of the β-galactosidase and neomycin resistance (Neor) gene (5), with a splicing acceptor (SA) immediately upstream, and a polyA signal downstream of the β−geo cassette (Fig. -
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 -
Cargo Specific Regulation of Cytoplasmic Dynein by Effector Proteins
University of Pennsylvania ScholarlyCommons Publicly Accessible Penn Dissertations 2018 Cargo Specific Regulation Of Cytoplasmic Dynein By Effector Proteins Mara Olenick University of Pennsylvania, [email protected] Follow this and additional works at: https://repository.upenn.edu/edissertations Part of the Biochemistry Commons, Biophysics Commons, and the Cell Biology Commons Recommended Citation Olenick, Mara, "Cargo Specific Regulation Of Cytoplasmic Dynein By Effector Proteins" (2018). Publicly Accessible Penn Dissertations. 3167. https://repository.upenn.edu/edissertations/3167 This paper is posted at ScholarlyCommons. https://repository.upenn.edu/edissertations/3167 For more information, please contact [email protected]. Cargo Specific Regulation Of Cytoplasmic Dynein By Effector Proteins Abstract Axonal transport is vital for the development and survival of neurons. The transport of cargo and organelles from the axon to the cell body is driven almost completely by the molecular motor, cytoplasmic dynein. Yet, it remains unclear how dynein is spatially and temporally regulated given the variety of cargo that must be properly localized to maintain cellular function. Previous work has suggested that adaptor proteins provide a mechanism for cargo-specific egulationr of motors. During my thesis work, I have investigated the role of mammalian Hook proteins, Hook1 and Hook3, as potential motor adaptors. Using optogenetic and single molecule assays, I found that Hook proteins interact with both dynein and dynactin, to effectively activate dynein motility, inducing longer run lengths and higher velocities than the previously characterized dynein activator, BICD2. In addition, I found that complex formation requires the N-terminal domain of Hook proteins, which resembles the calponin-homology domain of EB proteins yet cannot bind directly to microtubules. -
Peripherally Generated Foxp3+ Regulatory T Cells Mediate the Immunomodulatory Effects of Ivig in Allergic Airways Disease
Published February 20, 2017, doi:10.4049/jimmunol.1502361 The Journal of Immunology Peripherally Generated Foxp3+ Regulatory T Cells Mediate the Immunomodulatory Effects of IVIg in Allergic Airways Disease Amir H. Massoud,*,†,1 Gabriel N. Kaufman,* Di Xue,* Marianne Be´land,* Marieme Dembele,* Ciriaco A. Piccirillo,‡ Walid Mourad,† and Bruce D. Mazer* IVIg is widely used as an immunomodulatory therapy. We have recently demonstrated that IVIg protects against airway hyper- responsiveness (AHR) and inflammation in mouse models of allergic airways disease (AAD), associated with induction of Foxp3+ regulatory T cells (Treg). Using mice carrying a DTR/EGFP transgene under the control of the Foxp3 promoter (DEREG mice), we demonstrate in this study that IVIg generates a de novo population of peripheral Treg (pTreg) in the absence of endogenous Treg. IVIg-generated pTreg were sufficient for inhibition of OVA-induced AHR in an Ag-driven murine model of AAD. In the absence of endogenous Treg, IVIg failed to confer protection against AHR and airway inflammation. Adoptive transfer of purified IVIg-generated pTreg prior to Ag challenge effectively prevented airway inflammation and AHR in an Ag-specific manner. Microarray gene expression profiling of IVIg-generated pTreg revealed upregulation of genes associated with cell cycle, chroma- tin, cytoskeleton/motility, immunity, and apoptosis. These data demonstrate the importance of Treg in regulating AAD and show that IVIg-generated pTreg are necessary and sufficient for inhibition of allergen-induced AAD. The ability of IVIg to generate pure populations of highly Ag-specific pTreg represents a new avenue to study pTreg, the cross-talk between humoral and cellular immunity, and regulation of the inflammatory response to Ags. -
Dysregulation of Mitotic Machinery Genes Precedes Genome Instability
The Author(s) BMC Genomics 2016, 17(Suppl 8):728 DOI 10.1186/s12864-016-3068-5 RESEARCH Open Access Dysregulation of mitotic machinery genes precedes genome instability during spontaneous pre-malignant transformation of mouse ovarian surface epithelial cells Ulises Urzúa1*, Sandra Ampuero2, Katherine F. Roby3, Garrison A. Owens4,6 and David J. Munroe4,5 From 6th SolBio International Conference 2016 (SoIBio-IC&W-2016) Riviera Maya, Mexico. 22-26 April 2016 Abstract Background: Based in epidemiological evidence, repetitive ovulation has been proposed to play a role in the origin of ovarian cancer by inducing an aberrant wound rupture-repair process of the ovarian surface epithelium (OSE). Accordingly, long term cultures of isolated OSE cells undergo in vitro spontaneous transformation thus developing tumorigenic capacity upon extensive subcultivation. In this work, C57BL/6 mouse OSE (MOSE) cells were cultured up to passage 28 and their RNA and DNA copy number profiles obtained at passages 2, 5, 7, 10, 14, 18, 23, 25 and 28 by means of DNA microarrays. Gene ontology, pathway and network analyses were focused in passages earlier than 20, which is a hallmark of malignancy in this model. Results: At passage 14, 101 genes were up-regulated in absence of significant DNA copy number changes. Among these, the top-3 enriched functions (>30 fold, adj p < 0.05) comprised 7 genes coding for centralspindlin, chromosome passenger and minichromosome maintenance protein complexes. The genes Ccnb1 (Cyclin B1), Birc5 (Survivin), Nusap1 and Kif23 were the most recurrent in over a dozen GO terms related to the mitotic process. On the other hand, Pten plus the large non-coding RNAs Malat1 and Neat1 were among the 80 down-regulated genes with mRNA processing, nuclear bodies, ER-stress response and tumor suppression as relevant terms. -
Nº Ref Uniprot Proteína Péptidos Identificados Por MS/MS 1 P01024
Document downloaded from http://www.elsevier.es, day 26/09/2021. This copy is for personal use. Any transmission of this document by any media or format is strictly prohibited. Nº Ref Uniprot Proteína Péptidos identificados 1 P01024 CO3_HUMAN Complement C3 OS=Homo sapiens GN=C3 PE=1 SV=2 por 162MS/MS 2 P02751 FINC_HUMAN Fibronectin OS=Homo sapiens GN=FN1 PE=1 SV=4 131 3 P01023 A2MG_HUMAN Alpha-2-macroglobulin OS=Homo sapiens GN=A2M PE=1 SV=3 128 4 P0C0L4 CO4A_HUMAN Complement C4-A OS=Homo sapiens GN=C4A PE=1 SV=1 95 5 P04275 VWF_HUMAN von Willebrand factor OS=Homo sapiens GN=VWF PE=1 SV=4 81 6 P02675 FIBB_HUMAN Fibrinogen beta chain OS=Homo sapiens GN=FGB PE=1 SV=2 78 7 P01031 CO5_HUMAN Complement C5 OS=Homo sapiens GN=C5 PE=1 SV=4 66 8 P02768 ALBU_HUMAN Serum albumin OS=Homo sapiens GN=ALB PE=1 SV=2 66 9 P00450 CERU_HUMAN Ceruloplasmin OS=Homo sapiens GN=CP PE=1 SV=1 64 10 P02671 FIBA_HUMAN Fibrinogen alpha chain OS=Homo sapiens GN=FGA PE=1 SV=2 58 11 P08603 CFAH_HUMAN Complement factor H OS=Homo sapiens GN=CFH PE=1 SV=4 56 12 P02787 TRFE_HUMAN Serotransferrin OS=Homo sapiens GN=TF PE=1 SV=3 54 13 P00747 PLMN_HUMAN Plasminogen OS=Homo sapiens GN=PLG PE=1 SV=2 48 14 P02679 FIBG_HUMAN Fibrinogen gamma chain OS=Homo sapiens GN=FGG PE=1 SV=3 47 15 P01871 IGHM_HUMAN Ig mu chain C region OS=Homo sapiens GN=IGHM PE=1 SV=3 41 16 P04003 C4BPA_HUMAN C4b-binding protein alpha chain OS=Homo sapiens GN=C4BPA PE=1 SV=2 37 17 Q9Y6R7 FCGBP_HUMAN IgGFc-binding protein OS=Homo sapiens GN=FCGBP PE=1 SV=3 30 18 O43866 CD5L_HUMAN CD5 antigen-like OS=Homo