Gene Expression Profiling in Human Fetal Liver and Identification of Tissue
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Harnessing Gene Expression Profiles for the Identification of Ex Vivo Drug
cancers Article Harnessing Gene Expression Profiles for the Identification of Ex Vivo Drug Response Genes in Pediatric Acute Myeloid Leukemia David G.J. Cucchi 1 , Costa Bachas 1 , Marry M. van den Heuvel-Eibrink 2,3, Susan T.C.J.M. Arentsen-Peters 3, Zinia J. Kwidama 1, Gerrit J. Schuurhuis 1, Yehuda G. Assaraf 4, Valérie de Haas 3 , Gertjan J.L. Kaspers 3,5 and Jacqueline Cloos 1,* 1 Hematology, Cancer Center Amsterdam, Amsterdam UMC, Vrije Universiteit Amsterdam, 1081 HV Amsterdam, The Netherlands; [email protected] (D.G.J.C.); [email protected] (C.B.); [email protected] (Z.J.K.); [email protected] (G.J.S.) 2 Department of Pediatric Oncology/Hematology, Erasmus MC–Sophia Children’s Hospital, 3015 CN Rotterdam, The Netherlands; [email protected] 3 Princess Máxima Center for Pediatric Oncology, 3584 CS Utrecht, The Netherlands; [email protected] (S.T.C.J.M.A.-P.); [email protected] (V.d.H.); [email protected] (G.J.L.K.) 4 The Fred Wyszkowski Cancer Research, Laboratory, Department of Biology, Technion-Israel Institute of Technology, 3200003 Haifa, Israel; [email protected] 5 Emma’s Children’s Hospital, Amsterdam UMC, Vrije Universiteit Amsterdam, Pediatric Oncology, 1081 HV Amsterdam, The Netherlands * Correspondence: [email protected] Received: 21 April 2020; Accepted: 12 May 2020; Published: 15 May 2020 Abstract: Novel treatment strategies are of paramount importance to improve clinical outcomes in pediatric AML. Since chemotherapy is likely to remain the cornerstone of curative treatment of AML, insights in the molecular mechanisms that determine its cytotoxic effects could aid further treatment optimization. -
Polyclonal Antibody to ARFGAP3 (C-Term) - Aff - Purified
OriGene Technologies, Inc. OriGene Technologies GmbH 9620 Medical Center Drive, Ste 200 Schillerstr. 5 Rockville, MD 20850 32052 Herford UNITED STATES GERMANY Phone: +1-888-267-4436 Phone: +49-5221-34606-0 Fax: +1-301-340-8606 Fax: +49-5221-34606-11 [email protected] [email protected] AP15932PU-N Polyclonal Antibody to ARFGAP3 (C-term) - Aff - Purified Alternate names: ADP-ribosylation factor GTPase-activating protein 3, ARF GAP 3, ARFGAP1 Quantity: 0.1 mg Concentration: 0.5 mg/ml Background: The protein encoded by this gene is a GTPase-activating protein (GAP) which associates with the Golgi apparatus and which is thought to interact with ADP- ribosylation factor 1 (ARF1). The encoded protein likely promotes hydrolysis of ARF1-bound GTP, which is required for the dissociation of coat proteins from Golgi- derived membranes and vesicles. Dissociation of the coat proteins is a prerequisite for the fusion of these vesicles with target compartments. The activity of this protein is sensitive to phospholipids. This gene was originally known as ARFGAP1, but that is now the name of a related but different gene. Uniprot ID: Q9NP61 NCBI: NP_055385.3 GeneID: 26286 Host: Goat Immunogen: Peptide from C Terminus of the protein sequence according to NP_055385.3; NP_001135765.1 Genename: ARFGAP3 AA Sequence: C-NGVVTSIQDRYGS Format: State: Liquid Ig fraction Purification: Ammonium sulphate precipitation followed by antigen affinity chromatography using the immunizing peptide Buffer System: Tris saline, 0.02% sodium azide, pH7.3 with 0.5% bovine serum albumin Applications: Peptide ELISA: Limit dilution 1:8000. Western blot: 1-3 µg/ml. -
Identification and Characterization of Tissue-Resident Memory T Cells in Humans Brahma Vencel Kumar
Identification and characterization of tissue-resident memory T cells in humans Brahma Vencel Kumar Submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy under the Executive Committee of the Graduate School of Arts and Sciences COLUMBIA UNIVERSITY 2018 ©2017 Brahma Vencel Kumar All rights reserved ABSTRACT Identification and characterization of tissue-resident memory T cells in humans Brahma Vencel Kumar Memory T cells are critical for maintaining lifelong immunity by protecting against reinfection with previously encountered pathogens. In recent years, a subset of memory T cells termed tissue-resident memory T cells (TRM) has emerged as the primary mediator of protection at many tissue sites. Numerous studies in mice have demonstrated that TRM accelerate pathogen clearance compared with other subsets of memory T cells. The defining characteristic of TRM is that they are retained within tissues and do not circulate in the blood. The lack of TRM in blood has proved to be a barrier for investigating the role of TRM in healthy humans. As a result, there are many outstanding questions about TRM biology in humans, including which phenotypic markers identify TRM, if TRM represent a unique memory subset, as well as defining transcriptional and functional characteristics of this subset. Through a unique collaboration with the local organ procurement agency, we obtained samples from >15 tissue sites from healthy organ donors of all ages. We found that the surface marker CD69 was expressed by memory CD4 + and CD8 + T cells in multiple tissues including spleen and other lymphoid tissues, lung, and intestines, but not in blood, suggesting that this marker may identify TRM in human tissues. -
BMC Cell Biology Biomed Central
BMC Cell Biology BioMed Central Research article Open Access Mutational analysis of βCOP (Sec26p) identifies an appendage domain critical for function Carol J DeRegis1, Peter B Rahl2, Gregory R Hoffman3, Richard A Cerione4,5 and Ruth N Collins*4,6 Address: 1Graduate Program in Comparative Biomedical Sciences, Cornell University, Ithaca NY 14853, USA, 2Graduate Program in Pharmacology, Cornell University, Ithaca, NY 14853, USA, 3Graduate Program in Biophysics, Cornell University, Ithaca, NY 14853, USA, 4Department of Molecular Medicine, Cornell University, Ithaca, NY 14853, USA, 5Department of Chemistry and Chemical Biology, Cornell University, Ithaca, NY 14853, USA and 6Department of Molecular Medicine, Cornell University, C4-109 Veterinary Medical Center, Ithaca, NY 14853, USA Email: Carol J DeRegis - [email protected]; Peter B Rahl - [email protected]; Gregory R Hoffman - [email protected]; Richard A Cerione - [email protected]; Ruth N Collins* - [email protected] * Corresponding author Published: 22 January 2008 Received: 2 June 2007 Accepted: 22 January 2008 BMC Cell Biology 2008, 9:3 doi:10.1186/1471-2121-9-3 This article is available from: http://www.biomedcentral.com/1471-2121/9/3 © 2008 De Regis et al; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Abstract Background: The appendage domain of the γCOP subunit of the COPI vesicle coat bears a striking structural resemblance to adaptin-family appendages despite limited primary sequence homology. -
Supplementary Materials
Supplementary materials Supplementary Table S1: MGNC compound library Ingredien Molecule Caco- Mol ID MW AlogP OB (%) BBB DL FASA- HL t Name Name 2 shengdi MOL012254 campesterol 400.8 7.63 37.58 1.34 0.98 0.7 0.21 20.2 shengdi MOL000519 coniferin 314.4 3.16 31.11 0.42 -0.2 0.3 0.27 74.6 beta- shengdi MOL000359 414.8 8.08 36.91 1.32 0.99 0.8 0.23 20.2 sitosterol pachymic shengdi MOL000289 528.9 6.54 33.63 0.1 -0.6 0.8 0 9.27 acid Poricoic acid shengdi MOL000291 484.7 5.64 30.52 -0.08 -0.9 0.8 0 8.67 B Chrysanthem shengdi MOL004492 585 8.24 38.72 0.51 -1 0.6 0.3 17.5 axanthin 20- shengdi MOL011455 Hexadecano 418.6 1.91 32.7 -0.24 -0.4 0.7 0.29 104 ylingenol huanglian MOL001454 berberine 336.4 3.45 36.86 1.24 0.57 0.8 0.19 6.57 huanglian MOL013352 Obacunone 454.6 2.68 43.29 0.01 -0.4 0.8 0.31 -13 huanglian MOL002894 berberrubine 322.4 3.2 35.74 1.07 0.17 0.7 0.24 6.46 huanglian MOL002897 epiberberine 336.4 3.45 43.09 1.17 0.4 0.8 0.19 6.1 huanglian MOL002903 (R)-Canadine 339.4 3.4 55.37 1.04 0.57 0.8 0.2 6.41 huanglian MOL002904 Berlambine 351.4 2.49 36.68 0.97 0.17 0.8 0.28 7.33 Corchorosid huanglian MOL002907 404.6 1.34 105 -0.91 -1.3 0.8 0.29 6.68 e A_qt Magnogrand huanglian MOL000622 266.4 1.18 63.71 0.02 -0.2 0.2 0.3 3.17 iolide huanglian MOL000762 Palmidin A 510.5 4.52 35.36 -0.38 -1.5 0.7 0.39 33.2 huanglian MOL000785 palmatine 352.4 3.65 64.6 1.33 0.37 0.7 0.13 2.25 huanglian MOL000098 quercetin 302.3 1.5 46.43 0.05 -0.8 0.3 0.38 14.4 huanglian MOL001458 coptisine 320.3 3.25 30.67 1.21 0.32 0.9 0.26 9.33 huanglian MOL002668 Worenine -
Datasheet: AHP697
Datasheet: AHP697 Description: GOAT ANTI HUMAN ARFGAP3 Specificity: ARFGAP3 Format: Purified Product Type: Polyclonal Antibody Isotype: Polyclonal IgG Quantity: 0.1 mg 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 Flow Cytometry Immunohistology - Frozen Immunohistology - Paraffin ELISA Immunoprecipitation Western Blotting 1ug/ml - 3ug/ml Where this antibody has not been tested for use in a particular technique this does not necessarily exclude its use in such procedures. Suggested working dilutions are given as a guide only. It is recommended that the user titrates the antibody for use in their own system using appropriate negative/positive controls. Target Species Human Species Cross Reacts with: Mouse Reactivity N.B. Antibody reactivity and working conditions may vary between species. Product Form Purified IgG - liquid Antiserum Preparation Antisera to ARFGAP3 were raised by repeated immunisations of goats with highly purified antigen. Purified IgG was prepared from whole serum by affinity chromatography. Buffer Solution TRIS buffered saline Preservative 0.02% Sodium Azide Stabilisers 0.5% Bovine Serum Albumin Approx. Protein IgG concentration 0.5 mg/ml Concentrations Immunogen Synthetic peptide NGVVTSIQDRYGS derived from C terminus of ARFGAP3 protein. Page 1 of 3 External Database Links UniProt: Q9NP61 Related reagents Entrez Gene: 26286 ARFGAP3 Related reagents Synonyms ARFGAP1 Specificity Goat anti ARFGAP3 recognises ARFGAP3 (ADP - ribosylation factor GTPase activating protein 3), originally described as ARFGAP1. -
The Arf1p Gtpase-Activating Protein Glo3p Executes Its Regulatory Function Through a Conserved Repeat Motif at Its C-Terminus
2604 Research Article The Arf1p GTPase-activating protein Glo3p executes its regulatory function through a conserved repeat motif at its C-terminus Natsuko Yahara1,*, Ken Sato1,2 and Akihiko Nakano1,3,‡ 1Molecular Membrane Biology Laboratory, RIKEN Discovery Research Institute and 2PRESTO, Japan Science and Technology Agency, Hirosawa, Wako, Saitama 351-0198, Japan 3Department of Biological Sciences, Graduate School of Science, University of Tokyo, Hongo, Bunkyo-ku, Tokyo 113-0033, Japan *Present address: Department of Biochemistry, University of Geneva, Sciences II, Geneva, Switzerland ‡Author for correspondence (e-mail: [email protected]) Accepted 21 March 2006 Journal of Cell Science 119, 2604-2612 Published by The Company of Biologists 2006 doi:10.1242/jcs.02997 Summary ADP-ribosylation factors (Arfs), key regulators of ArfGAP, Gcs1p, we have shown that the non-catalytic C- intracellular membrane traffic, are known to exert multiple terminal region of Glo3p is required for the suppression of roles in vesicular transport. We previously isolated eight the growth defect in the arf1 ts mutants. Interestingly, temperature-sensitive (ts) mutants of the yeast ARF1 gene, Glo3p and its homologues from other eukaryotes harbor a which showed allele-specific defects in protein transport, well-conserved repeated ISSxxxFG sequence near the C- and classified them into three groups of intragenic terminus, which is not found in Gcs1p and its homologues. complementation. In this study, we show that the We name this region the Glo3 motif and present evidence overexpression of Glo3p, one of the GTPase-activating that the motif is required for the function of Glo3p in vivo. proteins of Arf1p (ArfGAP), suppresses the ts growth of a particular group of the arf1 mutants (arf1-16 and arf1-17). -
Views See [6,25,26])
Wirthlin et al. BMC Genomics 2014, 15:1082 http://www.biomedcentral.com/1471-2164/15/1082 RESEARCH ARTICLE Open Access Comparative genomics reveals molecular features unique to the songbird lineage Morgan Wirthlin1, Peter V Lovell1, Erich D Jarvis2 and Claudio V Mello1* Abstract Background: Songbirds (oscine Passeriformes) are among the most diverse and successful vertebrate groups, comprising almost half of all known bird species. Identifying the genomic innovations that might be associated with this success, as well as with characteristic songbird traits such as vocal learning and the brain circuits that underlie this behavior, has proven difficult, in part due to the small number of avian genomes available until recently. Here we performed a comparative analysis of 48 avian genomes to identify genomic features that are unique to songbirds, as well as an initial assessment of function by investigating their tissue distribution and predicted protein domain structure. Results: Using BLAT alignments and gene synteny analysis, we curated a large set of Ensembl gene models that were annotated as novel or duplicated in the most commonly studied songbird, the Zebra finch (Taeniopygia guttata), and then extended this analysis to 47 additional avian and 4 non-avian genomes. We identified 10 novel genes uniquely present in songbird genomes. A refined map of chromosomal synteny disruptions in the Zebra finch genome revealed that the majority of these novel genes localized to regions of genomic instability associated with apparent chromosomal breakpoints. Analyses of in situ hybridization and RNA-seq data revealed that a subset of songbird-unique genes is expressed in the brain and/or other tissues, and that 2 of these (YTHDC2L1 and TMRA) are highly differentially expressed in vocal learning-associated nuclei relative to the rest of the brain. -
Figure S1. HAEC ROS Production and ML090 NOX5-Inhibition
Figure S1. HAEC ROS production and ML090 NOX5-inhibition. (a) Extracellular H2O2 production in HAEC treated with ML090 at different concentrations and 24 h after being infected with GFP and NOX5-β adenoviruses (MOI 100). **p< 0.01, and ****p< 0.0001 vs control NOX5-β-infected cells (ML090, 0 nM). Results expressed as mean ± SEM. Fold increase vs GFP-infected cells with 0 nM of ML090. n= 6. (b) NOX5-β overexpression and DHE oxidation in HAEC. Representative images from three experiments are shown. Intracellular superoxide anion production of HAEC 24 h after infection with GFP and NOX5-β adenoviruses at different MOIs treated or not with ML090 (10 nM). MOI: Multiplicity of infection. Figure S2. Ontology analysis of HAEC infected with NOX5-β. Ontology analysis shows that the response to unfolded protein is the most relevant. Figure S3. UPR mRNA expression in heart of infarcted transgenic mice. n= 12-13. Results expressed as mean ± SEM. Table S1: Altered gene expression due to NOX5-β expression at 12 h (bold, highlighted in yellow). N12hvsG12h N18hvsG18h N24hvsG24h GeneName GeneDescription TranscriptID logFC p-value logFC p-value logFC p-value family with sequence similarity NM_052966 1.45 1.20E-17 2.44 3.27E-19 2.96 6.24E-21 FAM129A 129. member A DnaJ (Hsp40) homolog. NM_001130182 2.19 9.83E-20 2.94 2.90E-19 3.01 1.68E-19 DNAJA4 subfamily A. member 4 phorbol-12-myristate-13-acetate- NM_021127 0.93 1.84E-12 2.41 1.32E-17 2.69 1.43E-18 PMAIP1 induced protein 1 E2F7 E2F transcription factor 7 NM_203394 0.71 8.35E-11 2.20 2.21E-17 2.48 1.84E-18 DnaJ (Hsp40) homolog. -
Functional Analysis of Structural Variation in the 2D and 3D Human Genome
FUNCTIONAL ANALYSIS OF STRUCTURAL VARIATION IN THE 2D AND 3D HUMAN GENOME by Conor Mitchell Liam Nodzak A dissertation submitted to the faculty of The University of North Carolina at Charlotte in partial fulfillment of the requirements for the degree of Doctor of Philosophy in Bioinformatics and Computational Biology Charlotte 2019 Approved by: Dr. Xinghua Mindy Shi Dr. Rebekah Rogers Dr. Jun-tao Guo Dr. Adam Reitzel ii c 2019 Conor Mitchell Liam Nodzak ALL RIGHTS RESERVED iii ABSTRACT CONOR MITCHELL LIAM NODZAK. Functional analysis of structural variation in the 2D and 3D human genome. (Under the direction of DR. XINGHUA MINDY SHI) The human genome consists of over 3 billion nucleotides that have an average distance of 3.4 Angstroms between each base, which equates to over two meters of DNA contained within the 125 µm3 volume diploid cell nuclei. The dense compaction of chromatin by the supercoiling of DNA forms distinct architectural modules called topologically associated domains (TADs), which keep protein-coding genes, noncoding RNAs and epigenetic regulatory elements in close nuclear space. It has recently been shown that these conserved chromatin structures may contribute to tissue-specific gene expression through the encapsulation of genes and cis-regulatory elements, and mutations that affect TADs can lead to developmental disorders and some forms of cancer. At the population-level, genomic structural variation contributes more to cumulative genetic difference than any other class of mutation, yet much remains to be studied as to how structural variation affects TADs. Here, we study the func- tional effects of structural variants (SVs) through the analysis of chromatin topology and gene activity for three trio families sampled from genetically diverse popula- tions from the Human Genome Structural Variation Consortium. -
A Transcriptional Signature of Postmitotic Maintenance in Neural Tissues
Neurobiology of Aging 74 (2019) 147e160 Contents lists available at ScienceDirect Neurobiology of Aging journal homepage: www.elsevier.com/locate/neuaging Postmitotic cell longevityeassociated genes: a transcriptional signature of postmitotic maintenance in neural tissues Atahualpa Castillo-Morales a,b, Jimena Monzón-Sandoval a,b, Araxi O. Urrutia b,c,*, Humberto Gutiérrez a,** a School of Life Sciences, University of Lincoln, Lincoln, UK b Milner Centre for Evolution, Department of Biology and Biochemistry, University of Bath, Bath, UK c Instituto de Ecología, Universidad Nacional Autónoma de México, Ciudad de México, Mexico article info abstract Article history: Different cell types have different postmitotic maintenance requirements. Nerve cells, however, are Received 11 April 2018 unique in this respect as they need to survive and preserve their functional complexity for the entire Received in revised form 3 October 2018 lifetime of the organism, and failure at any level of their supporting mechanisms leads to a wide range of Accepted 11 October 2018 neurodegenerative conditions. Whether these differences across tissues arise from the activation of Available online 19 October 2018 distinct cell typeespecific maintenance mechanisms or the differential activation of a common molecular repertoire is not known. To identify the transcriptional signature of postmitotic cellular longevity (PMCL), Keywords: we compared whole-genome transcriptome data from human tissues ranging in longevity from 120 days Neural maintenance Cell longevity to over 70 years and found a set of 81 genes whose expression levels are closely associated with Transcriptional signature increased cell longevity. Using expression data from 10 independent sources, we found that these genes Functional genomics are more highly coexpressed in longer-living tissues and are enriched in specific biological processes and transcription factor targets compared with randomly selected gene samples. -
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.