A Transcriptomic Atlas of Aged Human Microglia
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Edinburgh Research Explorer
Edinburgh Research Explorer International Union of Basic and Clinical Pharmacology. LXXXVIII. G protein-coupled receptor list Citation for published version: Davenport, AP, Alexander, SPH, Sharman, JL, Pawson, AJ, Benson, HE, Monaghan, AE, Liew, WC, Mpamhanga, CP, Bonner, TI, Neubig, RR, Pin, JP, Spedding, M & Harmar, AJ 2013, 'International Union of Basic and Clinical Pharmacology. LXXXVIII. G protein-coupled receptor list: recommendations for new pairings with cognate ligands', Pharmacological reviews, vol. 65, no. 3, pp. 967-86. https://doi.org/10.1124/pr.112.007179 Digital Object Identifier (DOI): 10.1124/pr.112.007179 Link: Link to publication record in Edinburgh Research Explorer Document Version: Publisher's PDF, also known as Version of record Published In: Pharmacological reviews Publisher Rights Statement: U.S. Government work not protected by U.S. copyright General rights Copyright for the publications made accessible via the Edinburgh Research Explorer is retained by the author(s) and / or other copyright owners and it is a condition of accessing these publications that users recognise and abide by the legal requirements associated with these rights. Take down policy The University of Edinburgh has made every reasonable effort to ensure that Edinburgh Research Explorer content complies with UK legislation. If you believe that the public display of this file breaches copyright please contact [email protected] providing details, and we will remove access to the work immediately and investigate your claim. Download date: 02. Oct. 2021 1521-0081/65/3/967–986$25.00 http://dx.doi.org/10.1124/pr.112.007179 PHARMACOLOGICAL REVIEWS Pharmacol Rev 65:967–986, July 2013 U.S. -
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Patterns of DNA methylation on the human X chromosome and use in analyzing X-chromosome inactivation by Allison Marie Cotton B.Sc., The University of Guelph, 2005 A THESIS SUBMITTED IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF DOCTOR OF PHILOSOPHY in The Faculty of Graduate Studies (Medical Genetics) THE UNIVERSITY OF BRITISH COLUMBIA (Vancouver) January 2012 © Allison Marie Cotton, 2012 Abstract The process of X-chromosome inactivation achieves dosage compensation between mammalian males and females. In females one X chromosome is transcriptionally silenced through a variety of epigenetic modifications including DNA methylation. Most X-linked genes are subject to X-chromosome inactivation and only expressed from the active X chromosome. On the inactive X chromosome, the CpG island promoters of genes subject to X-chromosome inactivation are methylated in their promoter regions, while genes which escape from X- chromosome inactivation have unmethylated CpG island promoters on both the active and inactive X chromosomes. The first objective of this thesis was to determine if the DNA methylation of CpG island promoters could be used to accurately predict X chromosome inactivation status. The second objective was to use DNA methylation to predict X-chromosome inactivation status in a variety of tissues. A comparison of blood, muscle, kidney and neural tissues revealed tissue-specific X-chromosome inactivation, in which 12% of genes escaped from X-chromosome inactivation in some, but not all, tissues. X-linked DNA methylation analysis of placental tissues predicted four times higher escape from X-chromosome inactivation than in any other tissue. Despite the hypomethylation of repetitive elements on both the X chromosome and the autosomes, no changes were detected in the frequency or intensity of placental Cot-1 holes. -
Análise Integrativa De Perfis Transcricionais De Pacientes Com
UNIVERSIDADE DE SÃO PAULO FACULDADE DE MEDICINA DE RIBEIRÃO PRETO PROGRAMA DE PÓS-GRADUAÇÃO EM GENÉTICA ADRIANE FEIJÓ EVANGELISTA Análise integrativa de perfis transcricionais de pacientes com diabetes mellitus tipo 1, tipo 2 e gestacional, comparando-os com manifestações demográficas, clínicas, laboratoriais, fisiopatológicas e terapêuticas Ribeirão Preto – 2012 ADRIANE FEIJÓ EVANGELISTA Análise integrativa de perfis transcricionais de pacientes com diabetes mellitus tipo 1, tipo 2 e gestacional, comparando-os com manifestações demográficas, clínicas, laboratoriais, fisiopatológicas e terapêuticas Tese apresentada à Faculdade de Medicina de Ribeirão Preto da Universidade de São Paulo para obtenção do título de Doutor em Ciências. Área de Concentração: Genética Orientador: Prof. Dr. Eduardo Antonio Donadi Co-orientador: Prof. Dr. Geraldo A. S. Passos Ribeirão Preto – 2012 AUTORIZO A REPRODUÇÃO E DIVULGAÇÃO TOTAL OU PARCIAL DESTE TRABALHO, POR QUALQUER MEIO CONVENCIONAL OU ELETRÔNICO, PARA FINS DE ESTUDO E PESQUISA, DESDE QUE CITADA A FONTE. FICHA CATALOGRÁFICA Evangelista, Adriane Feijó Análise integrativa de perfis transcricionais de pacientes com diabetes mellitus tipo 1, tipo 2 e gestacional, comparando-os com manifestações demográficas, clínicas, laboratoriais, fisiopatológicas e terapêuticas. Ribeirão Preto, 2012 192p. Tese de Doutorado apresentada à Faculdade de Medicina de Ribeirão Preto da Universidade de São Paulo. Área de Concentração: Genética. Orientador: Donadi, Eduardo Antonio Co-orientador: Passos, Geraldo A. 1. Expressão gênica – microarrays 2. Análise bioinformática por module maps 3. Diabetes mellitus tipo 1 4. Diabetes mellitus tipo 2 5. Diabetes mellitus gestacional FOLHA DE APROVAÇÃO ADRIANE FEIJÓ EVANGELISTA Análise integrativa de perfis transcricionais de pacientes com diabetes mellitus tipo 1, tipo 2 e gestacional, comparando-os com manifestações demográficas, clínicas, laboratoriais, fisiopatológicas e terapêuticas. -
Identification of Potential Key Genes and Pathway Linked with Sporadic Creutzfeldt-Jakob Disease Based on Integrated Bioinformatics Analyses
medRxiv preprint doi: https://doi.org/10.1101/2020.12.21.20248688; this version posted December 24, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. All rights reserved. No reuse allowed without permission. Identification of potential key genes and pathway linked with sporadic Creutzfeldt-Jakob disease based on integrated bioinformatics analyses Basavaraj Vastrad1, Chanabasayya Vastrad*2 , Iranna Kotturshetti 1. Department of Biochemistry, Basaveshwar College of Pharmacy, Gadag, Karnataka 582103, India. 2. Biostatistics and Bioinformatics, Chanabasava Nilaya, Bharthinagar, Dharwad 580001, Karanataka, India. 3. Department of Ayurveda, Rajiv Gandhi Education Society`s Ayurvedic Medical College, Ron, Karnataka 562209, India. * Chanabasayya Vastrad [email protected] Ph: +919480073398 Chanabasava Nilaya, Bharthinagar, Dharwad 580001 , Karanataka, India NOTE: This preprint reports new research that has not been certified by peer review and should not be used to guide clinical practice. medRxiv preprint doi: https://doi.org/10.1101/2020.12.21.20248688; this version posted December 24, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. All rights reserved. No reuse allowed without permission. Abstract Sporadic Creutzfeldt-Jakob disease (sCJD) is neurodegenerative disease also called prion disease linked with poor prognosis. The aim of the current study was to illuminate the underlying molecular mechanisms of sCJD. The mRNA microarray dataset GSE124571 was downloaded from the Gene Expression Omnibus database. Differentially expressed genes (DEGs) were screened. -
G Protein-Coupled Receptors
S.P.H. Alexander et al. The Concise Guide to PHARMACOLOGY 2015/16: G protein-coupled receptors. British Journal of Pharmacology (2015) 172, 5744–5869 THE CONCISE GUIDE TO PHARMACOLOGY 2015/16: G protein-coupled receptors Stephen PH Alexander1, Anthony P Davenport2, Eamonn Kelly3, Neil Marrion3, John A Peters4, Helen E Benson5, Elena Faccenda5, Adam J Pawson5, Joanna L Sharman5, Christopher Southan5, Jamie A Davies5 and CGTP Collaborators 1School of Biomedical Sciences, University of Nottingham Medical School, Nottingham, NG7 2UH, UK, 2Clinical Pharmacology Unit, University of Cambridge, Cambridge, CB2 0QQ, UK, 3School of Physiology and Pharmacology, University of Bristol, Bristol, BS8 1TD, UK, 4Neuroscience Division, Medical Education Institute, Ninewells Hospital and Medical School, University of Dundee, Dundee, DD1 9SY, UK, 5Centre for Integrative Physiology, University of Edinburgh, Edinburgh, EH8 9XD, UK Abstract The Concise Guide to PHARMACOLOGY 2015/16 provides concise overviews of the key properties of over 1750 human drug targets with their pharmacology, plus links to an open access knowledgebase of drug targets and their ligands (www.guidetopharmacology.org), which provides more detailed views of target and ligand properties. The full contents can be found at http://onlinelibrary.wiley.com/doi/ 10.1111/bph.13348/full. G protein-coupled receptors are one of the eight major pharmacological targets into which the Guide is divided, with the others being: ligand-gated ion channels, voltage-gated ion channels, other ion channels, nuclear hormone receptors, catalytic receptors, enzymes and transporters. These are presented with nomenclature guidance and summary information on the best available pharmacological tools, alongside key references and suggestions for further reading. -
Remodeling Adipose Tissue Through in Silico Modulation of Fat Storage For
Chénard et al. BMC Systems Biology (2017) 11:60 DOI 10.1186/s12918-017-0438-9 RESEARCHARTICLE Open Access Remodeling adipose tissue through in silico modulation of fat storage for the prevention of type 2 diabetes Thierry Chénard2, Frédéric Guénard3, Marie-Claude Vohl3,4, André Carpentier5, André Tchernof4,6 and Rafael J. Najmanovich1* Abstract Background: Type 2 diabetes is one of the leading non-infectious diseases worldwide and closely relates to excess adipose tissue accumulation as seen in obesity. Specifically, hypertrophic expansion of adipose tissues is related to increased cardiometabolic risk leading to type 2 diabetes. Studying mechanisms underlying adipocyte hypertrophy could lead to the identification of potential targets for the treatment of these conditions. Results: We present iTC1390adip, a highly curated metabolic network of the human adipocyte presenting various improvements over the previously published iAdipocytes1809. iTC1390adip contains 1390 genes, 4519 reactions and 3664 metabolites. We validated the network obtaining 92.6% accuracy by comparing experimental gene essentiality in various cell lines to our predictions of biomass production. Using flux balance analysis under various test conditions, we predict the effect of gene deletion on both lipid droplet and biomass production, resulting in the identification of 27 genes that could reduce adipocyte hypertrophy. We also used expression data from visceral and subcutaneous adipose tissues to compare the effect of single gene deletions between adipocytes from each -
G Protein‐Coupled Receptors
S.P.H. Alexander et al. The Concise Guide to PHARMACOLOGY 2019/20: G protein-coupled receptors. British Journal of Pharmacology (2019) 176, S21–S141 THE CONCISE GUIDE TO PHARMACOLOGY 2019/20: G protein-coupled receptors Stephen PH Alexander1 , Arthur Christopoulos2 , Anthony P Davenport3 , Eamonn Kelly4, Alistair Mathie5 , John A Peters6 , Emma L Veale5 ,JaneFArmstrong7 , Elena Faccenda7 ,SimonDHarding7 ,AdamJPawson7 , Joanna L Sharman7 , Christopher Southan7 , Jamie A Davies7 and CGTP Collaborators 1School of Life Sciences, University of Nottingham Medical School, Nottingham, NG7 2UH, UK 2Monash Institute of Pharmaceutical Sciences and Department of Pharmacology, Monash University, Parkville, Victoria 3052, Australia 3Clinical Pharmacology Unit, University of Cambridge, Cambridge, CB2 0QQ, UK 4School of Physiology, Pharmacology and Neuroscience, University of Bristol, Bristol, BS8 1TD, UK 5Medway School of Pharmacy, The Universities of Greenwich and Kent at Medway, Anson Building, Central Avenue, Chatham Maritime, Chatham, Kent, ME4 4TB, UK 6Neuroscience Division, Medical Education Institute, Ninewells Hospital and Medical School, University of Dundee, Dundee, DD1 9SY, UK 7Centre for Discovery Brain Sciences, University of Edinburgh, Edinburgh, EH8 9XD, UK Abstract The Concise Guide to PHARMACOLOGY 2019/20 is the fourth in this series of biennial publications. The Concise Guide provides concise overviews of the key properties of nearly 1800 human drug targets with an emphasis on selective pharmacology (where available), plus links to the open access knowledgebase source of drug targets and their ligands (www.guidetopharmacology.org), which provides more detailed views of target and ligand properties. Although the Concise Guide represents approximately 400 pages, the material presented is substantially reduced compared to information and links presented on the website. -
Supplementary Materials
Supplementary Materials Supplemental Figure S1. Distinct difference in expression of 576 sensome genes comparing cortex versus microglia. (A) This heatmap shows all 576 sensome candidate genes ordered by DE and with the left column shows if the gene is present in the “Hickman et al. sensome” Supplemental Figure S2. Mouse sensome and human sensome genes categorized by group. (A) Bar graph showing the number of mouse and human sensome genes per group (Cell-Cell Interactions, Chemokine and related receptors, Cytokine receptors, ECM receptors, Endogenous ligands receptors, sensors and transporters, Fc receptors, Pattern recognition and related receptors, Potential sensors but no known ligands and Purinergic and related receptors). Supplementary Figure S3. Overlap of ligands recognized by microglia sensome (A) Overlap between the ligands of the receptors from respectively human and mouse core sensome was shown using Venn Diagrams. (B) Ligands of human and mouse receptors categorized in groups (Glycoproteins, Cytokines, Immunoglobulin, Amino acids, Carbohydrates, Electrolytes, Lipopeptides, Chemokines, Neuraminic acids, Nucleic acids, Receptors, Lipids, Fatty acids, Leukotrienes, Hormones, Steroids and Phospholipids) and spread of different groups shown as parts of whole again highlighting that the distribution of ligands what the human and mouse sensome genes can sense (Categorization of ligands in Supplementary Table S1). Supplementary Figure S4. Microglia core sensome expression during aging. (A) Two-log fold change of microglia core sensome genes in aging mice derived from Holtman et al. [12]. (B) Accelerated aging model (ERCC1), with impaired DNA repair mechanism, shows changes of microglia core sensome expression [12]. (C) Microglia core sensome expression during aging in human derived from Olah et al. -
Connecting Myelin-Related and Synaptic Dysfunction In
www.nature.com/scientificreports OPEN Connecting myelin-related and synaptic dysfunction in schizophrenia with SNP-rich Received: 24 October 2016 Accepted: 27 February 2017 gene expression hubs Published: 07 April 2017 Hedi Hegyi Combining genome-wide mapping of SNP-rich regions in schizophrenics and gene expression data in all brain compartments across the human life span revealed that genes with promoters most frequently mutated in schizophrenia are expression hubs interacting with far more genes than the rest of the genome. We summed up the differentially methylated “expression neighbors” of genes that fall into one of 108 distinct schizophrenia-associated loci with high number of SNPs. Surprisingly, the number of expression neighbors of the genes in these loci were 35 times higher for the positively correlating genes (32 times higher for the negatively correlating ones) than for the rest of the ~16000 genes. While the genes in the 108 loci have little known impact in schizophrenia, we identified many more known schizophrenia-related important genes with a high degree of connectedness (e.g. MOBP, SYNGR1 and DGCR6), validating our approach. Both the most connected positive and negative hubs affected synapse-related genes the most, supporting the synaptic origin of schizophrenia. At least half of the top genes in both the correlating and anti-correlating categories are cancer-related, including oncogenes (RRAS and ALDOA), providing further insight into the observed inverse relationship between the two diseases. Gene expression correlation, protein-protein interaction and other high-throughput experiments in the post-genomic era have revealed that genes tend to form complex, scale-free networks where most genes have a few connections with others and a few have a high number of interactions, commonly referred to as “hubs”, estab- lishing them as important central genes in these gene networks1. -
Normalized Expression Values *
Normalized expression values 0.0 0.2 0.4 0.6 0.8 1.0 1.2 PLCG1 * T CD5 MP T B TCF7 cDC UBASH3A BCL11B C5AR1 * MP TLR4 CXCR5 B CD79B VPREB3 XCR1 CADM1 BEND5 * ARGHAP22 * cDC CIITA ZBTB46 FLT3 PLEKHA5 Figure S1. qPCR analysis of the core gene expression signature of cDC, MP, B and T cells in the chicken cell suBsets. RNA from cDC, MP, T and B cells of 2 disUnct pools of 4 chicken spleen was subjected to qPCR detecUon of the core gene expression signatures of immune cell subsets established in Fig. 3 and of transcripts from the mouse and human gene subset selected compendia that could not be detected on the array due to defecUve probes, i.e. ARGHAP22, BEND5, C5AR1, and PLCG1 (labeled by a star on the figure). Data are represented as the mean and SD of relave gene expression levels normalized to GAPDH expression and the maximal expression across the cell types was set to 1 (independent experimental duplicates). B cell T cell cDC Monocyte/MP Chicken Human Mouse Figure S2. Unsupervised hierarchical clustering of orthologous immune response genes across chicken, human and mouse reveals globally conserved clusters of lymphoïd- specific and myeloïd- specific genes. Heatmap of cross-normalized expression profiles for immune response genes present on all three species arrays and regulated at least 2 folds across all cell suBsets, including chicken B cells (c_B), T cells (c_CD3), MP (c_MP) and cDC (c_cDC), human B cells (h_B), T cells (h_CD4_T and h_CD8_T), monocyte-derived MP (h_MoMP), peripheral blood mononucleated cell-derived MP (h_PBMC_MP), non-classical monocytes (h_non- classical_MO), classical monocytes (h_classical_MO), BDCA3+ cDC (h_BDCA3), BDCA1+ cDC (h_BDCA1), murine B cells (m_B), T cells (m_CD4_T and m_CD8_T), peritoneal cavity MP (m_PC_MPII-480HI), lung MP (m_LU_MP), non-classical monocytes (m_non-classical_MO), classical monocytes (m_classical_MO), splenic CD8α+ cDC (m_SP_DC1), suBcutaneous lymph node CD8α+ cDC (m_LN_DC1), splenic CD11B+ cDC (m_SP_DC2), suBcutaneous lymph node CD11B+ cDC (m_LN_DC2). -
RENBP (Human) ELISA Kit
RENBP (Human) ELISA Kit Catalog # : KA0498 規格 : [ 1 Kit ] List All Specification Application Image Product RENBP (Human) ELISA Kit is a sandwich enzyme immunoassay for the Quantification Description: quantitative measurement of human RENBP. Calibration 0.031 to 2 ug/mL Range: Limit of 0.008 ug/mL Detection: Reactivity: Human Quality Control Standard curve Testing: The standard curve is for the purpose of illustration only and should not be used to calculate unknowns. A standard curve should be generated each time the assay is performed. Storage Store components of the kit at 4°C or -20°C as described in the Instruction: protocol. Protocol: Protocol Download MSDS: Download Suitable Cell Culture Supernatant, Urine Sample: Sample 50 uL Volume: Label: Biotin-conjugate Detection Colorimetric Method: Page 1 of 3 2018/3/6 Intra-Assay: 4.20% Inter-Assay: 7.10% Spiking 98.50% Recovery: Regulation For research use only (RUO) Status: Publication Reference 1. Urinary retinol excretion in children with acute watery diarrhoea. Mitra AK, Wahed MA, Chowdhury AK, Stephensen CB.J Health Popul Nutr. 2002 Mar;20(1):12-7. 2. Urinary protein excretion in Type 2 diabetes with complications. Hong CY, Chia KS, Ling SL.J Diabetes Complications. 2000 Sep-Oct;14(5):259-65. 3. Assessment of renal function in patients with multiple myeloma: the role of urinary proteins. Corso A, Serricchio G, Zappasodi P, Klersy C, Bosoni T, Moratti R, Castagnola C, Lazzarino M, Pagnucco G, Bernasconi C.Ann Hematol. 1999 Aug;78(8):371-5. Applications Quantification Gene Information Entrez GeneID: 5973 Gene Name: RENBP Gene Alias: RBP,RNBP Gene renin binding protein Description: Omim ID: 312420 Gene Ontology: Hyperlink Gene Summary: The gene product inhibits renin activity by forming a dimer with renin, a complex known as high molecular weight renin. -
Oxygenated Fatty Acids Enhance Hematopoiesis Via the Receptor GPR132
Oxygenated Fatty Acids Enhance Hematopoiesis via the Receptor GPR132 The Harvard community has made this article openly available. Please share how this access benefits you. Your story matters Citation Lahvic, Jamie L. 2017. Oxygenated Fatty Acids Enhance Hematopoiesis via the Receptor GPR132. Doctoral dissertation, Harvard University, Graduate School of Arts & Sciences. Citable link http://nrs.harvard.edu/urn-3:HUL.InstRepos:42061504 Terms of Use This article was downloaded from Harvard University’s DASH repository, and is made available under the terms and conditions applicable to Other Posted Material, as set forth at http:// nrs.harvard.edu/urn-3:HUL.InstRepos:dash.current.terms-of- use#LAA Oxygenated Fatty Acids Enhance Hematopoiesis via the Receptor GPR132 A dissertation presented by Jamie L. Lahvic to The Division of Medical Sciences in partial fulfillment of the requirements for the degree of Doctor of Philosophy in the subject of Developmental and Regenerative Biology Harvard University Cambridge, Massachusetts May 2017 © 2017 Jamie L. Lahvic All rights reserved. Dissertation Advisor: Leonard I. Zon Jamie L. Lahvic Oxygenated Fatty Acids Enhance Hematopoiesis via the Receptor GPR132 Abstract After their specification in early development, hematopoietic stem cells (HSCs) maintain the entire blood system throughout adulthood as well as upon transplantation. The processes of HSC specification, renewal, and homing to the niche are regulated by protein, as well as lipid signaling molecules. A screen for chemical enhancers of marrow transplant in the zebrafish identified the endogenous lipid signaling molecule 11,12-epoxyeicosatrienoic acid (11,12-EET). EET has vasodilatory properties, but had no previously described function on HSCs.