List of 1124 Genes Whose Binding to Eif4e Was Induced by Radiation
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Podocyte Specific Knockdown of Klf15 in Podocin-Cre Klf15flox/Flox Mice Was Confirmed
SUPPLEMENTARY FIGURE LEGENDS Supplementary Figure 1: Podocyte specific knockdown of Klf15 in Podocin-Cre Klf15flox/flox mice was confirmed. (A) Primary glomerular epithelial cells (PGECs) were isolated from 12-week old Podocin-Cre Klf15flox/flox and Podocin-Cre Klf15+/+ mice and cultured at 37°C for 1 week. Real-time PCR was performed for Nephrin, Podocin, Synaptopodin, and Wt1 mRNA expression (n=6, ***p<0.001, Mann-Whitney test). (B) Real- time PCR was performed for Klf15 mRNA expression (n=6, *p<0.05, Mann-Whitney test). (C) Protein was also extracted and western blot analysis for Klf15 was performed. The representative blot of three independent experiments is shown in the top panel. The bottom panel shows the quantification of Klf15 by densitometry (n=3, *p<0.05, Mann-Whitney test). (D) Immunofluorescence staining for Klf15 and Wt1 was performed in 12-week old Podocin-Cre Klf15flox/flox and Podocin-Cre Klf15+/+ mice. Representative images from four mice in each group are shown in the left panel (X 20). Arrows show colocalization of Klf15 and Wt1. Arrowheads show a lack of colocalization. Asterisk demonstrates nonspecific Wt1 staining. “R” represents autofluorescence from RBCs. In the right panel, a total of 30 glomeruli were selected in each mouse and quantification of Klf15 staining in the podocytes was determined by the ratio of Klf15+ and Wt1+ cells to Wt1+ cells (n=6 mice, **p<0.01, unpaired t test). Supplementary Figure 2: LPS treated Podocin-Cre Klf15flox/flox mice exhibit a lack of recovery in proteinaceous casts and tubular dilatation after DEX administration. -
TRIM32 Is an E3 Ubiquitin Ligase for Dysbindin
Human Molecular Genetics, 2009, Vol. 18, No. 13 2344–2358 doi:10.1093/hmg/ddp167 Advance Access published on April 6, 2009 TRIM32 is an E3 ubiquitin ligase for dysbindin Matthew Locke1,2, Caroline L. Tinsley1, Matthew A. Benson2,{ and Derek J. Blake1,Ã 1Department of Psychological Medicine, Cardiff University, Henry Wellcome Building for Biomedical Research in Wales, Heath Park, Cardiff, CF14 4XN, UK and 2Department of Pharmacology, University of Oxford, Mansfield Road, Oxford OX1 3QT, UK Received December 15, 2008; Revised and Accepted April 2, 2009 Mutations in the gene encoding tripartite motif protein 32 (TRIM32) cause two seemingly diverse diseases: limb-girdle muscular dystrophy type 2H (LGMD2H) or sarcotubular myopathy (STM) and Bardet–Biedl syndrome type 11(BBS11). Although TRIM32 is involved in protein ubiquitination, its substrates and the molecular consequences of disease-causing mutations are poorly understood. In this paper, we show that Downloaded from TRIM32 is a widely expressed ubiquitin ligase that is localized to the Z-line in skeletal muscle. Using the yeast two-hybrid system, we found that TRIM32 binds and ubiquitinates dysbindin, a protein implicated in the genetic aetiology of schizophrenia, augmenting its degradation. Small-interfering RNA-mediated knock-down of TRIM32 in myoblasts resulted in elevated levels of dysbindin. Importantly, the LGMD2H/ STM-associated TRIM32 mutations, D487N and R394H impair ubiquitin ligase activity towards dysbindin http://hmg.oxfordjournals.org/ and were mislocalized in heterologous cells. These mutants were able to self-associate and also co-immuno- precipitated with wild-type TRIM32 in transfected cells. Furthermore, the D487N mutant could bind to both dysbindin and its E2 enzyme but was defective in monoubiquitination. -
Table 2. Significant
Table 2. Significant (Q < 0.05 and |d | > 0.5) transcripts from the meta-analysis Gene Chr Mb Gene Name Affy ProbeSet cDNA_IDs d HAP/LAP d HAP/LAP d d IS Average d Ztest P values Q-value Symbol ID (study #5) 1 2 STS B2m 2 122 beta-2 microglobulin 1452428_a_at AI848245 1.75334941 4 3.2 4 3.2316485 1.07398E-09 5.69E-08 Man2b1 8 84.4 mannosidase 2, alpha B1 1416340_a_at H4049B01 3.75722111 3.87309653 2.1 1.6 2.84852656 5.32443E-07 1.58E-05 1110032A03Rik 9 50.9 RIKEN cDNA 1110032A03 gene 1417211_a_at H4035E05 4 1.66015788 4 1.7 2.82772795 2.94266E-05 0.000527 NA 9 48.5 --- 1456111_at 3.43701477 1.85785922 4 2 2.8237185 9.97969E-08 3.48E-06 Scn4b 9 45.3 Sodium channel, type IV, beta 1434008_at AI844796 3.79536664 1.63774235 3.3 2.3 2.75319499 1.48057E-08 6.21E-07 polypeptide Gadd45gip1 8 84.1 RIKEN cDNA 2310040G17 gene 1417619_at 4 3.38875643 1.4 2 2.69163229 8.84279E-06 0.0001904 BC056474 15 12.1 Mus musculus cDNA clone 1424117_at H3030A06 3.95752801 2.42838452 1.9 2.2 2.62132809 1.3344E-08 5.66E-07 MGC:67360 IMAGE:6823629, complete cds NA 4 153 guanine nucleotide binding protein, 1454696_at -3.46081884 -4 -1.3 -1.6 -2.6026947 8.58458E-05 0.0012617 beta 1 Gnb1 4 153 guanine nucleotide binding protein, 1417432_a_at H3094D02 -3.13334396 -4 -1.6 -1.7 -2.5946297 1.04542E-05 0.0002202 beta 1 Gadd45gip1 8 84.1 RAD23a homolog (S. -
Seq2pathway Vignette
seq2pathway Vignette Bin Wang, Xinan Holly Yang, Arjun Kinstlick May 19, 2021 Contents 1 Abstract 1 2 Package Installation 2 3 runseq2pathway 2 4 Two main functions 3 4.1 seq2gene . .3 4.1.1 seq2gene flowchart . .3 4.1.2 runseq2gene inputs/parameters . .5 4.1.3 runseq2gene outputs . .8 4.2 gene2pathway . 10 4.2.1 gene2pathway flowchart . 11 4.2.2 gene2pathway test inputs/parameters . 11 4.2.3 gene2pathway test outputs . 12 5 Examples 13 5.1 ChIP-seq data analysis . 13 5.1.1 Map ChIP-seq enriched peaks to genes using runseq2gene .................... 13 5.1.2 Discover enriched GO terms using gene2pathway_test with gene scores . 15 5.1.3 Discover enriched GO terms using Fisher's Exact test without gene scores . 17 5.1.4 Add description for genes . 20 5.2 RNA-seq data analysis . 20 6 R environment session 23 1 Abstract Seq2pathway is a novel computational tool to analyze functional gene-sets (including signaling pathways) using variable next-generation sequencing data[1]. Integral to this tool are the \seq2gene" and \gene2pathway" components in series that infer a quantitative pathway-level profile for each sample. The seq2gene function assigns phenotype-associated significance of genomic regions to gene-level scores, where the significance could be p-values of SNPs or point mutations, protein-binding affinity, or transcriptional expression level. The seq2gene function has the feasibility to assign non-exon regions to a range of neighboring genes besides the nearest one, thus facilitating the study of functional non-coding elements[2]. Then the gene2pathway summarizes gene-level measurements to pathway-level scores, comparing the quantity of significance for gene members within a pathway with those outside a pathway. -
Genetic Basis of Simple and Complex Traits with Relevance to Avian Evolution
Genetic basis of simple and complex traits with relevance to avian evolution Małgorzata Anna Gazda Doctoral Program in Biodiversity, Genetics and Evolution D Faculdade de Ciências da Universidade do Porto 2019 Supervisor Miguel Jorge Pinto Carneiro, Auxiliary Researcher, CIBIO/InBIO, Laboratório Associado, Universidade do Porto Co-supervisor Ricardo Lopes, CIBIO/InBIO Leif Andersson, Uppsala University FCUP Genetic basis of avian traits Nota Previa Na elaboração desta tese, e nos termos do número 2 do Artigo 4º do Regulamento Geral dos Terceiros Ciclos de Estudos da Universidade do Porto e do Artigo 31º do D.L.74/2006, de 24 de Março, com a nova redação introduzida pelo D.L. 230/2009, de 14 de Setembro, foi efetuado o aproveitamento total de um conjunto coerente de trabalhos de investigação já publicados ou submetidos para publicação em revistas internacionais indexadas e com arbitragem científica, os quais integram alguns dos capítulos da presente tese. Tendo em conta que os referidos trabalhos foram realizados com a colaboração de outros autores, o candidato esclarece que, em todos eles, participou ativamente na sua conceção, na obtenção, análise e discussão de resultados, bem como na elaboração da sua forma publicada. Este trabalho foi apoiado pela Fundação para a Ciência e Tecnologia (FCT) através da atribuição de uma bolsa de doutoramento (PD/BD/114042/2015) no âmbito do programa doutoral em Biodiversidade, Genética e Evolução (BIODIV). 2 FCUP Genetic basis of avian traits Acknowledgements Firstly, I would like to thank to my all supervisors Miguel Carneiro, Ricardo Lopes and Leif Andersson, for the demanding task of supervising myself last four years. -
A Gene-Level Methylome-Wide Association Analysis Identifies Novel
bioRxiv preprint doi: https://doi.org/10.1101/2020.07.13.201376; this version posted July 14, 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. 1 A gene-level methylome-wide association analysis identifies novel 2 Alzheimer’s disease genes 1 1 2 3 4 3 Chong Wu , Jonathan Bradley , Yanming Li , Lang Wu , and Hong-Wen Deng 1 4 Department of Statistics, Florida State University; 2 5 Department of Biostatistics & Data Science, University of Kansas Medical Center; 3 6 Population Sciences in the Pacific Program, University of Hawaii Cancer center; 4 7 Tulane Center for Biomedical Informatics and Genomics, Deming Department of Medicine, 8 Tulane University School of Medicine 9 Corresponding to: Chong Wu, Assistant Professor, Department of Statistics, Florida State 10 University, email: [email protected] 1 bioRxiv preprint doi: https://doi.org/10.1101/2020.07.13.201376; this version posted July 14, 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. 11 Abstract 12 Motivation: Transcriptome-wide association studies (TWAS) have successfully facilitated the dis- 13 covery of novel genetic risk loci for many complex traits, including late-onset Alzheimer’s disease 14 (AD). However, most existing TWAS methods rely only on gene expression and ignore epige- 15 netic modification (i.e., DNA methylation) and functional regulatory information (i.e., enhancer- 16 promoter interactions), both of which contribute significantly to the genetic basis ofAD. -
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. -
A General Binding Mechanism for All Human Sulfatases by the Formylglycine-Generating Enzyme
A general binding mechanism for all human sulfatases by the formylglycine-generating enzyme Dirk Roeser*, Andrea Preusser-Kunze†, Bernhard Schmidt†, Kathrin Gasow*, Julia G. Wittmann*, Thomas Dierks‡, Kurt von Figura†, and Markus Georg Rudolph*§ *Department of Molecular Structural Biology, University of Go¨ttingen, Justus-von-Liebig-Weg 11, D-37077 Go¨ttingen, Germany; †Department of Biochemistry II, Heinrich-Du¨ker-Weg 12, University of Go¨ttingen, D-37073 Go¨ttingen, Germany; and ‡Department of Biochemistry I, Universita¨tsstrasse 25, University of Bielefeld, D-33615 Bielefeld, Germany Edited by Carolyn R. Bertozzi, University of California, Berkeley, CA, and approved November 8, 2005 (received for review September 1, 2005) The formylglycine (FGly)-generating enzyme (FGE) uses molecular tases, suggesting a general binding mechanism of substrate sulfa- oxygen to oxidize a conserved cysteine residue in all eukaryotic tases by FGE. sulfatases to the catalytically active FGly. Sulfatases degrade and The details of how O2-dependent cysteine oxidation is mediated remodel sulfate esters, and inactivity of FGE results in multiple by FGE are unknown. As a first step toward the elucidation of the sulfatase deficiency, a fatal disease. The previously determined FGE molecular mechanism of FGly formation, we have previously crystal structure revealed two crucial cysteine residues in the active determined crystal structures of FGE in various oxidation states site, one of which was thought to be implicated in substrate (8). FGE adopts a novel fold with surprisingly little regular sec- 2ϩ binding. The other cysteine residue partakes in a novel oxygenase ondary structure and contains two structural Ca ions and two mechanism that does not rely on any cofactors. -
1) (As of December 2018) and the Latest GWAS of AD (2
SUPPLEMENTARY FIGURES downstream intergenic ncRNA_exonic upstream ●936 ●918 group downstream intergenic ncRNA_exonic upstream group exonic exonicintronicintronic ncRNA_intronic ncRNA_intronicUTR3 UTR3 3.8% 1.2%1.5%1.9% 3.8% 5.4%5.4% 750 0.3% 3.8%1.2%1.5%1.9% ●700 5.4% ●670 0.3% 500 45.8% 40.240.2% % 45.8% ●329 ●274 250 ●223 Number (GWAS SNPs/studies) Number (GWAS ●128 ●105 45.8% ●54 ●57 ●58 ●48 ●42 ●46 ●50 ●30 ●3740.2% ● ●17 ●25 ●4 ●6 ●12 0 ● 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 Year Supplementary Figure S1. GWAS of AD since 2007. The figure is based on data from the GWAS Catalog (1) (as of December 2018) and the latest GWAS of AD (2). The green area shows the total number of AD-associated SNPs, and the purple area shows the total number of GWAS of AD. The insert chart shows the proportions of different types of all 936 AD-associated SNPs. 1 100 200 RPS27A TGFB2 BIN1 C4BPB MSH2 PROC UGT1A1 RAB1A TTN DISC1 50 PDCL3 COL4A3 CD55 ERCC3 100 USP21 C4BPA ITSN2 PTPRF MPZ FMN2 INPP5D CEP85 FNBP1L CSF1 CD46 ADAMTS4 PRKRA SPRED2 0 CTNNA2 DGKD ADCY10 ZAP70 LIMS2 PDE1A PROX1 0 CHRNB2 CR1 HSPG2 SH3BGRL3 DAB1 CTBS FCER1G MAP3K2 AD risk score or log10(P value) IL6R CDC73 CD34 AD risk score or log10(P value) −50 B4GALT3 IL19 0 50 100 150 200 250 0 50 100 150 200 Chromosome 1 (Mb) Chromosome 2 (Mb) ATP2B2 LTF ARF4 MECOM PAK2 EPHB1 40 VHL PRSS42 ARL6IP5 150 COL25A1 TDGF1 RPSA CCR2 CCR1 IL1RAP IRAK2 20 PTPRG 100 FLNB TF CX3CR1 IL17RD SH3RF1 FGG FANCD2 LIMD1 CCR5 50 0 WDR1 PDGFRA EIF4E FGB AD risk score or log10(P value) AD risk -
AP-4 Mediates Export of ATG9A from the Trans-Golgi Network to Promote
AP-4 mediates export of ATG9A from the trans-Golgi PNAS PLUS network to promote autophagosome formation Rafael Matteraa,1, Sang Yoon Parka,1, Raffaella De Pacea, Carlos M. Guardiaa, and Juan S. Bonifacinoa,2 aCell Biology and Neurobiology Branch, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, MD 20892 Edited by Pietro De Camilli, Howard Hughes Medical Institute and Yale University, New Haven, CT, and approved November 6, 2017 (received for review October 2, 2017) AP-4 is a member of the heterotetrameric adaptor protein (AP) mediated by a noncanonical YRYRF sequence in the receptor- complex family involved in protein sorting in the endomembrane associated, transmembrane AMPA receptor regulatory proteins system of eukaryotic cells. Interest in AP-4 has recently risen with (TARPs) (17). Finally, in the δ2 glutamate receptor protein, the discovery that mutations in any of its four subunits cause a binding to μ4 depends on several phenylalanine residues in a form of hereditary spastic paraplegia (HSP) with intellectual noncanonical context (18). disability. The critical sorting events mediated by AP-4 and the Interest in AP-4 has recently risen because of the discovery of pathogenesis of AP-4 deficiency, however, remain poorly under- mutations in genes encoding each of the subunits of AP-4 in stood. Here we report the identification of ATG9A, the only a subset of autosomal recessive hereditary spastic paraplegias multispanning membrane component of the core autophagy ma- (HSPs), namely, SPG47 (AP4B1/β4), SPG50 (AP4M1/μ4), SPG51 chinery, as a specific AP-4 cargo. AP-4 promotes signal-mediated (AP4E1/e), and SPG52 (AP4S1/σ4) (19–21). -
Spatial Protein Interaction Networks of the Intrinsically Disordered Transcription Factor C(%3$
Spatial protein interaction networks of the intrinsically disordered transcription factor C(%3$ Dissertation zur Erlangung des akademischen Grades Doctor rerum naturalium (Dr. rer. nat.) im Fach Biologie/Molekularbiologie eingereicht an der Lebenswissenschaftlichen Fakultät der Humboldt-Universität zu Berlin Von Evelyn Ramberger, M.Sc. Präsidentin der Humboldt-Universität zu Berlin Prof. Dr.-Ing.Dr. Sabine Kunst Dekan der Lebenswissenschaftlichen Fakultät der Humboldt-Universität zu Berlin Prof. Dr. Bernhard Grimm Gutachter: 1. Prof. Dr. Achim Leutz 2. Prof. Dr. Matthias Selbach 3. Prof. Dr. Gunnar Dittmar Tag der mündlichen Prüfung: 12.8.2020 For T. Table of Contents Selbstständigkeitserklärung ....................................................................................1 List of Figures ............................................................................................................2 List of Tables ..............................................................................................................3 Abbreviations .............................................................................................................4 Zusammenfassung ....................................................................................................6 Summary ....................................................................................................................7 1. Introduction ............................................................................................................8 1.1. Disordered proteins -
The Mammalian Adult Neurogenesis Gene Ontology (MANGO) Provides a Structural Framework for Published Information on Genes Regulating Adult Hippocampal Neurogenesis
The Mammalian Adult Neurogenesis Gene Ontology (MANGO) Provides a Structural Framework for Published Information on Genes Regulating Adult Hippocampal Neurogenesis Rupert W. Overall1, Maciej Paszkowski-Rogacz2, Gerd Kempermann1,3* 1 CRTD – Center for Regenerative Therapies Dresden, Technische Universita¨t Dresden, Dresden, Germany, 2 UCC – University Cancer Center, Medical Faculty, Technische Universita¨t Dresden, Dresden, Germany, 3 DZNE, German Center for Neurodegenerative Diseases, Dresden, Germany Abstract Background: Adult hippocampal neurogenesis is not a single phenotype, but consists of a number of sub-processes, each of which is under complex genetic control. Interpretation of gene expression studies using existing resources often does not lead to results that address the interrelatedness of these processes. Formal structure, such as provided by ontologies, is essential in any field for comprehensive interpretation of existing knowledge but, until now, such a structure has been lacking for adult neurogenesis. Methodology/Principal Findings: We have created a resource with three components 1. A structured ontology describing the key stages in the development of adult hippocampal neural stem cells into functional granule cell neurons. 2. A comprehensive survey of the literature to annotate the results of all published reports on gene function in adult hippocampal neurogenesis (257 manuscripts covering 228 genes) to the appropriate terms in our ontology. 3. An easy-to- use searchable interface to the resulting database made freely available online. The manuscript presents an overview of the database highlighting global trends such as the current bias towards research on early proliferative stages, and an example gene set enrichment analysis. A limitation of the resource is the current scope of the literature which, however, is growing by around 100 publications per year.