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METACYC ID Description A0AR23 GO:0004842 (Ubiquitin-Protein Ligase
Electronic Supplementary Material (ESI) for Integrative Biology This journal is © The Royal Society of Chemistry 2012 Heat Stress Responsive Zostera marina Genes, Southern Population (α=0. -
Gene Symbol Gene Description ACVR1B Activin a Receptor, Type IB
Table S1. Kinase clones included in human kinase cDNA library for yeast two-hybrid screening Gene Symbol Gene Description ACVR1B activin A receptor, type IB ADCK2 aarF domain containing kinase 2 ADCK4 aarF domain containing kinase 4 AGK multiple substrate lipid kinase;MULK AK1 adenylate kinase 1 AK3 adenylate kinase 3 like 1 AK3L1 adenylate kinase 3 ALDH18A1 aldehyde dehydrogenase 18 family, member A1;ALDH18A1 ALK anaplastic lymphoma kinase (Ki-1) ALPK1 alpha-kinase 1 ALPK2 alpha-kinase 2 AMHR2 anti-Mullerian hormone receptor, type II ARAF v-raf murine sarcoma 3611 viral oncogene homolog 1 ARSG arylsulfatase G;ARSG AURKB aurora kinase B AURKC aurora kinase C BCKDK branched chain alpha-ketoacid dehydrogenase kinase BMPR1A bone morphogenetic protein receptor, type IA BMPR2 bone morphogenetic protein receptor, type II (serine/threonine kinase) BRAF v-raf murine sarcoma viral oncogene homolog B1 BRD3 bromodomain containing 3 BRD4 bromodomain containing 4 BTK Bruton agammaglobulinemia tyrosine kinase BUB1 BUB1 budding uninhibited by benzimidazoles 1 homolog (yeast) BUB1B BUB1 budding uninhibited by benzimidazoles 1 homolog beta (yeast) C9orf98 chromosome 9 open reading frame 98;C9orf98 CABC1 chaperone, ABC1 activity of bc1 complex like (S. pombe) CALM1 calmodulin 1 (phosphorylase kinase, delta) CALM2 calmodulin 2 (phosphorylase kinase, delta) CALM3 calmodulin 3 (phosphorylase kinase, delta) CAMK1 calcium/calmodulin-dependent protein kinase I CAMK2A calcium/calmodulin-dependent protein kinase (CaM kinase) II alpha CAMK2B calcium/calmodulin-dependent -
Analysis of Gene–Environment Interactions in Postnatal
– Analysis of gene environment interactions in postnatal INAUGURAL ARTICLE development of the mammalian intestine Seth Rakoff-Nahouma,b,c,1, Yong Kongd, Steven H. Kleinsteine, Sathish Subramanianf, Philip P. Ahernf, Jeffrey I. Gordonf, and Ruslan Medzhitova,b,1 aHoward Hughes Medical Institute, bDepartment of Immunobiology, dDepartment of Molecular Biophysics and Biochemistry, W. M. Keck Foundation Biotechnology Resource Laboratory, and eInterdepartmental Program in Computational Biology and Bioinformatics and Department of Pathology, Yale University School of Medicine, New Haven, CT 06510; fCenter for Genome Sciences and Systems Biology, Washington University School of Medicine in St. Louis, St. Louis, MO 63108; and cDivision of Infectious Diseases, Department of Medicine, Boston Children’s Hospital and Harvard Medical School, Boston, MA 02115 This contribution is part of the special series of Inaugural Articles by members of the National Academy of Sciences elected in 2010. Contributed by Ruslan Medzhitov, December 31, 2014 (sent for review December 25, 2014; reviewed by Alexander V. Chervonsky and Alexander Y. Rudensky) Unlike mammalian embryogenesis, which takes place in the relatively immediately after birth, the intestine is exposed to mother’s milk predictable and stable environment of the uterus, postnatal develop- and undergoes initial colonization with microorganisms. Second, ment can be affected by a multitude of highly variable environmental after weaning, the intestinal tract becomes exposed to solid foods factors, including diet, exposure to noxious substances, and micro- and is no longer exposed to mother’s milk components, the host organisms. Microbial colonization of the intestine is thought to play a immune system matures, and the microbiota shifts. particularly important role in postnatal development of the gastroin- Although it is widely recognized that these transitions have testinal, metabolic, and immune systems. -
CRISPR Screening of Porcine Sgrna Library Identifies Host Factors
ARTICLE https://doi.org/10.1038/s41467-020-18936-1 OPEN CRISPR screening of porcine sgRNA library identifies host factors associated with Japanese encephalitis virus replication Changzhi Zhao1,5, Hailong Liu1,5, Tianhe Xiao1,5, Zichang Wang1, Xiongwei Nie1, Xinyun Li1,2, Ping Qian2,3, Liuxing Qin3, Xiaosong Han1, Jinfu Zhang1, Jinxue Ruan1, Mengjin Zhu1,2, Yi-Liang Miao 1,2, Bo Zuo1,2, ✉ ✉ Kui Yang4, Shengsong Xie 1,2 & Shuhong Zhao 1,2 1234567890():,; Japanese encephalitis virus (JEV) is a mosquito-borne zoonotic flavivirus that causes ence- phalitis and reproductive disorders in mammalian species. However, the host factors critical for its entry, replication, and assembly are poorly understood. Here, we design a porcine genome-scale CRISPR/Cas9 knockout (PigGeCKO) library containing 85,674 single guide RNAs targeting 17,743 protein-coding genes, 11,053 long ncRNAs, and 551 microRNAs. Subsequently, we use the PigGeCKO library to identify key host factors facilitating JEV infection in porcine cells. Several previously unreported genes required for JEV infection are highly enriched post-JEV selection. We conduct follow-up studies to verify the dependency of JEV on these genes, and identify functional contributions for six of the many candidate JEV- related host genes, including EMC3 and CALR. Additionally, we identify that four genes associated with heparan sulfate proteoglycans (HSPGs) metabolism, specifically those responsible for HSPGs sulfurylation, facilitate JEV entry into porcine cells. Thus, beyond our development of the largest CRISPR-based functional genomic screening platform for pig research to date, this study identifies multiple potentially vulnerable targets for the devel- opment of medical and breeding technologies to treat and prevent diseases caused by JEV. -
Molecular Mechanisms Involved Involved in the Interaction Effects of HCV and Ethanol on Liver Cirrhosis
Virginia Commonwealth University VCU Scholars Compass Theses and Dissertations Graduate School 2010 Molecular Mechanisms Involved Involved in the Interaction Effects of HCV and Ethanol on Liver Cirrhosis Ryan Fassnacht Virginia Commonwealth University Follow this and additional works at: https://scholarscompass.vcu.edu/etd Part of the Physiology Commons © The Author Downloaded from https://scholarscompass.vcu.edu/etd/2246 This Thesis is brought to you for free and open access by the Graduate School at VCU Scholars Compass. It has been accepted for inclusion in Theses and Dissertations by an authorized administrator of VCU Scholars Compass. For more information, please contact [email protected]. Ryan C. Fassnacht 2010 All Rights Reserved Molecular Mechanisms Involved in the Interaction Effects of HCV and Ethanol on Liver Cirrhosis A thesis submitted in partial fulfillment of the requirements for the degree of Master of Science at Virginia Commonwealth University. by Ryan Christopher Fassnacht, B.S. Hampden Sydney University, 2005 M.S. Virginia Commonwealth University, 2010 Director: Valeria Mas, Ph.D., Associate Professor of Surgery and Pathology Division of Transplant Department of Surgery Virginia Commonwealth University Richmond, Virginia July 9, 2010 Acknowledgement The Author wishes to thank his family and close friends for their support. He would also like to thank the members of the molecular transplant team for their help and advice. This project would not have been possible with out the help of Dr. Valeria Mas and her endearing -
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. -
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. -
PS CV Comp 050917
CURRICULUM VITAE NAME: Pamela Mary Stanley (nee Fetherstonhaugh) Lab Homepage http://www.einstein.yu.edu/departments/cellbiology/faculty/stanley/home/ NATIONALITY: Australian/American EDUCATION: l965-l967 Bachelor of Science University of Melbourne, Australia Majored in Biochemistry and Microbiology l968 B. Sc. Hons., Walter and Eliza Hall Institute, Melbourne, Australia Commonwealth Post-graduate Award Advisor: Gordon L. Ada Thesis: Tolerance to Foreign Erythrocytes Using Antigen-Containing Extracts of the Erythrocyte Membrane. l969-l972 Research for degree of Doctor of Philosophy in the Department of Microbiology, University of Melbourne, Australia Commonwealth Post-graduate Award Advisor: Professor David O. White Thesis: Influenza Virus Proteins l972-l975 Postdoctoral Fellow of the Medical Research Council of Canada in the Department of Medical Genetics, University of Toronto, Canada Advisor: Dr. Louis Siminovitch Postdoctoral Fellowship from the Medical Research Council of Canada Topic: The Isolation and Characterization of Lectin Resistant Chinese Hamster Ovary Cells. POSITIONS HELD: l976 Research Associate Department of Medical Genetics University of Toronto Toronto, Ontario, Canada l977-1982 Assistant Professor Dept. of Cell Biology Albert Einstein College of Medicine Bronx, New York 1982-1986 Associate Professor Dept. of Cell Biology Albert Einstein College of Medicine Bronx, New York 1986 Professor Department of Cell Biology Albert Einstein College of Medicine Bronx, New York 1994-2007 Director Training Program in Cell & Molecular Biology, Biochemistry & Genetics, NIGMS 1 1988-2012 Program leader Membrane Molecular Biology Albert Einstein Cancer Center 2002- Associate Director for Laboratory Research Albert Einstein NCI Cancer Center 2007- Horace W. Goldsmith Foundation Chair. HONORS: Dunlop Prize for First Place in Biochemistry (1966 and 1967) Aust. -
In Vivo Dual RNA-Seq Analysis Reveals the Basis for Differential Tissue Tropism of Clinical Isolates of Streptococcus Pneumoniae
In Vivo Dual RNA-Seq Analysis Reveals the Basis for Differential Tissue Tropism of Clinical Isolates of Streptococcus pneumoniae Vikrant Minhas,1,4 Rieza Aprianto,2,4 Lauren J. McAllister,1 Hui Wang,1 Shannon C. David,1 Kimberley T. McLean,1 Iain Comerford,3 Shaun R. McColl,3 James C. Paton,1,5,6,* Jan-Willem Veening,2,5 and Claudia Trappetti,1,5 Supplementary Information Supplementary Table 1. Pneumococcal differential gene expression in the lungs 6 h post-infection, 9-47-Ear vs 9-47M. Genes with fold change (FC) greater than 2 and p < 0.05 are shown. FC values highlighted in blue = upregulated in 9-47-Ear, while values highlighted in red = upregulated in 9- 47M. Locus tag in 9-47- Product padj FC Ear Sp947_chr_00844 Sialidase B 3.08E-10 313.9807 Sp947_chr_02077 hypothetical protein 4.46E-10 306.9412 Sp947_chr_00842 Sodium/glucose cotransporter 2.22E-09 243.4822 Sp947_chr_00841 N-acetylneuraminate lyase 4.53E-09 227.7963 scyllo-inositol 2-dehydrogenase Sp947_chr_00845 (NAD(+)) 4.36E-09 221.051 Sp947_chr_00848 hypothetical protein 1.19E-08 202.7867 V-type sodium ATPase catalytic subunit Sp947_chr_00853 A 1.29E-06 100.5411 Sp947_chr_00846 Beta-glucoside kinase 3.42E-06 98.18951 Sp947_chr_00855 V-type sodium ATPase subunit D 8.34E-06 85.94879 Sp947_chr_00851 V-type sodium ATPase subunit C 2.50E-05 72.46612 Sp947_chr_00843 hypothetical protein 2.17E-05 65.97758 Sp947_chr_00839 HTH-type transcriptional regulator RpiR 3.09E-05 61.28171 Sp947_chr_00854 V-type sodium ATPase subunit B 1.32E-06 50.86992 Sp947_chr_00120 hypothetical protein 3.00E-04 -
Yeast Genome Gazetteer P35-65
gazetteer Metabolism 35 tRNA modification mitochondrial transport amino-acid metabolism other tRNA-transcription activities vesicular transport (Golgi network, etc.) nitrogen and sulphur metabolism mRNA synthesis peroxisomal transport nucleotide metabolism mRNA processing (splicing) vacuolar transport phosphate metabolism mRNA processing (5’-end, 3’-end processing extracellular transport carbohydrate metabolism and mRNA degradation) cellular import lipid, fatty-acid and sterol metabolism other mRNA-transcription activities other intracellular-transport activities biosynthesis of vitamins, cofactors and RNA transport prosthetic groups other transcription activities Cellular organization and biogenesis 54 ionic homeostasis organization and biogenesis of cell wall and Protein synthesis 48 plasma membrane Energy 40 ribosomal proteins organization and biogenesis of glycolysis translation (initiation,elongation and cytoskeleton gluconeogenesis termination) organization and biogenesis of endoplasmic pentose-phosphate pathway translational control reticulum and Golgi tricarboxylic-acid pathway tRNA synthetases organization and biogenesis of chromosome respiration other protein-synthesis activities structure fermentation mitochondrial organization and biogenesis metabolism of energy reserves (glycogen Protein destination 49 peroxisomal organization and biogenesis and trehalose) protein folding and stabilization endosomal organization and biogenesis other energy-generation activities protein targeting, sorting and translocation vacuolar and lysosomal -
Novel Cardiovascular Findings in Association with a POMT2
European Journal of Human Genetics (2014) 22, 486–491 & 2014 Macmillan Publishers Limited All rights reserved 1018-4813/14 www.nature.com/ejhg ARTICLE Novel cardiovascular findings in association with a POMT2 mutation: three siblings with a-dystroglycanopathy Hugo R Martinez*,1, William J Craigen2, Monika Ummat3, Adekunle M Adesina4, Timothy E Lotze3 and John L Jefferies5 Dystroglycanopathies are a genetically heterogeneous subset of congenital muscular dystrophies that exhibit autosomal recessive inheritance and are characterized by abnormal glycosylation of a-dystroglycan. In particular, POMT2 (protein O-mannosyltransferase-2) mutations have been identified in congenital muscular dystrophy patients with a wide range of clinical involvement, ranging from the severe muscle-eye-brain disease and Walker–Warburg syndrome to limb girdle muscular dystrophy without structural brain or ocular involvement. Cardiovascular disease is thought to be uncommon in congenital muscular dystrophy, with rare reports of cardiac involvement. We describe three brothers aged 21, 19, and 17 years with an apparently homozygous POMT2 mutation who all presented with congenital muscular dystrophy, intellectual disabilities, and distinct cardiac abnormalities. All three brothers were homozygous for a p.Tyr666Cys missense mutation in exon 19 of the POMT2 gene. On screening echocardiograms, all siblings demonstrated significant dilatation of the aortic root and depressed left ventricular systolic function and/or left ventricular wall motion abnormalities. Our report is the first to document an association between POMT2 mutations and aortopathy with concomitant depressed left ventricular systolic function. On the basis of our findings, we suggest patients with POMT2 gene mutations be screened not only for myocardial dysfunction but also for aortopathy.