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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. -
The Landscape of Cancer Cell Line Metabolism
The Landscape of Cancer Cell Line Metabolism The Harvard community has made this article openly available. Please share how this access benefits you. Your story matters Citation Li, Haoxin, Shaoyang Ning, Mahmoud Ghandi, Gregory V. Kryukov, Shuba Gopal, Amy Deik, Amanda Souza, et. al. 2019. The Landscape of Cancer Cell Line Metabolism. Nature Medicine 25, no. 5: 850-860. Citable link http://nrs.harvard.edu/urn-3:HUL.InstRepos:41899268 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 HHS Public Access Author manuscript Author ManuscriptAuthor Manuscript Author Nat Med Manuscript Author . Author manuscript; Manuscript Author available in PMC 2019 November 08. Published in final edited form as: Nat Med. 2019 May ; 25(5): 850–860. doi:10.1038/s41591-019-0404-8. The Landscape of Cancer Cell Line Metabolism Haoxin Li1,2, Shaoyang Ning3, Mahmoud Ghandi1, Gregory V. Kryukov1, Shuba Gopal1, Amy Deik1, Amanda Souza1, Kerry Pierce1, Paula Keskula1, Desiree Hernandez1, Julie Ann4, Dojna Shkoza4, Verena Apfel5, Yilong Zou1, Francisca Vazquez1, Jordi Barretina4, Raymond A. Pagliarini4, Giorgio G. Galli5, David E. Root1, William C. Hahn1,2, Aviad Tsherniak1, Marios Giannakis1,2, Stuart L. Schreiber1,6, Clary B. Clish1,*, Levi A. Garraway1,2,*, and William R. Sellers1,2,* 1Broad Institute of Harvard and MIT, Cambridge, MA 02142, USA 2Department -
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. -
Integrative Pathway Analysis of Metabolic Signature in Bladder Cancer: a Linkage to the Cancer Genome Atlas Project and Prediction of Survival
Integrative Pathway Analysis of Metabolic Signature in Bladder Cancer: A Linkage to The Cancer Genome Atlas Project and Prediction of Survival Friedrich-Carl von Rundstedt,* Kimal Rajapakshe,* Jing Ma, James M. Arnold, Jie Gohlke, Vasanta Putluri, Rashmi Krishnapuram, D. Badrajee Piyarathna, Yair Lotan, Daniel Godde,€ Stephan Roth, Stephan Storkel,€ Jonathan M. Levitt, George Michailidis, Arun Sreekumar, Seth P. Lerner, Cristian Coarfa† and Nagireddy Putluri† From the Scott Department of Urology (FCvR, JML, SPL), Department of Molecular and Cell Biology, Alkek Center for Molecular Discovery (KR, JMA, JG, RK, DBP, AS, CC, NP), Verna and Marrs McLean Department of Biochemistry (AS), Advanced Technology Core (VP, DBP, AS, NP) and Department of Pathology and Immunology (JML), Baylor College of Medicine, Houston and Department of Urology, University of Texas Southwestern Medical Center (YL), Dallas, Texas, Departments of Urology (FCvR, SR) and Pathology Helios Klinikum (DG, SS), Witten-Herdecke University, Wuppertal, Germany, and Department of Statistics, University of Michigan (JM, GM), Ann Arbor, Michigan Purpose: We used targeted mass spectrometry to study the metabolic fingerprint of urothelial cancer and determine whether the biochemical pathway analysis Abbreviations and Acronyms gene signature would have a predictive value in independent cohorts of patients ¼ with bladder cancer. BCa bladder cancer Materials and Methods: Pathologically evaluated, bladder derived tissues, including benign adjacent tissue from 14 patients and bladder cancer from 46, were analyzed by liquid chromatography based targeted mass spectrometry. Differen- tial metabolites associated with tumor samples in comparison to benign tissue were identified by adjusting the p values for multiple testing at a false discovery rate threshold of 15%. -
RT² Profiler PCR Array (Rotor-Gene® Format) Human Amino Acid Metabolism I
RT² Profiler PCR Array (Rotor-Gene® Format) Human Amino Acid Metabolism I Cat. no. 330231 PAHS-129ZR For pathway expression analysis Format For use with the following real-time cyclers RT² Profiler PCR Array, Rotor-Gene Q, other Rotor-Gene cyclers Format R Description The Human Amino Acid Metabolism I RT² Profiler PCR Array profiles the expression of 84 key genes important in biosynthesis and degradation of functional amino acids. Of the 20 amino acids required for protein synthesis, six of them (arginine, cysteine, glutamine, leucine, proline, and tryptophan), collectively known as the functional amino acids, regulate key metabolic pathways involved in cellular growth, and development, as well as other important biological processes such as immunity and reproduction. For example, leucine activates mTOR signaling and increases protein synthesis, leading to lymphocyte proliferation. Therefore, a lack of leucine can compromise immune function. Metabolic pathways interrelated with the biosynthesis and degradation of these amino acids include vitamin and cofactor biosynthesis (such as SAM or S-Adenosyl Methionine) as well as neurotransmitter metabolism (such as glutamate). This array includes genes for mammalian functional amino acid metabolism as well as genes involved in methionine metabolism, important also for nutrient sensing and sulfur metabolism. Using realtime PCR, you can easily and reliably analyze the expression of a focused panel of genes involved in functional amino acid metabolism with this array. For further details, consult the RT² Profiler PCR Array Handbook. Shipping and storage RT² Profiler PCR Arrays in the Rotor-Gene format are shipped at ambient temperature, on dry ice, or blue ice packs depending on destination and accompanying products. -
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 -
Application of RNA-Seq in Ecotoxicogenomics: Exploring the Effects of Ibuprofen Exposure on Rainbow Trout and C
Application of RNA-Seq in Ecotoxicogenomics: Exploring the Effects of Ibuprofen Exposure on Rainbow Trout and C. elegans by Lorraine Lok-Lun Yu Brown B.Sc., University of British Columbia, 2007 Thesis Submitted in Partial Fulfillment of the Requirements for the Degree of Master of Science in the Department of Molecular Biology and Biochemistry Faculty of Science Lorraine Lok-Lun Yu Brown 2013 SIMON FRASER UNIVERSITY Fall 2013 Approval Name: Lorraine Lok-Lun Yu Brown Degree: Master of Science Title of Thesis: Application of RNA-Seq in Ecotoxicogenomics: Exploring the Effects of Ibuprofen Exposure on Rainbow Trout and C. elegans Examining Committee: Chair: Nicholas Harden Professor Fiona Brinkman Senior Supervisor Professor William Davidson Supervisor Professor Steven Jones Supervisor Professor Christopher Kennedy Internal Examiner Professor Department of Biological Sciences Date Defended/Approved: December 16, 2013 ii Partial Copyright Licence iii Ethics Statement iv Abstract RNA-Seq was applied in this ecotoxicogenomics study to investigate the effects of ibuprofen in two species, rainbow trout (Oncorhynchus mykiss), a fish routinely used in ecotoxicology tests, and Caenorhabditis elegans, a well-studied nematode with immense genomics information. Exposure to environmentally relevant levels of ibuprofen resulted in gene expression changes relating to stress, prostaglandin synthesis, reproduction and development in both species. In fish, we observed sex-dependent differences in vitellogenin and prostaglandin synthase gene expression, highlighting the importance of genetic sex determination of juvenile fish used in bioassays. In worms, we saw a decrease in progeny production count. Our results suggest that ibuprofen may have negative impacts on reproduction in both species but requires further investigation. -
CSE642 Final Version
Eindhoven University of Technology MASTER Dimensionality reduction of gene expression data Arts, S. Award date: 2018 Link to publication Disclaimer This document contains a student thesis (bachelor's or master's), as authored by a student at Eindhoven University of Technology. Student theses are made available in the TU/e repository upon obtaining the required degree. The grade received is not published on the document as presented in the repository. The required complexity or quality of research of student theses may vary by program, and the required minimum study period may vary in duration. General rights Copyright and moral rights for the publications made accessible in the public portal are retained by the authors and/or other copyright owners and it is a condition of accessing publications that users recognise and abide by the legal requirements associated with these rights. • Users may download and print one copy of any publication from the public portal for the purpose of private study or research. • You may not further distribute the material or use it for any profit-making activity or commercial gain Eindhoven University of Technology MASTER THESIS Dimensionality Reduction of Gene Expression Data Author: S. (Sako) Arts Daily Supervisor: dr. V. (Vlado) Menkovski Graduation Committee: dr. V. (Vlado) Menkovski dr. D.C. (Decebal) Mocanu dr. N. (Nikolay) Yakovets May 16, 2018 v1.0 Abstract The focus of this thesis is dimensionality reduction of gene expression data. I propose and test a framework that deploys linear prediction algorithms resulting in a reduced set of selected genes relevant to a specified case. Abstract In cancer research there is a large need to automate parts of the process of diagnosis, this is mainly to reduce cost, make it faster and more accurate. -
Relevance Network Between Chemosensitivity and Transcriptome in Human Hepatoma Cells1
Vol. 2, 199–205, February 2003 Molecular Cancer Therapeutics 199 Relevance Network between Chemosensitivity and Transcriptome in Human Hepatoma Cells1 Masaru Moriyama,2 Yujin Hoshida, topoisomerase II  expression, whereas it negatively Motoyuki Otsuka, ShinIchiro Nishimura, Naoya Kato, correlated with expression of carboxypeptidases A3 Tadashi Goto, Hiroyoshi Taniguchi, and Z. Response to nimustine was associated with Yasushi Shiratori, Naohiko Seki, and Masao Omata expression of superoxide dismutase 2. Department of Gastroenterology, Graduate School of Medicine, Relevance networks identified several negative University of Tokyo, Tokyo 113-8655 [M. M., Y. H., M. O., N. K., T. G., H. T., Y. S., M. O.]; Cellular Informatics Team, Computational Biology correlations between gene expression and resistance, Research Center, Tokyo 135-0064 [S. N.]; and Department of which were missed by hierarchical clustering. Our Functional Genomics, Graduate School of Medicine, Chiba University, results suggested the necessity of systematically Chiba 260-8670 [N. S.], Japan evaluating the transporting systems that may play a major role in resistance in hepatoma. This may provide Abstract useful information to modify anticancer drug action in Generally, hepatoma is not a chemosensitive tumor, hepatoma. and the mechanism of resistance to anticancer drugs is not fully elucidated. We aimed to comprehensively Introduction evaluate the relationship between chemosensitivity and Hepatoma is a major cause of death even in developed gene expression profile in human hepatoma cells, by countries, and its incidence is increasing (1). Despite the using microarray analysis, and analyze the data by progress of therapeutic technique (2), the efficacy of radical constructing relevance networks. therapy is hampered by frequent recurrence and advance of In eight hepatoma cell lines (HLE, HLF, Huh7, Hep3B, the tumor (3). -
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 -
Supplementary Information Genomice and Transcriptomic Analysis
Supplementary Information Genomice and Transcriptomic Analysis for Identification of Genes and Interlinked Pathways Mediating Artemisinin Resistance in Leishmania donovani Sushmita Ghosh1,2, Aditya Verma1, Vinay Kumar1, Dibyabhaba Pradhan3, Angamuthu Selvapandiyan 2, Poonam Salotra1, Ruchi Singh1* 1. ICMR- National Institute of Pathology, Safdarjung Hospital Campus, New Delhi-110029, India 2. Jamia Hamdard University-Institute of Molecular Medicine, New Delhi-110062, India 3. ICMR-AIIMS Computational Genomics Centre, Indian Council of Medical Research, New Delhi- 110029 *Correspondence: [email protected] Supplementary Figures and Tables: Figure S1. Figure S1: Comparative transcriptional responses following ART adaptation in L. donovani. Overlap of log2 transformed K133 AS-R and K133 WT expression ratio plotted as a function of chromosomal location of probes representing the full genome microarray. The plot represents the average values of three independent hybridizations for each isolate. Table S1: List of genes validated for their modulated expression by Quantitative real time- PCR S.N Primer Gene Name/ Function/relevance Primer Sequence o. Name Gene ID 1 AQP1 Aquaglyceropor Metal ion F- in (LinJ.31.0030) transmembrane 5’CAGGGACAGCTCGAGGGTAA transporter activity, AA3’ integral to membrane; transmembrane R- transport; transporter 5’GTTACCGGCGTGAAAGACAG activity; water TG3’ transport. 2 A2 A2 protein Cellular response to F- (LinJ.22.0670) stress 5’GTTGGCCCGCTTTCTGTTGG3’ R- 5’ACCAACGTCAACAGAGAGA GGG3’ 3 ABCG1 ATP-binding ATP binding, ATPase -
The Genetics of Bipolar Disorder
Molecular Psychiatry (2008) 13, 742–771 & 2008 Nature Publishing Group All rights reserved 1359-4184/08 $30.00 www.nature.com/mp FEATURE REVIEW The genetics of bipolar disorder: genome ‘hot regions,’ genes, new potential candidates and future directions A Serretti and L Mandelli Institute of Psychiatry, University of Bologna, Bologna, Italy Bipolar disorder (BP) is a complex disorder caused by a number of liability genes interacting with the environment. In recent years, a large number of linkage and association studies have been conducted producing an extremely large number of findings often not replicated or partially replicated. Further, results from linkage and association studies are not always easily comparable. Unfortunately, at present a comprehensive coverage of available evidence is still lacking. In the present paper, we summarized results obtained from both linkage and association studies in BP. Further, we indicated new potential interesting genes, located in genome ‘hot regions’ for BP and being expressed in the brain. We reviewed published studies on the subject till December 2007. We precisely localized regions where positive linkage has been found, by the NCBI Map viewer (http://www.ncbi.nlm.nih.gov/mapview/); further, we identified genes located in interesting areas and expressed in the brain, by the Entrez gene, Unigene databases (http://www.ncbi.nlm.nih.gov/entrez/) and Human Protein Reference Database (http://www.hprd.org); these genes could be of interest in future investigations. The review of association studies gave interesting results, as a number of genes seem to be definitively involved in BP, such as SLC6A4, TPH2, DRD4, SLC6A3, DAOA, DTNBP1, NRG1, DISC1 and BDNF.