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Identification and Classification of Differentially Expressed Genes
Informatics in Medicine Unlocked 20 (2020) 100384 Contents lists available at ScienceDirect Informatics in Medicine Unlocked journal homepage: http://www.elsevier.com/locate/imu Identification and classification of differentially expressed genes reveal potential molecular signature associated with SARS-CoV-2 infection in lung adenocarcinomal cells Opeyemi S. Soremekun, Kehinde F. Omolabi, Mahmoud E.S. Soliman * Molecular Bio-computation and Drug Design Laboratory, School of Health Sciences, University of KwaZulu-Natal, Westville Campus, Durban, 4001, South Africa ARTICLE INFO ABSTRACT Keywords: Genomic techniques such as next-generation sequencing and microarrays have facilitated the identification and Differentially expressed genes classification of molecular signatures inherent in cells upon viral infection, for possible therapeutic targets. SARS-CoV-2 Therefore, in this study, we performed a differential gene expression analysis, pathway enrichment analysis, and COVID-19 gene ontology on RNAseq data obtained from SARS-CoV-2 infected A549 cells. Differential expression analysis Enrichment analysis revealed that 753 genes were up-regulated while 746 down-regulated. SNORA81, OAS2, SYCP2, LOC100506985, RNAseq and SNORD35B are the top 5 upregulated genes upon SARS-Cov-2 infection. Expectedly, these genes have been implicated in the immune response to viral assaults. In the Ontology of protein classification, a high percentage of the genes are classified as Gene-specific transcriptional regulator, metabolite interconversion enzyme, and Protein modifying enzymes. Twenty pathways with P-value lower than 0.05 were enriched in the up-regulated genes while 18 pathways are enriched in the down-regulated DEGs. The toll-like receptor signalling pathway is one of the major pathways enriched. This pathway plays an important role in the innate immune system by identifying the pathogen-associated molecular signature emanating from various microorganisms. -
A Genetic Variant Protective Against Severe COVID-19 Is Inherited from Neandertals
bioRxiv preprint doi: https://doi.org/10.1101/2020.10.05.327197; this version posted October 9, 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 The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity.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 4.0 International license. A genetic variant protective against severe COVID-19 is inherited from Neandertals Authors Hugo Zeberg1,2* and Svante Pääbo1,3* Affiliations 1 Max Planck Institute for Evolutionary Anthropology, Deutscher Platz 6, D-04103 Leipzig, Germany. 2 Department of Neuroscience, Karolinska Institutet, SE-17177 Stockholm, Sweden. 3 Okinawa Institute of Science and Technology, Onna-son, Okinawa 904-0495, Japan. *Corresponding authors: [email protected], [email protected] Abstract It was recently shown that the major genetic risk factor associated with becoming severely ill with COVID-19 when infected by SARS-CoV-2 is inherited from Neandertals. Thanks to new genetic association studies additional risk factors are now being discovered. Using data from a recent genome- wide associations from the Genetics of Mortality in Critical Care (GenOMICC) consortium, we show that a haplotype at a region associated with requiring intensive care is inherited from Neandertals. It encodes proteins that activate enzymes that are important during infections with RNA viruses. As compared to the previously described Neandertal risk haplotype, this Neandertal haplotype is protective against severe COVID-19, is of more moderate effect, and is found at substantial frequencies in all regions of the world outside Africa. 1 bioRxiv preprint doi: https://doi.org/10.1101/2020.10.05.327197; this version posted October 9, 2020. -
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. -
Oligoadenylate Synthetase (OAS) Proteins
bioRxiv preprint doi: https://doi.org/10.1101/804716; this version posted October 15, 2019. 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. In silico identification of potential inhibitors against human 2’-5’- oligoadenylate synthetase (OAS) proteins Karen J. Gonzalez1, Diego Moncada-Giraldo1, Juan B. Gutierrez2* 1Institute of Bioinformatics, University of Georgia; 2Department of Mathematics, University of Texas at San Antonio. * [email protected] Abstract As part of the type I IFN signaling, the 2’-5’- oligoadenylate synthetase (OAS) proteins have been involved in the progression of several non-viral diseases. Notably, OAS has been correlated with immune-modulatory functions that promote chronic inflammatory conditions, autoimmune disorders, cancer, and infectious diseases. In spite of this, OAS enzymes have been ignored as drug targets, and to date, there are no reports of compounds that can inhibit their activity. In this study, we have used homology modeling and virtual high-throughput screening to identify potential inhibitors of the human proteins OAS1, OAS2, and OAS3. Altogether, we have found 37 molecules that could exert a competitive inhibition in the ATP binding sites of OAS proteins, independently of the activation state of the enzyme. This latter characteristic, which might be crucial for a versatile inhibitor, was observed in compounds interacting with the residues Asp75, Asp77, Gln229, and Tyr230 in OAS1, and their equivalents in OAS2 and OAS3. Although there was little correlation between specific chemical fragments and particular interactions, intermolecular contacts with OAS catalytic triad and other critical amino acids were mainly promoted by heterocycles with π electrons and hydrogen bond acceptors. -
5'-Oligoadenylate Synthetase 2 (OAS2)
Biochemistry and Cell Biology Impact of double-stranded RNA characteristics on the activation of human 2’-5’-oligoadenylate synthetase 2 (OAS2). Journal: Biochemistry and Cell Biology Manuscript ID bcb-2019-0060.R1 Manuscript Type: Article Date Submitted by the 29-Mar-2019 Author: Complete List of Authors: Koul, Amit; University of Manitoba Deo, Soumya; University of Lethbridge Booy, Evan; University of Manitoba Orriss, George;Draft University of Manitoba Genung, Matthew; University of Manitoba McKenna, Sean; University of Manitoba Keyword: oligoadenylate synthetase, RNA, viral RNA, enzymology Is the invited manuscript for consideration in a Special Ribowest RNA Issue? : https://mc06.manuscriptcentral.com/bcb-pubs Page 1 of 39 Biochemistry and Cell Biology Impact of double-stranded RNA characteristics on the activation of human 2’-5’- oligoadenylate synthetase 2 (OAS2). Amit, Koul1, Soumya Deo3, Evan P. Booy1, George L. Orriss1, Matthew Genung4 and Sean A. McKenna1, 2 Department of Chemistry1, Department of Biochemistry and Medical Genetics2, University of Manitoba, 144 Dysart Road, Winnipeg, Manitoba, R3T2N2, Canada. Alberta RNA Research and Training Institute3, Department of Chemistry and Biochemistry, University of Lethbridge, 4401 University Drive, Lethbridge, Alberta T1K 3M4, Canada. Max Rady College of Medicine4, Rady Faculty of Health Sciences, University of Manitoba, 750 Bannatyne Avenue, Winnipeg, Manitoba, R3E 0W2, Canada. Corresponding Author: Dr. Sean A. McKenna [email protected], +1-204-272-1562 Draft ACKNOWLEDGEMENTS This work was supported by Natural Sciences and Engineering Research Council of Canada (NSERC). We would like to thank Emy Komatsu, Dr. Hélène Perreault, and Dr. John Sorensen for help with mass spectrometry analysis of 2-5A. -
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. -
Module Analysis Using Single-Patient Differential Expression Signatures
bioRxiv preprint doi: https://doi.org/10.1101/2020.01.05.894931; this version posted January 6, 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. Module analysis using single-patient differential expression signatures improve the power of association study for Alzheimer's disease Jialan Huang1, Dong Lu1, and Guofeng Meng1,∗ 1Institute of interdisciplinary integrative Medicine Research, shanghai University of Traditional Chinese Medicine, shanghai, China Abstract The causal mechanism of Alzheimer's disease is extremely complex. It usually requires a huge number of samples to achieve a good statistical power in association studies. In this work, we illustrated a different strategy to identify AD risk genes by clustering AD patients into modules based on their single-patient differential expression signatures. Evaluation suggested that our method could enrich AD patients with common clinical manifestations. Applying it to a cohort of only 310 AD patients, we identified 175 AD risk loci at a strict threshold of empirical p < 0:05 while only two loci were identified using all the AD patients. As an evaluation, we collected 23 AD risk genes reported in a recent large-scale meta-analysis and found that 18 of them were re-discovered by association studies using clustered AD patients, while only three of them were re-discovered using all AD patients. Functional annotation suggested that AD associated genetic variants mainly disturbed neuronal/synaptic function. -
Single-Cell Transcriptome Profiling of the Kidney Glomerulus Identifies Key Cell Types and Reactions to Injury
BASIC RESEARCH www.jasn.org Single-Cell Transcriptome Profiling of the Kidney Glomerulus Identifies Key Cell Types and Reactions to Injury Jun-Jae Chung ,1 Leonard Goldstein ,2 Ying-Jiun J. Chen,2 Jiyeon Lee ,1 Joshua D. Webster,3 Merone Roose-Girma,2 Sharad C. Paudyal,4 Zora Modrusan,2 Anwesha Dey,5 and Andrey S. Shaw1 Due to the number of contributing authors, the affiliations are listed at the end of this article. ABSTRACT Background The glomerulus is a specialized capillary bed that is involved in urine production and BP control. Glomerular injury is a major cause of CKD, which is epidemic and without therapeutic options. Single-cell transcriptomics has radically improved our ability to characterize complex organs, such as the kidney. Cells of the glomerulus, however, have been largely underrepresented in previous single-cell kidney studies due to their paucity and intractability. Methods Single-cell RNA sequencing comprehensively characterized the types of cells in the glomerulus from healthy mice and from four different disease models (nephrotoxic serum nephritis, diabetes, doxo- rubicin toxicity, and CD2AP deficiency). Results Allcelltypesintheglomeruluswereidentified using unsupervised clustering analysis. Novel marker genes and gene signatures of mesangial cells, vascular smooth muscle cells of the afferent and efferent arteri- oles, parietal epithelial cells, and three types of endothelial cells were identified. Analysis of the disease models revealed cell type–specific and injury type–specific responses in the glomerulus, including acute activation of the Hippo pathway in podocytes after nephrotoxic immune injury. Conditional deletion of YAP or TAZ resulted in more severe and prolonged proteinuria in response to injury, as well as worse glomerulosclerosis. -
The Evolution of the Viral RNA Sensor OAS1 in Old World Monkeys and Cetartiodactyls
City University of New York (CUNY) CUNY Academic Works All Dissertations, Theses, and Capstone Projects Dissertations, Theses, and Capstone Projects 2-2016 The Evolution of the Viral RNA Sensor OAS1 in Old World Monkeys and Cetartiodactyls Ian Fish Graduate Center, City University of New York How does access to this work benefit ou?y Let us know! More information about this work at: https://academicworks.cuny.edu/gc_etds/759 Discover additional works at: https://academicworks.cuny.edu This work is made publicly available by the City University of New York (CUNY). Contact: [email protected] The Evolution of the Viral RNA Sensor OAS1 in Old World Monkeys and Cetartiodactyls by Ian Fish The City University of New York 2016 i Copyright 2016 by Fish, Ian All rights reserved ii This manuscript has been read and accepted for the Graduate Faculty in Biology in satisfaction of the dissertation requirement for the degree of Doctor of Philosophy. ______________ ______________________________ Date Chair of Examining Committee Dr. Stéphane Boissinot ______________ ______________________________ Date Executive Officer Dr. Laurel Eckhardt Supervising Committee Members: ____________________________ Dr. Cathy Savage-Dunn, Queens College ____________________________ Dr. Susan Rotenberg, Queens College ____________________________ Dr. Shaneen Singh, Brooklyn College ____________________________ Dr. Margaret MacDonald, The Rockefeller University iii Abstract The Evolution of the Viral RNA Sensor OAS1 in Old World Monkeys and Cetartiodactyls author: Ian Fish advisor: Dr. Stéphane Boissinot Animals produce an array of sensors patrolling the intracellular environment poised to detect and respond to viral infection. The oligoadenylate synthetase family of enzymes comprises a crucial part of this innate immune response, directly signaling endonuclease activity responsible for inhibiting viral replication. -
Nº Ref Uniprot Proteína Péptidos Identificados Por MS/MS 1 P01024
Document downloaded from http://www.elsevier.es, day 26/09/2021. This copy is for personal use. Any transmission of this document by any media or format is strictly prohibited. Nº Ref Uniprot Proteína Péptidos identificados 1 P01024 CO3_HUMAN Complement C3 OS=Homo sapiens GN=C3 PE=1 SV=2 por 162MS/MS 2 P02751 FINC_HUMAN Fibronectin OS=Homo sapiens GN=FN1 PE=1 SV=4 131 3 P01023 A2MG_HUMAN Alpha-2-macroglobulin OS=Homo sapiens GN=A2M PE=1 SV=3 128 4 P0C0L4 CO4A_HUMAN Complement C4-A OS=Homo sapiens GN=C4A PE=1 SV=1 95 5 P04275 VWF_HUMAN von Willebrand factor OS=Homo sapiens GN=VWF PE=1 SV=4 81 6 P02675 FIBB_HUMAN Fibrinogen beta chain OS=Homo sapiens GN=FGB PE=1 SV=2 78 7 P01031 CO5_HUMAN Complement C5 OS=Homo sapiens GN=C5 PE=1 SV=4 66 8 P02768 ALBU_HUMAN Serum albumin OS=Homo sapiens GN=ALB PE=1 SV=2 66 9 P00450 CERU_HUMAN Ceruloplasmin OS=Homo sapiens GN=CP PE=1 SV=1 64 10 P02671 FIBA_HUMAN Fibrinogen alpha chain OS=Homo sapiens GN=FGA PE=1 SV=2 58 11 P08603 CFAH_HUMAN Complement factor H OS=Homo sapiens GN=CFH PE=1 SV=4 56 12 P02787 TRFE_HUMAN Serotransferrin OS=Homo sapiens GN=TF PE=1 SV=3 54 13 P00747 PLMN_HUMAN Plasminogen OS=Homo sapiens GN=PLG PE=1 SV=2 48 14 P02679 FIBG_HUMAN Fibrinogen gamma chain OS=Homo sapiens GN=FGG PE=1 SV=3 47 15 P01871 IGHM_HUMAN Ig mu chain C region OS=Homo sapiens GN=IGHM PE=1 SV=3 41 16 P04003 C4BPA_HUMAN C4b-binding protein alpha chain OS=Homo sapiens GN=C4BPA PE=1 SV=2 37 17 Q9Y6R7 FCGBP_HUMAN IgGFc-binding protein OS=Homo sapiens GN=FCGBP PE=1 SV=3 30 18 O43866 CD5L_HUMAN CD5 antigen-like OS=Homo -
Lessons from the Gtex Dataset Tim O. Nieuwenhuis1,2
bioRxiv preprint doi: https://doi.org/10.1101/602367; this version posted January 2, 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 Basal Contamination of Sequencing: Lessons from the GTEx dataset 2 3 Tim O. Nieuwenhuis1,2, Stephanie Yang2, Rohan X. Verma1, Vamsee Pillalamarri2, Dan 4 E. Arking2, Avi Z. Rosenberg1, Matthew N. McCall3, Marc K. Halushka1* 5 6 7 1 Department of Pathology, Johns Hopkins University SOM, Baltimore, MD, USA 8 2McKusick-Nathans Institute, Department of Genetic Medicine, Johns Hopkins 9 University SOM, Baltimore, MD, USA 10 3Department of Biostatistics and Computational Biology, University of Rochester 11 Medical Center, Rochester, NY, USA 12 13 14 15 16 Email Addresses: 17 [email protected] 18 [email protected] 19 [email protected] 20 [email protected] 21 [email protected] 22 [email protected] 23 [email protected] 24 25 * Correspondence and address for reprints to: 26 Marc K. Halushka, M.D., Ph.D. 27 Johns Hopkins University School of Medicine 28 Ross Bldg. Rm 632B 29 720 Rutland Avenue 30 Baltimore, MD 21205 31 410-614-8138 (ph) 32 410-502-5862 (fax) 33 [email protected] 34 1 bioRxiv preprint doi: https://doi.org/10.1101/602367; this version posted January 2, 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. -
Aïda Homs Raubert
Epigenetic alterations in autism spectrum disorders (ASD) Aïda Homs Raubert DOCTORAL THESIS UPF 2015 THESIS SUPERVISORS Prof. Luis A. Pérez Jurado Dra. Ivon Cuscó Martí DEPARTAMENT DE CIÈNCIES EXPERIMENTALS I DE LA SALUT Als meus pares, a l’Alexandra a l’Agustí i als bessons que vindran iii ACKNOWLEDGEMENTS Aquesta no és nomes la meva tesi, en ella han contribuït moltes persones, tant de l’entorn del parc de recerca, de terres lleidatanes, Berguedanes i fins i tot de l’altra banda de l’Atlàntic. Primer, volia agrair als directors de tesi, al Prof. Luis Pérez Jurado i a la Dra. Ivon Cuscó, tot el temps dedicat a revisar i corregir els raonaments i les paraules en aquesta tesi, ja que sempre han tingut la porta oberta per atendre qualsevol dubte. També per haver-me ensenyat una metodologia, un rigor i un llenguatge científic, on l’entrenament és necessari per assolir els conceptes per la recerca en concret, i pel món de la ciència i la genètica. Gràcies per la dedicació, la paciencia, la feina i energia dipositada. No hagués arribat al mateix port si al laboratori no m’hagués trobat amb persones que m’inspiren. Primer de tot, a les nenes: a la Gabi, la companya de vaixell fins i tot el dia de dipositar la tesi, perquè sobretot ens hem sabut acompanyar i entendre malgrat tenir altres maneres de funcionar, gràcies. També a la Marta i la Cristina, que amb la seva honestedat i bona fe, omplen el laboratori de bones energies, gràcies per ser-hi en tot moment.