DOCSLIB.ORG

Tables and Figures

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text

Load more

Supplementary Tables and Figures Supplementary Table S1. List of representative coronaviruses for phylogeny reconstruction and codon usage analysis with ORF1ab Genus Virus Host Length (bp) GenBank AlphaCoV Alpaca respiratory coronavirus CA08-1/2008 Alpaca 27374 JQ410000Accesion AlphaCoV Bat coronavirus BtKYNL63-9a Bat 28363 NC_032107 AlphaCoV Bat coronavirus BtKY229E-1 Bat 27837 KY073747 AlphaCoV Bat coronavirus BtKYNL63-9b Bat 28679 KY073745 AlphaCoV Bat coronavirus HuB2013 Bat 28755 KJ473798 AlphaCoV Bat coronavirus 1A Bat 28326 NC_010437 AlphaCoV Bat coronavirus 008_16/M.bra/FIN/2016 Bat 28119 MN065811 AlphaCoV Bat coronavirus CDPHE15 Bat 28035 NC_022103 AlphaCoV BatMr 008_16/M.bra/FIN/2016 coronavirus SAX2011 Bat 27935 NC_028811 AlphaCoV BatNv coronavirus SC2013 Bat 27783 NC_028833 AlphaCoV BatRf coronavirus YN2012 Bat 26975 NC_028824 AlphaCoV BatRf coronavirus HuB2013 Bat 27608 NC_028814 AlphaCoV Camel coronavirus Riyadh/Ry141/2015 Camel 27395 NC_028752 AlphaCoV Canine coronavirus 1 strain 23/03 Canine 30004 KP849472 AlphaCoV Canine coronavirus strain 1-71 Canine 29462 JQ404409 AlphaCoV Feline alphacoronavirus 1 SB22 Feline 29137 MH817484 AlphaCoV Feline infectious peritonitis virus 79-1146 Feline 29355 NC_002306 AlphaCoV Ferret coronavirus FRCoV-NL-2010 Ferret 28434 NC_030292 AlphaCoV Ferret coronavirus FRCoV4370 Ferret 28550 LC119077 AlphaCoV Hipposideros pomona bat coronavirus CHB25 Hipposideros 28169 MN611525 AlphaCoV Human coronavirus NL63 Human 27553 NC_005831 AlphaCoV Human coronavirus 229E Human 27317 NC_002645 AlphaCoV Miniopterus bat coronavirus HKU8 Miniopterus 28773 NC_010438 AlphaCoV Mink coronavirus WD1127 Minkbat 28941 NC_023760 AlphaCoV Mink coronavirus China/1/2016 Mink 28924 MF113046 AlphaCoV Murine coronavirus AcCoV-JC34 Murine 27682 NC_034972 AlphaCoV Porcine epidemic diarrhea virus Porcine 28033 NC_003436 AlphaCoV Porcine transmissible gastroenteritis virus AHHF Porcine 28614 KX499468 AlphaCoV Rat coronavirus Lucheng-19 Rat 28763 KF294380 AlphaCoV Rhinolophus bat coronavirus HKU32 Rhinolophus 29201 MK720946 AlphaCoV Rhinolophus bat coronavirus HKU2 Rhinolophusbat 27165 NC_009988 AlphaCoV Rousettus bat coronavirus HKU10-183A Rousettusbat 28494 NC_018871 AlphaCoV Scotophilus bat coronavirus 512 Scobat tophilus 28203 NC_009657 AlphaCoV Swine acute diarrhea syndrome Swinebat 27184 MH615810 AlphaCoV Swine enteric coronavirus Swine 28111 NC_028806 AlphaCoV Tylonycteris coronavirus batCH -coronavirusFJWT-2018 HKU33 strain Tylonycteris 27636 MK720944 GZ151867 BetaCoV Bat Italy/213306/2009 coronavirus BM48 -31/BGR/2008 Batbat 29276 NC_014470 BetaCoV Bat coronavirus HKU9-2 Bat 29107 EF065514 BetaCoV Bat coronavirus SC2013 Bat 30423 KJ473821 BetaCoV Bat coronavirus RaTG13 Bat 29855 MN996532 BetaCoV Bat coronavirus HKU3-1 Bat 29728 DQ022305 BetaCoV Bat coronavirus WIV16 Bat 30290 KT444582 BetaCoV Bat coronavirus JPDB144 Bat 30321 KU182965 BetaCoV Bat coronavirus PREDICT/PDF-2180 Bat 29642 NC_034440 Genus Virus Host Length (bp) GenBank BetaCoV Bat coronavirus Rp3/2004 Bat 29736 DQ07161Accesion5 BetaCoV Bat coronavirus Yunnan2011 Bat 29452 JX993988 BetaCoV BatHp coronavirus Zhejiang2013 Bat 31491 NC_025217 BetaCoV Bovine coronavirus ENT Bovine 31028 NC_003045 BetaCoV Canine respiratory coronavirus K37 Canine 31028 JX860640 BetaCoV Civet coronavirus SZ3/2003 Civet 29741 AY304486 BetaCoV Dromedary camel coronavirus HKU23 Dromedary 31075 MN514966 BetaCoV Equine coronavirus NC99 Equinecamel 30992 EF446615 BetaCoV Giraffe HKU23 coronavirus US/OH3/2003 Giraffe 31002 EF424623 BetaCoV Hedgehog coronavirus Hedgehog 30148 NC_039207 BetaCoV Human coronavirus HKU1 Human 29926 NC_006577 BetaCoV Human VMC/DEU/2012 coronavirus OC43 strain Human 30741 NC_006213 BetaCoV Human SARS coronavirus Tor2 Human 29751 NC_004718 BetaCoV Human ATCC VRSA-RS759-CoV -2 strain Wuhan- Human 29903 NC_045512 BetaCoV Human MERS coronavirus Human 30119 NC_019843 BetaCoV HypsugoHu-1 bat coronavirus HKU25 isolate YD131305 Hypsugo bat 30498 KX442564 BetaCoV Murine coronavirus MHV-3 Murine 31448 FJ647224 BetaCoV Pangolin isolate YD131305 coronavirus PCoV_GX-P5L Pangolin 29806 MT040335 BetaCoV Pipistrellus bat coronavirus HKU5 Pipistrellus 30482 NC_009020 BetaCoV PorcineP5L hemagglutinating encephalomyelitis JL/2008 Porcinebat 30684 KY994645 BetaCoV Rabbit coronavirus HKU14 Rabbit 31100 NC_017083 BetaCoV Rat encephalomyelitis coronavirus Parker JL/2008 Rat 31250 NC_012936 BetaCoV Rat Betacoronavirus HKU24 Rat 31249 NC_026011 BetaCoV Rousettus bat coronavirus HKU9 Rousettus 29114 NC_009021 BetaCoV Rousettus bat coronavirus GCCDC1 356 Rousettusbat 30161 NC_030886 BetaCoV Sable antelope coronavirus US/OH1/2003 Sablebat 30995 EF424621 BetaCoV Tylonycteris bat coronavirus HKU4 Tylonycterisantelope 30286 NC_009019 BetaCoV Water US/OH1/2003 deer coronavirus W17-18 Waterbat deer 31034 MG518518 BetaCoV Yak coronavirus YAK/HY24/CH/2017 Yak 31032 MH810163 DeltaCoV Bulbul coronavirus HKU11-934 Bulbul 26487 NC_011547 DeltaCoV Common YAK/HY24/CH/2017 moorhen coronavirus HKU21 Common 26223 NC_016996 DeltaCoV Magpie-robin coronavirus HKU18 Magpiemoorhen-robin 26689 NC_016993 DeltaCoV Munia HKU21 coronavirus HKU13-3514 Munia 26552 NC_011550 DeltaCoV Night heron coronavirus HKU19 Night 26077 NC_016994 DeltaCoV Porcine coronavirus HKU15-155 Porcine 25425 NC_039208 DeltaCoV Sparrow coronavirus HKU17 Sparrow 26083 NC_016992 DeltaCoV Thrush coronavirus HKU12-600 Thrush 26396 NC_011549 DeltaCoV White-eye coronavirus HKU16 White-eye 26041 NC_016991 DeltaCoV Wigeon coronavirus HKU20 Wigeon 26227 NC_016995 GammaCoV Avian infectious bronchitis virus Avian 27608 NC_001451 GammaCoV Beluga whale coronavirus SW1 Beluga 31686 NC_010646 GammaCoV Bottlenose dolphin coronavirus HKU22 strain Bottlenosewhale 31769 KF793824 dolphin GammaCoV CF090325Duck coronavirus CF090325 DK/GD/27/2014 Duck 27754 KM454473 GammaCoV Pheasant coronavirus ph/China/I0710/17 Pheasant 27655 MK423876 GammaCoV Turkey coronavirus MG10 Turkey 27657 NC_010800 CF090325 ph/China/I0710/17 Supplementary Table S2. Acknowledgement Table for the 2,574 SARS-CoV-2 isolates retrieved from GISAID (www.gisaid.org) Excel Table Tree Base Composition 100 BetaCoV|Civet_coronavirus_SZ3/2003 100 ● BetaCoV|Human_SARS_coronavirus_Tor2 100 BetaCoV|Bat_coronavirus_WIV16 100 0.5 BetaCoV|Bat_coronavirus_Rp3/2004 100 BetaCoV|Bat_coronavirus_Yunnan2011 BetaCoV|Bat_coronavirus_HKU3−1 100 BetaCoV|Bat_coronavirus_RaTG13 100 100 ● BetaCoV|Human_SARS−CoV−2_strain_Wuhan−Hu−1 100 BetaCoV|Pangolin_coronavirus_PCoV_GX−P5L BetaCoV|Bat_coronavirus_BM48−31/BGR/2008 75 BetaCoV|BatHp_coronavirus_Zhejiang2013 100 BetaCoV|Bat_coronavirus_HKU9−2 100 BetaCoV|Rousettus_bat_coronavirus_HKU9 BetaCoV|Rousettus_bat_coronavirus_GCCDC1_356 100 100 BetaCoV|Bat_coronavirus_SC2013 100 BetaCoV|Hypsugo_bat_coronavirus_HKU25_isolate_YD131305 100 BetaCoV|Bat_coronavirus_PREDICT/PDF−2180 86 ● BetaCoV|Human_MERS_coronavirus 100 BetaCoV|Bat_coronavirus_JPDB144 100 100 BetaCoV|Tylonycteris_bat_coronavirus_HKU4 BetaCoV|Pipistrellus_bat_coronavirus_HKU5 BetaCoV|Hedgehog_coronavirus_VMC/DEU/2012 100 BetaCoV|Sable_antelope_coronavirus_US/OH1/2003 100 BetaCoV|Giraffe_coronavirus_US/OH3/2003 100 100 BetaCoV|Bovine_coronavirus_ENT 100 BetaCoV|Water_deer_coronavirus_W17−18 10094 BetaCoV|Canine_respiratory_coronavirus_K37 100 BetaCoV|Yak_coronavirus_YAK/HY24/CH/2017 100 BetaCoV|Dromedary_camel_coronavirus_HKU23 ● BetaCoV|Human_coronavirus_OC43_strain_ATCC_VR−759 100 BetaCoV|Porcine_hemagglutinating_encephalomyelitis_JL/2008 100 BetaCoV|Equine_coronavirus_NC99 100 BetaCoV|Rabbit_coronavirus_HKU14 100 BetaCoV|Rat_Betacoronavirus_HKU24 100 100 BetaCoV|Murine_coronavirus_MHV−3 BetaCoV|Rat_coronavirus_Parker ● BetaCoV|Human_coronavirus_HKU1 100 AlphaCoV|Rhinolophus_bat_coronavirus_HKU32 100 AlphaCoV|BatRf_coronavirus_HuB2013 100 AlphaCoV|Hipposideros_pomona_bat_coronavirus_CHB25 Base 78 AlphaCoV|Rousettus_bat_coronavirus_HKU10−183A 96 AlphaCoV|Bat_coronavirus_008_16/M.bra/FIN/2016 A 100 AlphaCoV|Scotophilus_bat_coronavirus_512 100 AlphaCoV|Porcine_epidemic_diarrhea_virus 100 G AlphaCoV|Bat_coronavirus_CDPHE15 100 100 AlphaCoV|Bat_coronavirus_HuB2013 100 AlphaCoV|Miniopterus_bat_coronavirus_HKU8 U 100 AlphaCoV|Bat_coronavirus_1A 100 AlphaCoV|Tylonycteris_bat_coronavirus_HKU33_strain_GZ151867 C 100 AlphaCoV|BatNv_coronavirus_SC2013 100 AlphaCoV|Alpaca_respiratory_coronavirus_CA08−1/2008 100 AlphaCoV|Camel_coronavirus_Riyadh/Ry141/2015 100 ● AlphaCoV|Human_coronavirus_229E 100 AlphaCoV|Bat_coronavirus_BtKY229E−1 98 100 AlphaCoV|Bat_coronavirus_BtKYNL63−9a 100 ● AlphaCoV|Human_coronavirus_NL63 AlphaCoV|Bat_coronavirus_BtKYNL63−9b AlphaCoV|BatMr_coronavirus_SAX2011 100 AlphaCoV|Swine_acute_diarrhea_syndrome_coronavirus_CH−FJWT−2018 100 AlphaCoV|Rhinolophus_bat_coronavirus_HKU2 100 AlphaCoV|BatRf_coronavirus_YN2012 100 AlphaCoV|Canine_coronavirus_strain_1−71 100 AlphaCoV|Canine_coronavirus_1_strain_23/03 100 AlphaCoV|Porcine_transmissible_gastroenteritis_virus_AHHF 100 AlphaCoV|Swine_enteric_coronavirus_Italy/213306/2009 100 100 AlphaCoV|Feline_alphacoronavirus_1_SB22 100 AlphaCoV|Feline_infectious_peritonitis_virus_79−1146 100 AlphaCoV|Ferret_coronavirus_FRCoV4370 100 AlphaCoV|Ferret_coronavirus_FRCoV−NL−2010 100 AlphaCoV|Mink_coronavirus_China/1/2016 AlphaCoV|Mink_coronavirus_WD1127 100 AlphaCoV|Murine_coronavirus_AcCoV−JC34 AlphaCoV|Rat_coronavirus_Lucheng−19 100 DeltaCoV|Porcine_coronavirus_HKU15−155 100 DeltaCoV|Sparrow_coronavirus_HKU17 100 DeltaCoV|Magpie−robin_coronavirus_HKU18 100 DeltaCoV|Munia_coronavirus_HKU13−3514 100 DeltaCoV|Bulbul_coronavirus_HKU11−934 100 99 DeltaCoV|Thrush_coronavirus_HKU12−600
Recommended publications
  • Predicting Hosts Based on Early SARS-Cov-2 Samples And

    Predicting Hosts Based on Early SARS-Cov-2 Samples And

    www.nature.com/scientificreports OPEN Predicting hosts based on early SARS‑CoV‑2 samples and analyzing the 2020 pandemic Qian Guo1,2,3,7, Mo Li4,7, Chunhui Wang4,7, Jinyuan Guo1,3,7, Xiaoqing Jiang1,2,5,7, Jie Tan1, Shufang Wu1,2, Peihong Wang1, Tingting Xiao6, Man Zhou1,2, Zhencheng Fang1,2, Yonghong Xiao6* & Huaiqiu Zhu1,2,3,5* The SARS‑CoV‑2 pandemic has raised concerns in the identifcation of the hosts of the virus since the early stages of the outbreak. To address this problem, we proposed a deep learning method, DeepHoF, based on extracting viral genomic features automatically, to predict the host likelihood scores on fve host types, including plant, germ, invertebrate, non‑human vertebrate and human, for novel viruses. DeepHoF made up for the lack of an accurate tool, reaching a satisfactory AUC of 0.975 in the fve‑ classifcation, and could make a reliable prediction for the novel viruses without close neighbors in phylogeny. Additionally, to fll the gap in the efcient inference of host species for SARS‑CoV‑2 using existing tools, we conducted a deep analysis on the host likelihood profle calculated by DeepHoF. Using the isolates sequenced in the earliest stage of the COVID‑19 pandemic, we inferred that minks, bats, dogs and cats were potential hosts of SARS‑CoV‑2, while minks might be one of the most noteworthy hosts. Several genes of SARS‑CoV‑2 demonstrated their signifcance in determining the host range. Furthermore, a large‑scale genome analysis, based on DeepHoF’s computation for the later pandemic in 2020, disclosed the uniformity of host range among SARS‑CoV‑2 samples and the strong association of SARS‑CoV‑2 between humans and minks.
  • On the Coronaviruses and Their Associations with the Aquatic Environment and Wastewater

    On the Coronaviruses and Their Associations with the Aquatic Environment and Wastewater

    water Review On the Coronaviruses and Their Associations with the Aquatic Environment and Wastewater Adrian Wartecki 1 and Piotr Rzymski 2,* 1 Faculty of Medicine, Poznan University of Medical Sciences, 60-812 Pozna´n,Poland; [email protected] 2 Department of Environmental Medicine, Poznan University of Medical Sciences, 60-806 Pozna´n,Poland * Correspondence: [email protected] Received: 24 April 2020; Accepted: 2 June 2020; Published: 4 June 2020 Abstract: The outbreak of Coronavirus Disease 2019 (COVID-19), a severe respiratory disease caused by betacoronavirus SARS-CoV-2, in 2019 that further developed into a pandemic has received an unprecedented response from the scientific community and sparked a general research interest into the biology and ecology of Coronaviridae, a family of positive-sense single-stranded RNA viruses. Aquatic environments, lakes, rivers and ponds, are important habitats for bats and birds, which are hosts for various coronavirus species and strains and which shed viral particles in their feces. It is therefore of high interest to fully explore the role that aquatic environments may play in coronavirus spread, including cross-species transmissions. Besides the respiratory tract, coronaviruses pathogenic to humans can also infect the digestive system and be subsequently defecated. Considering this, it is pivotal to understand whether wastewater can play a role in their dissemination, particularly in areas with poor sanitation. This review provides an overview of the taxonomy, molecular biology, natural reservoirs and pathogenicity of coronaviruses; outlines their potential to survive in aquatic environments and wastewater; and demonstrates their association with aquatic biota, mainly waterfowl. It also calls for further, interdisciplinary research in the field of aquatic virology to explore the potential hotspots of coronaviruses in the aquatic environment and the routes through which they may enter it.
  • Hydroxychloroquine Or Chloroquine for Treating Coronavirus Disease 2019 (COVID-19) – a PROTOCOL for a Systematic Review of Individual Participant Data

    Hydroxychloroquine Or Chloroquine for Treating Coronavirus Disease 2019 (COVID-19) – a PROTOCOL for a Systematic Review of Individual Participant Data

    Hydroxychloroquine or Chloroquine for treating Coronavirus Disease 2019 (COVID-19) – a PROTOCOL for a systematic review of Individual Participant Data Authors Fontes LE, Riera R, Miranda E, Oke J, Heneghan CJ, Aronson JK, Pacheco RL, Martimbianco ALC, Nunan D BACKGROUND In the face of the pandemic of SARS CoV2, urgent research is needed to test potential therapeutic agents against the disease. Reliable research shall inform clinical decision makers. Currently, there are several studies testing the efficacy and safety profiles of different pharmacological interventions. Among these drugs, we can cite antimalarial, antivirals, biological drugs, interferon, etc. As of 6 April 2020 there are three published reportsand 100 ongoing trials testing hydroxychloroquine/chloroquine alone or in association with other drugs for COVID-19. This prospective systematic review with Individual Participant data aims to assess the rigour of the best-available evidence for hydroxychloroquine or chloroquine as treatment for COVID-19 infection. The PICO framework is: P: adults with COVID-19 infection I: chloroquine or hydroxychloroquine (alone or in association) C: placebo, other active treatments, usual standard care without antimalarials O: efficacy and safety outcomes OBJECTIVES To assess the effects (benefits and harms) of chloroquine or hydroxychloroquine for the treatment of COVID-19 infection. METHODS Criteria for considering studies for this review Types of studies We shall include randomized controlled trials (RCTs) with a parallel design. We intend to include even small trials (<50 participants), facing the urgent need for evidence to respond to the current pandemic. Quasi-randomized, non-randomized, or observational studies will be excluded due to a higher risk of confounding and selection bias (1).
  • Complete Sections As Applicable

    Complete Sections As Applicable

    This form should be used for all taxonomic proposals. Please complete all those modules that are applicable (and then delete the unwanted sections). For guidance, see the notes written in blue and the separate document “Help with completing a taxonomic proposal” Please try to keep related proposals within a single document; you can copy the modules to create more than one genus within a new family, for example. MODULE 1: TITLE, AUTHORS, etc (to be completed by ICTV Code assigned: 2010.023a-dV officers) Short title: A new genus and three new species in the subfamily Coronavirinae (e.g. 6 new species in the genus Zetavirus) Modules attached 1 2 3 4 5 (modules 1 and 9 are required) 6 7 8 9 Author(s) with e-mail address(es) of the proposer: Raoul J. de Groot and Alexander E. Gorbalenya List the ICTV study group(s) that have seen this proposal: A list of study groups and contacts is provided at http://www.ictvonline.org/subcommittees.asp . If Submission on behalf of the Coronavirus Study in doubt, contact the appropriate subcommittee Group. Authors are CSG members (R.J de chair (fungal, invertebrate, plant, prokaryote or Groot, Chair) vertebrate viruses) ICTV-EC or Study Group comments and response of the proposer: Date first submitted to ICTV: Date of this revision (if different to above): Page 1 of 5 MODULE 2: NEW SPECIES Code 2010.023aV (assigned by ICTV officers) To create new species within: Genus: Deltacoronavirus (new) Subfamily: Coronavirinae Family: Coronaviridae Order: Nidovirales And name the new species: GenBank sequence accession number(s) of reference isolate: Bulbul coronavirus HKU11 [FJ376619] Thrush coronavirus HKU12 [FJ376621=NC_011549] Munia coronavirus HKU13 [FJ376622=NC_011550] Reasons to justify the creation and assignment of the new species: According to the demarcation criteria as outlined in Module 3 and agreed upon by the Coronavirus Study Group, the new coronaviruses isolated from Bulbul, Thrush and Munia are representatives of separates species.
  • Coronaviruses in Avian Species – Review with Focus on Epidemiology and Diagnosis in Wild Birds

    Coronaviruses in Avian Species – Review with Focus on Epidemiology and Diagnosis in Wild Birds

    J Vet Res 62, 249-255, 2018 DOI:10.2478/jvetres-2018-0035 REVIEW ARTICLE Coronaviruses in avian species – review with focus on epidemiology and diagnosis in wild birds Justyna Miłek, Katarzyna Blicharz-Domańska Department of Poultry Diseases, National Veterinary Research Institute, 24-100 Puławy, Poland [email protected] Received: May 2, 2018 Accepted: September 19, 2018 Abstract Coronaviruses (CoVs) are a large group of enveloped viruses with a single-strand RNA genome, which continuously circulate in mammals and birds and pose a threat to livestock, companion animals, and humans. CoVs harboured by avian species are classified to the genera gamma- and deltacoronaviruses. Within the gamma-CoVs the main representative is avian coronavirus, a taxonomic name which includes the highly contagious infectious bronchitis viruses (IBVs) in chickens and similar viruses infecting other domestic birds such as turkeys, guinea fowls, or quails. Additionally, IBVs have been detected in healthy wild birds, demonstrating that they may act as the vector between domestic and free-living birds. Moreover, CoVs other than IBVs, are identified in wild birds, which suggests that wild birds play a key role in the epidemiology of other gammaCoVs and deltaCoVs. Development of molecular techniques has significantly improved knowledge of the prevalence of CoVs in avian species. The methods adopted in monitoring studies of CoVs in different avian species are mainly based on detection of conservative regions within the viral replicase, nucleocapsid genes, and 3’UTR or 5’UTR. The purpose of this review is to summarise recent discoveries in the areas of epidemiology and diagnosis of CoVs in avian species and to understand the role of wild birds in the virus distribution.
  • Evolutionary Trajectory for the Emergence of Novel Coronavirus SARS-Cov-2

    Evolutionary Trajectory for the Emergence of Novel Coronavirus SARS-Cov-2

    Article Evolutionary Trajectory for the Emergence of Novel Coronavirus SARS-CoV-2 Saif ur Rehman 1, Laiba Shafique 1, Awais Ihsan 2,3,* and Qingyou Liu 1,* 1 State Key Laboratory for Conservation and Utilization of Subtropical Agro-bioresources of Guangxi University, Nanning 530005, China; [email protected] (S.u.R.), [email protected] (L.A.) 2 Department of Biosciences, COMSATS University Islamabad, Sahiwal Campus 57000, Pakistan 3 College of Pharmacy, South Central University for Nationalities, Wuhan 430074, China * Correspondence: [email protected] (A.I.) and [email protected] (Q.L.); Tel.: +8613878805296 Received: 3 March 2020; Accepted: 21 March 2020; Published: 23 March 2020 Table S1. Coronavirus and their NCBI accession numbers used for phylogenetic analysis. NCBI accession Strain Full Name number NC_038861.1 TGEV Purdue Transmissible gastroenteritis virus DQ811787.1 PRCV ISU-1 porcine respiratory coronavirus DQ848678.1 FCoV C1Je Feline coronavirus NC_005831.2 HCoV-NL63 Human Coronavirus NL63 NC_002645.1 HCoV-229E Human coronavirus 229E EU420139.1 Mi-BatCoV AFCD77 Miniopterus bat coronavirus EU420137.1 Mi-BatCoV 1B AFCD307 Bat coronavirus 1B strain AFCD307 NC_010437.1 Mi-BatCoV 1A AFCD62 Bat coronavirus 1A NC_018871.1 Ro-BatCoV HKU10 Rousettus bat coronavirus HKU10 NC_022103.1 BatCoV CDPHE15/USA/2006 BatCoV CDPHE15/USA/2006 NC_009657.1 Sc BatCoV 512/2005 Scotophilus bat coronavirus AF353511.1 PEDV CV777 Porcine epidemic diarrhea virus strain CV777 KU131570.1 HCoV-OC43 Human coronavirus OC43 strain DQ011855.1
  • Discovery of Bat Coronaviruses Through Surveillance and Probe Capture-Based Next-Generation Sequencing

    Discovery of Bat Coronaviruses Through Surveillance and Probe Capture-Based Next-Generation Sequencing

    RESEARCH ARTICLE Clinical Science and Epidemiology Discovery of Bat Coronaviruses through Surveillance and Probe Capture-Based Next-Generation Sequencing Bei Li,a Hao-Rui Si,a,b Yan Zhu,a Xing-Lou Yang,a Danielle E. Anderson,c Zheng-Li Shi,a Lin-Fa Wang,c Peng Zhoua aCAS Key Laboratory of Special Pathogens, Wuhan Institute of Virology, Center for Biosafety Mega-Science, Chinese Academy of Sciences, Wuhan, China bUniversity of Chinese Academy of Sciences, Beijing, China cProgramme in Emerging Infectious Diseases, Duke-NUS Medical School, Singapore, Singapore Bei Li and Hao-Rui Si contributed equally. Author order was determined by the importance of their work. ABSTRACT Coronaviruses (CoVs) of bat origin have caused two pandemics in this century. Severe acute respiratory syndrome (SARS)-CoV and Middle East respiratory syndrome (MERS)-CoV both originated from bats, and it is highly likely that bat coronaviruses will cause future outbreaks. Active surveillance is both urgent and essential to predict and mitigate the emergence of these viruses in humans. Next-generation sequencing (NGS) is currently the preferred methodology for vi- rus discovery to ensure unbiased sequencing of bat CoVs, considering their high genetic diversity. However, unbiased NGS is an expensive methodology and is prone to missing low-abundance CoV sequences due to the high background level of nonviral sequences present in surveillance field samples. Here, we employ a capture-based NGS approach using baits targeting most of the CoV species. Using this technology, we effectively reduced sequencing costs by increasing the sensitiv- ity of detection. We discovered nine full genomes of bat CoVs in this study and re- vealed great genetic diversity for eight of them.
  • Characterization of Codon Usage Pattern in SARS- Cov-2

    Characterization of Codon Usage Pattern in SARS- Cov-2

    Characterization of Codon Usage Pattern in SARS- CoV-2 Wei Hou ( [email protected] ) Short report Keywords: COVID-19, coronaviruses, SARS-CoV-2, codon usage pattern Posted Date: August 6th, 2020 DOI: https://doi.org/10.21203/rs.3.rs-21553/v2 License: This work is licensed under a Creative Commons Attribution 4.0 International License. Read Full License Version of Record: A version of this preprint was published on September 14th, 2020. See the published version at https://doi.org/10.1186/s12985-020-01395-x. Page 1/17 Abstract The outbreak of coronavirus disease 2019 (COVID-19) due to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has posed signicant threats to international health. The genetic traits as well as evolutionary processes in this novel coronavirus are not fully characterized, and their roles in viral pathogenesis are yet largely unknown. To get a better picture of the codon architecture of this newly emerging coronavirus, in this study we perform bioinformatic analysis, based on publicly available nucleotide sequences of SARS-CoV-2 along with those of other members of human coronaviruses as well as non-human coronaviruses in different hosts, to take a snapshot of the genome-wide codon usage pattern of SARS-CoV-2 and uncover that all over-represented codons end with A/U and this newly emerging coronavirus has a relatively low codon usage bias, which is shaped by both mutation pressure and natural selection. Additionally, there is slight variation in the codon usage pattern among the SARS- CoV-2 isolates from different geo-locations.
  • Avian Coronavirus in Wild Aquatic Birds

    Avian Coronavirus in Wild Aquatic Birds

    Avian Coronavirus in Wild Aquatic Birds Daniel K. W. Chu, Connie Y. H. Leung, Martin Gilbert, Priscilla H. Joyner, Erica M. Ng, Tsemay M. Tse, Yi Guan, Joseph S. M. Peiris and Leo L. M. Poon J. Virol. 2011, 85(23):12815. DOI: 10.1128/JVI.05838-11. Published Ahead of Print 28 September 2011. Downloaded from Updated information and services can be found at: http://jvi.asm.org/content/85/23/12815 http://jvi.asm.org/ These include: SUPPLEMENTAL MATERIAL http://jvi.asm.org/content/suppl/2011/10/27/85.23.12815.DC1.ht ml on January 22, 2012 by Glasgow University Library REFERENCES This article cites 25 articles, 12 of which can be accessed free at: http://jvi.asm.org/content/85/23/12815#ref-list-1 CONTENT ALERTS Receive: RSS Feeds, eTOCs, free email alerts (when new articles cite this article), more» Information about commercial reprint orders: http://jvi.asm.org/site/misc/reprints.xhtml To subscribe to to another ASM Journal go to: http://journals.asm.org/site/subscriptions/ JOURNAL OF VIROLOGY, Dec. 2011, p. 12815–12820 Vol. 85, No. 23 0022-538X/11/$12.00 doi:10.1128/JVI.05838-11 Copyright © 2011, American Society for Microbiology. All Rights Reserved. Avian Coronavirus in Wild Aquatic Birdsᰔ†‡ Daniel K. W. Chu,1 Connie Y. H. Leung,1 Martin Gilbert,2 Priscilla H. Joyner,2 Erica M. Ng,1 Tsemay M. Tse,1 Yi Guan,1 Joseph S. M. Peiris,1,3* and Leo L. M. Poon1* State Key Laboratory for Emerging Infectious Diseases, Department of Microbiology and Research Centre of Infection and Immunology, The University of Hong Kong, Hong Kong Special Administrative Region, China1; Wildlife Conservation Society, Cambodia2; and HKU-Pasteur Research Centre, Hong Kong Special Administrative Region, China3 Downloaded from Received 29 July 2011/Accepted 16 September 2011 We detected a high prevalence (12.5%) of novel avian coronaviruses in aquatic wild birds.
  • Gammacoronavirus and Deltacoronavirus of Avian

    Gammacoronavirus and Deltacoronavirus of Avian

    Discovery of Seven Novel Mammalian and Avian Coronaviruses in the Genus Downloaded from Deltacoronavirus Supports Bat Coronaviruses as the Gene Source of Alphacoronavirus and Betacoronavirus and Avian Coronaviruses as the Gene Source of Gammacoronavirus and Deltacoronavirus http://jvi.asm.org/ Patrick C. Y. Woo, Susanna K. P. Lau, Carol S. F. Lam, Candy C. Y. Lau, Alan K. L. Tsang, John H. N. Lau, Ru Bai, Jade L. L. Teng, Chris C. C. Tsang, Ming Wang, Bo-Jian Zheng, Kwok-Hung Chan and Kwok-Yung Yuen J. Virol. 2012, 86(7):3995. DOI: 10.1128/JVI.06540-11. Published Ahead of Print 25 January 2012. on February 11, 2014 by sanofi-aventis Scientific Information & Library Services US Updated information and services can be found at: http://jvi.asm.org/content/86/7/3995 These include: SUPPLEMENTAL MATERIAL Supplemental material REFERENCES This article cites 53 articles, 31 of which can be accessed free at: http://jvi.asm.org/content/86/7/3995#ref-list-1 CONTENT ALERTS Receive: RSS Feeds, eTOCs, free email alerts (when new articles cite this article), more» Information about commercial reprint orders: http://journals.asm.org/site/misc/reprints.xhtml To subscribe to to another ASM Journal go to: http://journals.asm.org/site/subscriptions/ Discovery of Seven Novel Mammalian and Avian Coronaviruses in the Genus Deltacoronavirus Supports Bat Coronaviruses as the Gene Downloaded from Source of Alphacoronavirus and Betacoronavirus and Avian Coronaviruses as the Gene Source of Gammacoronavirus and Deltacoronavirus http://jvi.asm.org/ Patrick C. Y. Woo,a,b,c,d Susanna K. P. Lau,a,b,c,d Carol S.
  • Comparative Transcriptome Profiling of Human and Pig Intestinal Epithelial Cells After

    Comparative Transcriptome Profiling of Human and Pig Intestinal Epithelial Cells After

    Comparative transcriptome profiling of human and pig intestinal epithelial cells after Deltacoronavirus infection Thesis Presented in Partial Fulfillment of the Requirements for the Degree Master of Science in the Graduate School of The Ohio State University By Diana Cruz Pulido, MSc Graduate Program in Comparative and Veterinary Medicine. The Ohio State University 2020 Thesis Committee: Scott P. Kenney, PhD, Advisor Vanessa Hale, DVM, PhD Anastasia Vlasova, DVM, PhD Copyrighted by Diana Cruz Pulido 2020 Abstract Porcine deltacoronavirus (PDCoV) is an emerging global infectious disease of the swine industry with unknown potential to cause human disease. Phylogenetic analysis suggests that PDCoV originated relatively recently from a host-switching event between birds and mammals. Little is known about how PDCoV interacts with its differing hosts. Although human derived cell lines are susceptible to PDCoV infection, there is no direct evidence that PDCoV causes morbidity in humans. Currently, there are no treatments or vaccines available for PDCoV partially due to the mechanisms of infection remaining unknown. In this study, we explored the gene expression profiles of the primary host organism (swine) to a potential novel host (humans) after infection with PDCoV. For this we utilized cell lines derived from intestinal lineages to reproduce the primary sites of viral infection in the host. Porcine intestinal epithelial cells (IPEC-J2) and human intestinal epithelial cells (HIEC) were infected with PDCoV. At 24 h post infection, total cellular RNA was harvested and analyzed using RNA-sequencing (RNA-seq) technology. We found that there are more differentially expressed genes (DEGs) in humans, 7,486, in comparison to pigs, 1134.
  • Journal of General Virology

    Journal of General Virology

    Journal of General Virology Discovery of a novel nidovirus in cattle with respiratory disease --Manuscript Draft-- Manuscript Number: VIR-D-14-00290R1 Full Title: Discovery of a novel nidovirus in cattle with respiratory disease Short Title: Genetic characterization of a novel nidovirus in cattle Article Type: Short Communication Section/Category: Animal - Positive-strand RNA Viruses Corresponding Author: Rafal Tokarz Columbia University New York, NY UNITED STATES First Author: Rafal Tokarz Order of Authors: Rafal Tokarz Stephen Sameroff Richard A. Hesse Ben M. Hause Aaloki Desai Komal Jain W. Ian Lipkin Abstract: The family Coronaviridae represents a diverse group of vertebrate RNA viruses, all with genomes greater than 26,000 nucleotides. Here, we report the discovery and genetic characterization of a novel virus present in cattle with respiratory disease. Phylogenetic characterization of this virus revealed that it clusters within Torovirinae, a subfamily of Coronaviridae. The complete genome consists of only 20,261 nucleotides, and represents the smallest reported Coronaviridae genome. We identified seven open reading frames, including the canonical nidovirus open reading frames 1a and b. Analysis of polyprotein 1ab revealed that this virus, tentatively named bovine nidovirus (BoNV), shares the highest homology with the recently described python-borne nidoviruses and contains several conserved nidovirus motifs, but does not encode the NendoU or O-MT domains that are present in other viruses within Coronaviridae. In concert with its reduced genome, the atypical domain architecture indicates that this virus represents a unique lineage within the order Nidovirales. Powered by Editorial Manager® and ProduXion Manager® from Aries Systems Corporation Manuscript Including References (Word document) Click here to download Manuscript Including References (Word document): BoNV MANUSCRIPT REVISION A.docx 1 Discovery of a novel nidovirus in cattle with respiratory disease 2 3 Rafal Tokarz1 *, Stephen Sameroff1, Richard A.