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Research Article | Ecological and Evolutionary Science

Comparative Genomic Analysis of Rapidly Evolving SARS-CoV-2 Reveals Mosaic Pattern of Phylogeographical Distribution

Roshan Kumar, Helianthous Verma, Nirjara Singhvi, Utkarsh Sood, Vipin Gupta, Mona Singh, Rashmi Kumari, Princy Hira, Shekhar Nagar, Chandni Talwar, Namita Nayyar, Shailly Anand, Charu Dogra Rawat, Mansi Verma, Ram Krishan Negi, Yogendra Singh, Rup Lal
Ileana M. Cristea, Editor
Roshan Kumar
aP.G. Department of Zoology, Magadh University, Bodh Gaya, Bihar, India
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Helianthous Verma
bDepartment of Zoology, Ramjas College, University of Delhi, Delhi, India
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Nirjara Singhvi
cDepartment of Zoology, University of Delhi, Delhi, India
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Utkarsh Sood
dThe Energy and Resources Institute, New Delhi, India
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Vipin Gupta
ePhiXGen Private Limited, Gurugram, Haryana, India
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Mona Singh
ePhiXGen Private Limited, Gurugram, Haryana, India
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Rashmi Kumari
fDepartment of Zoology, College of Commerce, Arts & Science, Patliputra University, Patna, Bihar, India
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Princy Hira
gDepartment of Zoology, Maitreyi College, University of Delhi, New Delhi, India
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Shekhar Nagar
cDepartment of Zoology, University of Delhi, Delhi, India
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Chandni Talwar
cDepartment of Zoology, University of Delhi, Delhi, India
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Namita Nayyar
hDepartment of Zoology, Sri Venkateswara College, University of Delhi, New Delhi, India
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Shailly Anand
iDepartment of Zoology, Deen Dayal Upadhyaya College, University of Delhi, New Delhi, India
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Charu Dogra Rawat
bDepartment of Zoology, Ramjas College, University of Delhi, Delhi, India
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Mansi Verma
hDepartment of Zoology, Sri Venkateswara College, University of Delhi, New Delhi, India
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Ram Krishan Negi
cDepartment of Zoology, University of Delhi, Delhi, India
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Yogendra Singh
cDepartment of Zoology, University of Delhi, Delhi, India
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Rup Lal
dThe Energy and Resources Institute, New Delhi, India
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Ileana M. Cristea
Princeton University
Roles: Editor
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DOI: 10.1128/mSystems.00505-20
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  • FIG 1
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    FIG 1

    (A) Core genome-based phylogenetic analysis of SARS-CoV-2 isolates using the maximum likelihood method based on the Tamura-Nei model. The analysis involved 95 SARS-CoV-2 sequences with a total of 28,451 nucleotide positions. Bootstrap values of more than 70% are shown on branches as blue dots with sizes corresponding to the bootstrap values. The colored circle represents the country of origin of each isolate. The two isolates from Wuhan are marked separately on the outer side of the ring. (B) The minimum spanning tree generated using maximum likelihood method and Tamura-Nei model showing the genetic relationships of SARS-CoV-2 isolates with their geographical distribution.

  • FIG 2
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    FIG 2

    (A) SNP-based phylogeny of SARS-CoV-2 isolates. Highly similar genomes of coronaviruses were taken as the input by Parsnp. Whole-genome alignments were made using libMUSCLE aligner and the annotated genome of MT121215 strain as the reference. Parsnp identifies the maximal unique matches (MUMs) among the query genomes provided in a single directory. As only the genomes corresponding to a specified MUM index (MUMI) distance threshold are recruited, option -c was used to force inclusion of all the strains. The output phylogeny based on single nucleotide polymorphisms was obtained following variant calling on core-genome alignment. (B) Multiple-sequence alignment of ORF1b protein showing amino acid substitutions at three positions: P1327L, Y1364C, and S2540F. The isolate USA/MN1-MDH1/2020 (MT188341) showed an amino acid addition leading to a change in an amino acid frame from position 2540 onward. (C and D) 2D and 3D structures for nsp16 in the wild-type strain (MT121215) and the mutant strain (MT188341) predicted using PDBsum and SWISS-MODEL. (E) Ramachandran plot of the predicted wild-type and mutant proteins, where the green region represents a most-favored region whereas the light green area denotes an allowed region. The white zone represents a generously allowed region.

  • FIG 3
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    FIG 3

    SARS-CoV-2–host interactome and its functional annotation. (A) SARS-CoV-2-host interaction map predicted using the IntAct database, showing human proteins interacting with 10 viral proteins. (B) Gene ontology (GO) analysis was performed for host proteins interacting with ORF1ab using the ClueGo Cytoscape app against database KEGG, the Gene Ontology—biological function database, and Reactome pathways. ClueGo parameters were set as follows: Go Term Fusion selected; P values of ≤0.05; GO tree interval, all levels; kappa score of 0.42.

  • FIG 4
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    FIG 4

    Estimation of purifying natural selection pressure in nine coding sequences of SARS-CoV-2. dN/dS values are plotted as a function of dS.

Tables

  • Figures
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  • TABLE 1

    General genomic attributes of SARS-CoV-2 strains

    TABLE 1
  • TABLE 2

    Major mutations present in different isolates of SARS-CoV-2 at different locations

    TABLE 2
    • ↵a NA, information not available.

Supplemental Material

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  • FIG S1

    Phylogeny construction of (A) nucleocapsid and (B) spike proteins of 95 SARS-CoV2 strains isolated from synanthropic animals. The accession numbers of the proteins are given in parentheses. The sequences were aligned using the MUSCLE (76) aligner, and phylogeny was constructed at MEGAX using the neighbor joining method (73) and visualized in interactive Tree of Life (iTOL) (74). Download FIG S1, PDF file, 0.04 MB.

    Copyright © 2020 Kumar et al.

    This content is distributed under the terms of the Creative Commons Attribution 4.0 International license.

  • TABLE S1

    The amino acid mutations in S-protein of SARS-CoV-2 isolates. Download Table S1, DOCX file, 0.01 MB.

    Copyright © 2020 Kumar et al.

    This content is distributed under the terms of the Creative Commons Attribution 4.0 International license.

  • TABLE S2

    List of host (human) proteins showing significant interaction with viral proteins. Download Table S2, XLSX file, 0.02 MB.

    Copyright © 2020 Kumar et al.

    This content is distributed under the terms of the Creative Commons Attribution 4.0 International license.

  • FIG S2

    Functional analysis of SARS-CoV-2–host interactome. Gene ontology (GO) analysis was performed for host proteins interacting with M, NSP8, E, S, and ORF7a by the use of the ClueGo Cytoscape app against database KEGG, Gene Ontology (biological function database), and Reactome pathways. Download FIG S2, EPS file, 0.7 MB.

    Copyright © 2020 Kumar et al.

    This content is distributed under the terms of the Creative Commons Attribution 4.0 International license.

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Comparative Genomic Analysis of Rapidly Evolving SARS-CoV-2 Reveals Mosaic Pattern of Phylogeographical Distribution
Roshan Kumar, Helianthous Verma, Nirjara Singhvi, Utkarsh Sood, Vipin Gupta, Mona Singh, Rashmi Kumari, Princy Hira, Shekhar Nagar, Chandni Talwar, Namita Nayyar, Shailly Anand, Charu Dogra Rawat, Mansi Verma, Ram Krishan Negi, Yogendra Singh, Rup Lal
mSystems Jul 2020, 5 (4) e00505-20; DOI: 10.1128/mSystems.00505-20

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Comparative Genomic Analysis of Rapidly Evolving SARS-CoV-2 Reveals Mosaic Pattern of Phylogeographical Distribution
Roshan Kumar, Helianthous Verma, Nirjara Singhvi, Utkarsh Sood, Vipin Gupta, Mona Singh, Rashmi Kumari, Princy Hira, Shekhar Nagar, Chandni Talwar, Namita Nayyar, Shailly Anand, Charu Dogra Rawat, Mansi Verma, Ram Krishan Negi, Yogendra Singh, Rup Lal
mSystems Jul 2020, 5 (4) e00505-20; DOI: 10.1128/mSystems.00505-20
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KEYWORDS

COVID-2019
SARS-CoV-2
viruses

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