Evidence map›Paper›PMID 34207362›Full record

ArticleBiomolecules2021

Genome-Wide Analysis of Codon Usage Patterns of SARS-CoV-2 Virus Reveals Global Heterogeneity of COVID-19.

Saadullah Khattak, Mohd Ahmar Rauf, Qamar Zaman, Yasir Ali, Shabeen Fatima, Pir Muhammad, Tao Li, Hamza Ali Khan, Azhar Abbas Khan, Ebenezeri Erasto Ngowi and 2 more

Abstract read
In one paragraph

Article in Biomolecules, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.

0numbers the graph read from it
0cells of the map it votes in
17citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

17 citing papers in PubMed.

  1. Article
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  9. Structural Evaluation and Conformational Dynamics ofBioengineering (Basel, Switzerland) · 2022
    Article
  10. Article
  11. Article
  12. Article
  13. Knowledge, Attitude, and Perception of Cancer Patients towards COVID-19 in Pakistan: A Cross-Sectional Study.International journal of environmental research and public health · 2022
    Article
  14. Article
  15. The monkeypox diagnosis, treatments and prevention: A review.Frontiers in cellular and infection microbiology · 2022
    Review
  16. Article
  17. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

12 authors.

Saadullah KhattakHenan International Joint Laboratory for Nuclear Protein Regulation, School of Basic Medical Sciences, Henan University, Kaifeng 475004, Henan, China.
Mohd Ahmar RaufSchool of Life Sciences, Henan University, Kaifeng 475004, Henan, China.ORCID 0000-0001-5639-2208
Qamar ZamanDepartment of Bioinformatics, Hazara University, Mansehra 21120, Pakistan.ORCID 0000-0002-6079-6536
Yasir AliNational Center for Bioinformatics, Quaid-i-Azam University, Islamabad 45320, Pakistan.
Shabeen FatimaDepartment of Biosciences and Bioinformatics, Capital University of Science and Technology, Islamabad 44000, Pakistan.
Pir MuhammadHenan-Macquarie University Joint Centre for Biomedical Innovation, School of Life Sciences, Henan University, Kaifeng 475004, Henan, China.ORCID 0000-0001-5960-0279
Tao LiHenan International Joint Laboratory for Nuclear Protein Regulation, School of Basic Medical Sciences, Henan University, Kaifeng 475004, Henan, China.
Hamza Ali KhanDepartment of Bioinformatics, Hazara University, Mansehra 21120, Pakistan.
Azhar Abbas KhanHenan International Joint Laboratory for Nuclear Protein Regulation, School of Basic Medical Sciences, Henan University, Kaifeng 475004, Henan, China.
Ebenezeri Erasto NgowiHenan International Joint Laboratory for Nuclear Protein Regulation, School of Basic Medical Sciences, Henan University, Kaifeng 475004, Henan, China.ORCID 0000-0003-4448-5276
Dong-Dong WuHenan International Joint Laboratory for Nuclear Protein Regulation, School of Basic Medical Sciences, Henan University, Kaifeng 475004, Henan, China.
Xin-Ying JiHenan International Joint Laboratory for Nuclear Protein Regulation, School of Basic Medical Sciences, Henan University, Kaifeng 475004, Henan, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The ongoing outbreak of coronavirus disease COVID-19 is significantly implicated by global heterogeneity in the genome organization of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The causative agents of global heterogeneity in the whole genome of SARS-CoV-2 are not well characterized due to the lack of comparative study of a large enough sample size from around the globe to reduce the standard deviation to the acceptable margin of error. To better understand the SARS-CoV-2 genome architecture, we have performed a comprehensive analysis of codon usage bias of sixty (60) strains to get a snapshot of its global heterogeneity. Our study shows a relatively low codon usage bias in the SARS-CoV-2 viral genome globally, with nearly all the over-preferred codons' A.U. ended. We concluded that the SARS-CoV-2 genome is primarily shaped by mutation pressure; however, marginal selection pressure cannot be overlooked. Within the A/U rich virus genomes of SARS-CoV-2, the standard deviation in G.C. (42.91% ± 5.84%) and the GC3 value (30.14% ± 6.93%) points towards global heterogeneity of the virus. Several SARS-CoV-2 viral strains were originated from different viral lineages at the exact geographic location also supports this fact. Taking all together, these findings suggest that the general root ancestry of the global genomes are different with different genome's level adaptation to host. This research may provide new insights into the codon patterns, host adaptation, and global heterogeneity of SARS-CoV-2.

Indexed as

Codon UsageGenome, ViralCOVID-19Evolution, MolecularHumansMutationPhylogenySARS-CoV-2Codon usage biasCoronavirusCOVID-19heterogeneity of COVID-19mutational biasnatural selectionSARS-CoV-2

Identifiers

PMID34207362
PMCPMC8233742

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LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.