Evidence map›Paper›PMID 36841805›Full record

ArticleJournal of translational medicine2023

Global landscape of SARS-CoV-2 mutations and conserved regions.

Mohammad Hadi Abbasian, Mohammadamin Mahmanzar, Karim Rahimian, Bahar Mahdavi, Samaneh Tokhanbigli, Bahman Moradi, Mahsa Mollapour Sisakht, Youping Deng

Open access · goldAbstract read
In one paragraph

Article in Journal of translational medicine, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 56 papers.

0numbers the graph read from it
0cells of the map it votes in
56citing papers in PubMed
18.3field-weighted citation impact, top 1% of its field
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

56 citing papers in PubMed, 94 citations in OpenAlex.

  1. Trial
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  5. bronko: ultrafast, alignment-free detection of viral genome variation.bioRxiv : the preprint server for biology · 2026
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  13. Therapeutic applications of interface-mimicking peptides for targeting the SARS-CoV-2 NSP12-NSP8 RdRp complex.Molecular therapy : the journal of the American Society of Gene Therapy · 2025
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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

8 authors at 7 institutions in 4 countries.

Mohammad Hadi Abbasian *Department of Medical Genetics, National Institute for Genetic Engineering and Biotechnology, Tehran, Iran.
Mohammadamin Mahmanzar *Department of Quantitative Health Sciences, John A. Burns School of Medicine, University of Hawaii at Manoa, Honolulu, HI, 96813, USA.
Karim Rahimian *Department of Bioinformatics, Institute of Biochemistry and Biophysics (IBB), University of Tehran, Tehran, Iran.
Bahar MahdaviDepartment of Computer Science, Tarbiat Modares University, Tehran, Iran.
Samaneh TokhanbigliDiscipline of Pharmacy, Graduate School of Health, University of Technology Sydney, Sydney, Australia.
Bahman MoradiDepartment of Biology, Faculty of Sciences, Shahid Bahonar University of Kerman, Kerman, Iran.
Mahsa Mollapour SisakhtDepartment of Biochemistry, Erasmus University Medical Center, 2040, 3000 CA, Rotterdam, The Netherlands.
Youping DengDepartment of Quantitative Health Sciences, John A. Burns School of Medicine, University of Hawaii at Manoa, Honolulu, HI, 96813, USA. dengy@hawaii.edu.ORCID 0000-0002-5951-8213
University of Hawaiʻi at Mānoa · USErasmus MC · NLNational Institute of Genetic Engineering and Biotechnology · IRShahid Bahonar University of Kerman · IRTarbiat Modares University · IRUniversity of Technology Sydney · AUUniversity of Tehran · IR

Funding

UH Hilo COP A&RP20GM103466 · NIGMS · UNIVERSITY OF HAWAII AT MANOA · PI Peter R Hoffmann · 2012 to 2026
$60.3M
The Role of gp120 on Cardiovascular Disease in People Living with HIVU54MD007601 · NIMHD · UNIVERSITY OF HAWAII AT MANOA · PI Jerris Robert Hedges · 2017 to 2026
$59.5M
University of Hawaii Cancer Center CCSGP30CA071789 · NCI · UNIVERSITY OF HAWAII AT MANOA · PI Xin Chen · 1996 to 2026
$56.2M
University of Guam/Cancer Research Center of Hawaii Partnership (1 of 2)U54CA143727 · NCI · UNIVERSITY OF HAWAII AT MANOA · PI LYNNE R WILKENS · 2009 to 2026
$19.1M
Tracking and Evaluation CoreU54GM138062 · NIGMS · UNIVERSITY OF HAWAII AT MANOA · PI KAHOLOKULA, JOSEPH KEAWE'AIMOKU · 2021 to 2025
$15.5M
Selenium Metabolism in the Heart: Impact of High Fructose and Low SeleniumP20GM139753 · NIGMS · UNIVERSITY OF HAWAII AT MANOA · PI Christoph Alexander Rettenmeier · 2022 to 2026
$13.3M
Small Grants ProgramP30GM114737 · NIGMS · UNIVERSITY OF HAWAII AT MANOA · PI NERURKAR, VIVEK RAMCHANDRA · 2015 to 2022
$8.1M
NCI NIH HHS U54 CA143727NIGMS NIH HHS P20 GM103466NIGMS NIH HHS P30 GM114737NIGMS NIH HHS U54 GM138062NIH HHS 1P20GM139753NIH HHS 1U54GM138062NIH HHS 2U54CA143727NIH HHS 5P20GM103466NIH HHS 5P30CA071789NIH HHS 5P30GM114737NIH HHS 5U54MD007601
6 · The paper itself

Abstract

backgroundAt the end of December 2019, a novel strain of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) disease (COVID-19) has been identified in Wuhan, a central city in China, and then spread to every corner of the globe. As of October 8, 2022, the total number of COVID-19 cases had reached over 621 million worldwide, with more than 6.56 million confirmed deaths. Since SARS-CoV-2 genome sequences change due to mutation and recombination, it is pivotal to surveil emerging variants and monitor changes for improving pandemic management.

methods10,287,271 SARS-CoV-2 genome sequence samples were downloaded in FASTA format from the GISAID databases from February 24, 2020, to April 2022. Python programming language (version 3.8.0) software was utilized to process FASTA files to identify variants and sequence conservation. The NCBI RefSeq SARS-CoV-2 genome (accession no. NC_045512.2) was considered as the reference sequence.

resultsSix mutations had more than 50% frequency in global SARS-CoV-2. These mutations include the P323L (99.3%) in NSP12, D614G (97.6) in S, the T492I (70.4) in NSP4, R203M (62.8%) in N, T60A (61.4%) in Orf9b, and P1228L (50.0%) in NSP3. In the SARS-CoV-2 genome, no mutation was observed in more than 90% of nsp11, nsp7, nsp10, nsp9, nsp8, and nsp16 regions. On the other hand, N, nsp3, S, nsp4, nsp12, and M had the maximum rate of mutations. In the S protein, the highest mutation frequency was observed in aa 508-635(0.77%) and aa 381-508 (0.43%). The highest frequency of mutation was observed in aa 66-88 (2.19%), aa 7-14, and aa 164-246 (2.92%) in M, E, and N proteins, respectively.

conclusionTherefore, monitoring SARS-CoV-2 proteomic changes and detecting hot spots mutations and conserved regions could be applied to improve the SARS-CoV-2 diagnostic efficiency and design safe and effective vaccines against emerging variants.

Indexed as

COVID-19SARS-CoV-2HumansMutationMutation RateProteomicsAmino AcidCOVID-19Emerging variantsGenomeSARS-CoV-2Vaccines

Identifiers

PMID36841805
PMCPMC9958328
OpenAlexW4322008709

What OpenQuestion holds

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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.