Evidence map›Paper›PMID 39561193›Full record

ArticlePloS one2024

Complete genome sequencing of SARS-CoV-2 strains that were circulating in Uzbekistan over the course of four pandemic waves.

Gulnoza Esonova, Abrorjon Abdurakhimov, Shakhnoza Ibragimova, Diyora Kurmaeva, Jakhongirbek Gulomov, Doniyor Mirazimov, Khonsuluv Sohibnazarova, Alisher Abdullaev, Shahlo Turdikulova, Dilbar Dalimova

Abstract read
In one paragraph

Article in PloS one, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Review
  2. 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

10 authors.

Gulnoza EsonovaLaboratory of Biotechnology, Center for Advanced Technologies under the Ministry of Higher Education, Science and Innovations, Tashkent, Uzbekistan.ORCID 0009-0009-8700-5034
Abrorjon AbdurakhimovLaboratory of Biotechnology, Center for Advanced Technologies under the Ministry of Higher Education, Science and Innovations, Tashkent, Uzbekistan.
Shakhnoza IbragimovaLaboratory of Biotechnology, Center for Advanced Technologies under the Ministry of Higher Education, Science and Innovations, Tashkent, Uzbekistan.
Diyora KurmaevaLaboratory of Biotechnology, Center for Advanced Technologies under the Ministry of Higher Education, Science and Innovations, Tashkent, Uzbekistan.
Jakhongirbek GulomovLaboratory of Biotechnology, Center for Advanced Technologies under the Ministry of Higher Education, Science and Innovations, Tashkent, Uzbekistan.
Doniyor MirazimovState Institution Zangiota No. 2 special hospital for the treatment of patients with coronavirus infection, Tashkent, Uzbekistan.
Khonsuluv SohibnazarovaLaboratory of Biotechnology, Center for Advanced Technologies under the Ministry of Higher Education, Science and Innovations, Tashkent, Uzbekistan.ORCID 0000-0002-8005-5284
Alisher AbdullaevLaboratory of Biotechnology, Center for Advanced Technologies under the Ministry of Higher Education, Science and Innovations, Tashkent, Uzbekistan.ORCID 0000-0002-8268-7699
Shahlo TurdikulovaLaboratory of Biotechnology, Center for Advanced Technologies under the Ministry of Higher Education, Science and Innovations, Tashkent, Uzbekistan.
Dilbar DalimovaLaboratory of Biotechnology, Center for Advanced Technologies under the Ministry of Higher Education, Science and Innovations, Tashkent, Uzbekistan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Since the rapid emergence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) as a global COVID-19 pandemic affecting millions of people globally, it has become one of the most urgent research topics worldwide to better understand the pathogenesis of COVID-19 and the impact of the harmful variants. In the present study, we conducted whole genome sequencing (WGS) analysis of 110 SARS-CoV-2 genomes, to give more data about the circulation of SARS-CoV-2 variants during the four waves of pandemic in Uzbekistan. The whole genome sequencing of SARS-CoV-2 samples isolated from PCR-positive patients from Tashkent, Uzbekistan, in the period of 2021 and 2022 were generated using next-generation sequencing approaches and subjected to further genomic analysis. According to our previous studies and the current genome-wide annotations of clinical samples, we have identified four waves of SARS-CoV-2 in Uzbekistan between 2020 and 2022. The dominant variants observed in each wave were Wuhan, Alpha, Delta, and Omicron, respectively. A total of 347 amino acid level variants were identified and of these changes, the most frequent mutations were identified in the ORF1ab region (n = 159), followed by the S gene (n = 115). There were several mutations in all parts of the SAR-CoV-2 genomes but S: D614G, E: T9I, M: A63T, N: G204 R and R203K, NSP12: P323L, and ORF3a(NS3): T223I were the most frequent mutations in these studied viruses. In our previous study, no mutation was found in the envelope (E) protein. In contrast, in our present study, we identified 3 (T9I, T11A and V58F) mutations that made changes to the structure and function of the E protein of SARS-CoV-2. In conclusion, our findings showed that with the emergence of each new variant in our country, the COVID-19 pandemic has also progressed. This may be due to the considerable increase in the number of mutations (Alpha-46, Delta- 146, and Omicron-200 mutations were observed in our samples) in each emerged variant that shows the SARS-CoV-2 evolution.

Indexed as

COVID-19Genome, ViralSARS-CoV-2Whole Genome SequencingHumansMutationPandemicsPhylogenyUzbekistan

Identifiers

PMID39561193
PMCPMC11575833

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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.