Evidence map›Paper›PMID 33580783›Full record

ArticleBriefings in bioinformatics2021

Functional alterations caused by mutations reflect evolutionary trends of SARS-CoV-2.

Liang Cheng, Xudong Han, Zijun Zhu, Changlu Qi, Ping Wang, Xue Zhang

Abstract read
In one paragraph

Article in Briefings in bioinformatics, 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
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. SARS-CoV-2 Mutations and their Viral Variants.Cytokine & growth factor reviews · 2022
    Review
  8. Article
  9. Article
  10. Article
  11. Article
  12. Hotspot Mutations in SARS-CoV-2.Frontiers in genetics · 2021
    Article
  13. Article
  14. Prediction of Gastric Cancer-Related Proteins Based on Graph Fusion Method.Frontiers in cell and developmental biology · 2021
    Article
  15. Genomic Variation Prediction: A Summary From Different Views.Frontiers in cell and developmental biology · 2021
    Review
  16. Review
  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

6 authors.

Liang ChengNHC and CAMS Key Laboratory of Molecular Probe and Targeted Theranostics, Harbin Medical University, Harbin, Heilongjiang 150028, China.
Xudong HanCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, Heilongjiang 150081, China.
Zijun ZhuCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, Heilongjiang 150081, China.
Changlu QiCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, Heilongjiang 150081, China.
Ping WangCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, Heilongjiang 150081, China.
Xue ZhangNHC and CAMS Key Laboratory of Molecular Probe and Targeted Theranostics, Harbin Medical University, Harbin, Heilongjiang 150028, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Since the first report of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in December 2019, the COVID-19 pandemic has spread rapidly worldwide. Due to the limited virus strains, few key mutations that would be very important with the evolutionary trends of virus genome were observed in early studies. Here, we downloaded 1809 sequence data of SARS-CoV-2 strains from GISAID before April 2020 to identify mutations and functional alterations caused by these mutations. Totally, we identified 1017 nonsynonymous and 512 synonymous mutations with alignment to reference genome NC_045512, none of which were observed in the receptor-binding domain (RBD) of the spike protein. On average, each of the strains could have about 1.75 new mutations each month. The current mutations may have few impacts on antibodies. Although it shows the purifying selection in whole-genome, ORF3a, ORF8 and ORF10 were under positive selection. Only 36 mutations occurred in 1% and more virus strains were further analyzed to reveal linkage disequilibrium (LD) variants and dominant mutations. As a result, we observed five dominant mutations involving three nonsynonymous mutations C28144T, C14408T and A23403G and two synonymous mutations T8782C, and C3037T. These five mutations occurred in almost all strains in April 2020. Besides, we also observed two potential dominant nonsynonymous mutations C1059T and G25563T, which occurred in most of the strains in April 2020. Further functional analysis shows that these mutations decreased protein stability largely, which could lead to a significant reduction of virus virulence. In addition, the A23403G mutation increases the spike-ACE2 interaction and finally leads to the enhancement of its infectivity. All of these proved that the evolution of SARS-CoV-2 is toward the enhancement of infectivity and reduction of virulence.

Indexed as

Biological EvolutionMutationCOVID-19HumansLinkage DisequilibriumOpen Reading FramesSARS-CoV-2Virulencedominant mutationevolutionary trendinteractionSARS-CoV-2virus virulence

Identifiers

PMID33580783
PMCPMC7953981

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.