Evidence map›Paper›PMID 33050053›Full record

ArticleVaccines2020

Evolutionary Analysis of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) Reveals Genomic Divergence with Implications for Universal Vaccine Efficacy.

Nanda Kumar Yellapu, Shachi Patel, Bo Zhang, Richard Meier, Lisa Neums, Dong Pei, Qing Xia, Duncan Rotich, Rosalyn C Zimmermann, Emily Nissen and 7 more

Open access · goldAbstract read
In one paragraph

Article in Vaccines, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.1field-weighted citation impact, top 48% 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

3 citing papers in PubMed, 4 citations in OpenAlex.

  1. Review
  2. Novel and emerging mutations of SARS-CoV-2: Biomedical implications.Biomedicine & pharmacotherapy = Biomedecine & pharmacotherapie · 2021
    Review
  3. Review
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

17 authors at 2 institutions in 1 country.

Nanda Kumar YellapuDepartment of Biostatistics & Data Science, University of Kansas Medical Center, 3901 Rainbow Boulevard, Kansas City, KS 66160, USA.ORCID 0000-0002-3095-6375
Shachi PatelDepartment of Biostatistics & Data Science, University of Kansas Medical Center, 3901 Rainbow Boulevard, Kansas City, KS 66160, USA.
Bo ZhangDepartment of Biostatistics & Data Science, University of Kansas Medical Center, 3901 Rainbow Boulevard, Kansas City, KS 66160, USA.
Richard MeierDepartment of Biostatistics & Data Science, University of Kansas Medical Center, 3901 Rainbow Boulevard, Kansas City, KS 66160, USA.
Lisa NeumsDepartment of Biostatistics & Data Science, University of Kansas Medical Center, 3901 Rainbow Boulevard, Kansas City, KS 66160, USA.
Dong PeiDepartment of Biostatistics & Data Science, University of Kansas Medical Center, 3901 Rainbow Boulevard, Kansas City, KS 66160, USA.
Qing XiaDepartment of Biostatistics & Data Science, University of Kansas Medical Center, 3901 Rainbow Boulevard, Kansas City, KS 66160, USA.
Duncan RotichDepartment of Biostatistics & Data Science, University of Kansas Medical Center, 3901 Rainbow Boulevard, Kansas City, KS 66160, USA.
Rosalyn C ZimmermannDepartment of Cancer Biology, University of Kansas Medical Center, 3901 Rainbow Boulevard, Kansas City, KS 66160, USA.
Emily NissenDepartment of Biostatistics & Data Science, University of Kansas Medical Center, 3901 Rainbow Boulevard, Kansas City, KS 66160, USA.
Shelby Bell-GlennDepartment of Biostatistics & Data Science, University of Kansas Medical Center, 3901 Rainbow Boulevard, Kansas City, KS 66160, USA.
Whitney ShaeDepartment of Biostatistics & Data Science, University of Kansas Medical Center, 3901 Rainbow Boulevard, Kansas City, KS 66160, USA.
Jinxiang HuDepartment of Biostatistics & Data Science, University of Kansas Medical Center, 3901 Rainbow Boulevard, Kansas City, KS 66160, USA.
Prabhakar ChaliseDepartment of Biostatistics & Data Science, University of Kansas Medical Center, 3901 Rainbow Boulevard, Kansas City, KS 66160, USA.ORCID 0000-0001-5581-1220
Lynn Chollet-HintonDepartment of Biostatistics & Data Science, University of Kansas Medical Center, 3901 Rainbow Boulevard, Kansas City, KS 66160, USA.
Devin C KoestlerDepartment of Biostatistics & Data Science, University of Kansas Medical Center, 3901 Rainbow Boulevard, Kansas City, KS 66160, USA.
Jeffery A ThompsonDepartment of Biostatistics & Data Science, University of Kansas Medical Center, 3901 Rainbow Boulevard, Kansas City, KS 66160, USA.ORCID 0000-0002-0876-2582
University of Kansas Medical Center · USThe University of Kansas Cancer Center · US

Funding

Mentoring CoreP20GM103418 · NIGMS · UNIVERSITY OF KANSAS MEDICAL CENTER · PI Douglas E Wright · 2012 to 2026
$63.0M
Using Integrated Omics to Identify Dysfunctional Genetic Mechanisms Influencing Schizophrenia and Sleep DisturbancesP20GM130423 · NIGMS · UNIVERSITY OF KANSAS MEDICAL CENTER · PI Kalyani Pyaram, Steven Allan Soper · 2019 to 2026
$21.5M
Widely Distributed Software for Using Mass Spectrometry to Identify GlycansR01GM103428 · NIGMS · PALO ALTO RESEARCH CENTER · PI BERN, MARSHALL WAYNE · 2012 to 2013
$799k
National Institute of General Medical Science P20GM103428NCI NIH HHS P20GM130423NIGMS NIH HHS P20 GM103418NIGMS NIH HHS P20 GM130423
6 · The paper itself

Abstract

Coronavirus disease (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), is one of the pressing contemporary public health challenges. Investigations into the genomic structure of SARS-CoV-2 may inform ongoing vaccine development efforts and/or provide insights into vaccine efficacy to fight against COVID-19. Evolutionary analysis of 540 genomes spanning 20 different countries/territories was conducted and revealed an increase in the genomic divergence across successive generations. The ancestor of the phylogeny was found to be the isolate from the 2019/2020 Wuhan outbreak. Its transmission was outlined across 20 countries/territories as per genomic similarity. Our results demonstrate faster evolving variations in the genomic structure of SARS-CoV-2 when compared to the isolates from early stages of the pandemic. Genomic alterations were predominantly located and mapped onto the reported vaccine candidates of structural genes, which are the main targets for vaccine candidates. S protein showed 34, N protein 25, E protein 2, and M protein 3 amino acid variations in 246 genomes among 540. Among identified mutations, 23 in S protein, 1 in E, 2 from M, and 7 from N protein were mapped with the reported vaccine candidates explaining the possible implications on universal vaccines. Hence, potential target regions for vaccines would be ideally chosen from the structural regions of the genome that lack high variation. The increasing variations in the genome of SARS-CoV-2 together with our observations in structural genes have important implications for the efficacy of a successful universal vaccine against SARS-CoV-2.

Indexed as

COVID-19genomic divergencephylogenetic analysisSARS-CoV-2vaccine development

Identifiers

PMID33050053
PMCPMC7720133
OpenAlexW3092320610

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.