Evidence map›Paper›PMID 32924062›Full record

ArticleBriefings in bioinformatics2021

Origin-independent analysis links SARS-CoV-2 local genomes with COVID-19 incidence and mortality.

Wenzhong Yang, Guangxu Jin

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. Not yet cited in PubMed.

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

What it found

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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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

2 authors.

Wenzhong Yang
Guangxu Jin

Funding

Tumor Tissue CoreP30CA012197 · NCI · WAKE FOREST UNIVERSITY HEALTH SCIENCES · PI Ruben A. Mesa · 1985 to 2026
$55.4M
NCI NIH HHS P30 CA012197
6 · The paper itself

Abstract

There is an urgent public health need to better understand Severe Acute Respiratory Syndrome (SARS)-CoV-2/COVID-19, particularly how sequences of the viruses could lead to diverse incidence and mortality of COVID-19 in different countries. However, because of its unknown ancestors and hosts, elucidating the genetic variations of the novel coronavirus, SARS-CoV-2, has been difficult. Without needing to know ancestors, we identified an uneven distribution of local genome similarities among the viruses categorized by geographic regions, and it was strongly correlated with incidence and mortality. To ensure unbiased and origin-independent analyses, we used a pairwise comparison of local genome sequences of virus genomes by Basic Local Alignment Search Tool (BLAST). We found a strong statistical correlation between dominance of the SARS-CoV-2 in distributions of uneven similarities and the incidence and mortality of illness. Genomic annotation of the BLAST hits also showed that viruses from geographic regions with severe infections tended to have more dynamic genomic regions in the SARS-CoV-2 receptor-binding domain (RBD) and receptor-binding motif (RBM) of the spike protein (S protein). Dynamic domains in the S protein were also confirmed by a canyon region of mismatches coincident with RBM and RBD, without hits of alignments of 100% matching. Thus, our origin-independent analysis suggests that the dynamic and unstable SARS-CoV-2-RBD could be the main reason for diverse incidence and mortality of COVID-19 infection.

Indexed as

Genome, ViralCOVID-19HumansIncidenceSARS-CoV-2bioinformaticsdynamic RBD and RBMorigin-independent analysisSARS-CoV-2S proteinuneven local genomic similarities

Identifiers

PMID32924062
PMCPMC7543285

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.