Evidence map›Paper›PMID 33581339›Full record

ArticleGenomics, proteomics & bioinformatics2020

Compositional Variability and Mutation Spectra of Monophyletic SARS-CoV-2 Clades.

Xufei Teng, Qianpeng Li, Zhao Li, Yuansheng Zhang, Guangyi Niu, Jingfa Xiao, Jun Yu, Zhang Zhang, Shuhui Song

Abstract read
In one paragraph

Article in Genomics, proteomics & bioinformatics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing 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

8 citing papers in PubMed.

  1. Review
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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

9 authors.

Xufei TengChina National Center for Bioinformation, Beijing 100101, China; National Genomics Data Center & CAS Key Laboratory of Genome Sciences and Information, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing 100101, China; University of Chinese Academy of Sciences, Beijing 100049, China.
Qianpeng LiChina National Center for Bioinformation, Beijing 100101, China; National Genomics Data Center & CAS Key Laboratory of Genome Sciences and Information, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing 100101, China; University of Chinese Academy of Sciences, Beijing 100049, China.
Zhao LiChina National Center for Bioinformation, Beijing 100101, China; National Genomics Data Center & CAS Key Laboratory of Genome Sciences and Information, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing 100101, China; University of Chinese Academy of Sciences, Beijing 100049, China.
Yuansheng ZhangChina National Center for Bioinformation, Beijing 100101, China; National Genomics Data Center & CAS Key Laboratory of Genome Sciences and Information, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing 100101, China; University of Chinese Academy of Sciences, Beijing 100049, China.
Guangyi NiuChina National Center for Bioinformation, Beijing 100101, China; National Genomics Data Center & CAS Key Laboratory of Genome Sciences and Information, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing 100101, China; University of Chinese Academy of Sciences, Beijing 100049, China.
Jingfa XiaoChina National Center for Bioinformation, Beijing 100101, China; National Genomics Data Center & CAS Key Laboratory of Genome Sciences and Information, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing 100101, China; University of Chinese Academy of Sciences, Beijing 100049, China.
Jun YuChina National Center for Bioinformation, Beijing 100101, China; National Genomics Data Center & CAS Key Laboratory of Genome Sciences and Information, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing 100101, China; University of Chinese Academy of Sciences, Beijing 100049, China. Electronic address: junyu@big.ac.cn.
Zhang ZhangChina National Center for Bioinformation, Beijing 100101, China; National Genomics Data Center & CAS Key Laboratory of Genome Sciences and Information, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing 100101, China; University of Chinese Academy of Sciences, Beijing 100049, China. Electronic address: zhangzhang@big.ac.cn.
Shuhui SongChina National Center for Bioinformation, Beijing 100101, China; National Genomics Data Center & CAS Key Laboratory of Genome Sciences and Information, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing 100101, China; University of Chinese Academy of Sciences, Beijing 100049, China. Electronic address: songshh@big.ac.cn.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

COVID-19 and its causative pathogen SARS-CoV-2 have rushed the world into a staggering pandemic in a few months, and a global fight against both has been intensifying. Here, we describe an analysis procedure where genome composition and its variables are related, through the genetic code to molecular mechanisms, based on understanding of RNA replication and its feedback loop from mutation to viral proteome sequence fraternity including effective sites on the replicase-transcriptase complex. Our analysis starts with primary sequence information, identity-based phylogeny based on 22,051 SARS-CoV-2 sequences, and evaluation of sequence variation patterns as mutation spectra and its 12 permutations among organized clades. All are tailored to two key mechanisms: strand-biased and function-associated mutations. Our findings are listed as follows: 1) The most dominant mutation is C-to-U permutation, whose abundant second-codon-position counts alter amino acid composition toward higher molecular weight and lower hydrophobicity, albeit assumed most slightly deleterious. 2) The second abundance group includes three negative-strand mutations (U-to-C, A-to-G, and G-to-A) and a positive-strand mutation (G-to-U) due to DNA repair mechanisms after cellular abasic events. 3) A clade-associated biased mutation trend is found attributable to elevated level of negative-sense strand synthesis. 4) Within-clade permutation variation is very informative for associating non-synonymous mutations and viral proteome changes. These findings demand a platform where emerging mutations are mapped onto mostly subtle but fast-adjusting viral proteomes and transcriptomes, to provide biological and clinical information after logical convergence for effective pharmaceutical and diagnostic applications. Such actions are in desperate need, especially in the middle of the War against COVID-19.

Indexed as

COVID-19SARS-CoV-2Evolution, MolecularGenome, ViralHumansMutationMutation spectrumNucleotide compositionSARS-CoV-2Viral replication

Identifiers

PMID33581339
PMCPMC7875716

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.