Identification of the hyper-variable genomic hotspot for the novel coronavirus SARS-CoV-2

Wen, Feng; Yu, Hai; Guo, Jianming; Yong, Li; Luo, Kaijian; Huang, Shujian

doi:10.1016/j.jinf.2020.02.027

Cited by 44 publications

(39 citation statements)

References 11 publications

(10 reference statements)

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“…Genomic comparison of the studied population allowed us to gain insights into virus mutations occurrence over time and within different geographic areas. In the SARS-CoV virus, the SNPs distribution is not random, and it is more dominant in critical genes for the virus [21,31]. Our results confirmed what was previously described and elucidate the presence of numerous hotspot mutations.…”

Section: Plos Onesupporting

confidence: 90%

Large scale genomic analysis of 3067 SARS-CoV-2 genomes reveals a clonal geo-distribution and a rich genetic variations of hotspots mutations

Laamarti¹,

Alouane²,

Kartti³

et al. 2020

PLoS ONE

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In late December 2019, an emerging viral infection COVID-19 was identified in Wuhan, China, and became a global pandemic. Characterization of the genetic variants of SARS-CoV-2 is crucial in following and evaluating it spread across countries. In this study, we collected and analyzed 3,067 SARS-CoV-2 genomes isolated from 55 countries during the first three months after the onset of this virus. Using comparative genomics analysis, we traced the profiles of the whole-genome mutations and compared the frequency of each mutation in the studied population. The accumulation of mutations during the epidemic period with their geographic locations was also monitored. The results showed 782 variants sites, of which 512 (65.47%) had a non-synonymous effect. Frequencies of mutated alleles revealed the presence of 68 recurrent mutations, including ten hotspot non-synonymous mutations with a prevalence higher than 0.10 in this population and distributed in six SARS-CoV-2 genes. The distribution of these recurrent mutations on the world map revealed that certain genotypes are specific to geographic locations. We also identified co-occurring mutations resulting in the presence of several haplotypes. Moreover, evolution over time has shown a mechanism of mutation co-accumulation which might affect the severity and spread of the SARS-CoV-2. The phylogentic analysis identified two major Clades C1 and C2 harboring mutations L3606F and G614D, respectively and both emerging for the first time in China. On the other hand, analysis of the selective pressure revealed the presence of negatively selected residues that could be taken into considerations as therapeutic targets. We have also created an inclusive unified database (http://covid-19.medbiotech.ma) that lists all of the genetic variants of the SARS-CoV-2 genomes found in this study with phylogeographic analysis around the world.

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Section: Plos Onesupporting

confidence: 90%

Large scale genomic analysis of 3067 SARS-CoV-2 genomes reveals a clonal geo-distribution and a rich genetic variations of hotspots mutations

Laamarti¹,

Alouane²,

Kartti³

et al. 2020

PLoS ONE

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“…The 3ʹ terminus of the genome encodes for structural and accessory proteins [3]. Hypervariable genomic hot spots have been detected in the spike gene and in other ORFs for nonstructural proteins [14].…”

Section: Virology and Genome Of Sars-cov-2mentioning

confidence: 99%

Epidemiology, genome, and clinical features of the pandemic SARS-CoV-2: a recent view

Abduljalil

2020

New Microbes and New Infections

112

123

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Since the emergence of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in Wuhan, China, the number of globally confirmed cases according to World Health Organization statistics reached 292 124 in 189 countries by 22 March 2020. The number of deaths reached 12 784, with estimated case-fatality rates ranging from 0.5% to 5.7%. Children population seems to be the least affected by the disease, while the highest rate of death is among the elderly and people with comorbidities. Most infected individuals are asymptomatic or only exhibit mild symptoms. After the incubation period, the most common symptoms are fever, cough and fatigue.Asymptomatic carrier state is of paramount importance because of carriers' ability to spread the infection and to shed the virus into the air and surroundings. Although much is still unknown about SARS-CoV-2, the scientific research is moving at an unprecedented pace towards understanding the nature, effective control, prevention and treatment of SARS-CoV-2. Various reports have suggested an in vivo evolution of the virus, which may explain the rapid spread and changing epidemiology of SARS-CoV-2, but further evidence is needed.Unfortunately, no effective treatment or therapeutic drug is available for the disease; only supportive treatment and classical intervention measures are available for confronting the SARS-CoV-2 pandemic.

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“…In addition to their influence on phylogenetic inference, recurrent systematic errors can also lead to erroneous inferences about viral mutation processes, recombination and selection. For example, artefactual biases in mutational processes could confound signatures of mutational hotspots [28][29][30][31][32][33] . The issue of whether or not recombination has occurred during the outbreak is critical to the immunological battle against the virus and is under intense debate [6,[34][35][36][37][38][39][40] .…”

Section: Figure 1: Effect Of Recurrent Sequencing Mutations On Phylogmentioning

confidence: 99%

Stability of SARS-CoV-2 Phylogenies

Turakhia

Thornlow

Gozashti

et al. 2020

Preprint

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The SARS-CoV-2 pandemic has led to unprecedented, nearly real-time genetic tracing due to the rapid community sequencing response. Researchers immediately leveraged these data to infer the evolutionary relationships among viral samples and to study key biological questions, including whether host viral genome editing and recombination are features of SARS-CoV-2 evolution. This global sequencing effort is inherently decentralized and must rely on data collected by many labs using a wide variety of molecular and bioinformatic techniques. There is thus a strong possibility that systematic errors associated with lab-specific practices affect some sequences in the repositories. We find that some recurrent mutations in reported SARS-CoV-2 genome sequences have been observed predominantly or exclusively by single labs, co-localize with commonly used primer binding sites and are more likely to affect the protein coding sequences than other similarly recurrent mutations. We show that their inclusion can affect phylogenetic inference on scales relevant to local lineage tracing, and make it appear as though there has been an excess of recurrent mutation and/or recombination among viral lineages. We suggest how samples can be screened and problematic mutations removed. We also develop tools for comparing and visualizing differences among phylogenies and we show that consistent clade-and tree-based comparisons can be made between phylogenies produced by different groups. These will facilitate evolutionary inferences and comparisons among phylogenies produced for a wide array of purposes. Building on the SARS-CoV-2 Genome Browser at UCSC, we present a toolkit to compare, analyze and combine SARS-CoV-2 phylogenies, find and remove potential sequencing errors and establish a widely shared, stable clade structure for a more accurate scientific inference and discourse.Foreword:

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Identification of the hyper-variable genomic hotspot for the novel coronavirus SARS-CoV-2

Cited by 44 publications

References 11 publications

Large scale genomic analysis of 3067 SARS-CoV-2 genomes reveals a clonal geo-distribution and a rich genetic variations of hotspots mutations

Large scale genomic analysis of 3067 SARS-CoV-2 genomes reveals a clonal geo-distribution and a rich genetic variations of hotspots mutations

Epidemiology, genome, and clinical features of the pandemic SARS-CoV-2: a recent view

Stability of SARS-CoV-2 Phylogenies

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