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

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-...

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Autores principales: Laamarti, Meriem, Alouane, Tarek, Kartti, Souad, Chemao-Elfihri, M. W., Hakmi, Mohammed, Essabbar, Abdelomunim, Laamarti, Mohamed, Hlali, Haitam, Bendani, Houda, Boumajdi, Nassma, Benhrif, Oussama, Allam, Loubna, El Hafidi, Naima, El Jaoudi, Rachid, Allali, Imane, Marchoudi, Nabila, Fekkak, Jamal, Benrahma, Houda, Nejjari, Chakib, Amzazi, Saaid, Belyamani, Lahcen, Ibrahimi, Azeddine
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7654798/
https://www.ncbi.nlm.nih.gov/pubmed/33170902
http://dx.doi.org/10.1371/journal.pone.0240345
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author Laamarti, Meriem
Alouane, Tarek
Kartti, Souad
Chemao-Elfihri, M. W.
Hakmi, Mohammed
Essabbar, Abdelomunim
Laamarti, Mohamed
Hlali, Haitam
Bendani, Houda
Boumajdi, Nassma
Benhrif, Oussama
Allam, Loubna
El Hafidi, Naima
El Jaoudi, Rachid
Allali, Imane
Marchoudi, Nabila
Fekkak, Jamal
Benrahma, Houda
Nejjari, Chakib
Amzazi, Saaid
Belyamani, Lahcen
Ibrahimi, Azeddine
author_facet Laamarti, Meriem
Alouane, Tarek
Kartti, Souad
Chemao-Elfihri, M. W.
Hakmi, Mohammed
Essabbar, Abdelomunim
Laamarti, Mohamed
Hlali, Haitam
Bendani, Houda
Boumajdi, Nassma
Benhrif, Oussama
Allam, Loubna
El Hafidi, Naima
El Jaoudi, Rachid
Allali, Imane
Marchoudi, Nabila
Fekkak, Jamal
Benrahma, Houda
Nejjari, Chakib
Amzazi, Saaid
Belyamani, Lahcen
Ibrahimi, Azeddine
author_sort Laamarti, Meriem
collection PubMed
description 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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spelling pubmed-76547982020-11-18 Large scale genomic analysis of 3067 SARS-CoV-2 genomes reveals a clonal geo-distribution and a rich genetic variations of hotspots mutations Laamarti, Meriem Alouane, Tarek Kartti, Souad Chemao-Elfihri, M. W. Hakmi, Mohammed Essabbar, Abdelomunim Laamarti, Mohamed Hlali, Haitam Bendani, Houda Boumajdi, Nassma Benhrif, Oussama Allam, Loubna El Hafidi, Naima El Jaoudi, Rachid Allali, Imane Marchoudi, Nabila Fekkak, Jamal Benrahma, Houda Nejjari, Chakib Amzazi, Saaid Belyamani, Lahcen Ibrahimi, Azeddine PLoS One Research Article 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. Public Library of Science 2020-11-10 /pmc/articles/PMC7654798/ /pubmed/33170902 http://dx.doi.org/10.1371/journal.pone.0240345 Text en © 2020 Laamarti et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Laamarti, Meriem
Alouane, Tarek
Kartti, Souad
Chemao-Elfihri, M. W.
Hakmi, Mohammed
Essabbar, Abdelomunim
Laamarti, Mohamed
Hlali, Haitam
Bendani, Houda
Boumajdi, Nassma
Benhrif, Oussama
Allam, Loubna
El Hafidi, Naima
El Jaoudi, Rachid
Allali, Imane
Marchoudi, Nabila
Fekkak, Jamal
Benrahma, Houda
Nejjari, Chakib
Amzazi, Saaid
Belyamani, Lahcen
Ibrahimi, Azeddine
Large scale genomic analysis of 3067 SARS-CoV-2 genomes reveals a clonal geo-distribution and a rich genetic variations of hotspots mutations
title Large scale genomic analysis of 3067 SARS-CoV-2 genomes reveals a clonal geo-distribution and a rich genetic variations of hotspots mutations
title_full Large scale genomic analysis of 3067 SARS-CoV-2 genomes reveals a clonal geo-distribution and a rich genetic variations of hotspots mutations
title_fullStr Large scale genomic analysis of 3067 SARS-CoV-2 genomes reveals a clonal geo-distribution and a rich genetic variations of hotspots mutations
title_full_unstemmed Large scale genomic analysis of 3067 SARS-CoV-2 genomes reveals a clonal geo-distribution and a rich genetic variations of hotspots mutations
title_short Large scale genomic analysis of 3067 SARS-CoV-2 genomes reveals a clonal geo-distribution and a rich genetic variations of hotspots mutations
title_sort large scale genomic analysis of 3067 sars-cov-2 genomes reveals a clonal geo-distribution and a rich genetic variations of hotspots mutations
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7654798/
https://www.ncbi.nlm.nih.gov/pubmed/33170902
http://dx.doi.org/10.1371/journal.pone.0240345
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