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10.1155/2021/5553173 http://scihub22266oqcxt.onion/10.1155/2021/5553173 34258267!8241501!34258267     free     free     free Deprecated: Implicit conversion from float 231.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 231.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 231.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 231.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       Biomed+Res+Int 2021 ; 2021 (ä): 5553173 Nephropedia Template TP {{tp|p=34258267|t=2021. Relevant SARS-CoV-2 Genome Variation through Six Months of Worldwide Monitoring |pdf=|usr=}}{{34258267}} gab.com Text Relevant SARS-CoV-2 Genome Variation through Six Months of Worldwide Monitoring JO: Biomed Res Int http://www.kidney.de/pget.php?&tw=1&pmid=34258267 #FOAvip Real-time genome monitoring of the SARS-CoV-2 pandemic outbreak is of utmost importance for designing diagnostic tools, guiding antiviral treatment and vaccination strategies. In this study, we present an accurate method for temporal and geographical comparison of mutational events based on GISAID database genome sequencing. Among 42523 SARS-CoV-2 genomes analyzed, we found 23202 variants compared to the reference genome. The Ti/Tv (transition/transversion) ratio was used to filter out possible false-positive errors. Transition mutations generally occurred more frequently than transversions. Our clustering analysis revealed remarkable hotspot mutation patterns for SARS-CoV-2. Mutations were clustered based on how their frequencies changed over time according to each geographical location. We observed some clusters showing a clear variation in mutation frequency and continuously evolving in the world. However, many mutations appeared in specific periods without a clear pattern over time. Various important nonsynonymous mutations were observed, mainly in Oceania and Asia. More than half of these mutations were observed only once. Four hotspot mutations were found in all geographical locations at least once: T265I (NSP2), P314L (NSP12), D614G (S), and Q57H (ORF3a). The current analysis of SARS-CoV-2 genomes provides valuable information on the geographical and temporal mutational evolution of SARS-CoV-2. Twit Text FOAVip Relevant SARS-CoV-2 Genome Variation through Six Months of Worldwide Monitoring ????Biomed Res Int http://www.kidney.de/pget.php?&tw=1&pmid=34258267 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=34258267 #FOAvip English Wikipedia <ref>{{Cite pmid|34258267}}</ref> Relevant SARS-CoV-2 Genome Variation through Six Months of Worldwide Monitoring #MMPMID34258267 Hakmaoui A; Khan F; Liacini A; Kaur A; Berka Y; Machraoui S; Soualhine H; Berka N; Rais H; Admou B Biomed Res Int 2021[]; 2021 (ä): 5553173 PMID34258267show ga Real-time genome monitoring of the SARS-CoV-2 pandemic outbreak is of utmost importance for designing diagnostic tools, guiding antiviral treatment and vaccination strategies. In this study, we present an accurate method for temporal and geographical comparison of mutational events based on GISAID database genome sequencing. Among 42523 SARS-CoV-2 genomes analyzed, we found 23202 variants compared to the reference genome. The Ti/Tv (transition/transversion) ratio was used to filter out possible false-positive errors. Transition mutations generally occurred more frequently than transversions. Our clustering analysis revealed remarkable hotspot mutation patterns for SARS-CoV-2. Mutations were clustered based on how their frequencies changed over time according to each geographical location. We observed some clusters showing a clear variation in mutation frequency and continuously evolving in the world. However, many mutations appeared in specific periods without a clear pattern over time. Various important nonsynonymous mutations were observed, mainly in Oceania and Asia. More than half of these mutations were observed only once. Four hotspot mutations were found in all geographical locations at least once: T265I (NSP2), P314L (NSP12), D614G (S), and Q57H (ORF3a). The current analysis of SARS-CoV-2 genomes provides valuable information on the geographical and temporal mutational evolution of SARS-CoV-2. |*COVID-19/epidemiology/genetics[MESH] |*Databases, Nucleic Acid[MESH] |*Evolution, Molecular[MESH] |*Genome, Viral[MESH] |*Mutation[MESH] |*Pandemics[MESH] |*Phylogeny[MESH] |Humans[MESH]Relevant SARS-CoV-2 Genome Variation through Six Months of Worldwide M(epmc).pdf DeepDyve Pubget Overpricing