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Global Geographic and Temporal Analysis of SARS-CoV-2 Haplotypes Normalized by COVID-19 Cases during the Pandemic

View ORCID ProfileSantiago Justo Arevalo, View ORCID ProfileDaniela Zapata Sifuentes, Cesar Huallpa Robles, View ORCID ProfileGianfranco Landa Bianchi, View ORCID ProfileAdriana Castillo Chavez, View ORCID ProfileRomina Garavito-Salini Casas, Guillermo Uceda-Campos, View ORCID ProfileRoberto Pineda Chavarria
doi: https://doi.org/10.1101/2020.07.12.199414
Santiago Justo Arevalo
1Universidad Ricardo Palma, Universidad de Sao Paulo
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  • For correspondence: santiago.jus.are@usp.br
Daniela Zapata Sifuentes
2Universidad Ricardo Palma
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Cesar Huallpa Robles
3Universidad Agraria La Molina
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Gianfranco Landa Bianchi
2Universidad Ricardo Palma
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Adriana Castillo Chavez
2Universidad Ricardo Palma
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Romina Garavito-Salini Casas
2Universidad Ricardo Palma
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Guillermo Uceda-Campos
4Universidade de Sao Paulo, Universidad Nacional Pedro Ruiz Gallo
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Roberto Pineda Chavarria
2Universidad Ricardo Palma
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ABSTRACT

Since the identification of SARS-CoV-2, a large number of genomes have been sequenced with unprecedented speed around the world. This marks a unique opportunity to analyze virus spreading and evolution in a worldwide context. Currently, there is not a useful haplotype description to help to track important and globally scattered mutations. Also, differences in the number of sequenced genomes between countries and/or months make it difficult to identify the emergence of haplotypes in regions where few genomes are sequenced but a large number of cases are reported. We propose an approach based on the normalization by COVID-19 cases of relative frequencies of mutations using all the available data to identify major haplotypes. Furthermore, we can use a similar normalization approach to tracking the temporal and geographic distribution of haplotypes in the world. Using 171 461 genomes, we identify five major haplotypes (OTUs) based on nine high-frequency mutations. OTU_3 characterized by mutations R203K and G204R is currently the most frequent haplotype circulating in four of the six continents analyzed. On the other hand, during almost all months analyzed, OTU_5 characterized by the mutation T85I in nsp2 is the most frequent in North America. Recently (since September), OTU_2 has been established as the most frequent in Europe. OTU_1, the ancestor haplotype is near to extinction showed by its low number of isolations since May. Also, we analyzed whether age, gender, or patient status is more related to a specific OTU. We did not find OTU’s preference for any age group, gender, or patient status. Finally, we discuss structural and functional hypotheses in the most frequently identified mutations, none of those mutations show a clear effect on the transmissibility or pathogenicity.

Competing Interest Statement

The authors have declared no competing interest.

Footnotes

  • This version contains an updated analysis of the global geographical and temporal distribution of SARS-CoV-2 haplotypes. Here, we analyzed the data up to November 30th. We also present a better analysis of the haplotypes related to patient features

  • http://sarscov2haplofinder.urp.edu.pe/

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license.
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Posted December 22, 2020.
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Global Geographic and Temporal Analysis of SARS-CoV-2 Haplotypes Normalized by COVID-19 Cases during the Pandemic
Santiago Justo Arevalo, Daniela Zapata Sifuentes, Cesar Huallpa Robles, Gianfranco Landa Bianchi, Adriana Castillo Chavez, Romina Garavito-Salini Casas, Guillermo Uceda-Campos, Roberto Pineda Chavarria
bioRxiv 2020.07.12.199414; doi: https://doi.org/10.1101/2020.07.12.199414
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Global Geographic and Temporal Analysis of SARS-CoV-2 Haplotypes Normalized by COVID-19 Cases during the Pandemic
Santiago Justo Arevalo, Daniela Zapata Sifuentes, Cesar Huallpa Robles, Gianfranco Landa Bianchi, Adriana Castillo Chavez, Romina Garavito-Salini Casas, Guillermo Uceda-Campos, Roberto Pineda Chavarria
bioRxiv 2020.07.12.199414; doi: https://doi.org/10.1101/2020.07.12.199414

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