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

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 or operational taxonomic units (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 (South America, North America, Europe, Asia, Africa, and Oceania). 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.

Dynamics of SARS-CoV-2 mutations reveals regional-specificity and similar trends of N501 and High-Frequency mutation N501Y in different levels of control measures

“…In our previous work [46], we observed that the mutation T85I in nsp2 has a higher frequency in North America than in other continents. Here, we show that this MF mutation maintains this tendency, persisting since its appearance at a global NRFp of ∼0.2 (Fig.…”

“…A global, roughly constant, relative frequency of MF and LF mutations could be explained by their persistence in regions with specific climatological factors. In our previous work [33], we observed that the mutation T85I in nsp2 has much more frequency in North America than in other continents. Here, we showed that this MF mutation maintains this tendency persisting since its appearance at ~10 % NRFp (Fig.…”

“…To perform mutation frequency analysis considering the number of cases in each country we followed similar steps as described in Justo et al 2021 [33], with some modifications: we first downloaded 1 221 746 genomes from the GISAID database (as of April 24th, 2021). Sequences with less than 29 000 nt were removed and the resulting sequences were aligned against the reference SARS-CoV-2 genome (EPI_ISL_402125) from nt 203 to nt 29674 using ViralMSA.py [36,37].…”

Structure and Function of N-Terminal Zinc Finger Domain of SARS-CoV-2 NSP2

“…The study of viral-host protein interaction found that SARS-CoV nsp2 could interact with host proteins widely including prohibitin 1 (PHB1) and PHB2, which were implicated in a number of cellular functions, including cellular migration, differentiation, apoptosis, and so on (von Brunn et al 2007 ; Cornillez-Ty et al . 2009 ; Justo Arevalo et al 2021 ). Deletions of the nsp2 in MHV and SARS-CoV resulted in attenuating of viral growth and RNA synthesis, but not death (Graham et al 2005 ).…”

Identification of Epidemiological Traits by Analysis of SARS−CoV−2 Sequences

“…Mercatelli and Giorgi detected and annotated all mutations in 48,635 SARS−CoV−2 sequences in the GISAID database by comparing with the reference Wuhan genome and found that the major mutational type is single nucleotide transitions, and some clads of sequences have geographic and genomic specificity [ 24 ]. Arevalo et al identified five major haplotypes of 171,461 SARS−CoV−2 genomes in the GISAID database through normalization by relative mutation frequencies and found that the haplotypes are associated with the temporal and geographic distribution, but not with age, gender, or patient status [ 25 ]. Shen et al also found that the haplotypes are associated with a localized transmission pattern at the city, state and country level [ 26 ].…”