Phylo-geo haplotype network-based characterization of SARS-CoV-2 strains circulating in India (2020-2022)

Material & Methods

This study was undertaken at National Influenza Centre and Bioinformatics Group, ICMR-National Institute of Virology (ICMR-NIV), Pune from 2020-2022 after obtaining approval from Institutional Ethics Committee.

Results & Discussion

A median-joining haplotype network was constructed in comparison with phylogenetic trees to study the evolution of SARS-CoV-2 strains circulating in different geographical regions of India during 2020-2022. This study’s analysis of SARS-CoV-2 genomic sequences (n=612) revealed 171 parsimony informative (PI) sites among the 643 segregating sites. Nucleotide diversity among the sequences was noted as 0.0133. The negative value (-2.72) of statistic Tajima’s D denoted that these PI sites were significant in the evolution of these viral genomes. Allocation of each genome sequence to a haplotype was carried out through the detection of the mutation motif, which was haplotype-specific, based on the sites of segregation among the sequences, and that had revealed 420 different haplotypes (Supplementary Material II). The median-joining networks of the haplotypes (with traits coloured based on geographical region as in Supplementary Fig. 2 and clades as in Supplementary Fig. 3) were constructed, and the network topology (Supplementary Fig. 2 and 3) showed multiple star-like appearances, denoting the expansion of highly differentiated haplotypes. On analysis of molecular variance, the genetic distance found among the viral haplotypes from different geographical regions was insignificant (5.14%, PhiST=0.0514). Thus, the viral haplotypes of different geographical areas of this study showed a lot of haplotype sharing (Supplementary Fig. 2), which might indicate frequent travel inhuman populations among the geographical regions of this study. Due to human travel, previous investigators reported the distribution of haplotypes across geographical areas in the early phase of the pandemic in 2020^8,16-18.

Further, the analysis of molecular variance denoted a significant genetic distance among the viral haplotypes from different clades (60.07%, PhiST=0.6007), which differentiated the strains into distinct haplo-groups that showed a minimal haplotype sharing (Supplementary Fig. 3). Haplotypes viz., 9, 45, 107, 83, 160, 14 and 14 were identified among the haplogroups/clades: O, G, GH, GR, GK, GRA and others (S, GRY/alpha variant and GV), respectively. The circulation of the strains from the different clades in India during March 2020 – March 2022 are depicted in Figure. A few SARS-CoV-2 sequences of O and S clades in India that circulated during 2020, similar to the Wuhan prototype strain, were noted to have evolved into G and GR/gamma variant clades that circulated during 2020-21and were followed by subsequent evolutions into clades GH/beta variant that also circulated during 2020-21, GK/delta variant, that circulated during 2021 and GRA/ omicron variant that circulated during 2022 (Supplementary Fig. 3). Strikingly, G and GR clades co-evolved and became epicentres for the evolution of other clades. The GK that caused a wave in the pandemic during 2021, the GRA that caused a wave in the pandemic during 2022 and the viral strains from other less prevalent clades in India, such as GRY/alpha variant and GV clades, were found to arise from G-GR background only. Thus, the haplotype analysis concerning clades could throw light on the likely clade diversification pattern, emphasizing G-GR as the epicentre for the evolution of the other clades.

Close

Figure

. Circulation of the SARS-CoV-2 strains from different clades in India during March 2020-2022.

Export to PPT

Pango lineages B.1, B.1.1, B.1.36, B.617.2 and BA.2 were predominantly found among the strains of G, GR, GH, GK and GRA clades, respectively, while B.1 and B.1.1.7 lineages represented co-evolution/emergence of G, GR and GH clades (Supplementary Fig. 4). Mutation analysis with respect to the Wuhan prototype reference sequence showed that the amino acid substitutions D614G in spike and P323L in NSP12_RdRp proteins, which were earlier found to be associated with the predominantly transmitting strains¹⁹, were frequently detected in strains across the G, GH, GR, GK and GRA clades in this study (Supplementary Fig. 5). These findings were in agreement with that of other investigators^20,21.

Analysis of the distribution of clades among different geographical regions of India had denoted that strains from clade GH reported predominantly during the first wave in 2020 were more frequently identified among the genomes submitted from northern parts of India than those from other parts of India, whereas the strains from clade GK reported predominantly during the second wave in 2021 were detected less in northern India than that in other parts (Supplementary Fig. 6). Notably, the clade distribution (Supplementary Fig. 6) showed the prevalence of an average of three clades per region. Besides the study sample set, this scenario was reflected among all the sequences submitted to GISAID from March 2020 to March 2022 (data not shown). Similarly, distribution bias of different clades among geographical regions has been noted during 2020 by other investigators^22,23. However, further studies would be essential to understand the factors affecting the distribution bias of different SARS-CoV-2 clades. An evolutionary stasis was noted relatively in 2020 during the initial phase of the pandemic, while variants of concern such as delta and omicron that acquired selective advantages to the host immune system were found to be emerging over time due to mutational jumps (Figure; Supplementary Fig. 3, 4 and 5). This observation agrees with a few previous studies from other countries^24-27.

The maximum likelihood phylogenetic trees were constructed using individual viral sequences (Supplementary Fig. 7) and viral haplotype sequences (Supplementary Fig. 8) to compare the above results with reference to the direct use of phylogenetic methods. The value addition in the case of the haplotype network (Supplementary Fig. 3) in terms of emerging lineages/pathways of the virus’s evolution through the topology was evident when compared with the phylogenic trees constructed based on either the individual viral sequences (Supplementary Fig. 7) or viral haplotype sequences (Supplementary Fig. 8). Similar observations were reported in other studies as well^6-8.

By using the haplotype network approach that uses the most frequent mutational events and viral haplotypes with common variants, we could note a more explicit inference and clarification of the genetic background of variants of concern, better visualization of the pathways of evolution among different variants and efficient identification of recurrent mutations and steps in the emergence of the variants.

In conclusion, this study characterized the SARS-CoV2 strains circulating in India during 2020-2022. The findings indicated G-GR as the epicentre for the evolution of several other clades of SARS-CoV2 and differential circulation of GH and GK clades in different geographical regions of India during March 2020–March 2022. The study also reiterated that haplotype network approaches were effective and more robust than the surveillance strategies based only on phylogenetic trees, especially in large-scale analysis of less variable viral populations such as SARS-CoV-2. In the recent SARS-CoV-2 pandemic scenario, understanding the viral evolutionary strategies was crucial to identify emerging variants that might fit better as vaccine-escapes or more virulence. The knowledge generated by us might be helpful in designing efficient preventive and therapeutic strategies during possible resurgence, if any, in future.