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. 2024 Feb 7;10(4):e25618.
doi: 10.1016/j.heliyon.2024.e25618. eCollection 2024 Feb 29.

Genetic characteristics of SARS-CoV-2 virus variants observed upon three waves of the COVID-19 pandemic in Ukraine between February 2021-January 2022

Affiliations

Genetic characteristics of SARS-CoV-2 virus variants observed upon three waves of the COVID-19 pandemic in Ukraine between February 2021-January 2022

Ganna V Gerashchenko et al. Heliyon. .

Abstract

The aim: of our study was to identify and characterize the SARS-CoV-2 variants in COVID-19 patients' samples collected from different regions of Ukraine to determine the relationship between SARS-CoV-2 phylogenetics and COVID-19 epidemiology.

Patients and methods: Samples were collected from COVID-19 patients during 2021 and the beginning of 2022 (401 patients). The SARS-CoV-2 genotyping was performed by parallel whole genome sequencing.

Results: The obtained SARS-CoV-2 genotypes showed that three waves of the COVID-19 pandemic in Ukraine were represented by three main variants of concern (VOC), named Alpha, Delta and Omicron; each VOC successfully replaced the earlier variant. The VOC Alpha strain was presented by one B.1.1.7 lineage, while VOC Delta showed a spectrum of 25 lineages that had different prevalence in 19 investigated regions of Ukraine. The VOC Omicron in the first half of the pandemic was represented by 13 lines that belonged to two different clades representing B.1 and B.2 Omicron strains. Each of the three epidemic waves (VOC Alpha, Delta, and Omicron) demonstrated their own course of disease, associated with genetic changes in the SARS-CoV-2 genome. The observed epidemiological features are associated with the genetic characteristics of the different VOCs, such as point mutations, deletions and insertions in the viral genome. A phylogenetic and transmission analysis showed the different mutation rates; there were multiple virus sources with a limited distribution between regions.

Conclusions: The evolution of SARS-CoV-2 virus and high levels of morbidity due to COVID-19 are still registered in the world. Observed multiple virus sourses with the limited distribution between regions indicates the high efficiency of the anti-epidemic policy pursued by the Ministry of Health of Ukraine to prevent the spread of the epidemic, despite the low level of vaccination of the Ukrainian population.

Keywords: COVID-19; Delta; NGS; Omicron; SARS-CoV-2 genotyping; VOC Alpha.

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Conflict of interest statement

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Figures

Fig. 1
Fig. 1
Geographical distributions of the patients group (n = 401): the regions of Ukraine are represented by the name of the relevant regional center.
Fig. 2
Fig. 2
The spectrum and SARS-variants frequencies in 7 NGS runs: Run A: 17 samples from Ivano-Frankivsk region (Ivano-Frankivsk, Nadvirna, Tysmenytsia, Kosovo, Kalush, Bohorodchany, Brushtyn) and 2 samples from Kyiv; Run B: 11 samples (Kyiv region - 7; Transcarpathian - 2; Kherson - 1; Sumy - 1); Run C: 54 samples (Cherkasy region - 4; Dnipropetrovsk region - 5; Kherson region - 4; Khmelnytsky region - 6; Kyiv region - 10; Volyn region - 7; Donetsk region - 4; Mykolaiv region - 1; Odesa region - 6; Poltava region - 5 Rivne - 2); Run D: 75 samples (Cherkasy - 5; Chernivtsi - 1; Ivano-Frankivsk - 13; Kyiv −1; Lviv - 7; Poltava - 9; Rivne - 6; Luhansk - 27; Ternopil - 4; Zaporizhia - 2); Run E: 75 samples (Dnipropetrovsk - 10; Kharkiv - 8; Kherson - 10; Kyiv - 9; Volyn - 9; Lviv - 9; Odesa - 10; Transcarpathian - 10); Run F: 74 samples (Dnipropetrovsk - 8; Mykolaiv - 3; Odesa - 39; Poltava - 5; Volyn - 3; Sumy - 5; Zaporizhia - 7; Zhytomyr - 4); Run G: 93 samples (Cherkasy - 10; Ivano-Frankivsk - 9; Kharkiv - 10; Khmelnytsky - 9; Kyiv - 10; Odesa - 9; Poltava - 9; Rivne - 6; Sumy - 7; Ternopil - 9; Transcarpathian - 5).
Fig. 3
Fig. 3
Epidemiological data of COVID-19 (Main epidemiological indexes): new cases, hospitalization, mortality in Ukraine (open data) between February 2021 – beginning of 2022.
Fig. 4
Fig. 4
Dates of sampling for the NGS run according to three COVID-19 waves in Ukraine.
Fig. 5
Fig. 5
Visualization of SARS-CoV-2 phylogenetics of 338 Ukrainian samples using Nextstraine Auspice software (https://auspice.us/). (A) clustered by the date of sample collection; (B) clustered by the genetic divergence.
Fig. 6
Fig. 6
The transmission network of the VOC Alpha Ukrainian samples (n = 97). Multi-colored nodes – the same sources from the regions shown in the legend, black node – theoretically calculated primary source of the network; red nodes - unsampled sources; light green oval - Kyiv transmission cluster, dark green oval – Dnipro transmission cluster, light blue oval - Ivano-Frankivsk transmission cluster; black arrow – potentially first node in the transmission network. (For interpretation of the references to color in this figure legend, the reader is referred to the Web version of this article.)
Fig. 7
Fig. 7
The transmission network of the Omicron Ukrainian samples (n = 76). Multi-colored nodes – the same sources from the regions shown in the legend, black nodes – theoretically calculated primary sources of the networks, red nodes - unsampled sources; purple oval - Poltava and Odesa regions' cluster, blue oval - Ternopil-Rivne-Sumy cluster, dark blue oval – Kharkiv cluster, brown oval - Cherkasy cluster, light blue oval - Ivano-Frankivsk cluster; black arrow – potentially first node in the transmission network. (For interpretation of the references to color in this figure legend, the reader is referred to the Web version of this article.)
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