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. 2022 Nov:321:198908.
doi: 10.1016/j.virusres.2022.198908. Epub 2022 Aug 31.

Genomic surveillance: Circulating lineages and genomic variation of SARS-CoV-2 in early pandemic in Ceará state, Northeast Brazil

Affiliations

Genomic surveillance: Circulating lineages and genomic variation of SARS-CoV-2 in early pandemic in Ceará state, Northeast Brazil

Francisca Andréa da Silva Oliveira et al. Virus Res. 2022 Nov.

Abstract

In the Northeast of Brazil, Ceará was the second state most impacted by COVID-19 in number of cases and death rate. Despite that, the early dynamics of the pandemic in Ceará was not yet well understood due the low genomic surveillance of SARS-CoV-2 in 2020. In this study, we analyze the circulating lineages and the genomic variation of the virus in Ceará state. Thirty-four genomes were sequenced and combined with sequences available in GISAID database from March 2020 to June 2021 to compose the study dataset. The most prevalent lineages detected were B.1.1.33, in 2020, and P.1, in 2021. Other lineages were found, such as P.2, sublineages of P.1, B.1, B.1.1, B.1.1.28 and B.1.212. Analyzing the mutations, a total of 202 single-nucleotide polymorphisms (SNPs) were identified among the 34 genomes sequenced, of which 127 were missense, 74 synonymous, and one was a nonsense mutation. Among the missense mutations, C14408T, A23403G, T27299C, G28881A G28883C, and T29148C were the most prevalent within the dataset. Although SARS-CoV-2 sequencing data was limited in 2020, our results could provide insights to better understand the genetic diversity of the circulating lineages in Ceará.

Keywords: COVID-19; Genome sequences; Mutations.

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Conflict of interest statement

Declaration of Competing Interest 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
Prevalence of SARS-CoV-2 genome sequences for each month from Ceará.
Fig. 2
Fig. 2
Mutations of SARS-CoV-2 genome sequences from Ceará state, Northeast Brazil. a) Frequency of SNPs per SARS-CoV-2 genome position among the 34 genome sequences (missense SNPs with prevalence >40% were labelled). b) Frequency of SNPs in Spike protein (S) among the 34 genome sequences (SNPs with prevalence >20% were labelled).
Fig. 3
Fig. 3
ML phylogenetic tree of the genomes obtained in the present study (red branches) and representatives of all VOCs and VOIs circulating during the study period. Colored highlights indicate variants that are represented within the genomes sequenced in the study.

References

    1. Alonge M., Soyk S., Ramakrishnan S., Wang X., Goodwin S., Sedlazeck F.J., Lippman Z.B., Schatz M.C. RaGOO: fast and accurate reference-guided scaffolding of draft genomes. Genome Biol. 2019;20:1–17. doi: 10.1186/s13059-019-1829-6. - DOI - PMC - PubMed
    1. Andrews, S., 2010. A Quality Control Tool for High Throughput Sequence Data. Available online at: http://www.bioinformatics.babraham.ac.uk/projects/fastqc/.
    1. Bolger A.M., Lohse M., Usadel B. Trimmomatic: a flexible trimmer for illumina sequence data. Bioinformatics. 2014;30:2114–2120. doi: 10.1093/bioinformatics/btu170. - DOI - PMC - PubMed
    1. Botelho-Souza L.F., Nogueira-Lima F.S., Roca T.P., Naveca F.G., de Oliveria dos Santos A., Maia A.C.S., da Silva C.C., de Melo Mendonça A.L.F., Lugtenburg C.A.B., Azzi C.F.G., Fontes J.L.F., Cavalcante S., de Cássia Pontello Rampazzo R., Santos C.H.N., Di Sabatino Guimarães A.P., Máximo F.R., Villalobos-Salcedo J.M., Vieira D.S. SARS-CoV-2 genomic surveillance in Rondônia, Brazilian Western Amazon. Sci. Rep. 2021;11:1–12. doi: 10.1038/s41598-021-83203-2. - DOI - PMC - PubMed
    1. Candido D.S., Claro I.M., de Jesus J.G., Souza W.M., Moreira F.R.R., Dellicour S., Mellan T.A., du Plessis L., Pereira R.H.M., Sales F.C.S., Manuli E.R., Thézé J., Almeida L., Menezes M.T., Voloch C.M., Fumagalli M.J., Coletti T.M., da Silva C.A.M., Ramundo M.S., Amorim M.R., Hoeltgebaum H.H., Mishra S., Gill M.S., Carvalho L.M., Buss L.F., Prete C.A., Ashworth J., Nakaya H.I., Peixoto P.S., Brady O.J., Nicholls S.M., Tanuri A., Rossi Á.D., Braga C.K.V., Gerber A.L., de Guimarães A.P.C., Gaburo N., Alencar C.S., Ferreira A.C.S., Lima C.X., Levi J.E., Granato C., Ferreira G.M., Francisco R.S., Granja F., Garcia M.T., Moretti M.L., Perroud M.W., Castiñeiras T.M.P.P., Lazari C.S., Hill S.C., de Souza Santos A.A., Simeoni C.L., Forato J., Sposito A.C., Schreiber A.Z., Santos M.N.N., de Sá C.Z., Souza R.P., Resende-Moreira L.C., Teixeira M.M., Hubner J., Leme P.A.F., Moreira R.G., Nogueira M.L., Ferguson N.M., Costa S.F., Proenca-Modena J.L., Vasconcelos A.T.R., Bhatt S., Lemey P., Wu C.H., Rambaut A., Loman N.J., Aguiar R.S., Pybus O.G., Sabino E.C., Faria N.R. Evolution and epidemic spread of SARS-CoV-2 in Brazil. Science. 2020;369:1255–1260. doi: 10.1126/science.abd2161. 80-. - DOI - PMC - PubMed

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