Journal
FRONTIERS IN MICROBIOLOGY
Volume 13, Issue -, Pages -Publisher
FRONTIERS MEDIA SA
DOI: 10.3389/fmicb.2022.1037455
Keywords
genomics and proteomics; big data; SWeeP; machine learning; diversity; virus
Categories
Funding
- group of Artificial Intelligence Applied to Bioinformatics of Federal University of Parana
- Coordination for the Improvement of Higher Education Personnel (CAPES)
- NAPI Bioinformatica from Fundacao Araucaria
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This study tracked the development of the COVID-19 pandemic in Brazil from a genomic/proteomic perspective and analyzed the comparative and evolutionary panorama of the lineages in the country. The study found two different genetic profiles of the epidemics in Brazil, with the emergence of the more aggressive P.1 lineages in the second wave. The unbalanced sequencing among Brazilian states may have facilitated the silent entry and dissemination of P.1 and other dangerous variants.
Brazil was the epicenter of worldwide pandemics at the peak of its second wave. The genomic/proteomic perspective of the COVID-19 pandemic in Brazil could provide insights to understand the global pandemics behavior. In this study, we track SARS-CoV-2 molecular information in Brazil using real-time bioinformatics and data science strategies to provide a comparative and evolutive panorama of the lineages in the country. SWeeP vectors represented the Brazilian and worldwide genomic/proteomic data from Global Initiative on Sharing Avian Influenza Data (GISAID) between February 2020 and August 2021. Clusters were analyzed and compared with PANGO lineages. Hierarchical clustering provided phylogenetic and evolutionary analyses of the lineages, and we tracked the P.1 (Gamma) variant origin. The genomic diversity based on Chao's estimation allowed us to compare richness and coverage among Brazilian states and other representative countries. We found that epidemics in Brazil occurred in two moments with different genetic profiles. The P.1 lineages emerged in the second wave, which was more aggressive. We could not trace the origin of P.1 from the variants present in Brazil. Instead, we found evidence pointing to its external source and a possible recombinant event that may relate P.1 to a B.1.1.28 variant subset. We discussed the potential application of the pipeline for emerging variants detection and the PANGO terminology stability over time. The diversity analysis showed that the low coverage and unbalanced sequencing among states in Brazil could have allowed the silent entry and dissemination of P.1 and other dangerous variants. This study may help to understand the development and consequences of variants of concern (VOC) entry.
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