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Virol J ; 21(1): 121, 2024 May 30.
Artigo em Inglês | MEDLINE | ID: mdl-38816844

RESUMO

BACKGROUND: During the pandemic, whole genome sequencing was critical to characterize SARS-CoV-2 for surveillance, clinical and therapeutical purposes. However, low viral loads in specimens often led to suboptimal sequencing, making lineage assignment and phylogenetic analysis difficult. We propose an alternative approach to sequencing these specimens that involves sequencing in triplicate and concatenation of the reads obtained using bioinformatics. This proposal is based on the hypothesis that the uncovered regions in each replicate differ and that concatenation would compensate for these gaps and recover a larger percentage of the sequenced genome. RESULTS: Whole genome sequencing was performed in triplicate on 30 samples with Ct > 32 and the benefit of replicate read concatenation was assessed. After concatenation: i) 28% of samples reached the standard quality coverage threshold (> 90% genome covered > 30x); ii) 39% of samples did not reach the coverage quality thresholds but coverage improved by more than 40%; and iii) SARS-CoV-2 lineage assignment was possible in 68.7% of samples where it had been impaired. CONCLUSIONS: Concatenation of reads from replicate sequencing reactions provides a simple way to access hidden information in the large proportion of SARS-CoV-2-positive specimens eliminated from analysis in standard sequencing schemes. This approach will enhance our potential to rule out involvement in outbreaks, to characterize reinfections and to identify lineages of concern for surveillance or therapeutical purposes.


Assuntos
COVID-19 , Genoma Viral , Filogenia , SARS-CoV-2 , Carga Viral , Sequenciamento Completo do Genoma , SARS-CoV-2/genética , SARS-CoV-2/classificação , SARS-CoV-2/isolamento & purificação , Humanos , COVID-19/virologia , Carga Viral/métodos , Genoma Viral/genética , Sequenciamento Completo do Genoma/métodos , Biologia Computacional/métodos , RNA Viral/genética , Sequenciamento de Nucleotídeos em Larga Escala/métodos
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