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Sub-genomic RNA Expression in SARS-CoV-2 B.1.411 and B.1.1.7 Infections in Sri Lanka
PURPOSE: As experienced by many countries, Sri Lanka is currently experiencing a large COVID-19 outbreak, with over 90 cases/one million population. The previous outbreak, which was due to the B.1.411 virus (Sri Lankan lineage) resulted in a significantly fewer number of cases and deaths compared to...
Autores principales: | , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Published by Elsevier Ltd.
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8884804/ http://dx.doi.org/10.1016/j.ijid.2021.12.058 |
Sumario: | PURPOSE: As experienced by many countries, Sri Lanka is currently experiencing a large COVID-19 outbreak, with over 90 cases/one million population. The previous outbreak, which was due to the B.1.411 virus (Sri Lankan lineage) resulted in a significantly fewer number of cases and deaths compared to the current outbreak caused by B.1.1.7. Therefore, we sought to explore if the differences in the transmission rates and higher mortality rates with the introduction of B.1.1.7 is due to an increased expression of sub-genomic RNA, which is an essential step in the virus life cycle. METHODS & MATERIALS: Sputum or nasopharyngeal samples of 472 patients with SARS-CoV-2 infection were included in the analysis. Samples with the cycle threshold <30, were sequenced using 247 amplicons targeting the SARS-CoV-2 genome (MN908947v3). Library preparation was done using AmpliSeq prep kit and sequenced either on illumina iSeq100 or Nextseq550 platforms. Basecalling and demultiplexing were done using the default bcl2fastq (v2.20) pipeline. Raw index-trimmed fastqs were analyzed for sub-genomic RNA using Periscope (https://github.com/sheffield-bioinformatics-core/periscope). Raw reads were aligned and checked for the leader sequence at the start of each open reading frame (ORF). The sgRNA detected reads were counted, classified into ORFs and normalized using the genomic RNA counts at each position. Groups were compared with an unpaired Wilcoxon test using R\rstatix package. Figures were generated in R\ggpubr. RESULTS: Out of the remaining 434 datasets after the quality control step, 164 were of B.1.1.7 lineage while 237 were B.1.4.11. Means of the normalized sgRNA counts between B.1.411 and B.1.1.7 viruses were significantly different in six ORFs. Viruses of the B.1.411 lineage expressed significantly higher sgRNA for Spike protein (p = 0.014), ORF3a (p = 0. 0001), Membrane protein (p = 3.62E-10), ORF8 (p = 1.81E-05), and ORF7a (p = 0.0004) than those in B.1.1.7 samples. Contrastingly, Nucleocapsid (N) protein had significantly higher sgRNA expression in B.1.1.7 samples (p=0.0001). CONCLUSION: Our results suggest that increased expression of sgRNA for a particular virus lineage does not necessarily associate with higher transmissibility as higher expression of sgRNA of B.1.1.7 compared to the B.1.411 lineage virus was only seen for the N protein. |
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