Quantitative and qualitative subgenomic RNA profiles of SARS-CoV-2 in respiratory samples : A comparison between Omicron BA.2 and non-VOC-D614G
Copyright © 2024 The Authors. Publishing services by Elsevier B.V. All rights reserved..
The SARS-CoV-2 Omicron variants are notorious for their transmissibility, but little is known about their subgenomic RNA (sgRNA) expression. This study applied RNA-seq to delineate the quantitative and qualitative profiles of canonical sgRNA of 118 respiratory samples collected from patients infected with Omicron BA.2 and compared with 338 patients infected with non-variant of concern (non-VOC)-D614G. A unique characteristic profile depicted by the relative abundance of 9 canonical sgRNAs was reproduced by both BA.2 and non-VOC-D614G regardless of host gender, age and presence of pneumonia. Remarkably, such profile was lost in samples with low viral load, suggesting a potential application of sgRNA pattern to indicate viral activity of individual patient at a specific time point. A characteristic qualitative profile of canonical sgRNAs was also reproduced by both BA.2 and non-VOC-D614G. The presence of a full set of canonical sgRNAs carried a coherent correlation with crude viral load (AUC = 0.91, 95% CI 0.88-0.94), and sgRNA ORF7b was identified to be the best surrogate marker allowing feasible routine application in characterizing the infection status of individual patient. Further potentials in using sgRNA as a target for vaccine and antiviral development are worth pursuing.
| Medienart: |
E-Artikel |
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| Erscheinungsjahr: |
2024 |
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| Erschienen: |
2024 |
| Enthalten in: |
Zur Gesamtaufnahme - year:2024 |
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| Enthalten in: |
Virologica Sinica - (2024) vom: 03. Feb. |
| Sprache: |
Englisch |
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| Beteiligte Personen: |
Chen, Zigui [VerfasserIn] |
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| Links: |
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| Themen: |
Coronavirus |
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| Anmerkungen: |
Date Revised 27.02.2024 published: Print-Electronic Citation Status Publisher |
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| doi: |
10.1016/j.virs.2024.01.010 |
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| funding: |
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| Förderinstitution / Projekttitel: |
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| PPN (Katalog-ID): |
NLM368056279 |
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| 520 | |a Copyright © 2024 The Authors. Publishing services by Elsevier B.V. All rights reserved. | ||
| 520 | |a The SARS-CoV-2 Omicron variants are notorious for their transmissibility, but little is known about their subgenomic RNA (sgRNA) expression. This study applied RNA-seq to delineate the quantitative and qualitative profiles of canonical sgRNA of 118 respiratory samples collected from patients infected with Omicron BA.2 and compared with 338 patients infected with non-variant of concern (non-VOC)-D614G. A unique characteristic profile depicted by the relative abundance of 9 canonical sgRNAs was reproduced by both BA.2 and non-VOC-D614G regardless of host gender, age and presence of pneumonia. Remarkably, such profile was lost in samples with low viral load, suggesting a potential application of sgRNA pattern to indicate viral activity of individual patient at a specific time point. A characteristic qualitative profile of canonical sgRNAs was also reproduced by both BA.2 and non-VOC-D614G. The presence of a full set of canonical sgRNAs carried a coherent correlation with crude viral load (AUC = 0.91, 95% CI 0.88-0.94), and sgRNA ORF7b was identified to be the best surrogate marker allowing feasible routine application in characterizing the infection status of individual patient. Further potentials in using sgRNA as a target for vaccine and antiviral development are worth pursuing | ||
| 650 | 4 | |a Journal Article | |
| 650 | 4 | |a Coronavirus | |
| 650 | 4 | |a Non-VOC-D614G | |
| 650 | 4 | |a Omicron BA.2 | |
| 650 | 4 | |a RNA-seq | |
| 650 | 4 | |a SARS-CoV-2 | |
| 650 | 4 | |a Subgenomic RNA(sgRNA) | |
| 700 | 1 | |a Ng, Rita Way Yin |e verfasserin |4 aut | |
| 700 | 1 | |a Lui, Grace |e verfasserin |4 aut | |
| 700 | 1 | |a Ling, Lowell |e verfasserin |4 aut | |
| 700 | 1 | |a Leung, Agnes S Y |e verfasserin |4 aut | |
| 700 | 1 | |a Chow, Chit |e verfasserin |4 aut | |
| 700 | 1 | |a Boon, Siaw Shi |e verfasserin |4 aut | |
| 700 | 1 | |a Ho, Wendy C S |e verfasserin |4 aut | |
| 700 | 1 | |a Wang, Maggie Haitian |e verfasserin |4 aut | |
| 700 | 1 | |a Chan, Renee Wan Yi |e verfasserin |4 aut | |
| 700 | 1 | |a Li, Albert Martin |e verfasserin |4 aut | |
| 700 | 1 | |a Hui, David Shu Cheong |e verfasserin |4 aut | |
| 700 | 1 | |a Chan, Paul Kay Sheung |e verfasserin |4 aut | |
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