Transcriptional and epi-transcriptional dynamics of SARS-CoV-2 during cellular infection.
Transcriptional and epi-transcriptional dynamics of SARS-CoV-2 during cellular infection.
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DOI:
10.1016/j.celrep.2021.109108
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发表时间:
2021-05-11
期刊:
影响因子:
8.8
通讯作者:
Coin LJM
中科院分区:
文献类型:
--
作者:
Chang JJ;Rawlinson D;Pitt ME;Taiaroa G;Gleeson J;Zhou C;Mordant FL;De Paoli-Iseppi R;Caly L;Purcell DFJ;Stinear TP;Londrigan SL;Clark MB;Williamson DA;Subbarao K;Coin LJM
Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) uses subgenomic RNA (sgRNA) to produce viral proteins for replication and immune evasion. We apply long-read RNA and cDNA sequencing to in vitro human and primate infection models to study transcriptional dynamics. Transcription-regulating sequence (TRS)-dependent sgRNA upregulates earlier in infection than TRS-independent sgRNA. An abundant class of TRS-independent sgRNA consisting of a portion of open reading frame 1ab (ORF1ab) containing nsp1 joins to ORF10, and the 3′ untranslated region (UTR) upregulates at 48 h post-infection in human cell lines. We identify double-junction sgRNA containing both TRS-dependent and -independent junctions. We find multiple sites at which the SARS-CoV-2 genome is consistently more modified than sgRNA and that sgRNA modifications are stable across transcript clusters, host cells, and time since infection. Our work highlights the dynamic nature of the SARS-CoV-2 transcriptome during its replication cycle. SARS-CoV-2 is the pathogen that is responsible for the global COVID-19 pandemic. Chang et al. demonstrate that the transcriptome of SARS-CoV-2 is dynamic and complex, with expression and relative proportions of viral mRNA changing to reflect the stage of infection in vitro. In contrast, the epi-transcriptome is stable throughout infection.
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DOI:
10.1093/bioinformatics/btr215
发表时间:
2011-07-01
期刊:
Bioinformatics (Oxford, England)
影响因子:
--
作者:
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影响因子:
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DOI:
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发表时间:
2019-12-15
期刊:
Bioinformatics (Oxford, England)
影响因子:
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作者:
通讯作者:
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影响因子:
14.9
作者:
Kalvari I;Argasinska J;Quinones-Olvera N;Nawrocki EP;Rivas E;Eddy SR;Bateman A;Finn RD;Petrov AI
通讯作者:
Petrov AI
影响因子:
14.9
作者:
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通讯作者:
Noble WS