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A Negative Feedback Model to Explain Regulation of SARS-CoV-2 Replication and Transcription

Authors: Xin Li; Xin Li; Zhi Cheng; Fang Wang; Jia Chang; Qiang Zhao; Hao Zhou; +4 Authors

A Negative Feedback Model to Explain Regulation of SARS-CoV-2 Replication and Transcription

Abstract

Abstract Background: Coronavirus disease 2019 (COVID-19) is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Although a preliminary understanding of the replication and transcription mechanisms of SARS-CoV-2 has recently emerged, their regulation remains unclear.Results: Based on reanalysis of public data, we propose a negative feedback model to explain the regulation of replication and transcription in—but not limited to—CoVs. The key step leading to new discoveries was the identification of the cleavage sites of nsp15—an RNA uridylate-specific endoribonuclease, encoded by CoVs. According to this model, nsp15 regulates the synthesis of subgenomic RNAs (sgRNAs) and genomic RNAs (gRNAs) by cleaving transcription regulatory sequences in the body. The expression level of nsp15 determines the relative proportions of sgRNAs and gRNAs, which in turn change the expression level of nps15 to reach equilibrium between the replication and transcription of CoVs.Conclusions: The replication and transcription of CoVs are regulated by a negative feedback mechanism that influences the persistence of CoVs in hosts. Our findings enrich fundamental knowledge in the field of gene expression and its regulation, and provide new clues for future studies. One important clue is that nsp15 may be an important and ideal target for the development of drugs (e.g. uridine derivatives) against CoVs.

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Keywords

replication, nsp15, coronavirus, regulation model, Genetics, QH426-470, transcription

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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
14
Top 10%
Average
Top 10%
Green
gold