One Year of SARS-CoV-2: How Much Has the Virus Changed?
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Abstract
Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has caused a worldwide crisis with profound effects on both public health and the economy. In order to combat the COVID-19 pandemic, research groups have shared viral genome sequence data through the Global Initiative on Sharing All Influenza Data (GISAID). Over the past year, ≈290,000 full SARS-CoV-2 proteome sequences have been deposited in the GISAID. Here, we used these sequences to assess the rate of nonsynonymous mutants over the entire viral proteome. Our analysis shows that SARS-CoV-2 proteins are mutating at substantially different rates, with most of the viral proteins exhibiting little mutational variability. As anticipated, our calculations capture previously reported mutations that arose in the first months of the pandemic, such as D614G (Spike), P323L (NSP12), and R203K/G204R (Nucleocapsid), but they also identify more recent mutations, such as A222V and L18F (Spike) and A220V (Nucleocapsid), among others. Our comprehensive temporal and geographical analyses show two distinct periods with different proteome mutation rates: December 2019 to July 2020 and August to December 2020. Notably, some mutation rates differ by geography, primarily during the latter half of 2020 in Europe. Furthermore, our structure-based molecular analysis provides an exhaustive assessment of SARS-CoV-2 mutation rates in the context of the current set of 3D structures available for SARS-CoV-2 proteins. This emerging sequence-to-structure insight is beginning to illuminate the site-specific mutational (in)tolerance of SARS-CoV-2 proteins as the virus continues to spread around the globe.
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SciScore for 10.1101/2020.12.16.423071: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
Institutional Review Board Statement not detected. Randomization not detected. Blinding not detected. Power Analysis not detected. Sex as a biological variable not detected. Table 2: Resources
Software and Algorithms Sentences Resources The residue mutation rates (MRs) of the human sequences were calculated in Python [54] considering sequences with the same length, including gaps, as the original Wuhan sequences extracted in December 2019 for all the viral proteins. Pythonsuggested: (IPython, RRID:SCR_001658)Residue MRs were computed as described above and plotted in world maps using MATLAB. MATLABsuggested: (MATLAB, RRID:SCR_001622)Protein structure-based mutational analysis: Mapping sequence mutations into … SciScore for 10.1101/2020.12.16.423071: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
Institutional Review Board Statement not detected. Randomization not detected. Blinding not detected. Power Analysis not detected. Sex as a biological variable not detected. Table 2: Resources
Software and Algorithms Sentences Resources The residue mutation rates (MRs) of the human sequences were calculated in Python [54] considering sequences with the same length, including gaps, as the original Wuhan sequences extracted in December 2019 for all the viral proteins. Pythonsuggested: (IPython, RRID:SCR_001658)Residue MRs were computed as described above and plotted in world maps using MATLAB. MATLABsuggested: (MATLAB, RRID:SCR_001622)Protein structure-based mutational analysis: Mapping sequence mutations into colored 3D crystallized proteins was performed in PyMOL [57]. PyMOLsuggested: (PyMOL, RRID:SCR_000305)Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).
Results from LimitationRecognizer: An explicit section about the limitations of the techniques employed in this study was not found. We encourage authors to address study limitations.Results from TrialIdentifier: No clinical trial numbers were referenced.
Results from Barzooka: We did not find any issues relating to the usage of bar graphs.
Results from JetFighter: We did not find any issues relating to colormaps.
Results from rtransparent:- Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
- Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
- No protocol registration statement was detected.
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