Investigating the evolutionary origins of the first three SARS-CoV-2 variants of concern
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Abstract
The emergence of Variants of Concern (VOCs) of SARS-CoV-2 with increased transmissibility, immune evasion properties, and virulence poses a great challenge to public health. Despite unprecedented efforts to increase genomic surveillance, fundamental facts about the evolutionary origins of VOCs remain largely unknown. One major uncertainty is whether the VOCs evolved during transmission chains of many acute infections or during long-term infections within single individuals. We test the consistency of these two possible paths with the observed dynamics, focusing on the clustered emergence of the first three VOCs, Alpha, Beta, and Gamma, in late 2020, following a period of relative evolutionary stasis. We consider a range of possible fitness landscapes, in which the VOC phenotypes could be the result of single mutations, multiple mutations that each contribute additively to increasing viral fitness, or epistatic interactions among multiple mutations that do not individually increase viral fitness—a “fitness plateau”. Our results suggest that the timing and dynamics of the VOC emergence, together with the observed number of mutations in VOC lineages, are in best agreement with the VOC phenotype requiring multiple mutations and VOCs having evolved within single individuals with long-term infections.
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SciScore for 10.1101/2022.05.09.491227: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
NIH rigor criteria are not applicable to paper type.Table 2: Resources
Software and Algorithms Sentences Resources Inferring the selective advantage of VOCs: Finally, the selective advantage s of the VOCs is determined by fitting an exponential function, f(t), of the form, f(t)=aest, to the proportion of Alpha, Beta, and Gamma variants sampled in the country where they were first detected (i.e., UK, South Africa, and Brazil) using the NonlinearModelFit function in Mathematica 11.0 (cite Mathematica). Gammasuggested: (GAMMA, RRID:SCR_009484)Mathematicasuggested: (Wolfram Mathematica, RRID:SCR_014448)Results from OddPub: Thank you for sharing your code.
Results from LimitationRecognizer: An explicit …SciScore for 10.1101/2022.05.09.491227: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
NIH rigor criteria are not applicable to paper type.Table 2: Resources
Software and Algorithms Sentences Resources Inferring the selective advantage of VOCs: Finally, the selective advantage s of the VOCs is determined by fitting an exponential function, f(t), of the form, f(t)=aest, to the proportion of Alpha, Beta, and Gamma variants sampled in the country where they were first detected (i.e., UK, South Africa, and Brazil) using the NonlinearModelFit function in Mathematica 11.0 (cite Mathematica). Gammasuggested: (GAMMA, RRID:SCR_009484)Mathematicasuggested: (Wolfram Mathematica, RRID:SCR_014448)Results from OddPub: Thank you for sharing your code.
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.
- No funding statement was detected.
- No protocol registration statement was detected.
Results from scite Reference Check: We found no unreliable references.
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