A map of the SARS-CoV-2 RNA structurome
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Abstract
SARS-CoV-2 has exploded throughout the human population. To facilitate efforts to gain insights into SARS-CoV-2 biology and to target the virus therapeutically, it is essential to have a roadmap of likely functional regions embedded in its RNA genome. In this report, we used a bioinformatics approach, ScanFold, to deduce the local RNA structural landscape of the SARS-CoV-2 genome with the highest likelihood of being functional. We recapitulate previously-known elements of RNA structure and provide a model for the folding of an essential frameshift signal. Our results find that SARS-CoV-2 is greatly enriched in unusually stable and likely evolutionarily ordered RNA structure, which provides a large reservoir of potential drug targets for RNA-binding small molecules. Results are enhanced via the re-analyses of publicly-available genome-wide biochemical structure probing datasets that are broadly in agreement with our models. Additionally, ScanFold was updated to incorporate experimental data as constraints in the analysis to facilitate comparisons between ScanFold and other RNA modelling approaches. Ultimately, ScanFold was able to identify eight highly structured/conserved motifs in SARS-CoV-2 that agree with experimental data, without explicitly using these data. All results are made available via a public database (the RNAStructuromeDB: https://structurome.bb.iastate.edu/sars-cov-2) and model comparisons are readily viewable at https://structurome.bb.iastate.edu/sars-cov-2-global-model-comparisons.
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SciScore for 10.1101/2020.04.17.045161: (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 For comparisons made between the Sarbecovirus genomes, the SARS-CoV genome (NC_004718.3) was aligned to SARS-CoV-2 (NC_045512.2) using the MAFFT webserver28 with default settings (in this case the FFT-ns-i method13 was implemented) CONCLUSION This work lays out the predicted local RNA folding landscape of the SARS-CoV-2 transcriptome. MAFFTsuggested: (MAFFT, SCR_011811)The MFE and z-score are depicted using a 120 nt moving averages of values, raw values can be seen in Table S1. b) Overall distribution of raw z-score … SciScore for 10.1101/2020.04.17.045161: (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 For comparisons made between the Sarbecovirus genomes, the SARS-CoV genome (NC_004718.3) was aligned to SARS-CoV-2 (NC_045512.2) using the MAFFT webserver28 with default settings (in this case the FFT-ns-i method13 was implemented) CONCLUSION This work lays out the predicted local RNA folding landscape of the SARS-CoV-2 transcriptome. MAFFTsuggested: (MAFFT, SCR_011811)The MFE and z-score are depicted using a 120 nt moving averages of values, raw values can be seen in Table S1. b) Overall distribution of raw z-score values calculated across the genome are shown alongside two other positive strand RNA genomes, ZIKV and HIV-1, which were analyzed using the same parameters as SARSCoV-2. c) Generic model of the first four stem loops found in the 5 UTR of Betacoronavirus genomes7,18(based on the Rfam entry for SL1-2; RF02910). d) Generi model showing the general architecture of the frameshift element (FSE) found in the similar coronavirus genomes11 (based on Rfam entry RF00507). Rfamsuggested: (Rfam, SCR_007891)Results from OddPub: Thank you for sharing your data.
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