Genomic variance of the 2019‐nCoV coronavirus
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Abstract
There is a rising global concern for the recently emerged novel coronavirus (2019‐nCoV). Full genomic sequences have been released by the worldwide scientific community in the last few weeks to understand the evolutionary origin and molecular characteristics of this virus. Taking advantage of all the genomic information currently available, we constructed a phylogenetic tree including also representatives of other coronaviridae, such as Bat coronavirus (BCoV) and severe acute respiratory syndrome. We confirm high sequence similarity (>99%) between all sequenced 2019‐nCoVs genomes available, with the closest BCoV sequence sharing 96.2% sequence identity, confirming the notion of a zoonotic origin of 2019‐nCoV. Despite the low heterogeneity of the 2019‐nCoV genomes, we could identify at least two hypervariable genomic hotspots, one of which is responsible for a Serine/Leucine variation in the viral ORF8‐encoded protein. Finally, we perform a full proteomic comparison with other coronaviridae, identifying key aminoacidic differences to be considered for antiviral strategies deriving from previous anti‐coronavirus approaches.
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SciScore for 10.1101/2020.02.02.931162: (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 MSA visualization was generated via Jalview v 2.11.0 [17] Jalviewsuggested: (Jalview, RRID:SCR_006459)Phylogenetic model generation and tree visualization was done using MEGAX v 10.1.7 [18], using the Maximum Likelihood method and Tamura-Nei model [10]. MEGAXsuggested: NoneCategorical Principal Component Analysis was performed on R version 3.6.1 using the package FactoMineR [11]. FactoMineRsuggested: (FactoMineR, RRID:SCR_014602)Specifically, a MSA FASTA file from MUSCLE is loaded in R and converted into a categorical matrix, with genomes as rows and nucleotide coordinates as columns. MUSCLEsu…SciScore for 10.1101/2020.02.02.931162: (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 MSA visualization was generated via Jalview v 2.11.0 [17] Jalviewsuggested: (Jalview, RRID:SCR_006459)Phylogenetic model generation and tree visualization was done using MEGAX v 10.1.7 [18], using the Maximum Likelihood method and Tamura-Nei model [10]. MEGAXsuggested: NoneCategorical Principal Component Analysis was performed on R version 3.6.1 using the package FactoMineR [11]. FactoMineRsuggested: (FactoMineR, RRID:SCR_014602)Specifically, a MSA FASTA file from MUSCLE is loaded in R and converted into a categorical matrix, with genomes as rows and nucleotide coordinates as columns. MUSCLEsuggested: (MUSCLE, RRID:SCR_011812)Nucleotide sequence identity and coverage were calculated using BLAST nucleotide v2.6.0 [20]. BLASTsuggested: (BLASTX, RRID:SCR_001653)Results from OddPub: Thank you for sharing your data.
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:- No conflict of interest statement was detected. If there are no conflicts, we encourage authors to explicit state so.
- No funding statement was detected.
- No protocol registration statement was detected.
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SciScore for 10.1101/2020.02.02.931162: (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 We aligned all the 70 coronavirus sequences using MUSCLE [9] and inferred the evolutionary relationships between these sequences with a Tamura-Nei Maximum Likelihood estimation [10] with 100 bootstraps for model robustness estimation. MUSCLEsuggested: (MUSCLE, SCR_011812)Phylogenetic model generation and tree visualization was done using MEGAX v 10.1.7 [ 18] , using the Maximum Likelihood method and Tamura-Nei model [ 10] . MEGAXsuggested: NoneCategorical Principal … SciScore for 10.1101/2020.02.02.931162: (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 We aligned all the 70 coronavirus sequences using MUSCLE [9] and inferred the evolutionary relationships between these sequences with a Tamura-Nei Maximum Likelihood estimation [10] with 100 bootstraps for model robustness estimation. MUSCLEsuggested: (MUSCLE, SCR_011812)Phylogenetic model generation and tree visualization was done using MEGAX v 10.1.7 [ 18] , using the Maximum Likelihood method and Tamura-Nei model [ 10] . MEGAXsuggested: NoneCategorical Principal Component Analysis was performed on R version 3.6.1 using the package FactoMineR [ 11] . FactoMineRsuggested: (FactoMineR, SCR_014602)Pairwise protein identity and coverage was calculated using BLAST protein v2.6.0 [ 20 ] with BLOSUM62 matrix and default parameters . BLASTsuggested: (BLASTX, SCR_001653)MSA visualization was generated via Jalview v 2.11.0 [ 17] Jalviewsuggested: (Jalview, SCR_006459)Results from OddPub: Thank you for sharing your data.
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