Genome Detective Coronavirus Typing Tool for rapid identification and characterization of novel coronavirus genomes

Cleemput, Sara; Dumon, Wim; Fonseca, Vagner; Karim, Wasim Abdool; Giovanetti, Marta; Alcantara, Luiz Carlos; Deforche, Koen; de Oliveira, Tulio

© The Author(s) 2020. Published by Oxford University Press. This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact [e-mail] This coronavirus outbreak has been unprecedented; so too is the way that the scientific community has responded to it. They have openly and rapidly shared genomic and clinical data as never seen before allowing research results to be released almost instantaneously. This has helped the understanding of the transmission dynamics, the development of rapid diagnostic and has informed public health response. Here, we present a new contribution that can speed up this communal effort. The Genome Detective Coronavirus Typing Tool is a free-of-charge web-based bioinformatics pipeline that can accurately and quickly identify, assemble and classify coronaviruses genomes. The tool also identifies changes at nucleotides, coding regions and proteins using a novel dynamic aligner to allow tracking new viral mutations (Figure 1 ). Figure 1 : Genome Detective Coronavirus Typing Tool assembles genomes from next generation sequencing (NGS) in FASTAQ format or assembled genomes in FASTA format. A user can submit up to 1Gb of NGS data or 2,000 assembled genomic sequences. For each assembled genomic sequence, the tool identifies the virus species, constructs a phylogenetic tree and identifies phylogenetic clusters, which includes the novel coronavirus identified in Wuhan China in 2019 (SARS-CoV-2). The tool identifies changes at nucleotides, coding regions and proteins using a novel dynamic aligner and display all of the mutations in detailed tables and reports. . To this reference dataset, we added 47 whole genomes of the current Coronavirus 2019 (SARS-CoV-2) outbreak that originated in Wuhan, China, in December 2019. The SARS-CoV-2 sequences were downloaded from the GISAID database (https://www.gisaid.org) together with annotation of its original location, collection date and originating and submitting laboratory. The SARS-CoV-2 data generators are properly acknowledged in the acknowledgements section of this paper and detailed information is provided in Supplementary Table 1. The 431 reference WGS were aligned with MUSCLE (Edgar 2004) . The alignment was manually edited until a codon alignment was attained in all coding sequences (CDS). A Maximum likelihood phylogenetic tree, 1000 bootstrap replicates was constructed in PhyML (Guidon & Gascuel 2003; Lemoine et al., 2018 ) and a Bayesian tree using MrBayes (Ronquist & Huelsenbeck 2003) were constructed. The trees were visualized in Figtree (Rambaut 2018). We selected 25 reference sequences that represent the diversity of each well-defined phylogenetic cluster (with bootstrap support of 100% and posterior probability of 1). We identified five well supported phylogenetic clusters with more than two sequences of SARSr-CoV and used them to set up our automated phylogenetic classification tool. Cluster 1 included SARS strains from the 2002 and 2003 Asian outbreaks. In our tool, we named this cluster SARS-CoV Outbreak 2000s but may rename it as SARS-A if a new proposed naming system for SARSr-Cov is adopted in the near future (Rambaut 2020). Cluster 2 (provisionally named as SARS related CoV) in