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. Highlights 56 genomic sequences from distinct 2019‐nCoV patients were analyzed, showing very high (99%) sequence similarity. There exist few variable genomic regions within the 2019‐nCoV population. One of these affects the ORF8 locus. The closest publicly available genomic sequences to 2019‐nCoV appear to be coronaviruses infecting bats, while SARS and MERS viruses are more distantly related.
【저자키워드】 coronavirus, virus classification, Data visualization, biostatistics & bioinformatics, clustal analysis, 【초록키워드】 coronavirus, Variation, Genome, MERS, virus, heterogeneity, Novel coronavirus, Protein, Characteristics, ORF8, Patient, bat, Scientific community, genomes, molecular, genomic, bats, antiviral strategy, proteomic, Phylogenetic tree, acute respiratory syndrome, genomic region, locus, approaches, sequence, sequence similarity, zoonotic origin, genomic sequence, sequence identity, infecting, genomic information, Affect, responsible, analyzed, identify, sequenced, released, rising, Taking,