Novel Coronaviruses Discovery in Bat with an Innovative Bioinformatics Workflow

This project analyzed the sequencing results of 230 bat samples to investigatenovel Coronaviruses (CoVs) appearance. A bioinformatics workflow solution was developed to process the Next-Generation Sequencing (NGS) data to identify novel CoV genomes. A parallel computing scheme was implemented to enhance performance. Among the 230 bat samples, 14 samples previously tested positive for CoV appearance by a pan-CoV quantitative polymerase chain reaction (qPCR). The Illumina NGS techniques are used to generate the shotgun readings. With the newly developed bioinformatics pipeline, the sequencing reads from each bat sample, and a positive control sample were quality controlled and assembled to generate longer viral contigs. They then went through a Basic Local Alignment Search Tool X (BLASTx) query against a customized CoV database from the National Center for Biotechnology Information (NCBI) databases. After further filtering with BLASTx and megaBLAST against the NCBI nucleotide collection (nr/nt) database, the confirmed CoV contigs were used to build bootstrapped phylogenetic trees with several representative Alpha, Beta, and Gamma-CoV genomes. Two bat samples contained potentially novel CoV fragments corresponding to the Open Reading Frame 1ab (ORF1ab), ORF7, and Nucleocapsid (N) gene regions. The phylogenetic trees showed that the fragments are Alpha-CoVs, which are closely related to Eptesicus Bat Coronavirus, Pipistrellus Bat Coronavirus, and Tadarida Brasiliensis Bat Alphacoronavirus 1.