TY - JOUR T1 - sgDI-tector: defective interfering viral genome bioinformatics for detection of coronavirus subgenomic RNAs JF - bioRxiv DO - 10.1101/2021.11.30.470527 SP - 2021.11.30.470527 AU - Andrea Di Gioacchino AU - Rachel Legendre AU - Yannis Rahou AU - Valérie Najburg AU - Pierre Charneau AU - Benjamin D Greenbaum AU - Frédéric Tangy AU - Sylvie van der Werf AU - Simona Cocco AU - Anastasia V Komarova Y1 - 2021/01/01 UR - http://biorxiv.org/content/early/2021/11/30/2021.11.30.470527.abstract N2 - Coronavirus RNA-dependent RNA polymerases produce subgenomic RNAs (sgRNAs) that encode viral structural and accessory proteins. User-friendly bioinformatic tools to detect and quantify sgRNA production are urgently needed to study the growing number of next-generation sequencing (NGS) data of SARS-CoV-2. We introduced sgDI-tector to identify and quantify sgRNA in SARS-CoV-2 NGS data. sgDI-tector allowed detection of sgRNA without initial knowledge of the transcription-regulatory sequences. We produced NGS data and successfully detected the nested set of sgRNAs with the ranking M>ORF3a>N>ORF6>ORF7a>ORF8>S>E>ORF7b. We also compared the level of sgRNA production with other types of viral RNA products such as defective interfering viral genomes.Competing Interest StatementBDG is a consultant or received honoraria for Darwin Health, Merck, PMV Pharma, ROME Therapeutics (of which he is a co-founder), Bristol-Meyers Squibb, and Chugai Pharmaceuticals and has research funding from Bristol-Meyers Squibb and Merck. The other authors declare that they have no competing interests. ER -