PT  - JOURNAL ARTICLE
AU  - Robert C. Edgar
AU  - Jeff Taylor
AU  - Victor Lin
AU  - Tomer Altman
AU  - Pierre Barbera
AU  - Dmitry Meleshko
AU  - Dan Lohr
AU  - Gherman Novakovsky
AU  - Benjamin Buchfink
AU  - Basem Al-Shayeb
AU  - Jillian F. Banfield
AU  - Marcos de la Peña
AU  - Anton Korobeynikov
AU  - Rayan Chikhi
AU  - Artem Babaian
TI  - Petabase-scale sequence alignment catalyses viral discovery
AID  - 10.1101/2020.08.07.241729
DP  - 2021 Jan 01
TA  - bioRxiv
PG  - 2020.08.07.241729
4099  - http://biorxiv.org/content/early/2021/03/14/2020.08.07.241729.short
4100  - http://biorxiv.org/content/early/2021/03/14/2020.08.07.241729.full
AB  - Public databases contain a planetary collection of nucleic acid sequences, but their systematic exploration has been inhibited by a lack of efficient methods for searching this corpus, now exceeding multiple petabases and growing exponentially [1, 2]. We developed a cloud computing infrastructure, Serratus, to enable ultra-high throughput sequence alignment at the petabase scale. We searched 5.7 million biologically diverse samples (10.2 petabases) for the hallmark gene RNA dependent RNA polymerase, identifying well over 105 novel RNA viruses and thereby expanding the number of known species by roughly an order of magnitude. We characterised novel viruses related to coronaviruses and to hepatitis δ virus, respectively and explored their environmental reservoirs. To catalyse a new era of viral discovery, we established a free and comprehensive database of these data and tools. Expanding the known sequence diversity of viruses can reveal the evolutionary origins of emerging pathogens and improve pathogen surveillance for the anticipation and mitigation of future pandemics.Competing Interest StatementThe authors have declared no competing interest.