NatureBioinformaticsPeer-reviewed journal article
Petabase-scale sequence alignment catalyses viral discovery
R. C. EdgariD, Brie Taylor, Victor LiniD, Tomer AltmaniD, Pierre BarberaiD, Dmitry MeleshkoiD, Dan Lohr, Gherman NovakovskyiD, Benjamin BuchfinkiD, Basem Al-ShayebiD, Jillian F. BanfieldiD, Marcos de la PeñaiD, Anton KorobeynikoviD, Rayan ChikhiiD, Artem BabaianiD
Abstract
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{delta} 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.
- assay: whole-genome sequencing
- research focus: variant calling
- research focus: database / resource
- research focus: benchmarking
- approach: statistical model
- approach: experimental assay
- Citations
- 499
- FWCI
- 33.54
- Field percentile
- top 1%
Reproducibility ledger
Nobody has reported trying to reproduce this paper yet. Did you replicate an experiment or run the code? Your report saves the next lab a week.
Sign in to file a reproducibility report.
Related papers
- Petabase-scale Papillomavirus Discovery
Jessica Shen, Anton Korobeynikov, … Artem Babaian·bioRxiv·Apr 22, 2026
- Hidden viral sequences in public sequencing data and warning for future emerging diseases
J. Kawasaki, S. Kojima, … M. Horie·bioRxiv·May 17, 2021
- VirID: Beyond Virus Discovery - An Integrated Platform for Comprehensive RNA Virus Characterization
Ziyue Yang, Yongtao Shan, … Mǎng Shī·Molecular Biology and EvolutionPeer-reviewed·Sep 25, 2024
- Novel NGS Pipeline for Virus Discovery from a Wide Spectrum of Hosts and Sample Types
Ilya Plyusnin, Ravi Kant, … Teemu Smura·Virus EvolutionPeer-reviewed·Jul 1, 2020
- Data-Driven Virus Discovery with Virushunter and Virusgatherer
Liubov Chuprikova, Li Chuin Chong, … Chris Lauber·bioRxiv·Jan 28, 2026
- Using artificial intelligence to document the hidden RNA virosphere